Multipartite Quantum States and their Marginals

Michael Walter

Chapter 1 Introduction

The pure state of a quantum system is described by a vector in a Hilbert space, or, more precisely, by a point in the corresponding projective space. Since the Hilbert space for multiple particles is given by the tensor product of the Hilbert spaces of the individual particles, its dimension grows exponentially with the number of particles. This exponential behavior is the key obstruction to the classical modeling of quantum systems. The observation is as old as quantum theory itself, and physicists ever since have tried to find ways around it. One way to address the aforementioned exponential complexity is to make use of the following simple yet powerful observation: Important physical properties often do not depend on the whole wave function but rather only on a small part, namely the reduced density matrix, or quantum marginal, of a few particles [Löw55]. For instance, the ground state energy of a spin chain is given by a minimization over nearest-neighbor reduced density matrices (Figure 1.1). In quantum chemistry, the binding energy of a molecule is similarly given by a minimization over two-electron reduced density matrices arising from many-electron wave functions. Mathematically, the reduced density matrix is the contraction of (or trace over) the indices of the projection operator onto the wave function over the remaining particles.

Not every collection of reduced density matrices can arise as the marginals of a quantum state—there are profound “kinematic” constraints that are purely due to the geometry of the quantum state space. The fundamental problem of characterizing the compatibility of reduced density matrices is known as the quantum marginal problem in quantum information theory and as the nn-representability problem in quantum chemistry (Figure 1.2). It has been long recognized for its importance in many-body quantum physics and quantum chemistry [Col63, Rus69, CY00, Col01]. Unfortunately, the general problem is QMA\mathbf{QMA}-complete and therefore NP\mathbf{NP}-hard, and so believed to be computationally intractable, even on a quantum computer [Liu06, LCV07]. However, even a partial understanding of the problem has proved to be immensely useful. Entropy inequalities such as the strong subadditivity of the von Neumann entropy [LR73], which constrain the reduced density matrices of a quantum state, are indispensable tools in quantum statistical physics and quantum information theory [OP93]. In computational quantum physics, the power of variational methods can be explained by their ability to reproduce the marginals of the ground state [VC06]. The fundamental Pauli exclusion principle [Pau25, Pau46], which states that the occupation numbers of a fermionic quantum state cannot exceed one, can be understood as a constraint on the one-body reduced density matrix.

The aim of this thesis is a systematic and rigorous study of the relation between multipartite quantum states and their marginals, which we carry out by using a diverse set of mathematical tools. It is naturally divided into two parts: Chapters 2–6 are concerned with one-body reduced density matrices and Chapters 7–9 with general marginals. Each part starts with an initial chapter that introduces background material. The subsequent chapters then present our research contributions; each begins with a summary of the main results that are obtained in the chapter and concludes with a discussion of the results presented. We now give a brief overview of the contents of the individual chapters.

In Chapter 2 we formally introduce the one-body quantum marginal problem, i.e., the problem characterizing the one-body reduced density matrices that are compatible with a global pure state. We describe the fundamental connection of this problem to geometric invariant theory, which is an appropriate mathematical framework for its study, and explain the physical consequences of the mathematical theory. For any given number of particles, local dimensions and statistics, there exists a finite set of linear inequalities that constrain the eigenvalues of compatible one-body reduced density matrices; these inequalities together cut out a convex polytope, known as a moment polytope in mathematics. The facets of this polytope acquire a physical interpretation through associated “selection rules”. We also discuss a dual, representation-theoretic description of the polytope. Many aspects are clarified greatly by using the appropriate perspective.

In Chapter 3 we first review some of the history of the one-body quantum marginal problem, which has seen some significant progress in recent years, culminating in Klyachko’s general solution. Along the way we give some concrete examples. We then present a different, geometric approach to the computation of moment polytopes, which is inspired by recent work of Ressayre. Significantly, our approach completely avoids many technicalities that have appeared in previous solutions to the problem, and it can be readily implemented algorithmically.

Chapter 4is devoted to the phenomenon of quantum entanglement, which profoundly influences the relation between a quantum system and its parts. We find that in the case of multipartite pure states, features of the entanglement can already be extracted from the local eigenvalues—the natural generalization of the Schmidt coefficients or entanglement spectrum. To study this systematically, we associate with any given class of entanglement an entanglement polytope, formed by the eigenvalues of the one-body marginals compatible with the class. In this way we obtain local witnesses for the multipartite entanglement of a global pure state. Our construction is applicable to systems of arbitrary size and statistics, and we explain how it can be adapted to states that are affected by low levels of noise.

In Chapter 5 we consider the following quantitative version of the one-body quantum marginal problem: Given a pure state chosen uniformly at random, what is the joint probability distribution of its one-body reduced density matrices? We obtain the exact probability distribution by reducing to the corresponding distribution of diagonal entries, which corresponds to a quantitative version of a classical marginal problem. This reduction is an instance of a more general “derivative principle” for Duistermaat–Heckman measures in symplectic geometry.

In Chapter 6 we digress in a brief interlude into a study of multiplicities of irreducible representations of compact, connected Lie groups. The asymptotic growth of such multiplicities in a “semiclassical limit” is directly related to the probability measures considered in the preceding chapter. We show that the ideas of the preceding chapter can be discretized, or “quantized”, to give an efficient algorithm for the branching problem, which asks for the multiplicity of an irreducible representation of a subgroup K⊆K′K\subseteq K^{\prime} in the restriction of an irreducible representation of K′K^{\prime}. In particular, we obtain the first polynomial-time algorithm for computing Kronecker coefficients for Young diagrams of bounded height. There is a surprising connection between our results on entanglement polytopes and multiplicities to recent efforts in the geometric complexity approach to the P\mathbf{P} vs. NP\mathbf{NP} problem in computer science. We sketch this connection and explain some additional observations regarding the relevance of asymptotics.

In Chapter 7 we initiate our study of general quantum marginals, motivated by the fundamental role of entropy in physics and information theory. Like the marginals themselves, these entropies are not independent; instead, they are constrained by linear entropy inequalities – the “laws of information theory” – such as the strong subadditivity of the von Neumann entropy, which is an indispensable tool in the analysis of quantum systems. A major open question is to decide if there are any further entropy inequalities satisfied by the von Neumann entropy that are not a consequence of strong subadditivity. Classically, such entropy inequalities have been found for the Shannon entropy, and the discovery of any further entropy inequality would be considered a major breakthrough.

In Chapter 8 we describe a first approach to the study of entropy inequalities. We consider two classes of quantum states – stabilizer states and Gaussian states – which are versatile enough to exhibit intrinsically quantum features, such as multipartite entanglement, but possess enough structure to allow for a concise and computationally efficient description. Quantum phase-space methods have been built around both classes of states, and we show how they can be used to construct a classical model that can be used to lift entropy inequalities for the Shannon entropy to quantum entropies. In particular, our technique immediately implies that the von Neumann entropy of stabilizer states satisfies all conjectured entropy inequalities.

In Chapter 9 we introduce a second approach, which is applicable to general quantum states. To this end, we unveil a novel connection between the existence of multipartite quantum states with given marginal eigenvalues and the representation theory of the symmetric group. We use this connection to give a new proof of the strong subadditivity and weak monotonicity of the von Neumann entropy, and propose a general approach to finding further entropy inequalities based on studying representation-theoretic symbols and their symmetry properties.

The list of symbols (pp. Multipartite Quantum States and their Marginals–List of Symbols) summarizes the most important notation used throughout this thesis. This introduction has been adapted from [CDKW14]. Earlier versions of Figures 1.1 and 1.2 have been used in several presentations by Matthias Christandl and the author. Most of the material in this thesis has been assembled from the works [WDGC13, CDKW14, CDW12, GW13, CŞW12], and we give the corresponding references at the beginning of each chapter.

Chapter 2 The One-Body Quantum Marginal Problem

In this chapter we formally introduce the one-body quantum marginal problem and discuss some fundamental properties. We recall some basic concepts from the theory of Lie groups and their representations that are used throughout this thesis. Next, we introduce the connection to geometric invariant theory, which is the appropriate mathematical framework for the study of the one-body quantum marginal problem and its variants. We then explain the physical consequences of the mathematical theory for the quantum marginal problem and conclude by discussing the dual, representation-theoretic description in terms of Kronecker coefficients. None of the results in this chapter are new; in each section we give pointers to relevant background literature.

Composite quantum systems are modeled by the tensor product of the Hilbert spaces describing their constituents. Throughout this thesis, we will assume that all Hilbert spaces are finite-dimensional unless stated otherwise. It is useful to think of the constituents as individual particles, although they can be of more general nature; for instance, the subsystems can describe different degrees of freedom such as position and spin. Depending on whether the particles are in principle distinguishable or indistinguishable, we distinguish two basic classes of composite systems, which are of fundamentally different nature.

In the case of distinguishable particles, the system is described by the tensor-product H=⨂k=1nHk\mathcal{H}=\bigotimes_{k=1}^{n}\mathcal{H}_{k} of the Hilbert spaces describing the individual particles. Given a density matrix ρ\rho on H\mathcal{H}, the one-body reduced density matrices ρk\rho_{k} are defined by taking the partial trace of ρ\rho over all subsystems other than kk. In other words,

In physical terms, (2.1) asserts that ρk\rho_{k} reproduces faithfully the expectation values of all local observables OkO_{k}. Hence ρk\rho_{k} describes the effective state of the kk-th particle. The one-body quantum marginal problem then is the following compatibility problem:

Let H=⨂k=1nHk\mathcal{H}=\bigotimes_{k=1}^{n}\mathcal{H}_{k}. Given density matrices ρk\rho_{k} on Hk\mathcal{H}_{k} for all k=1,…,nk=1,\dots,n, does there exist a pure state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert on H\mathcal{H} such that ρk\rho_{k} are its one-body reduced density matrices?

We will call such density matrices ρ1,…,ρn\rho_{1},\dots,\rho_{n} compatible (with a global pure state). The term “quantum marginal problem” has been coined by Klyachko in analogy to the classical marginal problem in probability theory, which asks for the existence of a joint probability distribution for a given set of marginal distributions [Kly04]. Its one-body version was first solved in the paper [Kly04]; cf. [DH04].

For two particles, n=2n=2, the one-body quantum marginal problem is rather straightforward to solve. For this, recall that any vector ∣ψ⟩\ket{\psi} on a tensor product H1⊗H2\mathcal{H}_{1}\otimes\mathcal{H}_{2} can be expanded in the form

for orthonormal sets of vectors ∣i⟩\ket{i} in H1\mathcal{H}_{1} and ∣i~⟩\ket{\widetilde{i}} in H2\mathcal{H}_{2} and positive numbers pj>0p_{j}>0. In quantum information theory this is called the Schmidt decomposition; it is a simple consequence of the singular value decomposition in linear algebra. Thus if ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert is a pure state then it follows that ρ1=∑ipi∣i⟩⟨i∣\rho_{1}=\sum_{i}p_{i}\lvert i\rangle\langle i\rvert and ρ2=∑ipi∣i~⟩⟨i~∣\rho_{2}=\sum_{i}p_{i}\lvert\widetilde{i}\rangle\langle\widetilde{i}\rvert have the same non-zero eigenvalues, including multiplicities (and indeed the same spectrum if H1\mathcal{H}_{1} and H2\mathcal{H}_{2} are of the same dimension). Conversely, for any two such density matrices ρ1\rho_{1} and ρ2\rho_{2}, we can always use (2.2) with the respective eigenbases to define a corresponding global pure state. We record for future reference:

Any two density matrices ρ1\rho_{1} and ρ2\rho_{2} are compatible with a global pure state if and only if ρ1\rho_{1} and ρ2\rho_{2} have the same non-zero eigenvalues (including multiplicities), i.e., if and only if λ⃗1∖{0}=λ⃗2∖{0}\vec{\lambda}_{1}\setminus\{0\}=\vec{\lambda}_{2}\setminus\{0\}.

In particular, any density matrix ρ1\rho_{1} can be realized as the reduced density matrix of a pure state. In quantum information, such a pure state is called a purification of the density matrix ρ1\rho_{1}.

An important consequence of Chapter 2 is that n+1n+1 spectra λ⃗1\vec{\lambda}_{1}, …, λ⃗n\vec{\lambda}_{n}, μ⃗\vec{\mu} are compatible with a pure state if and only if λ⃗1\vec{\lambda}_{1}, …, λ⃗n\vec{\lambda}_{n} are compatible with a global state of spectrum μ⃗\vec{\mu}. Therefore there is no loss of generality in restricting to pure states in our formulation of Chapter 2.

Another useful corollary is that the one-body quantum marginal problem for an arbitrary number of particles can always be reduced to the case n=3n=3: A given collection of spectra λ⃗1,…,λ⃗n\vec{\lambda}_{1},\dots,\vec{\lambda}_{n} is compatible if and only if there exists a spectrum μ⃗\vec{\mu} such that both λ⃗1,λ⃗2,μ⃗\vec{\lambda}_{1},\vec{\lambda}_{2},\vec{\mu} as well as μ⃗,λ⃗3,…,λ⃗n\vec{\mu},\vec{\lambda}_{3},\dots,\vec{\lambda}_{n} are compatible, and this process can be iterated. This is immediate from the preceding and Chapter 2, which also shows that the rank of μ⃗\vec{\mu} can be bounded by the minimum of dim⁡H1×dim⁡H2\dim\mathcal{H}_{1}\times\dim\mathcal{H}_{2} and ∏k=3ndim⁡Hk\prod_{k=3}^{n}\dim\mathcal{H}_{k}.

Identical Particles

In the case of nn identical particles, the system is described by the nn-th symmetric or antisymmetric tensor power of the single-particle Hilbert space, H=\SymnH1\mathcal{H}=\Sym^{n}\mathcal{H}_{1} or H=⋀nH1\mathcal{H}=\bigwedge^{n}\mathcal{H}_{1} depending on whether the particles are bosons or fermions. By considering H\mathcal{H} as a subspace of H1⊗n\mathcal{H}_{1}^{\otimes n}, we can define the one-body reduced density matrices as in the case of distinguishable particles. Of course, ρ1=⋯=ρn\rho_{1}=\dots=\rho_{n}, since for bosons as well as for fermions the global state ρ\rho is permutation-invariant. In summary,

where in the last expression ai†a_{i}^{\dagger} and aja_{j} denote the creation and annihilation operators with respect to an arbitrary basis ∣i⟩\ket{i} of the single-particle Hilbert space.

For fermions, we thus arrive at the following variant of Chapter 2:

Given a density matrix ρ1\rho_{1} on H1\mathcal{H}_{1}, does there exist a pure state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert on ⋀nH1\bigwedge^{n}\mathcal{H}_{1} such that ρ1\rho_{1} is its one-body reduced density matrix?

We will call such a density matrix ρ1\rho_{1} nn-representable. In the context of second quantization, it is often more convenient to normalize the one-body marginal to trace nn. Following quantum chemistry conventions, we correspondingly set γ1:=nρ1\gamma_{1}:=n\rho_{1} and call it the first-order density matrix [Löw55] (but remark that it is not a density matrix in the strict sense). In quantum chemistry, the diagonal entries of γ1\gamma_{1} are called occupation numbers, while its eigenvalues are called the natural occupation numbers. As in the case of distinguishable particles, Chapter 2 depends only on the eigenvalues of ρ1\rho_{1}, or, equivalently, on the natural occupation numbers of γ1\gamma_{1}. In this language, the Pauli exclusion principle asserts that the natural occupation numbers, and hence all occupation numbers, never exceed one [Pau25]. This is obvious from second quantization, since ⟨i∣γ1∣i⟩=\trρ ai†ai≤1\braket{i|\gamma_{1}|i}=\tr\rho\,a_{i}^{\dagger}a_{i}\leq 1. Equivalently, the largest eigenvalue of an nn-representable one-body density matrix is at most 1/n1/n. However, there are many more constraints on the natural occupation numbers of a pure state of nn fermions [BD72, KA08].

Chapter 2can also be formulated for bosons. Here it can be shown that the resulting problem is in fact trivial: Any density matrix ρ1=∑ipi∣i⟩⟨i∣\rho_{1}=\sum_{i}p_{i}\lvert i\rangle\langle i\rvert arises as the one-body reduced density matrix of a pure ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert state on the symmetric subspace, e.g., ∣ψ⟩=∑ipi∣i⟩⊗n\ket{\psi}=\sum_{i}\sqrt{p_{i}}\ket{i}^{\otimes n} [KA08].

Further variants of the one-body quantum marginal problem may arise from physical or mathematical considerations. For instance, the analysis of fermionic systems with several internal degrees of freedom leads to the study of other irreducible representations besides the symmetric or antisymmetric subspace [KA08]. We will discuss one such example at the end of Section 3.4. We may also combine systems composed of different species of particles, some of them indistinguishable among each other. On a mathematical level, this situation also arises when the “purification trick” that we used to restrict to global pure states in the formulation of Chapter 2 is applied to systems of identical particles. The mathematical framework that we outline in the subsequent sections subsumes all these variants of the marginal problem.

1 Lie Groups and their Representations

Before we proceed it will be useful to recall some fundamental notions from the theory of Lie groups and their representations. We illustrate the general theory in the important case of the unitary groups and their complexification, the general linear groups, and summarize the notation in Table 2.1. We refer to [Kna86, FH91, CSM95, Kna02, Pro07, Bri10] for comprehensive introductions to the subject.

The Lie group GG acts on itself by conjugation, g.h:=ghg−1g.h:=ghg^{-1}. By taking the derivative, we obtain the adjoint representation \Ad ⁣:G→\GL(g)\Ad\colon G\rightarrow\GL(\mathfrak{g}) of GG on g\mathfrak{g}. Its differential is the representation of the Lie algebra g\mathfrak{g} on itself by the Lie bracket, \ad(X)Y=[X,Y]\ad(X)Y=[X,Y]. By decomposing the adjoint representation into weight spaces gα\mathfrak{g}_{\alpha} and observing that g0=h\mathfrak{g}_{0}=\mathfrak{h}, we obtain

where RG:={α≠0:gα≠0}⊆ΛG∗R_{G}:=\{\alpha\neq 0:\mathfrak{g}_{\alpha}\neq 0\}\subseteq\Lambda^{*}_{G} is the set of non-trivial weights of the adjoint representation, called the roots. The corresponding weight spaces

are called root spaces. For an arbitrary representation VV we have that π(gα)Vω⊆Vω+α\pi(\mathfrak{g}_{\alpha})V_{\omega}\subseteq V_{\omega+\alpha}; in particular, [gα,gβ]⊆gα+β[\mathfrak{g}_{\alpha},\mathfrak{g}_{\beta}]\subseteq\mathfrak{g}_{\alpha+\beta}. All root spaces gα\mathfrak{g}_{\alpha} are one-dimensional, and for each root α\alpha, −α-\alpha is also a root. We can find basis vectors Eα∈gαE_{\alpha}\in\mathfrak{g}_{\alpha} and elements Zα∈itZ_{\alpha}\in i\mathfrak{t}, called co-roots, such that

The “Pauli matrices” Xα:=Eα+E−αX_{\alpha}:=E_{\alpha}+E_{-\alpha} and Yα:=i(E−α−Eα)Y_{\alpha}:=i(E_{-\alpha}-E_{\alpha}) are a basis of ikαi\mathfrak{k}_{\alpha}; they satisfy the commutation relations

Now choose a decomposition RG=RG,+⊔RG,−R_{G}=R_{G,+}\sqcup R_{G,-} of the set of roots into positive and negative roots. That is, RG,−=−RG,+R_{G,-}=-R_{G,+} and each subset is strictly contained in a half-space of the (real) span of the roots (which is equal to it∗i\mathfrak{t}^{*} if GG is semisimple). Then we have a decomposition

where the n±\mathfrak{n}_{\pm} are nilpotent Lie algebras; the corresponding Lie groups N±⊆GN_{\pm}\subseteq G are called maximal unipotent subgroups.

Another consequence of the choice of positive roots is the following. Consider the dual of the adjoint representation of GG on g\mathfrak{g}, given by (\Ad∗(g)φ)(X)=φ(\Ad(g−1)X)(\Ad^{*}(g)\varphi)(X)=\varphi(\Ad(g^{-1})X) for all g∈Gg\in G, φ∈g∗\varphi\in\mathfrak{g}^{*} and XX in g\mathfrak{g}. It is not hard to see that its restriction to KK preserves the real subspace

and we shall call it the coadjoint representation of KK on ik∗i\mathfrak{k}^{*} (our choice of factor ii is somewhat idiosyncratic but will be rather convenient in the sequel). We may consider h∗⊆g∗\mathfrak{h}^{*}\subseteq\mathfrak{g}^{*} and it∗⊆ik∗i\mathfrak{t}^{*}\subseteq i\mathfrak{k}^{*} by extending each functional by zero on the root spaces gα\mathfrak{g}_{\alpha}. Then the positive Weyl chamber

is a cross-section for the coadjoint action of KK. In other words, each coadjoint orbit \Ad∗(K)φ\Ad^{*}(K)\varphi intersects the positive Weyl chamber in a single point λ∈it+∗\lambda\in i\mathfrak{t}^{*}_{+}. We write OK,λ:=\Ad∗(K)λ\mathcal{O}_{K,\lambda}:=\Ad^{*}(K)\lambda for the coadjoint orbit through λ\lambda. The positive Weyl chamber is a convex cone (pointed if GG is semisimple). Its (relative) interior is

For any λ∈it>0∗\lambda\in i\mathfrak{t}^{*}_{>0}, the KK-stabilizer is the maximal torus TT, so that OK,λ≅K/T\mathcal{O}_{K,\lambda}\cong K/T.

The last piece of structure is the Weyl group WK=NK(T)/TW_{K}=N_{K}(T)/T, where NK(T)={k∈K:kT=Tk}N_{K}(T)=\{k\in K:kT=Tk\} denotes the normalizer of the maximal torus T⊆KT\subseteq K. It is a finite group that acts on it∗i\mathfrak{t}^{*}. For any representation VV, the action of the Weyl group leaves the set of weights invariant. In particular, the set of roots is left invariant. The Weyl group acts simply transitively on the set of Weyl chambers obtained from different choices of positive roots. In particular, every WKW_{K}-orbit in it∗i\mathfrak{t}^{*} has a unique point of intersection with the positive Weyl chamber it+∗i\mathfrak{t}^{*}_{+}, and there exists a Weyl group element, known as the longest Weyl group element w0w_{0}, that exchanges the positive and negative roots and hence sends the “negative Weyl chamber” −it+∗-i\mathfrak{t}^{*}_{+} to it+∗i\mathfrak{t}^{*}_{+}. More generally, one can define the length l(w)l(w) of a Weyl group element as the minimal number of certain standard generators required to write ww, but we will not need this level of generality.

Representation Theory

Let Π ⁣:G→\GL(V)\Pi\colon G\rightarrow\GL(V) be a finite-dimensional representation of GG, with infinitesimal representation π ⁣:g→gl(V)\pi\colon\mathfrak{g}\rightarrow\mathfrak{gl}(V) and weight space decomposition V=⨁ωVωV=\bigoplus_{\omega}V_{\omega}. A weight vector ∣ψ⟩∈Vω\ket{\psi}\in V_{\omega} is called a highest weight vector if Π(N+)∣ψ⟩≡∣ψ⟩\Pi(N_{+})\ket{\psi}\equiv\ket{\psi}, or, equivalently, if π(n+)∣ψ⟩=0\pi(\mathfrak{n}_{+})\ket{\psi}=0. The corresponding highest weight ω\omega is necessarily dominant, i.e., an element of ΛG,+∗:=ΛG∗∩it+∗\Lambda^{*}_{G,+}:=\Lambda^{*}_{G}\cap i\mathfrak{t}^{*}_{+}.

The fundamental theorem of the representation theory of compact connected Lie groups KK asserts that the irreducible representations of GG can be labeled by their highest weight: Any irreducible representation contains a highest weight vector ∣λ⟩\ket{\lambda}, unique up to multiplication by a scalar. Conversely, for every λ∈ΛG,+∗\lambda\in\Lambda^{*}_{G,+} there exists a unique irreducible representation VK,λV_{K,\lambda} with λ\lambda as the highest weight. The dual representation VK,λ∗V^{*}_{K,\lambda} of an irreducible representation is again irreducible, and its highest weight is λ∗:=−w0λ\lambda^{*}:=-w_{0}\lambda, where w0w_{0} is the longest Weyl group element as defined above. Like any finite-dimensional representation of KK, VK,λV_{K,\lambda} extends to a rational representation VG,λV_{G,\lambda} of the algebraic group GG, i.e., a representation whose matrix elements are given by rational functions on the algebraic group GG (that is, by morphisms of algebraic varieties, which is the appropriate notion in this context). All irreducible rational representations of GG can be obtained in this way. Therefore, the representation theory of KK and of GG are essentially equivalent.

An arbitrary GG-representation VV can always be equipped with a KK-invariant inner product (choose an arbitrary inner product and average). In this case, Π(K)⊆\U(V)\Pi(K)\subseteq\U(V), and so π(k)\pi(\mathfrak{k}) consist of anti-Hermitian and π(ik)\pi(i\mathfrak{k}) of Hermitian operators. Moreover, VV can always be decomposed into irreducible representations and the irreducible representations that occur in VV are in one-to-one correspondence with the highest weight vectors in VV (up to rescaling). In particular, the subspace VG={v∈V:Π(g)v=v  (∀g∈G)}V^{G}=\{v\in V:\Pi(g)v=v\;(\forall g\in G)\} of invariant vectors is the sum of all trivial representations that occur in VV.

The General Linear and Unitary Groups

The general linear group G=\GL(d)G=\GL(d) of invertible d×dd\times d-matrices is a connected reductive algebraic group, with Lie algebra g=gl(d)\mathfrak{g}=\mathfrak{gl}(d) the space of complex d×dd\times d-matrices. The Lie bracket is the usual commutator, [X,Y]:=XY−YX[X,Y]:=XY-YX, and the exponential map is the usual matrix exponential. The unitary group K=\U(d)K=\U(d), whose elements are unitary d×dd\times d-matrices, is a maximal compact subgroup, with Lie algebra k=u(d)\mathfrak{k}=\mathfrak{u}(d) the space of anti-Hermitian matrices. Thus iki\mathfrak{k} is the set of Hermitian matrices, which we may identify with ik∗i\mathfrak{k}^{*} by using the Hilbert–Schmidt inner product.

The roots of \GL(d)\GL(d) are the functionals αij(H)=Hi,i−Hj,j\alpha_{ij}(H)=H_{i,i}-H_{j,j}, and the corresponding root spaces gij\mathfrak{g}_{ij} are spanned by the elementary matrices Eij=∣i⟩⟨j∣E_{ij}=\lvert i\rangle\langle j\rvert that have a single non-zero entry in the ii-th row and jj-th column. Indeed, we have that [H,∣i⟩⟨j∣]=(Hi,i−Hj,j)∣i⟩⟨j∣[H,\lvert i\rangle\langle j\rvert]=(H_{i,i}-H_{j,j})\lvert i\rangle\langle j\rvert for any diagonal matrix H=∑jHj,j∣j⟩⟨j∣∈hH=\sum_{j}H_{j,j}\lvert j\rangle\langle j\rvert\in\mathfrak{h}. A choice of positive roots is given by those roots αij\alpha_{ij} with i<ji<j. Thus the nilpotent Lie algebras n±\mathfrak{n}_{\pm} consist of the strictly upper and lower triangular matrices, respectively. The corresponding unipotent subgroups N±N_{\pm} are upper and lower triangular with ones on the diagonal.

The adjoint action is by conjugation. If we identify ik≅ik∗i\mathfrak{k}\cong i\mathfrak{k}^{*} then the coadjoint orbits of K=\U(d)K=\U(d) consist of Hermitian matrices with fixed spectrum. Then the positive Weyl chamber it+∗i\mathfrak{t}^{*}_{+} can be identified with the set of Hermitian diagonal matrices whose entries are weakly decreasing, or with their spectra λ1≥⋯≥λd\lambda_{1}\geq\dots\geq\lambda_{d}. The assertion that it+∗i\mathfrak{t}^{*}_{+} is a cross-section for the coadjoint action of KK on ik∗i\mathfrak{k}^{*} corresponds to the plain fact that any Hermitian matrix can be diagonalized by a unitary. Its interior it>0∗i\mathfrak{t}^{*}_{>0} then corresponds to the set of non-degenerate spectra λ1>⋯>λd\lambda_{1}>\dots>\lambda_{d}. The claim that the KK-stabilizer of any λ∈it>0∗\lambda\in i\mathfrak{t}^{*}_{>0} is TT amounts to the fact that the only unitaries that commute with a diagonal matrix with non-degenerate spectrum are the diagonal unitary matrices.

Finally, the Weyl group can be identified with the symmetric group SdS_{d}; it acts on iti\mathfrak{t} by permuting diagonal entries. The length l(w)l(w) of a permutation ww is the number of transpositions (i  i ⁣+ ⁣1)(i\;i\!+\!1) required to write the permutation w∈Sdw\in S_{d}, and the longest Weyl group element w0w_{0} is the “order-reversing permutation” which sends any −λ∈−it+∗-\lambda\in-i\mathfrak{t}^{*}_{+} to λ∗:=(−λd,…,−λ1)∈it+∗\lambda^{*}:=(-\lambda_{d},\dots,-\lambda_{1})\in i\mathfrak{t}^{*}_{+}.

The first diagram in the example has two rows and four boxes, while the second diagram has three boxes as well as rows. The number of rows is also called the height of a Young diagram λ\lambda. We write λ⊢dk\lambda\vdash_{d}k for a Young diagram with kk boxes and at most dd rows.

2 Geometric Invariant Theory

In this section, we introduce some geometric invariant theory, which is a powerful mathematical framework for studying the one-body quantum marginal problem and its variants. We refer to [Kir84a, MFK94, Bri10, Woo10, VB11, GRS13] for further material.

where ρ′′=∣ψ′′⟩⟨ψ′′∣\rho^{\prime\prime}=\lvert\psi^{\prime\prime}\rangle\langle\psi^{\prime\prime}\rvert. In other words, the traceless part of each one-body reduced density matrix ρk′′\rho^{\prime\prime}_{k} vanishes. We conclude that each one-body reduced density matrix ρk′′\rho^{\prime\prime}_{k} is proportional to the identity matrix. In the language of quantum information theory, the quantum state ρ′′\rho^{\prime\prime} is locally maximally mixed. This way of reasoning establishes a first link between the existence of invariants and of pure states with prescribed marginals. In the following we will see that the above argument can be generalized to arbitrary one-body marginals and turned into an equivalence that completely characterizes the one-body quantum marginal problem and its variants. We follow along the lines of the exposition in [VB11] and take some ideas from [NM84, Bri87].

Mathematically, the set of pure states on a Hilbert space H\mathcal{H},

is known as a complex projective space. It is a smooth submanifold of the real vector space of Hermitian operators on H\mathcal{H}. The unitary group \U(H)\U(\mathcal{H}) acts transitively by conjugation, U∣ψ⟩⟨ψ∣U†U\lvert\psi\rangle\langle\psi\rvert U^{\dagger}, so that the tangent space at a point ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert is spanned by the tangent vectors Xρ=[X,ρ]X_{\rho}=[X,\rho] for all X∈u(H)X\in\mathfrak{u}(\mathcal{H}). Since the XX are anti-Hermitian, it is easy to verify that the tangent space can be equivalently written as

In this way, the tangent space acquires a complex structure, which can be written as

as well as a Hermitian inner product. The real part of the inner product is a Riemannian metric, g(V,W)=\trVWg(V,W)=\tr VW, and its imaginary part is the Fubini–Study symplectic form

For tangent vectors generated by elements of the Lie algebra u(H)\mathfrak{u}(\mathcal{H}), this becomes

The action of \U(H)\U(\mathcal{H}) can be extended to its complexification, the general linear group \GL(H)\GL(\cal H) by the formula

The tangent vector generated by a Hermitian matrix iX∈iu(H)iX\in i\mathfrak{u}(\mathcal{H}) is then given by (iX)ρ:={iX,ρ}−2(\triXρ)ρ(iX)_{\rho}:=\{iX,\rho\}-2(\tr iX\rho)\rho, with {A,B}:=AB+BA\{A,B\}:=AB+BA the anti-commutator. It is easily verified that (iX)ρ=J[Xρ](iX)_{\rho}=J[X_{\rho}]. Thus the complex structures of projective space and of the Lie group are compatible with each other.

The Moment Map

Unfortunately, there are as many conventions for the moment map as there are textbooks on the subject. For the representation H\mathcal{H} that we considered at the beginning of this section, the moment map maps pure states onto the functionals evaluating (traceless) local observables; cf. (2.7). Thus the one-body quantum marginal problem is equivalent to characterizing the image of a moment map. In Section 2.3 we will explain this connection in more detail.

A crucial property of the moment map is the following relation between the differential of its components and the tangent vector Xρ=[π(X),ρ]X_{\rho}=[\pi(X),\rho] generated by the infinitesimal action of the Lie algebra of the compact group:

This follows readily from (2.10). Since the Fubini–Study form is non-degenerate, an immediate consequence is that the component (2.13) of the differential vanishes if and only if Xρ=0X_{\rho}=0. Dually, we find that the range of the differential of the moment map at any point ρ\rho is given by the annihilator of kρ:={X∈k:Xρ=[π(X),ρ]=0}\mathfrak{k}_{\rho}:=\{X\in\mathfrak{k}:X_{\rho}=[\pi(X),\rho]=0\}, the Lie algebra of the KK-stabilizer of ρ\rho [GS82a]:

Thus its image consists of a union of coadjoint orbits, and so is characterized by its intersection with the positive Weyl chamber it+∗i\mathfrak{t}^{*}_{+}. In the context of the quantum marginal problem, this amounts to our previous observation that its solution depends only on the eigenvalues of the one-body reduced density matrices.

Our basic argument above showed that any non-zero vector of minimal length in an orbit closure has expectation value zero with respect to all local traceless observables (i.e., the image under the moment map is zero). The following result by Kempf and Ness shows a converse [KN79] (cf. [Kem78, NM84] and Figure 2.1 for an illustration).

Suppose for the sake of finding a contradiction that the GG-orbit through ∣ψ⟩\ket{\psi} is not closed. Then the Hilbert–Mumford criterion asserts that we can reach a point in the “boundary” Π(G)∣ψ⟩‾∖Π(G)∣ψ⟩\overline{\Pi(G)\ket{\psi}}\setminus\Pi(G)\ket{\psi} by using a single one-parameter subgroup (e.g., [Kra85, p. 171]). More formally, it states that there exists X∈ikX\in i\mathfrak{k} such that

Let ∣ψ⟩=∑k∣ψk⟩\ket{\psi}=\sum_{k}\ket{\psi_{k}} be the decomposition of ∣ψ⟩\ket{\psi} into eigenvectors of the Hermitian operator π(X)\pi(X), with ∣ψk⟩\ket{\psi_{k}} an eigenvector with eigenvalue kk. Clearly, ∣ψk⟩=0\ket{\psi_{k}}=0 for all k>0k>0, since otherwise the limit (2.15) cannot exist. But then

so that ∣ψk⟩=0\ket{\psi_{k}}=0 also for all k<0k<0. It follows that ∣ψ⟩=∣ψ0⟩\ket{\psi}=\ket{\psi_{0}}, i.e. π(X)∣ψ⟩=0\pi(X)\ket{\psi}=0. Thus the one-parameter subgroup in fact leaves the vector invariant,

This is the desired contradiction to (2.15). ∎

In the following we need to study the image of the moment map not only for the set of all pure states but also for certain subsets of projective space. In the context of algebraic geometry, it is natural to consider GG-invariant projective subvarieties, which we define in the following way (e.g., [Har77]):

To generalize Section 2.2 to arbitrary points in the image of the moment map, we need as the last ingredient the Borel–Weil theorem (see, e.g., [VB11, Lemma 94]).

The Moment Polytope

The following proposition formalizes the fundamental link between the image of the moment map and the decomposition of the ring of regular functions into irreducible representations [GS82b, NM84, Bri87].

Fix λ∈ΛG,+∗\lambda\in\Lambda^{*}_{G,+} and k>0k>0. Let H~:=\Symk(H)⊗VG,λ∗\widetilde{\mathcal{H}}:=\Sym^{k}(\mathcal{H})\otimes V_{G,\lambda^{*}}. Then

It follows by using the second assertion in (2.16) and λ∗=−w0λ\lambda^{*}=-w_{0}\lambda that

It is instructive to apply Section 2.2 to the situation of Section 2.2.

It follows as an immediate consequence that

is a convex polytope with rational vertices, whose rational points are given by

The study of moment maps and their convexity properties has a long history in mathematics. Among the well-known special cases are: The Schur–Horn theorem concerning the diagonal entries of Hermitian matrices with fixed spectrum [Sch23, Hor54]; Kostant’s convexity theorem, which is the generalization to general coadjoint orbits [Kos73]; the Atiyah–Guillemin–Sternberg convexity theorem for torus actions [Ati82, GS82a]; Heckman’s convexity theorem, which considers projections of coadjoint orbits [Hec82]; and Kirwan’s convexity theorem, which is the symplectic analogue of Theorem 2.11 [Kir84b] (cf. [Sja98, Bri99] and the recent monograph [GS05]).

3 Consequences for the Quantum Marginal Problem

We now describe the precise connection between the geometry of the moment map and the one-body quantum marginal problem and draw some general consequences.

where we identify diagonal matrices with non-increasing entries with their spectrum (as in Section 2.1 and Table 2.1).

In practice, the above modeling of the quantum marginal problem has the disadvantage that the moment polytope is always of positive codimension: since \trρk≡\trρ=1\tr\rho_{k}\equiv\tr\rho=1, ΔK\Delta_{K} is contained in the affine subspace ∑jλk,j=1\sum_{j}\lambda_{k,j}=1 for all k=1,…,nk=1,\dots,n. It will usually be more convenient to instead use the special linear and unitary groups, G=\SL(H1)×⋯×\SL(Hn)G=\SL(\mathcal{H}_{1})\times\dots\times\SL(\mathcal{H}_{n}) and K=\SU(H1)×⋯×\SU(Hn)K=\SU(\mathcal{H}_{1})\times\dots\times\SU(\mathcal{H}_{n}), so that iki\mathfrak{k} consists of tuples of traceless Hermitian matrices. Then the moment map preserves only the traceless part of the one-body reduced density matrices, which avoids the above degeneracy.

For fermions, we similarly choose H=⋀nH1\mathcal{H}=\bigwedge^{n}\mathcal{H}_{1} and G=\SL(H1)G=\SL(\mathcal{H}_{1}) acting by Π(g1)=g1⊗n\Pi(g_{1})=g_{1}^{\otimes n}. With K=\SU(H1)K=\SU(\mathcal{H}_{1}) and using (2.3) we obtain that

where γ1:=nρ1\gamma_{1}:=n\rho_{1} is the first-order density matrix from quantum chemistry with trace nn that we had defined below (2.3). Again we find that the one-body nn-representability problem, Chapter 2, is precisely equivalent to determining the moment polytope.

We can similarly model the other variants of the one-body quantum marginal problem alluded to at the end of the introduction of this chapter by considering different representations of unitary groups or their composition. For example, if H0\mathcal{H}_{0} is a K0K_{0}-representation describing a pure-state problem then the corresponding mixed-state problem can be studied by taking H=H0⊗H0\mathcal{H}=\mathcal{H}_{0}\otimes\mathcal{H}_{0} and K=K0×\SU(H0)K=K_{0}\times\SU(\mathcal{H}_{0}); e.g., the mixed-state problem for fermions amounts to the moment polytope for the \SU(H1)⊗\SU(⋀nH1)\SU(\mathcal{H}_{1})\otimes\SU(\bigwedge^{n}\mathcal{H}_{1})-representation ⋀nH1⊗⋀nH1\bigwedge^{n}\mathcal{H}_{1}\otimes\bigwedge^{n}\mathcal{H}_{1}. In Section 3.4 we discuss another example that involves the marginal problem for the spin and orbital degrees of freedom of a fermionic system. In Table 2.3 we summarize the mathematical modeling of the scenarios of main physical interest.

For all these variants of the one-body quantum marginal problem, Theorem 2.11 immediately implies that the solution is given by a convex polytope, i.e., by linear inequalities on the eigenvalues of the one-body reduced density matrices. For example, Pauli’s original exclusion principle is one such inequality—but in general there are many further constraints. As we will see in several concrete examples in Chapter 3, there is a rich variety of subtle kinematic constraints on the one-body marginals of a multipartite quantum state.

To compute the actual linear inequalities for a given number of particles, statistics and local dimensions is in general a difficult problem that we will study in the next chapter. All known general solutions rely in one way or the other on the invariant-theoretic description of the moment polytope given by Theorem 2.11, including the original solution by Klyachko [Kly04] and the solution that we present in Chapter 3. In the remainder of this section we discuss the physical significance of the facets of the moment polytope, and we then describe more explicitly the representation-theoretic content of Theorem 2.11.

Pinning

An important consequence of the general theory is that the facets of the polytope have a rather particular structure. Before we show this, we record the following useful lemma for future reference.

Consider the symplectic cross section Y:=μK−1(it>0∗)Y:=\mu_{K}^{-1}(i\mathfrak{t}^{*}_{>0}). By KK-equivariance of the moment map, μK\mu_{K} meets it>0∗i\mathfrak{t}^{*}_{>0} transversally, so that YY is a smooth manifold with tangent space TρY=dμK−1∣ρ(it∗)T_{\rho}Y=d\mu_{K}^{-1}\big|_{\rho}(i\mathfrak{t}^{*}) [GS84b, Theorem 26.7]. Thus we may choose any curve in YY that starts with ρ0=0\rho_{0}=0 and ρ˙0=V\dot{\rho}_{0}=V. ∎

Let ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert be a pure state such that μK(ρ)∈it>0∗\mu_{K}(\rho)\in i\mathfrak{t}^{*}_{>0} is a point on a facet of the moment polytope corresponding to the inequality (−,H)≥c(-,H)\geq c. Then

Since (μK(ρt),H)≥c(\mu_{K}(\rho_{t}),H)\geq c is an inequality for the moment polytope, it follows that (ω,H)=0(\omega,H)=0—for otherwise we could walk through the facet! On the other hand, (2.14) shows that

Therefore, H∈itH\in i\mathfrak{t} is necessarily an element of the Lie algebra of the TT-stabilizer of ρ\rho, i.e., Hρ=[π(H),ρ]=0H_{\rho}=[\pi(H),\rho]=0. This implies that d(μK,H)∣ρ=0d(\mu_{K},H)\big|_{\rho}=0 by (2.13), but also that ∣ψ⟩\ket{\psi} is an eigenvector of π(H)\pi(H), with corresponding eigenvalue ⟨ψ∣π(H)∣ψ⟩=(μK(ρ),H)=c\braket{\psi|\pi(H)|\psi}=(\mu_{K}(\rho),H)=c. ∎

In the language of Klyachko, the eigenvalue equation (2.19) is called the selection rule which is satisfied by a quantum state that is pinned to a facet of the moment polytope [Kly09]. Thus pinned states live on a potentially much lower-dimensional subspace of the Hilbert space, with potential implications on the physics.

It is an interesting question if and under which circumstances states in concrete systems are pinned. For example, it is an empirical fact that many molecules are well-explained by assuming that the natural occupation numbers are close to 0 and 1 (pinning), so that the global state can be well-approximated by a Slater determinant (the corresponding selection rule), which is a first step to Hartree–Fock theory and the Aufbau principle. Thus it is not be unreasonable to wonder if approximate pinning might hold for some of the other defining inequalities of the moment polytope. See [Kly09, Kly13] for preliminary investigations in the context of small molecules and magnetism and [SGC13] for a study of pinning in a model with small harmonic interactions.

Crucially, the selection rule is stable at least in an elementary sense. We phrase the following result in terms of the trace norm ∥X∥1:=\tr∣X∣\lVert X\rVert_{1}:=\tr\lvert X\rvert, which has a useful operational meaning (but this choice is completely arbitrary since the proof is based on a purely topological argument):

and δ(ε)↘0\delta(\varepsilon)\searrow 0 as ε↘0\varepsilon\searrow 0.

is well-defined. Clearly, δ(ε)\delta(\varepsilon) is monotonic in ε\varepsilon, and δ(0)=0\delta(0)=0 by Section 2.3.

For concrete applications, it might be interesting to obtain explicit bounds of the form δ(ε)≤Lε\delta(\varepsilon)\leq L\varepsilon. So far this has only been achieved in rather special situations [SGC13, BRGBS13]. It might be possible to obtain a general solution by carefully analyzing the local model for symplectic group actions [GS82a, GS84a, Mar85].

4 Kronecker coefficients, Schur–Weyl duality, and Plethysms

In this section we describe more explicitly the representation-theoretic content of Theorem 2.11 for Problems 2 and 2.

Thus the Kronecker coefficients can be equivalently defined as the dimension of the invariant subspace in a triple tensor product of irreducible representations of the symmetric group:

In particular, we find that each Kronecker coefficient only depends on the triple of Young diagrams rather than the concrete values chosen for aa, bb and cc (but of course aa, bb and cc have to be chosen at least as large as the number of rows of the Young diagrams). The role of the Kronecker coefficients for the one-body quantum marginal problem has first been observed in [CM06] by using the spectrum estimation theorem (cf. [Kly04, CHM07] and the proof of Theorem 9.6). They also play a fundamental role in representation theory [Ful97] and in Mulmuley and Sohoni’s geometric complexity theory approach to the P\mathbf{P} vs. NP\mathbf{NP} problem in computer science [MS01, MS08, Mul07, BLMW11] (see Section 6.1), and they occur in the “quantum method of types” [Har05]. In Chapter 6 we will give an efficient algorithm for their computation.

There is a different, asymmetric way of defining the Kronecker coefficients that is also quite useful. For this, we recall that the irreducible representations of the symmetric group are self-dual, i.e., [λ]≅[λ]∗[\lambda]\cong[\lambda]^{*} [JK81, §2.1]. Therefore,

for the space of GG-equivariant linear maps, or GG-linear maps between two representations VV and WW. For irreducible VV and WW, Schur’s lemma asserts that

It follows that gα,β,γg_{\alpha,\beta,\gamma} can also be defined as the multiplicity of [α][\alpha] in the tensor product [β]⊗[γ][\beta]\otimes[\gamma] of two irreducible representations of the symmetric group:

In particular, for [γ]=1[\gamma]=\mathbf{1} the trivial representation of SkS_{k} we obtain that gα,β,1=δα,βg_{\alpha,\beta,\mathbf{1}}=\delta_{\alpha,\beta}. In view of Schur–Weyl duality, this implies that

This equation corresponds to the one-body quantum marginal problem for n=2n=2 particles and is therefore the bipartite counterpart of (2.21). The fact that the irreducible representations of the two factors are perfectly paired is the representation-theoretic version of the fact that the marginals of a bipartite pure state are isospectral (Chapter 2)—indeed, the latter is a direct consequence of (2.25) and Theorem 2.11.

Geometric Quantization

Before we proceed, we offer a word of caution for people acquainted with the theory of geometric quantization [GS77, GS84b, Woo92]. Although we formally use a similar mathematical framework as in geometric quantization, the physical interpretation is markedly different. Unlike in geometric quantization, our quantum states do not arise via some quantization procedure from a classical symplectic phase space. On the contrary, in the mathematical modeling of the quantum marginal problem the projective space of pure states corresponds to the classical phase space, while its description in terms of the representations that occur in the ring of regular functions can be seen as its ‘‘quantization’’. The ‘‘semiclassical limit’’ k→∞k\rightarrow\infty in which we recover the description of the moment polytope plays a purely purely mathematical role (cf. Section 6.6).

Chapter 3 Solving The One-Body Quantum Marginal Problem

In this chapter we review some of the history of the one-body quantum marginal problem that culminated in Klyachko’s general solution and give some concrete examples. We then present a different approach to the problem of computing moment polytopes for projective space, which we have seen subsumes the one-body quantum marginal problem and its variants. Significantly, our geometric approach completely avoids many technicalities that have appeared in previous solutions to the problem, such as Schubert calculus, and it can be readily implemented algorithmically. We illustrate our method with a number of illustrative examples.

The results in this chapter are based on unpublished joint work in progress with Michèle Vergne.

The history of the quantum marginal problem goes back at least to the late 1950s, where it had been observed that the ground state energy of a two-body Hamiltonian is a function of the two-body reduced density matrices only [Löw55, May55]. The main focus was therefore on the two-body nn-representability problem—given a two-body density matrix, is it compatible with a state of nn fermions [Col63, Rus69, CY00, Col01]? Some results had also been obtained for the one-body marginals. For instance, Coleman proved that a first-order density matrix γ1\gamma_{1} is compatible with a (not necessarily pure) state of nn fermions if and only if the natural occupation numbers do not exceed 11—that is, if and only if the Pauli principle is satisfied [Col63, Theorem 9.3].

(see Figure 3.3). This was perhaps the first non-trivial solution of Chapter 2. Remarkably, the resulting polytope is only three-dimensional; this coincides with the fact that any pure state can be written as a linear combination of only 8 Slater determinants as was proved by Ruskai and Kingsley (while dim⁡it∗=5\dim i\mathfrak{t}^{*}=5 and dim⁡H=20\dim\mathcal{H}=20). It is interesting to observe that the equality λ1+λ6=1\lambda_{1}+\lambda_{6}=1 strengthens the Pauli principle λ1≤1\lambda_{1}\leq 1.

(see Figure 3.3). In fact, these inequalities hold for any multipartite quantum state, but they are in general not sufficient for compatibility (see Section 9.7 for an elementary proof based on the variational principle). In the meanwhile, the three-qutrit polytope had already been computed by Franz [Fra02], as was only later recognized.

Subsequently, Bravyi solved the case of mixed states of two qubits by a remarkable explicit argument [Bra04]. Here, the necessary and sufficient conditions are given by

The connection of the one-body quantum marginal problem to representation theory was first observed in [CM06] by using quantum information methods rather than the theory of Section 2.2 (cf. [CHM07]). Shortly after, a completely general solution was given by Klyachko both for distinguishable particles [Kly04] and for fermions [KA08, Alt08]. Almost simultaneously, Daftuar and Hayden had published a solution to the “one-sided” problem that concerns the constraints between the eigenvalues of ρAB\rho_{AB} and ρA\rho_{A} [DH04]. Both results build on previous work by Berenstein and Sjamaar [BS00], who used geometric invariant theory to study the moment polytope for projections of coadjoint orbits; this latter work in turn generalizes techniques from Klyachko’s seminal paper on Weyl’s problem [Kly98] (see the discussion at the end of the preceding chapter). We refer to [Kly04, Knu09] for eloquent expositions of the method. More recently, Ressayre has refined the result of Berenstein and Sjamaar to give an irredundant set of necessary and sufficient inequalities in a very general mathematical setup [Res10b, Res10a]. We remark that a variant of the quantum marginal problem for Gaussian states has been considered in [EG08] (mathematically, this scenario is covered by a more general convexity theorem for non-compact manifolds with proper moment maps).

1 Summary of Results

Our approach in the following is based on analyzing the non-trivial facets in terms of the local differential geometry of their preimages up to second order. Conceptually, such an analysis should be sufficient since the moment map is locally quadratic.

In Section 3.2 we start by studying the moment map to first order. It is well-known that interior points of non-trivial facets are critical values for (μK,H)(\mu_{K},H), where HH is the normal vector of the facet. Indeed, this is equivalent to the selection rule from Section 2.3. We show that as a consequence any non-trivial facet of ΔK\Delta_{K} is necessarily contained in a hyperplane spanned by weights of the representation H\mathcal{H}. This already reduces the problem to a finite set of candidates.

In Section 3.3 we then consider the Hessian of the moment map. If a state is mapped into the interior of a non-trivial facet of the polytope then this implies a positive semidefiniteness of the corresponding Hessian in certain tangent directions. We exploit this fact to obtain another necessary condition that is satisfied by non-trivial facets (−,H)≥c(-,H)\geq c of the moment polytope. To state it, let n−(H<0)\mathfrak{n}_{-}(H<0) denote the direct sum of negative root spaces gα\mathfrak{g}_{\alpha} with (α,H)<0(\alpha,H)<0 and H(H<c)\mathcal{H}(H<c) the sum of eigenspaces of π(H)\pi(H) with eigenvalue smaller than cc. Then we show that there necessarily exists an eigenvector ∣ψ⟩∈H\ket{\psi}\in\mathcal{H} of π(H)\pi(H) with eigenvalue cc such that the map

is an isomorphism. Conversely, we prove that any inequality (−,H)≥c(-,H)\geq c that satisfies the above two necessary conditions is a valid inequality of the moment polytope. We thus obtain a complete description of the moment polytope ΔK\Delta_{K} in terms of what we call inequalities of Ressayre type (Section 3.3 and Theorem 3.14).

Our notion of a Ressayre-type inequality is closely related to Ressayre’s notion of a dominant pair, and our approach is inspired by his ideas [Res10b, Res10a]. Our description of the moment polytope is also related to a result by Brion [Bri99], as we explain further below. However, while the more refined results of [Bri99, Res10b, Res10a] are established using high-powered algebraic geometry, we proceed in essence by a straightforward differential-geometric analysis, combined with Theorem 2.11.

In Section 3.4, we illustrate the method with some examples. We remark that, crucially, our description of the moment polytope obtained in Theorem 3.14 can be completely automatized: It is straightforward to determine all inequalities of Ressayre type in a mechanical fashion, and hence also on a computer.

2 The Torus Action

A facet of the moment polytope is trivial if it is of the form (−,Zα)≥0(-,Z_{\alpha})\geq 0 for some positive root α∈RG,+\alpha\in R_{G,+}. Otherwise, the facet is called non-trivial.

Non-trivial facets have also been called “general” in the literature [Bri99]. We record the following straightforward observation:

Any non-trivial facet of ΔK\Delta_{K} meets the relative interior it>0∗i\mathfrak{t}^{*}_{>0} of the positive Weyl chamber.

Any facet of ΔK\Delta_{K} that does not intersect the relative interior of the positive Weyl chamber is fully contained in

which is a finite arrangement of hyperplanes. Since by assumption the facet is of codimension one, it has to be contained in a single one of these hyperplanes. Thus its normal vector is either ±Zα\pm Z_{\alpha} for some positive root α\alpha. If it was −Zα-Z_{\alpha} then the moment polytope would be strictly contained in the hyperplane (−,Zα)=0(-,Z_{\alpha})=0, and therefore not of maximal dimension, in contradiction with our assumption. We conclude that the facet is of the form (−,Zα)≥0(-,Z_{\alpha})\geq 0, and therefore trivial. ∎

We now consider the moment map for the action of the maximal torus T⊆KT\subseteq K,

For the quantum marginal problem, this amounts to considering diagonal entries rather than eigenvalues. Let H=⨁ω∈ΩHω\mathcal{H}=\bigoplus_{\omega\in\Omega}\mathcal{H}_{\omega} be the decomposition of H\mathcal{H} into weight spaces, and ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert a pure state with ∣ψ⟩=∑ωψω∣ω⟩\ket{\psi}=\sum_{\omega}\psi_{\omega}\ket{\omega} decomposed accordingly. Then μT\mu_{T} has the following concrete description:

The set of critical values of μT\mu_{T} is equal to the union of the codimension-one convex hulls of subsets of weights.

We now derive a basic necessary condition that cuts down the defining inequalities of the moment polytope to a finite set of candidates.

Any non-trivial facet of ΔK\Delta_{K} is contained in an affine hyperplane spanned by a subset of weights.

By Section 3.2, the intersection of any non-trivial facet with the interior of the positive Weyl chamber it>0∗i\mathfrak{t}^{*}_{>0} is non-empty. Each point in this intersection is a critical value for (μK,H)=(μT,H)(\mu_{K},H)=(\mu_{T},H) by selection rule (Section 2.3), hence of μT\mu_{T}, and therefore contained in an affine hyperplane spanned by a subset of weights (Section 3.2). Since this is true for all points in the intersection, which contains the relative interior of the facet, it follows that the facet is in fact contained in a single such hyperplane. ∎

3 Facets of the Moment Polytope

Throughout this section, let ρ\rho be the preimage of a point μK(ρ)∈it>0∗\mu_{K}(\rho)\in i\mathfrak{t}^{*}_{>0} on the facet (−,H)≥c(-,H)\geq c of the moment polytope. We have seen that the selection rule Section 2.3 shows that ρ\rho is a critical point of the component (μK,H)(\mu_{K},H), and we have used this in Section 3.2 to gain information on the set of possible facets.

It is thus natural to continue by studying the Hessian of (μK,H)(\mu_{K},H), which is a quadratic form Q(−,−)Q(-,-) on the tangent space at ρ\rho. Since ρ\rho is a critical point, we can compute it by

for all anti-Hermitian operators X∈u(H)X\in\mathfrak{u}(\mathcal{H}). It follows that [GS84b, (32.8)]

for all X,Y∈u(H)X,Y\in\mathfrak{u}(\mathcal{H}) (which is indeed symmetric in XX and YY). We now decompose

where H(H<c)=⨁ω:(ω,H)<cHω\mathcal{H}(H<c)=\bigoplus_{\omega:(\omega,H)<c}\mathcal{H}_{\omega} is the sum of the eigenspaces of the Hermitian operator π(H)\pi(H) with eigenvalue less than cc, etc. Then we have the following interpretation of the index of the Hessian (the dimension of a maximal subspace on which the quadratic form QQ is negative definite):

The index of the Hessian at ρ\rho is equal to the real dimension of H(H<c)\mathcal{H}(H<c).

Since ψ\psi itself is in H(H=c)\mathcal{H}(H=c) by the selection rule, the claim follows. ∎

Since (μK(ρ),H)=c(\mu_{K}(\rho),H)=c and d(μK,H)∣ρ=0d(\mu_{K},H)\big|_{\rho}=0, the Hessian is necessarily positive semidefinite on the subspace of those tangent vectors that get mapped to it∗i\mathfrak{t}^{*}. Indeed, let V∈dμK−1∣ρ(it∗)V\in d\mu_{K}^{-1}\big|_{\rho}(i\mathfrak{t}^{*}) and consider the curve ρt\rho_{t} from Section 2.3. Then,

which shows that, indeed, Q(V,V)≥0Q(V,V)\geq 0. The subspace of all such VV can be computed in a different way. For this, let r=⨁α∈RG,+kα\mathfrak{r}=\bigoplus_{\alpha\in R_{G,+}}\mathfrak{k}_{\alpha} denote the sum of the root spaces of the compact Lie algebra as in (2.5) and

the corresponding subspace of tangent vectors. Then,

The Hessian at ρ\rho is positive semidefinite on the subspace

The first claim is a reformulation of the fact that the KK-stabilizer of any λ∈it>0∗\lambda\in i\mathfrak{t}^{*}_{>0} is TT, while k=t⊕r\mathfrak{k}=\mathfrak{t}\oplus\mathfrak{r}. The second claim follows from the first, since μK(ρ)∈it>0∗\mu_{K}(\rho)\in i\mathfrak{t}^{*}_{>0} and dμK(Rρ)=\ad∗(R)μK(ρ)d\mu_{K}(R_{\rho})=\ad^{*}(R)\mu_{K}(\rho) by equivariance of the moment map. ∎

The tangent space at ρ\rho decomposes as a direct sum

and the Hessian QQ is block-diagonal with respect to this decomposition.

For the first claim we only need to show that M∩Mω=0M\cap M^{\omega}=0, which is standard (see, e.g., [GS82a, Lemma 6.7]): Let R∈rR\in\mathfrak{r}. Suppose that Rρ∈MωR_{\rho}\in M^{\omega}. That is,

For the second claim, observe that (3.6) immediately implies that

for all Rρ∈MR_{\rho}\in M and V∈MωV\in M^{\omega}, since [−iH,R]∈r[-iH,R]\in\mathfrak{r} and hence [−iH,R]ρ∈M[-iH,R]_{\rho}\in M. ∎

The index of the Hessian at ρ\rho is equal to twice the number of positive roots α∈RG,+\alpha\in R_{G,+} such that (α,H)>0(\alpha,H)>0.

Since the tangent map R↦RρR\mapsto R_{\rho} is injective (Section 3.3), we may instead consider the form

on r\mathfrak{r}. For this, observe that Q~\widetilde{Q} is block-diagonal with respect to r=⨁α∈RG,+kα\mathfrak{r}=\bigoplus_{\alpha\in R_{G,+}}\mathfrak{k}_{\alpha}, since for all R∈kαR\in\mathfrak{k}_{\alpha} and S∈kβS\in\mathfrak{k}_{\beta}, [[H,R],S]∈ikα±β[[H,R],S]\in i\mathfrak{k}_{\alpha\pm\beta}, while μK(ρ)∈it∗\mu_{K}(\rho)\in i\mathfrak{t}^{*}. And for each root space kα\mathfrak{k}_{\alpha}, we have that

where we have used the “Pauli matrices” Xα,Yα,ZαX_{\alpha},Y_{\alpha},Z_{\alpha} and their commutation relations (2.6). Likewise, Q~(iYα,iYα)=−2(α,H)(μK(ρ),Zα)\widetilde{Q}(iY_{\alpha},iY_{\alpha})=-2(\alpha,H)(\mu_{K}(\rho),Z_{\alpha}), while Q~(iXα,iYα)=0\widetilde{Q}(iX_{\alpha},iY_{\alpha})=0. Since (μK(ρ),Zα)>0(\mu_{K}(\rho),Z_{\alpha})>0, we conclude that the index of QQ is equal to twice the number of positive roots α\alpha with (α,H)>0(\alpha,H)>0. ∎

Ressayre Elements

So far we have used the Lie algebra k\mathfrak{k} of the compact Lie group in our analysis. We will now translate the preceding to the complexified setting. To this end, we consider the Lie algebra n−=⨁α∈RG,−gα\mathfrak{n}_{-}=\bigoplus_{\alpha\in R_{G,-}}\mathfrak{g}_{\alpha} of the negative unipotent subgroup, which plays a role analogous to r\mathfrak{r} for states ρ\rho that are mapped into the positive Weyl chamber (compare the following with Section 3.3).

The tangent map n−→H,X→π(X)∣ψ⟩\mathfrak{n}_{-}\rightarrow\mathcal{H},X\to\pi(X)\ket{\psi} is injective.

Let E−:=∑α∈RG,+zαE−αE_{-}:=\sum_{\alpha\in R_{G,+}}z_{\alpha}E_{-\alpha} be an arbitrary element in n−\mathfrak{n}_{-}. Since π(E±α)†=π(E∓α)\pi(E_{\pm\alpha})^{\dagger}=\pi(E_{\mp\alpha}), we find that π(E−)†=π(E+)\pi(E_{-})^{\dagger}=\pi(E_{+}) with E+:=∑α∈RG,+zˉαEαE_{+}:=\sum_{\alpha\in R_{G,+}}\bar{z}_{\alpha}E_{\alpha} (the Cartan involution of E−E_{-}). Therefore,

so that by using μK(ρ)∈it>0∗\mu_{K}(\rho)\in i\mathfrak{t}^{*}_{>0} we find that

In contrast to Section 3.3, which continues to hold true if μK(ρ)\mu_{K}(\rho) is mapped to the relative interior of a different Weyl chamber (since KK is invariant under the Weyl group), it is important in Section 3.3 to choose the negative unipotent subgroup (relative to the choice of positive Weyl chamber). For example, consider an irreducible GG-representation H=VG,λ\mathcal{H}=V_{G,\lambda} with highest weight λ∈it>0∗\lambda\in i\mathfrak{t}^{*}_{>0} and highest weight vector ∣λ⟩\ket{\lambda}. Then μK(∣λ⟩⟨λ∣)=λ∈it>0∗\mu_{K}(\lvert\lambda\rangle\langle\lambda\rvert)=\lambda\in i\mathfrak{t}^{*}_{>0} by Section 2.2, and the “lowering operators” in n−\mathfrak{n}_{-} act indeed injectively (all π(E−α)∣λ⟩\pi(E_{-\alpha})\ket{\lambda} live in different weight spaces and are non-zero, since π(Eα)π(E−α)∣λ⟩=π(Zα)∣λ⟩=(λ,Zα)∣λ⟩≠0\pi(E_{\alpha})\pi(E_{-\alpha})\ket{\lambda}=\pi(Z_{\alpha})\ket{\lambda}=(\lambda,Z_{\alpha})\ket{\lambda}\neq 0). On the other hand, the “raising operators” in the positive nilpotent Lie algebra n+\mathfrak{n}_{+} annihilate the highest weight vector (by definition).

We now decompose the Lie algebra n−\mathfrak{n}_{-} similarly to (3.7),

where n−(H<0)=⨁α∈RG,−:(α,H)<0gα\mathfrak{n}_{-}(H<0)=\bigoplus_{\alpha\in R_{G,-}:(\alpha,H)<0}\mathfrak{g}_{\alpha} is the sum of the complex root spaces with negative HH-weight (α,H)<0(\alpha,H)<0, etc. By combining Lemmas 3.3 and 3.3 and using RG,−=−RG,+R_{G,-}=-R_{G,+}, we observe that

Note that π(n−(H<0))H(H=c)⊆H(H<c)\pi(\mathfrak{n}_{-}(H<0))\mathcal{H}(H=c)\subseteq\mathcal{H}(H<c), since for any ∣ψ⟩∈H(H=c)\ket{\psi}\in\mathcal{H}(H=c) and X∈gαX\in\mathfrak{g}_{\alpha} we have that

Thus we obtain the following important result:

The fact that ∣ψ⟩∈H(H=c)\ket{\psi}\in\mathcal{H}(H=c) is just a reformulation of the selection rule. By the preceding discussion, the tangent map is well-defined as a map from n−(H<0)\mathfrak{n}_{-}(H<0) to H(H<c)\mathcal{H}(H<c); it is injective by Section 3.3 and surjective since the dimensions agree according to (3.10). ∎

We now prove a partial converse to Section 3.3. Our proof is inspired by the argument of Ressayre [Res10b].

Suppose there exists ∣ψ⟩∈H(H=c)\ket{\psi}\in\mathcal{H}(H=c) such that the tangent map

is surjective. Then (−,H)≥c(-,H)\geq c is a valid inequality for the moment polytope.

Its differential at (1,∣ψ⟩)(1,\ket{\psi}) is the linear map

The assumption implies that this map is surjective. It follows that Π(N−)H(H≥c)⊆H\Pi(N_{-})\mathcal{H}(H\geq c)\subseteq\mathcal{H} contains a small Euclidean ball around ∣ψ⟩\ket{\psi}. In particular, any polynomial that is zero on Π(N−)H(H≥c)\Pi(N_{-})\mathcal{H}(H\geq c) is zero everywhere on H\mathcal{H}.

We now prove the inequality. By the description of the moment polytope of Theorem 2.11, it suffices to show that (λ/k,H)≥c(\lambda/k,H)\geq c for all highest weights λ\lambda such that VG,λ∗⊆Rk(H)V^{*}_{G,\lambda}\subseteq R_{k}(\mathcal{H}). Recall that the highest weight of VG,λ∗V^{*}_{G,\lambda} is λ∗=−w0λ\lambda^{*}=-w_{0}\lambda, where w0w_{0} is the longest Weyl group element that flips the positive and negative roots. Consider a lowest weight vector, i.e., a homogeneous polynomial P∈Rk(H)P\in R_{k}(\mathcal{H}) that is a weight vector of weight −λ-\lambda and stabilized by N−N_{-}. Then π(H)P=−(λ,H)P\pi(H)P=-(\lambda,H)P and the restriction of PP to H(H≥c)\mathcal{H}(H\geq c) is non-zero by our discussion above. But this restriction is an element of Rk(H(H≥c))=\Symk(H(H≥c))∗R_{k}(\mathcal{H}(H\geq c))=\Sym^{k}(\mathcal{H}(H\geq c))^{*}, the space of homogeneous polynomials of degree kk on H(H≥c)\mathcal{H}(H\geq c). Thus all HH-weights in Rk(H(H≥c))R_{k}(\mathcal{H}(H\geq c)) are less or equal to −kc-kc. It follows that −(λ,H)≤−kc-(\lambda,H)\leq-kc, hence (λ/k,H)≥c(\lambda/k,H)\geq c, as we set out to prove. ∎

We remark that Section 3.3 holds unconditionally without any assumption on the dimension of the moment polytope ΔK\Delta_{K}. We summarize our findings in the following definition and theorem:

An inequality (−,H)≥c(-,H)\geq c is said to be of Ressayre type if

(−,H)=c(-,H)=c is an affine hyperplane spanned by a subset of weights.

There exists ∣ψ⟩∈H(H=c)\ket{\psi}\in\mathcal{H}(H=c) such that the map

We note that the first condition is invariant under the action of the Weyl group.

This follows directly from Section 3.2, Section 3.3 and Section 3.3. ∎

Theorem 3.14gives a complete description of the moment polytope of the projective space of an arbitrary GG-representation H\mathcal{H} (under the assumption that ΔK\Delta_{K} is of maximal dimension). The set of inequalities thus obtained may still be redundant (i.e., not all inequalities necessarily correspond to facets of the moment polytope). In contrast, Ressayre’s well-covering pairs [Res10b, Res10a] characterize the facets of the moment polytope precisely. Our characterization is also related to [Bri99, Theorem 2], which uses algebraic geometry to characterize non-trivial faces of arbitrary codimension. Unlike Section 3.3, it relies on an assumption about lower-dimensional moment polytopes, which can in principle be obtained recursively.

It is straightforward to enumerate all inequalities of Ressayre type. Since there are only finitely many weights, the first condition in Section 3.3 cuts down the number of possible inequalities down to a finite list of candidates, and for each such candidate (−,H)≥c(-,H)\geq c, the second condition can be easily checked: Indeed, we only need to verify that dim⁡n−(H<0)=dim⁡H(H<c)\dim\mathfrak{n}_{-}(H<0)=\dim\mathcal{H}(H<c) and that the determinant polynomial

is non-zero (take the determinant with respect to any fixed pair of bases). Both steps can easily be implemented in a short computer program.

4 Examples

We now illustrate the method by considering some of the examples discussed at the beginning of the chapter.

We will start by showing that the solution of the one-body quantum marginal problem for nn qubits is indeed given by the polygonal inequalities (3.2), which we recall are given by

By using that λk,1+λk,2=1\lambda_{k,1}+\lambda_{k,2}=1 for each qubit, we find that (3.12) is equivalent to the following inequality for the moment polytope ΔK\Delta_{K},

which we will now prove by using the criterion of Section 3.3.

On the other hand, there is precisely one negative root with (−,H)<0(-,H)<0, namely −αn-\alpha_{n}. Therefore,

where the generator E−nE_{-n} acts as the “lowering operator” ∣1⟩⟨0∣\lvert 1\rangle\langle 0\rvert on the nn-th tensor factor of H\mathcal{H}. But then π(E−n)∣0…0⟩=∣0…01⟩\pi(E_{-n})\ket{0\dots{}0}=\ket{0\dots{}01}, so that the map

is indeed an isomorphism for ∣ψ⟩=∣0…0⟩∈H(H=2−n)\ket{\psi}=\ket{0\dots{}0}\in\mathcal{H}(H=2-n). Thus Section 3.3 shows that the polygonal inequality (3.12) is indeed valid. We remark that the nn weights corresponding to (3.13) span the hyperplane (−,H)=2−n(-,H)=2-n and hence the inequality is of Ressayre type—but we did not need this to apply the proposition. The other polygonal inequalities follow from the above since the solution to the one-body quantum marginal problem is symmetric under permutation of the qubits.

To see that there are no further constraints, we could now verify that the polygonal inequalities imply all other Ressayre-type inequalities (which, according to Theorem 3.14, characterize the moment polytope completely). In the case at hand, we observe instead that for each k≤n−2k\leq n-2 as well as for k=nk=n the quantum states

and likewise for their permutations. These points are just the vertices of the convex polytope cut out by the polygonal inequalities (3.2), which is therefore equal to the moment polytope.

Mixed States of Two Qubits

We now consider the mixed-state one-body quantum marginal problem for two qubits. We will focus on the last constraint in (3.3),

which by symmetry can be reduced to the following two linear inequalities

In [Bra04], the inequalities are proved by a “formidable” two-page calculation that is tailored towards the two-qubit scenario. In contrast we will obtain (3.14) completely mechanically by using the general machinery developed in Section 3.3.

is an isomorphism for some ∣ψ⟩∈H(H=0)\ket{\psi}\in\mathcal{H}(H=0). We can do so completely mechanically by computing the determinant polynomial (3.11) with respect to the bases in (3.15) and (3.16). Using that each EX,ijE_{X,ij} acts by ∣i⟩⟨j∣\lvert i\rangle\langle j\rvert on the corresponding tensor factor, we readily find that it is given by

and thus is indeed non-zero. For example, ∣ψ⟩=∣121⟩+∣112⟩+∣213⟩∈H(H=0)\ket{\psi}=\ket{121}+\ket{112}+\ket{213}\in\mathcal{H}(H=0) is a choice for which (3.17) is an isomorphism. Thus Section 3.3 shows that the first inequality in (3.14) is indeed a valid inequality for the one-body marginal problem for mixed states of two qubits. The second inequality can be established in a completely identical fashion.

Three Qutrits

corresponding to the facet h7h_{7} in [Fra02, Proposition 5.1].

The significance of this facet is that it is neither trivial nor does it contain the vertex λA,1=λB,1=λC,1=1\lambda_{A,1}=\lambda_{B,1}=\lambda_{C,1}=1 of the moment polytope that corresponds to product states ∣000⟩\ket{000} – unlike in the case of nn qubits, where the polygonal inequalities (3.2) are saturated for product states (cf. Figure 3.3). As was pointed out in [Fra02, Remark 5.3], this shows that in general the moment polytope is not determined by the trivial facets together with the local cone at the point corresponding to the product state (more generally, the local cone at the highest weight of an irreducible representation).

Let K=\SU(3)×\SU(3)×\SU(3)K=\SU(3)\times\SU(3)\times\SU(3) and G=\SL(3)×\SL(3)×\SL(3)G=\SL(3)\times\SL(3)\times\SL(3) with their tensor product action on the Hilbert space H\mathcal{H}. Using the same notation as in the preceding example, we find that (3.18) can be written in the form

and thus (3.18) is indeed a valid inequality.

Three Fermions with Total Spin 1/21/2

(In analogy to (2.25), each Young diagram is paired with its transpose.) The different summands in the decomposition correspond to different sectors of total spin J=1/2,3/2J=1/2,3/2. Now suppose that we know in addition that the global state is a pure state in the sector for total spin J=1/2J=1/2:

Then the problem of determining the relation between the orbital and spin occupation numbers amounts to computing the moment polytope for the GG-representation H\mathcal{H}. This illustrates how representations other than those in Table 2.3 may enter the picture due to physical considerations. In [KA08, §6.1] it was observed that there are five inequalities which are “apparently independent” of the orbital dimension dd, as they verified for d=4,5d=4,5. Their first equation is

where λ1≥⋯≥λd\lambda_{1}\geq\dots\geq\lambda_{d} denote the natural occupation numbers of the first-order orbital density matrix γO\gamma_{O}, normalized to trace 33, and μ1≥μ2\mu_{1}\geq\mu_{2} the eigenvalues of the spin density matrix ρS=γS/3\rho_{S}=\gamma_{S}/3, normalized to trace 11.

We will now prove (3.19) for arbitrary dd. For this, we will use the following description of the irreducible \GL(d)\GL(d)-representation V\vbox\vbox\vbox\hruleheight=0.3pt\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997pt\hruleheight=0.3pt\vskip−0.3pt\vbox\hruleheight=0.3pt\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997pt\hruleheight=0.3pt\vskip−0.3ptdV^{d}_{\hskip 0.0pt\vbox{\vbox{\vbox{\hrule height=0.3pt\hbox{\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt}\hrule height=0.3pt}\vskip-0.3pt\vbox{\hrule height=0.3pt\hbox{\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt}\hrule height=0.3pt}\vskip-0.3pt}}\hskip 0.0pt} (see, e.g., [Ful97]): Let VV denote the vector space with one basis vector ⟩\ket{\text{\scriptsize\hskip 0.0pt\vbox{\vbox{\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfila\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfilb\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfilc\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt}}\hskip 0.0pt}} for each filling of the Young diagram with numbers a,b,c∈{1,…,d}a,b,c\in\{1,\dots,d\}. Then V\vbox\vbox\vbox\hruleheight=0.3pt\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997pt\hruleheight=0.3pt\vskip−0.3pt\vbox\hruleheight=0.3pt\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997pt\hruleheight=0.3pt\vskip−0.3ptdV^{d}_{\hskip 0.0pt\vbox{\vbox{\vbox{\hrule height=0.3pt\hbox{\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt}\hrule height=0.3pt}\vskip-0.3pt\vbox{\hrule height=0.3pt\hbox{\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt}\hrule height=0.3pt}\vskip-0.3pt}}\hskip 0.0pt} can be identified with the quotient of VV by the relations

It is not hard to see that a basis of V\vbox\vbox\vbox\hruleheight=0.3pt\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997pt\hruleheight=0.3pt\vskip−0.3pt\vbox\hruleheight=0.3pt\vruleheight=3.52pt,width=0.3pt,depth=0.87997ptto4.4pt\hfil\vruleheight=3.52pt,width=0.3pt,depth=0.87997pt\hruleheight=0.3pt\vskip−0.3ptdV^{d}_{\hskip 0.0pt\vbox{\vbox{\vbox{\hrule height=0.3pt\hbox{\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt}\hrule height=0.3pt}\vskip-0.3pt\vbox{\hrule height=0.3pt\hbox{\vrule height=3.52pt,width=0.3pt,depth=0.87997pt\hbox to4.4pt{\hfil}\vrule height=3.52pt,width=0.3pt,depth=0.87997pt}\hrule height=0.3pt}\vskip-0.3pt}}\hskip 0.0pt} is given by those ⟩\ket{\text{\scriptsize\hskip 0.0pt\vbox{\vbox{\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfila\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfilb\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfilc\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt}}\hskip 0.0pt}} with a≤ba\leq b, a<ca<c (in the literature, these fillings are known as the semistandard Young tableaux of shape ). Each vector ⟩\ket{\text{\scriptsize\hskip 0.0pt\vbox{\vbox{\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfila\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfilb\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfilc\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt}}\hskip 0.0pt}} is a weight vector of weight ω(H)=Ha,a+Hb,b+Hc,c\omega(H)=H_{a,a}+H_{b,b}+H_{c,c}, and the generators EijE_{ij} of gij\mathfrak{g}_{ij} send ⟩\ket{\text{\scriptsize\hskip 0.0pt\vbox{\vbox{\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfila\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfilb\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfilc\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt}}\hskip 0.0pt}} to the sum of all vectors that arise by replacing a single jj by ii. For example,

where we have used the first relation in (3.20).

where we have used that μ1−μ2=1−2μ2\mu_{1}-\mu_{2}=1-2\mu_{2}. Furthermore,

But then (3.21) shows that the tangent map n−(H<0)→H(H<−3)\mathfrak{n}_{-}(H<0)\rightarrow\mathcal{H}(H<-3) is an isomorphism for ⟩⊗|1⟩\ket{\psi}=\ket{\text{\scriptsize\hskip 0.0pt\vbox{\vbox{\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfil1\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfil1\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt\vbox{\hrule height=0.3pt\hbox{\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt\hbox to7.4pt{\hfil2\hfil}\vrule height=5.92001pt,width=0.3pt,depth=1.47997pt}\hrule height=0.3pt}\vskip-0.3pt}}\hskip 0.0pt}}\otimes\ket{1}. By Section 3.3, it follows that the inequality (3.19) is true for all dd. In the same way the other four inequalities asserted in [KA08, §6.1] can be proved for arbitrary dd; but this will be presented elsewhere.

We have developed a small computer program using Sage [S+13] that uses the methods of this chapter to automatically enumerate and verify inequalities for moment polytopes of projective spaces by using the method developed in this chapter.

5 Discussion

In Section 4.5 we describe a rather different approach to the computation of moment polytopes which is based on Kirwan’s gradient flow [Kir84a]. The resulting numerical algorithm is probabilistic in nature but has the advantage of being applicable to more general projective subvarieties than projective space, such as the SLOCC entanglement classes introduced in Chapter 4.

Chapter 4 Multipartite Entanglement

In this chapter we consider entanglement in multipartite quantum systems. We show that in the case of pure states, features of the global entanglement can already be extracted from local information alone. This is achieved by associating with any given class of entanglement an entanglement polytope—a geometric object which characterizes the one-body marginals compatible with that class. In this way we obtain local witnesses for the multipartite entanglement of a global pure state. Our approach is applicable to systems of arbitrary size and statistics, and it can be generalized to states affected by low levels of noise. We also describe a gradient flow technique that can be used for entanglement distillation and the computation of moment polytopes.

The results in this chapter have been obtained in collaboration with Matthias Christandl, Brent Doran, David Gross and Konstantin Wernli, and they have appeared in [WDGC13].

Entanglement is a uniquely quantum mechanical feature. It is responsible for fundamentally new effects – such as quantum non-locality – and constitutes the basic resource for concrete tasks such as quantum computing [Vid03] and interferometry beyond the standard limit [LBS+04, GLM04]. Considerable efforts have been directed at obtaining a systematic characterization of multi-particle entanglement; however, our understanding remains limited as the complexity of entanglement scales exponentially with the number of particles [DVC00].

In this chapter, we show that, for pure quantum states, single-particle information alone can serve as a powerful witness to multipartite entanglement. In fact, we find that a finite list of linear inequalities characterizes the eigenvalues of the one-body reduced density matrices in any given class of entanglement. Their violation provides a criterion for witnessing multipartite entanglement that (i) only requires access to a linear number of degrees of freedom, (ii) applies universally to quantum systems of arbitrary size and statistics, and (iii) distinguishes among many important classes of entanglement, including genuine multipartite entanglement. Geometrically, these inequalities cut out a hierarchy of polytopes, which captures all information about the global pure-state entanglement deducible from local information alone. Our methods are sufficiently robust to be applicable to situations where the state is affected by low levels of noise.

Formally, a pure state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert is said to be entangled if it cannot be written as a tensor product ∣ψ⟩≠∣ψ1⟩⊗⋯⊗∣ψn⟩\ket{\psi}\neq\ket{\psi_{1}}\otimes\dots\otimes\ket{\psi_{n}} [NC04]. Two states can be considered to belong to the same entanglement class if they can be converted into each other with finite probability of success using local operations and classical communication (stochastic LOCC, or SLOCC) [BPR+00, DVC00]. In physical terms, this corresponds to performing arbitrary quantum operations on each of the individual particles, where each operation may depend on outcomes of previous measurements on different particles and where we may post-select on measurement outcomes. We give a precise definition in Section 4.2. For small systems, these entanglement classes are well-understood. In the simplest scenario of three qubits, there exist two classes of genuinely entangled states of strikingly different nature: the first contains the famous Greenberger–Horne–Zeilinger (GHZ) state (∣000⟩+∣111⟩)/2(\ket{000}+\ket{111})/\sqrt{2}, which exhibits a particularly strong form of quantum correlations [GHZ89]; the second contains the W state (∣100⟩+∣010⟩+∣001⟩)/3(\ket{100}+\ket{010}+\ket{001})/\sqrt{3} [DVC00]. Whereas states in the W class can be approximated to arbitrary precision by states from the GHZ class, the converse is not true—implying stronger entanglement of the GHZ class [DVC00]. Already for four particles there exist infinitely many entanglement classes [VDDMV02], and the number of parameters required to determine the class grows exponentially with the particle number [DVC00]. As a result, only sporadic results have been obtained for larger systems, despite the enormous amount of literature dedicated to the problem. Mathematically, the characterization of SLOCC entanglement classes can be formulated in terms of invariant theory, studied since the 19th century—Cayley’s hyperdeterminant, e.g., appears as the 3-tangle [CKW00]. Similar techniques underpin modern developments, such as the geometric complexity theory approach to the P\mathbf{P} vs. NP\mathbf{NP} problem [BLMW11] (see Section 6.1).

Our approach to multipartite entanglement is based on establishing a connection to the one-body quantum marginal problem (Section 4.3). The crucial observation is that the one-body reduced density matrices ρ1,…,ρn\rho_{1},\dots,\rho_{n} or, equivalently, their eigenvalues λ⃗1,…,λ⃗n\vec{\lambda}_{1},\dots,\vec{\lambda}_{n} alone can already give considerable information about the entanglement of the global state, provided that it is pure. To make this precise, we consider the set of local eigenvalues λ⃗=(λ⃗1,…,λ⃗n)\vec{\lambda}=(\vec{\lambda}_{1},\dots,\vec{\lambda}_{n}) of the states in the closure X‾\overline{\mathcal{X}} of a given entanglement class X\mathcal{X}. Surprisingly, this set also forms a convex polytope (i.e., it is the convex hull of finitely many such vectors), and we call it the entanglement polytope ΔX\Delta_{\mathcal{X}} of the class. Entanglement polytopes immediately lead to a local criterion for witnessing multipartite entanglement: If the collection of eigenvalues λ⃗\vec{\lambda} of the one-body reduced density matrices of a pure quantum state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert does not lie in an entanglement polytope, then the given state cannot belong to the closure of the corresponding entanglement class X\mathcal{X} (Figure 4.1):

In other words, the criterion allows us to witness the presence of a highly entangled state by showing that its local eigenvalues are incompatible with all less-entangled classes. This way of reasoning is similar to the exclusion of a local hidden variable model by witnessing the violation of a Bell inequality. Strikingly, there are always only finitely many entanglement polytopes, and they naturally form a hierarchy: if a state in some class X\mathcal{X} can be approximated arbitrarily well by states from Y\mathcal{Y} then ΔX⊆ΔY\Delta_{\mathcal{X}}\subseteq\Delta_{\mathcal{Y}}. This reflects geometrically the fact that states in the second class are more powerful for quantum information processing.

To describe ΔX\Delta_{\mathcal{X}} mathematically and establish these claims, we work in the framework of Chapter 2. Using the characterization of SLOCC operations as invertible local operators g1⊗⋯⊗gng_{1}\otimes\dots\otimes g_{n} [DVC00], we find that the closure of an entanglement class is a projective subvariety of the space of pure states. Thus ΔX\Delta_{\mathcal{X}} can be identified with its moment polytope, and the above-mentioned properties follow from the general theory. We explain how ΔX\Delta_{\mathcal{X}} can in principle be computed using computational invariant theory [DK02].

We now illustrate the method with some examples taken from Section 4.4. For qubit systems, each one-body reduced density matrix ρk\rho_{k} has two eigenvalues, which are non-negative and sum to one; hence its spectrum is completely characterized by the maximal eigenvalue λk,1\lambda_{k,1}, which can take values in the interval [0.5,1][0.5,1]. In the case of three qubits, we may therefore regard the entanglement polytopes as subsets of three-dimensional space. There are two full-dimensional polytopes, as has already been observed in [HZG04]: one for the W class (the upper pyramid in Figure 4.1) and the other for the GHZ class (the entire polytope, i.e., the union of both pyramids). The tip of the upper pyramid constitutes a polytope by itself, indicating a product state. Three further one-dimensional polytopes are given by the edges emanating from this vertex. They correspond to the three possibilities of embedding an EPR pair (∣00⟩+∣11⟩)/2(\ket{00}+\ket{11})/\sqrt{2} into three qubits. Thus, eigenvalues in the interior of the polytope are compatible only with the W and GHZ classes, i.e., genuine three-partite entanglement. If the eigenvalues lie in the lower pyramid, λ1,1+λ2,1+λ3,1<2\lambda_{1,1}+\lambda_{2,1}+\lambda_{3,1}<2, then by (4.1) the state cannot be contained in the closure of the WW class—we have witnessed GHZ-type entanglement.

In systems of 4 qubits, there exist 9 infinite families of entanglement classes, each described by up to three complex parameters [VDDMV02] that are not directly accessible; arguably, the complete classification is too detailed to be practical. In contrast, entanglement polytopes strike an attractive balance between coarse-graining and preserving structure (Figure 4.2): Up to permutations, there are 12 entanglement polytopes, 7 of which are full-dimensional and correspond to distinct types of genuine four-partite entanglement. One example is the 4-qubit W class: in complete analogy to the previous case, its polytope is an “upper pyramid” of eigenvalues that fulfill λ1,1+λ2,1+λ3,1+λ4,1≥3\lambda_{1,1}+\lambda_{2,1}+\lambda_{3,1}+\lambda_{4,1}\geq 3.

In Section 4.4 we give further details on these computations. We also discuss the notion of genuinely multipartite entangled states, which are of particular interest [GTB05]. These are pure states which do not factorize with respect to any partition of the system into two sets of subsystems. We show for arbitrary systems that the entanglement polytopes of the biseparable states (i.e., the states that do factorize) do not account for all possible eigenvalues. Therefore, the presence of genuine multipartite entanglement in a pure quantum state can be witnessed by checking that the local eigenvalues do not lie in any biseparable polytope. We can also obtain more quantitative information about the multipartite entanglement of a quantum state, e.g., by witnessing genuine kk-partite entanglement [GTB05] by using a generalization of the method sketched above. Entanglement polytopes can also be constructed for quantum systems composed of bosons or fermions [WDGC13].

In Section 4.5 we then consider the linear entropy of entanglement E(ρ)=1−1n∑j=1n\trρj2E(\rho)=1-\frac{1}{n}\sum_{j=1}^{n}\tr\rho_{j}^{2} [ZHP93, BKO+04, BM08], used, e.g., in metrology [FNP98]. Entanglement polytopes allow us to bound the maximal linear entropy of entanglement distillable by SLOCC operations: Since 1−E(ρ)1-E(\rho) corresponds to the Euclidean length of the vector λ⃗\vec{\lambda} of local eigenvalues, shorter vectors imply more entanglement. In particular, quantum states of maximal entropy of entanglement in a class X\mathcal{X} map to the point of minimal distance to the origin in the entanglement polytope ΔX\Delta_{\mathcal{X}}. Therefore, if the local eigenvalues of a given state lie only in polytopes with small distance to the origin, a high amount of entanglement can be distilled. We explain how to turn this observation into a quantitative statement and describe a distillation procedure based on Kirwan and Ness’ gradient flow [Kir84a, NM84]. Intriguingly, we find that a generalization of this technique gives rise to a probabilistic classical algorithm for the computation of entanglement polytopes and, in fact, general moment polytopes of orbit closures (cf. [Wer13]).

After completion of the work described in this chapter, we have learned about independent related work by Sawicki, Oszmaniec and Kuś [SOK12b, SOK12a].

2 Classification of Entanglement

A pure quantum state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert of a multi-particle system with Hilbert space H=H1⊗⋯⊗Hn\mathcal{H}=\mathcal{H}_{1}\otimes\dots\otimes\mathcal{H}_{n} is called entangled if it cannot be written as a tensor product [NC04]

It is easy to see that ρ\rho is unentangled, or separable, if and only if each its one-body reduced density matrices ρk\rho_{k} is itself a pure state. More generally, mixed states are called separable if they are convex combinations of product states, but in this chapter we are primarily concerned with the entanglement of pure states.

In order to classify the entanglement present in a given multipartite quantum state ρ\rho, one fruitful approach has been to compare the capability of ρ\rho for quantum information processing tasks with that of other quantum states [BPR+00]. Specifically, suppose that ρ′\rho^{\prime} is a state that can be obtained from ρ\rho by some suitable class of operations. Then ρ\rho can be used as a replacement for ρ′\rho^{\prime} in any quantum information processing scenario where these operations are considered to be “free”. If the operations themselves cannot create entanglement then we may think of ρ\rho to be at least as entangled as ρ′\rho^{\prime}. If, conversely, ρ\rho can also be obtained from ρ′\rho^{\prime} then we may regard the two states to possess the same kind of multipartite entanglement. In this way the set of quantum states is partitioned into equivalence classes.

For example, any local operation that only acts on one of the nn subsystems can never create entanglement. Local operations, including measurements, can be described by trace-preserving, completely positive maps that act on the space of density operators on Hk\mathcal{H}_{k}. Conversely, Stinespring’s dilation theorem shows that such maps can always be implemented by locally adding an ancilla system, performing a unitary operation, and tracing out. It is also useful to allow for classical communication between the subsystems, which can create classical correlations but no entanglement. This allows to condition each subsequent operation on the outcomes of previous measurements, even if those were performed at different subsystems. To model this formally, one needs an additional, classical register that stores the measurement outcome (as opposed to the post-measurement state); this leads to the definition of a quantum instrument (see, e.g., the exposition in [CLM+14]). We thus obtain a class of operations known as local operations and classical communication, or LOCC. For mixed states, the resulting theory is rather rich and has been extensively studied in the literature (also asymptotically in the limit of many copies of a given state). For pure states, however, the resulting notion of LOCC equivalence is quite restrictive: Two pure states can be interconverted by LOCC if and only if they are related by local unitaries [Nie99, BPR+00].

In the context of this work it will thus be convenient to consider a stochastic version of LOCC, known as SLOCC [BPR+00, DVC00]. Here, the conversion of one state into another is only required to succeed with non-zero probability. Operationally, this amounts to allowing post-selection on measurement outcomes that occur with non-zero probability.

In [DVC00], it has been shown that two pure states ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert and ρ′=∣ψ′⟩⟨ψ′∣\rho^{\prime}=\lvert\psi^{\prime}\rangle\langle\psi^{\prime}\rvert are interconvertible using SLOCC if and only if there exist invertible operators gkg_{k} acting on Hk\mathcal{H}_{k} such that ∣ψ′⟩=(g1⊗⋯⊗gn)∣ψ⟩\ket{\psi^{\prime}}=(g_{1}\otimes\dots\otimes g_{n})\ket{\psi}. Here, the non-trivial part is to show that invertible operators gkg_{k} can be constructed by following a successful branch of an SLOCC conversion protocol. For the converse, we may simply successively perform local POVM measurements with Kraus operators

Let H=H1⊗⋯⊗Hn\mathcal{H}=\mathcal{H}_{1}\otimes\dots\otimes\mathcal{H}_{n} be a tensor-product Hilbert space. The (SLOCC) entanglement class of a pure state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert is defined as

In this way, the group GG that had already appeared in the preceding chapters acquires a physical interpretation in terms of SLOCC operations. It is clear that the product states form a single entanglement class. The closure of an entanglement class contains in addition to the class itself also those quantum states which can be arbitrarily well approximated by states in the class. It can thus be given a similar operational interpretation as the class itself. While the entanglement classes partition the set of multipartite quantum states, their closures naturally form a hierarchy. Indeed, it is immediate that ρ′∈Xρ‾\rho^{\prime}\in\overline{\mathcal{X}_{\rho}} implies Xρ′‾⊆Xρ‾\overline{\mathcal{X}_{\rho^{\prime}}}\subseteq\overline{\mathcal{X}_{\rho}}. Every entanglement class contains in its closure the class of unentangled states.

Stochastic local operations and classical communication provide a systematic framework for studying multi-particle entanglement. However, it is immediate from the fact that the dimension of GG grows only linearly with the particle number nn that there is generically an infinite number of distinct SLOCC entanglement classes, labeled by an exponential number of continuous parameters (cf. Section 4.4). It is therefore necessary to coarsen the classification in a systematic way in order to arrive at a tractable way of witnessing multi-particle entanglement. This is one motivation for the notion of entanglement polytopes that we will define in the next section.

We conclude this section by noting that an extraordinary amount of research has been devoted to the classification of entanglement and its experimental identification. The field is far too large to allow for an exhaustive bibliography; we refer to [HHHH09, EG08] for reviews of the general theory and to [GT09] for a review focusing on detection. Methods from algebraic geometry and classical invariant theory have long been used to analyze entanglement classes, see, e.g., [VDDMV02, Kly02, BLT03, VDDM03, Miy03, LLW04, HZG04, OS05, OS06, Kly07, ĐO09, BKM+09, Ost10, GW11, VES11, EBOS12] and references therein.

3 Entanglement Polytopes

The entanglement polytope of an entanglement class X\mathcal{X} is

the set of local eigenvalues of the one-body reduced density matrices of all quantum states in the closure of the entanglement class.

If the vector λ⃗=(λ⃗1,…,λ⃗n)\vec{\lambda}=(\vec{\lambda}_{1},\dots,\vec{\lambda}_{n}) of local eigenvalues of a state ρ\rho is not contained in a given entanglement polytope ΔX\Delta_{\mathcal{X}} then by definition ρ\rho cannot be contained in the closure of the class X\mathcal{X}. This establishes (4.1), our criterion for witnessing multi-particle entanglement. The entanglement polytopes form a hierarchy which coarsens the hierarchy of the closures of entanglement classes:

We remark that λ⃗\vec{\lambda} is a natural generalization of the Schmidt coefficients or entanglement spectrum for bipartite states.

We remark that subsequent works have proposed a similar analysis of entanglement based on entropies rather than eigenvalues, which leads to a coarser notion than our entanglement polytopes [HdV13, HPLdV13] (cf. Chapter 7).

The convexity of moment polytopes and their description relies on the decomposition of the ring of regular functions into irreducible representations (Theorem 2.11). In the case of the closure of an entanglement class X=G⋅ρ\mathcal{X}=G\cdot\rho, this description can be slightly simplified. For this, we consider the following definition from classical invariant theory [KP96].

A covariant of degree kk and weight λ=(λ1,…,λn)\lambda=(\lambda_{1},\dots,\lambda_{n}) is a GG-equivariant map

whose components are homogeneous polynomials of degree kk and where di=dim⁡Hid_{i}=\dim\mathcal{H}_{i}.

The covariants of degree kk are in bijection with the highest weight vectors in Rk(H)R_{k}(\mathcal{H}), the space of homogeneous polynomials of degree kk on H\mathcal{H}. Indeed, if Φ\Phi is a covariant of degree kk and weight λ\lambda then its component

is a highest weight vector in Rk(H)R_{k}(\mathcal{H}) of highest weight λ∗\lambda^{*}, where ∣w0λ⟩∈VG,λ\ket{w_{0}\lambda}\in V_{G,\lambda} is a fixed “lowest weight vector” of weight w0λ=−λ∗w_{0}\lambda=-\lambda^{*}. What is more,

since the GG-orbit through ∣w0λ⟩\ket{w_{0}\lambda} spans the entire irreducible representation VG,λV_{G,\lambda}, while any polynomial that vanishes on G⋅ρG\cdot\rho must also vanish on the closure. The following lemma is already implicit in [Bri87]:

For an entanglement class X=G⋅ρ\mathcal{X}=G\cdot\rho, the following are equivalent:

There exists an irreducible representation VG,λ∗⊆Rk(X‾)V_{G,\lambda^{*}}\subseteq R_{k}(\overline{\mathcal{X}}).

There exists a covariant Φ\Phi of degree kk and weight λ\lambda such that Φ(ρ)≠0\Phi(\rho)\neq 0.

(1)⇒(2)(1)\Rightarrow(2): Let PP denote a highest weight vector of the irreducible representation VG,λ∗⊆Rk(X‾)V_{G,\lambda^{*}}\subseteq R_{k}(\overline{\mathcal{X}}). Then we may consider PP as a polynomial in Rk(H)R_{k}(\mathcal{H}) that does not vanish on X‾\overline{\mathcal{X}}, and (4.4) implies that the corresponding covariant Φ\Phi is non-zero at ρ\rho.

(2)⇒(1)(2)\Rightarrow(1): Conversely, any covariant Φ\Phi with Φ(ρ)≠0\Phi(\rho)\neq 0 corresponds to a highest weight vector PP of highest weight λ∗\lambda^{*} in Rk(H)R_{k}(\mathcal{H}). By virtue of (4.4), PP does not fully vanish on X‾\overline{\mathcal{X}}. Therefore, PP determines a highest weight vector in Rk(X‾)R_{k}(\overline{\mathcal{X}}) and there exists a corresponding irreducible representation VG,λ∗⊆Rk(X‾)V_{G,\lambda^{*}}\subseteq R_{k}(\overline{\mathcal{X}}). ∎

To show that moment polytopes are not only convex but indeed polytopes, we had used the crucial fact that the algebra of N+N_{+}-invariant polynomials R(H)N+R(\mathcal{H})^{N_{+}} – whose elements are linear combinations of highest weight vectors – is finitely generated [Gro73] (see proof of Section 2.2). We saw that there exist finitely many highest weight vectors P(1),…,P(m)P^{(1)},\dots,P^{(m)} such that all other highest weight vectors can be obtained as linear combinations of monomials in the P(j)P^{(j)}. Let us call the corresponding covariants Φ(1),…,Φ(m)\Phi^{(1)},\dots,\Phi^{(m)} a generating set of covariants.

The entanglement polytope of an entanglement class X=G⋅ρ\mathcal{X}=G\cdot\rho is given by

where Φ(1),…,Φ(m)\Phi^{(1)},\dots,\Phi^{(m)} denotes a generating set of covariants with degrees k(j)k^{(j)} and weights λ(j)\lambda^{(j)}.

Recall from Section 4.3 that ΔX\Delta_{\mathcal{X}} can be identified with the moment polytope of the KK-action on X‾\overline{\mathcal{X}}. By Theorem 2.11 and Section 4.3, the rational points of the entanglement polytope are thus given by the normalized weights λ/k\lambda/k corresponding to covariants that do not vanish at ρ\rho. In particular, the inclusion (⊇)(\supseteq) is immediate.

For (⊆)(\subseteq), we closely follow the proof of Section 2.2. Let λ/k∈ΔX\lambda/k\in\Delta_{\mathcal{X}} with corresponding covariant Φ\Phi of degree kk and weight λ\lambda. We denote by P∈Rk(H)P\in R_{k}(\mathcal{H}) the highest weight vector (4.3) corresponding to the covariant Φ\Phi. Since the P(j)P^{(j)} are generators of the algebra of highest weight vectors, we may write PP as a linear combination of monomials in the P(j)P^{(j)}. If the linear combination is chosen minimally then the degrees k(j)k^{(j)} and weights λ(j)\lambda^{(j)} of each monomial P(j1)⋯P(jp)P^{(j_{1})}\dotsm P^{(j_{p})} add up to the degree kk and weight λ\lambda of PP. Thus,

We know from (4.4) that PP does not completely vanish on X\mathcal{X}. Thus same must be true for all factors in at least one of the monomials in the linear combination. Again using (4.4), the corresponding covariants Φ(j1),…,Φ(jp)\Phi^{(j_{1})},\dots,\Phi^{(j_{p})} are all non-zero at ρ\rho. But then (4.5) shows that λ/k\lambda/k is indeed a convex combination of normalized weights λ(j)/k(j)\lambda^{(j)}/k^{(j)} of non-vanishing covariants. ∎

Finite generation also implies other desirable properties, which hold more generally for moment polytopes of projective subvarieties [Bri87]. For example, there are only finitely many entanglement polytopes, since by Section 4.3 any entanglement polytope is the convex hull of some subset of the finite list of normalized weights λ(j)/k(j)\lambda^{(j)}/k^{(j)}. What is more, the set of quantum states for which all generators are non-zero,

is a finite intersection of Zariski-open sets, hence itself Zariski-open. In particular, its complement has positive codimension. It follows that the entanglement polytope of a generic quantum state is maximal and equal to

which we recognize as the solution of the one-body quantum marginal problem for pure-states on H\mathcal{H}.

We stress that this observation does not imply that the method is trivial. Even if mathematically a given entanglement class has measure zero in projective space, it can still be an important task to show that a quantum state prepared in the laboratory is not contained in the class—this is perhaps most obvious if the class is the set of separable pure states! In our approach, this can be done using criterion (4.1) by showing that the local eigenvalues of the state are sufficiently far away from the entanglement polytope of the class. As we explain in Section 4.6, in the presence of small noise our method can be adapted to exclude convex combinations of classes (which always have positive measure). We remark that in classical statistics, testing for non-independence of random variables is similarly concerned with rejecting a measure-zero property (with respect to the natural measure on the probability simplex of joint distributions).

Computation

By virtue of Section 4.3, the computation of entanglement polytopes is a finite problem that can in principle be completely algorithmized. By using the relation

which is in fact at the heart of the proof of finite generation [Gro73], the problem of computing a set of generating covariants is transformed into a problem of computing invariants for a complex reductive group (see [Dol03, §4.2] for details; cf. [DK07]). For the latter problem there exists a Gröbner-basis algorithm in computational invariant theory [DK02] that has been implemented, e.g., in the Magma computer algebra system [BCP97] (but see Section 4.7). Once a set of generating covariants has been found, Section 4.3 can be used to compute the entanglement polytope both for specific states as well as for families of states. We demonstrate this method when computing examples in the next section (relying on generating sets of covariants that had been previously computed). In Section 4.5 we describe an alternative approach that does not rely on computational invariant theory.

4 Examples

Before we proceed, we introduce some notational simplifications. It will be convenient to represent the local eigenvalues of a pure state of nn qubits by the tuple (λ1,1,…,λn,1)∈[0.5,1]n(\lambda_{1,1},\dots,\lambda_{n,1})\in[0.5,1]^{n} of maximal local eigenvalues; this is without loss of information since the eigenvalues of the one-body reduced density matrix of each qubit sum to one. Thus a covariant of degree kk and weight (λ1,…,λn)(\lambda_{1},\dots,\lambda_{n}) determines the point (λ1,1,…,λ1,n)/k(\lambda_{1,1},\dots,\lambda_{1,n})/k in the polytope of maximal local eigenvalues.

the other is the class of product states, represented by ∣00⟩\ket{00}. Using Chapter 2, it is not hard to see that the entanglement polytope of the former class is given the convex hull of (0.5,0.5)(0.5,0.5) and (1,1)(1,1), while the entanglement polytope of the product states is a single point (1,1)(1,1). We can also see this formally by using the method of covariants. There are two generating covariants: One is the identity map

which never vanishes and therefore shows that the point (1,1)(1,1) is contained in both entanglement polytopes. The other is the map

that sends a quantum state to the determinant of its coefficients. It is of degree 2 and therefore corresponds to the point (0.5,0.5)(0.5,0.5) in an entanglement polytope. Since the determinant is zero on the class of product states but not on the EPR pair, we obtain the two entanglement polytopes from above by using Section 4.3.

Three Qubits

three classes that correspond to EPR pairs shared between any two of the three subsystems,

and the class of product states, represented by

We shall now compute the corresponding entanglement polytopes by following the general method of covariants described in Section 4.3. A minimal generating set of six covariants has been determined in late 19th century invariant theory [LP81] in the context of the classification of binary three-linear forms, as explained in [Luq07]. Recall that each irreducible representation Vμ2V^{2}_{\mu} of \SU(2)\SU(2) can be realized as the space of homogeneous polynomials of degree μ1−μ2\mu_{1}-\mu_{2} in two formal variables. Therefore, any covariant for three qubits can be written as a homogeneous polynomial in formal variables xix_{i}, yjy_{j} and zkz_{k}, whose coefficients are themselves homogeneous polynomials in the components ψijk\psi_{ijk} of the quantum state (the degree in the ψijk\psi_{ijk} is equal to the degree of the covariant, whereas the degrees in the formal variables determine its weight). For example, the identity map can be written as the multilinear polynomial f=∑i,j,kψijkxiyjzkf=\sum_{i,j,k}\psi_{ijk}x_{i}y_{j}z_{k}; it is a generating covariant of degree 11 and weight (

We remark that using techniques crafted towards the special situation of three qubits, these same polytopes had already been previously computed in [HZG04, SWK13]. The one-body quantum marginal problem, which as we have explained amounts to computing the maximal entanglement polytope, has been solved in [HSS03], and we saw a different derivation in Chapter 3.

We now illustrate the method of entanglement witnessing via (4.1). Let ρ\rho be a quantum state with maximal local eigenvalues λ⃗=(λ1,1,λ2,1,λ3,1)\vec{\lambda}=(\lambda_{1,1},\lambda_{2,1},\lambda_{3,1}).

If the point λ⃗\vec{\lambda} is contained in the lower part of the entanglement polytope of the GHZ class (lower pyramid in Figure 4.3, (a)),

then it is not contained in any other entanglement polytope. Therefore the quantum state ρ\rho must be entangled of GHZ type.

More generally, if λ⃗\vec{\lambda} is not contained in any of the lower-dimensional polytopes corresponding to EPR pairs (Figure 4.3, (c), which includes (d)), i.e., if

then the quantum state ρ\rho must be entangled of either GHZ or W class. These classes of states are the ones that possess genuine three-qubit entanglement (see discussion below).

As a final example, we consider the quantum state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert, where

It is easy to verify by the method of covariants that the entanglement polytope of ρ\rho is full-dimensional. Thus it follows from the above classification that ρ\rho is of GHZ type. However, its collection of local eigenvalues (λ1,1,λ2,1,λ3,1)≈(0.76,0.79,0.88)(\lambda_{1,1},\lambda_{2,1},\lambda_{3,1})\approx(0.76,0.79,0.88) is contained in the interior of the upper pyramid. As we just discussed, the entanglement criterion in this case only allows us to conclude that ρ\rho is either of GHZ or of W type. In Section 4.5 we will describe a distillation procedure that allows us to transform ρ\rho by SLOCC operations into another state whose local eigenvalues are arbitrarily close to the “origin” (0.5,0.5,0.5)(0.5,0.5,0.5) (cf. Figure 4.6). In this way, we may arrive at a quantum state which is both more entangled and for which the entanglement criterion is maximally informative.

Four Qubits

In contrast to case of three qubits, where there are finitely many entanglement classes represented faithfully by the hierarchy of entanglement polytopes, the situation for four qubits is the generic one: There are infinitely many entanglement classes. According to the classification of [VDDMV02], up to permutation of the qubits they can be partitioned into nine families with up to three complex continuous parameters each (cf. [CD07]). Neither the family itself nor the complex parameters within a family are directly experimentally accessible.

We have determined all entanglement polytopes of four qubits using the general method of Section 4.3 applied to a minimal generating set of 170 covariants found in [BLT03]. More precisely, for every family in [VDDMV02], we consider the covariants as a function of the parameters aa, bb, etc. of the family. Deciding whether a normalized weight λ(j)/k(j)\lambda^{(j)}/k^{(j)} is included in the entanglement polytope ΔX\Delta_{\mathcal{X}} of a state in the family then amounts to solving the explicit polynomial equation Pj≠0P_{j}\neq 0 in the parameters aa, bb, etc.; this can be automatized by using a computer algebra system.

The maximal entanglement polytope is equal to the solution of the one-body quantum marginal problem for four qubits as given by the polygonal inequalities (3.2) for n=4n=4. It is a convex hull of 12 vertices, which can be easily described as follows: One vertex, (1,1,1,1)(1,1,1,1) corresponds to the class of product states; (0.5,0.5,1,1)(0.5,0.5,1,1) and its permutations correspond to the six possibilities of embedding an EPR pair into four qubits; (0.5,0.5,0.5,1)(0.5,0.5,0.5,1) and its permutations correspond to the four possibilities of embedding a GHZ state of three qubits; and the vertex (0.5,0.5,0.5,0.5)(0.5,0.5,0.5,0.5) is the image of, e.g., a four-partite GHZ state.

As in the case of three qubits, there are several lower-dimensional entanglement polytopes, corresponding to the different ways of embedding entanglement classes of systems of fewer qubits into four qubits. These are precisely the biseparable entanglement classes, i.e., the classes whose elements are tensor products ρ=ρI⊗ρIc\rho=\rho_{I}\otimes\rho_{I^{c}} with respect to some proper bipartition I:IcI:I^{c} of the four qubits. For example, the state ∣\GHZ⟩⊗∣0⟩\ket{\GHZ}\otimes\ket{0} generates an entanglement class whose elements are tensor products of the three-qubit GHZ class and a one-qubit pure state, and its entanglement polytope is the Cartesian product of the three-qubit GHZ polytope with the point {1}\{1\}. All possibilities are listed in Table 4.2.

We now turn to the full-dimensional polytopes. There are seven such polytopes, listed together with some of their properties in Table 4.3 and Figure 4.4. For example, the entanglement classes of the four-qubit GHZ state and of the cluster states [BR01] are both associated with the maximal polytope (last row in Table 4.3 and Figure 4.4). The four-qubit WW-state, ∣W4⟩=(∣0001⟩+∣0010⟩+∣0100⟩+∣1000⟩)/2\ket{W_{4}}=(\ket{0001}+\ket{0010}+\ket{0100}+\ket{1000})/2, corresponds to polytope no. 5 in Table 4.3 and Figure 4.4. In analogy with the WW-state for three qubits, its polytope is an “upper pyramid” given by the intersection of the maximal polytope with the half-space

Any violation of this inequality may be taken as an indication of “high entanglement”. One way to make this precise is to read off Table 4.3 that violations imply that the state ρ\rho can be converted into one whose linear entropy of entanglement is at least 0.450.45, which might be much higher than E(ρ)E(\rho) itself. We will explain this more carefully in Section 4.5 below.

We now comment on properties that can be read off graphically from Figure 4.4. From the first column, one can see that only three of the entanglement polytopes (no. 4, 6 and 7) include the “origin” (0.5,0.5,0.5,0.5)(0.5,0.5,0.5,0.5). These reach the maximal value for the linear entropy of entanglement E(ρ)=1−1n∑j=1n\trρj2E(\rho)=1-\frac{1}{n}\sum_{j=1}^{n}\tr\rho_{j}^{2}. The last column exhibits the behavior of the class when the fourth particle is projected onto a generic pure state. We then obtain a pure state of three qubits on the remaining subsystems. Polytopes no. 1, 3, 6, and 7 give the full three-qubit polytope, implying that in general a GHZ-type state is generated, while polytopes no. 2, 4, and 5 collapse to the upper pyramid of Figure 4.1. Hence states in the latter classes can never product a state of GHZ-type when the fourth qubit is projected onto a pure state. It follows that the mixed 3-tangle (and any other convex-roof extension of a polynomial monotone) vanishes on the mixed state generated by tracing out the last particle of any state in these classes. This observation allows us to graphically recover some properties calculated algebraically in [VDDMV02], such as the vanishing 3-tangle for the class Lab3,a=b=0L_{{ab}_{3}},a=b=0 (corresponding to polytope no. 5).

In summary, up to permutations, there are 12 entanglement polytopes for four qubits, 7 of which are full-dimensional and belong to genuinely four-partite entangled states. These numbers increase to 41 and 22, respectively, if distinct permutations are counted separately. Slightly abusing the tradition of [DVC00, VDDMV02], we might say that from the perspective of entanglement polytopes, four qubits can be entangled in seven different ways.

We remark that there is a numerical coincidence between our findings and the ones in [ĐO09], where also seven non-biseparable entanglement classes have been identified on four qubits. The two classifications are, however, not identical. Indeed, [ĐO09] is based purely on invariants, as opposed to the more general covariant-theoretic description of our polytopes. It follows from Section 4.3 – as we discuss in Section 4.5 below – that all polynomial invariants vanish identically on any entanglement class whose polytope does not contain the “origin” (0.5,0.5,0.5,0.5)(0.5,0.5,0.5,0.5). Since this is the case for our polytopes no. 1, 2, 3 and 5, the corresponding classes cannot be distinguished from each other by polynomial invariants (in fact, not even from the class of product states!) Thus our classification differs from the one in [ĐO09]. From a mathematical perspective, our methods are complementary (entanglement polytopes can also distinguish among unstable vectors, whereas [ĐO09] provides a better resolution in the semistable case).

Genuine Multipartite Entanglement

Perhaps surprisingly, it still remains true that spectral information alone can be used to show that a state is not biseparable. To make this precise, we consider the following definition from [GTB05]; see also [HHH01, HHHH09, GT09, LM13, SU01, HMGH10] and references therein.

Let H=H1⊗⋯⊗Hn\mathcal{H}=\mathcal{H}_{1}\otimes\dots\otimes\mathcal{H}_{n}. A pure state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert on H\mathcal{H} is called producible using kk-partite entanglement if it is of the form

where I1∪⋯∪Im={1,…,n}I_{1}\cup\dots\cup I_{m}=\{1,\dots,n\} and each subset IjI_{j} is of size at most kk.

Otherwise, ρ\rho is called genuinely (k+1)(k+1)-partite entangled. In particular, the genuinely nn-partite entangled states are precisely those which are not biseparable.

We remark that some authors use the term “genuine nn-partite entanglement” in a different sense (e.g., [OS05, OS06] where it is also required that there exists a non-vanishing invariant polynomial).

To state our result, recall that the maximal entanglement polytope for nn qubits is given by the polygonal inequalities (3.2). Therefore, the constraints on the local eigenvalues of states that factorize with respect to a fixed partition I1∪⋯∪Im={1,…,n}I_{1}\cup\dots\cup I_{m}=\{1,\dots,n\} are given by

Mathematically, while this set of states does not form a single entanglement class, it is still a GG-invariant projective subvariety – known as a Segré variety in algebraic geometry –, and so has a corresponding moment polytope, namely the one cut out by the inequalities (4.7). The inequalities (4.7) hold for quantum states of arbitrary local dimension, since the same is true for the polygonal inequalities, but in general there are additional constraints.

Let n≥3n\geq 3 and k∈{⌈n/2⌉,…,n}k\in\{\lceil n/2\rceil,\dots,n\}. For any ε∈(0,1/(2k−2)]\varepsilon\in(0,1/(2k-2)], the local eigenvalues

can only originate from a genuinely kk-partite entangled state.

Conversely, if k≠n−1k\neq n-1 then there exists a corresponding pure state of nn qubits that is producible using kk-partite entanglement (i.e., that is not genuinely k+1k+1-partite entangled).

For the first claim, suppose that ρ=ρI1⊗⋯⊗ρIm\rho=\rho_{I_{1}}\otimes\dots\otimes\rho_{I_{m}} is a state with the displayed local eigenvalues. Without loss of generality, suppose that 1∈I11\in I_{1}. Then (4.7) for l=1l=1 reads

Since this holds for all partitions, we conclude that ρ\rho is genuinely kk-partite entangled.

For the second claim, consider the bipartition I1={1,…,k}I_{1}=\{1,\dots,k\}, I2={k+1,…,n}I_{2}=\{k+1,\dots,n\}. Then (4.8) is satisfied and all other inequalities in (4.7) are satisfied for I1I_{1} since k≥⌈n/2⌉≥2k\geq\lceil n/2\rceil\geq 2. For I2I_{2}, which we need to consider only if k<nk<n, (4.7) is equivalent to k≤n−2k\leq n-2. ∎

Section 4.4shows that some correlations between the one-body reduced density matrices of a global pure state can only be explained by the presence of genuine nn-partite entanglement. Since the complement of the union of biseparable entanglement polytopes is open, the first claim in the proposition is in fact true for a small ball around the eigenvalues (intersected with the overall polytope). See Figure 4.5 for an illustration.

5 Gradient Flow

the corresponding entanglement monotone [VDDM03]. Then PP attains at ρ\rho its maximal value over all states in the entanglement class Xρ=G⋅ρ\mathcal{X}_{\rho}=G\cdot\rho [Kly07]. To see this, recall from (2.7) that for a locally maximally mixed state ρ=∣ψ⟩⟨ψ∣\rho=\lvert\psi\rangle\langle\psi\rvert the norm square of the corresponding vector ∣ψ⟩\ket{\psi} does not change to first order as we move along the GG-orbit in Hilbert space; that is ∣ψ⟩\ket{\psi} is a critical point of ∥−∥2\lVert-\rVert^{2} on its GG-orbit. Kempf and Ness have shown that in fact any such vector has minimal length in its GG-orbit [KN79], so that ∥Π(g)∣ψ⟩∥≥∥∣ψ⟩∥=1\lVert\Pi(g)\ket{\psi}\rVert\geq\lVert\ket{\psi}\rVert=1 for all g∈Gg\in G. Thus,

From the perspective of entanglement polytopes, locally maximally mixed quantum states correspond to the point

which we will call the origin. We have used O⃗\vec{O} as the origin of the coordinate systems in most of the figures in this chapter. Indeed, if we identify an entanglement polytope ΔX\Delta_{\mathcal{X}} with the corresponding moment polytope ΔK(X‾)\Delta_{K}(\overline{\mathcal{X}}) then the origin O⃗\vec{O} corresponds to the point 0∈ik∗0\in i\mathfrak{k}^{*}, which justifies the terminology (recall that we work with G=\SL(H1)×⋯×\SL(Hn)G=\SL(\mathcal{H}_{1})\times\dots\times\SL(\mathcal{H}_{n})). It follows from the basic Section 2.2 that

In particular, any entanglement monotone of the form (4.9) vanishes on quantum states whose entanglement polytope does not include the origin; such states are also called unstable in geometric invariant theory [MFK94]. This observation has lead to the suggestion that unstable states should be considered “unentangled” [Kly07] or “not genuinely multipartite entangled” [OS05, OS06]. However they are certainly considered entangled according to the standard definition that we have adopted in this work (Section 4.2). There is also an interesting connection between the theory of entanglement polytopes and the selection rule of Equation 2.19 that should be well-known mathematically:

Let X=G⋅ρ\mathcal{X}=G\cdot\rho be the entanglement class of a quantum state ρ\rho with non-degenerate local eigenvalues that is pinned to a facet (of the maximal entanglement polytope) that does not contain the origin. Then ΔX\Delta_{\mathcal{X}} does not contain the origin.

for t→±∞t\rightarrow\pm\infty depending on the sign of c≠0c\neq 0. Therefore, 0∈Π(G)∣ψ⟩‾0\in\overline{\Pi(G)\ket{\psi}}. But then any GG-invariant homogeneous polynomial ought to vanish at ρ\rho. We conclude from (4.10) that ΔX\Delta_{\mathcal{X}} does not contain the origin. ∎

Section 4.5can be strengthened by considering facets of the entanglement polytope ΔX\Delta_{\mathcal{X}} rather than of the maximal entanglement polytope.

The Linear Entropy of Entanglement

The geometric picture provided by entanglement polytopes suggests another way of quantifying entanglement. For this, we consider the multipartite version of the linear entropy of entanglement [ZHP93, FNP98, BKO+04],

Gradient Flow and Distillation

Given the linear entropy of entanglement as a means of quantifying multipartite entanglement, it is natural to ask for a corresponding distillation procedure, i.e., for a protocol that transforms a given quantum state by SLOCC operations to a state with maximal linear entropy of entanglement. This transformation might only be possible asymptotically, as the maximum might only be attained by points in the closure proper. Our approach will be based on maximizing E(ρ)E(\rho) by following its gradient flow.

The gradient flow for E(ρ)E(\rho) is closely related to the gradient flow for the norm-square of the moment map as studied by Kirwan and Ness [Kir84a, NM84]. To see this, recall that iki\mathfrak{k} consists of tuples of traceless Hermitian matrices. We may equip iki\mathfrak{k} with the KK-invariant inner product corresponding to the norm ∥(X1,…,Xn)∥2=∑k∥Xk∥HS⁡2\lVert(X_{1},\dots,X_{n})\rVert^{2}=\sum_{k}\lVert X_{k}\rVert_{\operatorname{HS}}^{2} and use this to identify ik≅ik∗i\mathfrak{k}\cong i\mathfrak{k}^{*}. This amounts to identifying μK(ρ)∈ik∗\mu_{K}(\rho)\in i\mathfrak{k}^{*} with the traceless part of its one-body reduced density matrices,

Thus the norm-square of the moment map and the linear entropy of entanglement are directly related by an affine transformation—maximizing the linear entropy of entanglement is equivalent to minimizing the norm-square of the moment map, and the gradients are proportional.

We will now review some known results on the norm-square of the moment map and its gradient flow. All these results hold for general moment maps on projective space and we will thus use the general language of Section 2.2; see, e.g., [GRS13] for a comprehensive recent exposition from the differential-geometric point of view. The first observation is that the gradient of ∥μK∥2\lVert\mu_{K}\rVert^{2} is given by [Kir84a, NM84]

where μK(ρ)ρ\mu_{K}(\rho)_{\rho} denotes as in Section 2.2 the tangent vector at ρ\rho generated by the infinitesimal action of μK(ρ)∈ik∗\mu_{K}(\rho)\in i\mathfrak{k}^{*}, considered as an element of iki\mathfrak{k} by using the KK-invariant inner product. This follows from the calculation

where we have used (2.13) and the relation (2.9) between the Riemannian metric gg and the Fubini–Study form ω\omega. An important consequence of (4.13) is that the gradient flow

automatically stays in the GG-orbit of ρ\rho, i.e., in its entanglement class X=G⋅ρ\mathcal{X}=G\cdot\rho at all times t≥0t\geq 0. What is more, the gradient flow converges to a unique limit point ρ∞=lim⁡t→∞ρt∈X‾\rho_{\infty}=\lim_{t\rightarrow\infty}\rho_{t}\in\overline{\mathcal{X}} [Ler05, GRS13]. Since any critical point is a minimum [Kir84a, NM84], this limit point is a state that minimizes the norm-square of the moment map over all states in the orbit closure X‾=G⋅ρ‾\overline{\mathcal{X}}=\overline{G\cdot\rho} [GRS13]. We remark that such states are unique up to the KK-action [NM84].

We now specialize these results to the scenario of entanglement polytopes. By the above discussion, the gradient flow (4.14) converges to the global maximum of the linear entropy of entanglement of all states in X‾=G⋅ρ‾\overline{\mathcal{X}}=\overline{G\cdot\rho}. Remarkably, at each point this flow is given by the infinitesimal action of (the traceless part of) the one-body reduced density matrices (4.12). In practice, the gradient flow needs to be implemented with finite time steps Δt\Delta t, which amounts to the SLOCC transformation

where π ⁣:g→gl(H)\pi\colon\mathfrak{g}\rightarrow\mathfrak{gl}(\mathcal{H}) denotes the infinitesimal action of the Lie algebra and where we have used that scalar multiples of the identity act trivially on projective space according to (2.11). To realize this scheme in the laboratory, one would start by preparing the quantum state ρ\rho, measuring its one-body reduced density matrices, re-preparing, and implementing the SLOCC transformation (4.15) by using local POVM measurements with Kraus operators as in (4.2). If the transformation succeeded then entanglement has been distilled. By successively repeating this procedure with the concatenated SLOCC operations, one asymptotically arrives at a quantum state with maximal linear entropy of entanglement. Notably, this method of entanglement distillation only requires local tomography and works on a single copy of the state at a time. See Figure 4.6 for a numerical simulation.

Towards a Probabilistic Algorithm for Computing Moment Polytopes of Orbit Closures

From a theoretical perspective, the limit point ρ∞\rho_{\infty} of the gradient flow can also be seen as a normal form of the state ρ\rho in its entanglement class, as it is unique up to local unitaries. This is the point of view taken in [VDDM03], where a similar algorithm has been proposed for the case when the entanglement polytope contains the origin. In contrast, the gradient flow works in the general case and flows towards the point in the moment polytope of minimal Euclidean norm. We will now sketch how this idea leads towards a probabilistic algorithm for computing moment polytopes of arbitrary orbit closures. As above, let ∥−∥\lVert-\rVert denote the norm corresponding to a KK-invariant inner product (−,−)(-,-) on ik∗i\mathfrak{k}^{*}. We start with a simple observation:

Let λ,μ∈it+∗\lambda,\mu\in i\mathfrak{t}^{*}_{+}. Then:

The right-hand side maximization can be understood as an optimization of the linear functional (−,λ)(-,\lambda) over the Abelian moment polytope of the coadjoint orbit OK,μ\mathcal{O}_{K,\mu}. By Kostant’s convexity theorem [Kos73], the latter is equal to the convex hull of the orbit of μ\mu under the Weyl group, which in turn is a subset of μ\mu plus the cone spanned by the negative roots. We conclude that

By assumption and using that OK,λ∗=−OK,λ\mathcal{O}_{K,\lambda^{*}}=-\mathcal{O}_{K,\lambda},

where the last equality is due to Section 4.5. On the other hand,

The following algorithm returns the moment polytope of the orbit closure (if it terminates):

To show that the algorithm is correct it suffices to observe that (4.16) is a loop invariant. In the case μ=ν\mu=\nu this is immediate. If μ≠ν\mu\neq\nu then the convexity of the moment polytope implies that it is contained in the half-space {λ∈it∗:(λ−μ,ν−μ)≤0}\{\lambda\in i\mathfrak{t}^{*}:(\lambda-\mu,\nu-\mu)\leq 0\}. ∎

One choice of outer approximation is given by the moment polytope for the action of the maximal torus T⊆KT\subseteq K, which is equal to the convex hull of the weights of the representation H\mathcal{H} (Section 3.2). See Figure 4.7 for an illustration of the algorithm. Section 4.5, its theoretical properties and implications still need be investigated more carefully; we refer to [Wer13] for an initial study and first applications of the algorithm to the computation of entanglement polytopes. We remark that it can also be used to obtain a solution of the one-body quantum marginal problem when applied to a generic state ρ\rho (chosen, e.g., according to the unitarily invariant measure on projective space). We remark that the gradient flow gives us in essence a separation oracle [GLS93]. There are geometric algorithms that work with a separation oracle, e.g., based on the ellipsoid method, which are well-studied in the optimization community (as was kindly pointed out to us by Peter Bürgisser). A combination of these techniques might lead to further progress towards solving the membership problem for moment polytopes.

6 Experimental Noise

A quantum state prepared in the laboratory will always be a mixed state ρ\rho and it is a priori unclear what statements can be inferred about its entanglement from its local eigenvalues. Here, we give two slightly different ways for applying the preceding results to the more realistic scenario of small noise.

For both approaches, we will assume that a lower bound p>1/2p>1/2 on the purity \trρ2\tr\rho^{2} is available. One natural way of obtaining such an estimate is the well-known swap test [BCWdW01], which directly estimates \trρ2\tr\rho^{2} using a series of two-body measurements on two copies of ρ\rho. We sketch an alternative procedure which may be simpler to implement for some experimental platforms. Suppose that ρ\rho has been prepared by acting on an initial product state with a quantum operation Λ\Lambda that approximates an entangling unitary gate UU (e.g., a spin squeezing operation). Act on ρ\rho by a quantum operation Λ′\Lambda^{\prime} that approximates the corresponding “disentangling unitary” U−1U^{-1} and denote by ρ′=Λ′(ρ)\rho^{\prime}=\Lambda^{\prime}(\rho) the state thus obtained. Now assume that the noise mechanism never increases the purity—this holds, e.g., for dephasing and depolarizing noise, which are two noise models applicable to the majority of experiments. Then we can use the following lower bound [Aud07]

for the purity in terms of the local spectra λ1′⃗,…,λn′⃗\vec{\lambda^{\prime}_{1}},\dots,\vec{\lambda^{\prime}_{n}}, which can be obtained from tomography of the single-particle reduced density matrices ρ1′,…,ρn′\rho^{\prime}_{1},\dots,\rho^{\prime}_{n}. For small noise, ρ′\rho^{\prime} is still approximately product and so this bound likely not too loose (as it is tight for product states).

The first way of dealing with noise is to realize that in the vicinity of any mixed state ρ\rho there is a pure state whose local eigenvalues do not differ too much from those of the mixed state, provided that the purity of the mixed state is sufficiently high. To make this precise, it is convenient to consider the fidelity between ρ\rho and an arbitrary pure state σ=∣ψ⟩⟨ψ∣\sigma=\lvert\psi\rangle\langle\psi\rvert, which is defined by F(ρ,σ):=⟨ψ∣ρ∣ψ⟩F(\rho,\sigma):=\braket{\psi|\rho|\psi}. Note that F(ρ,σ)≤1F(\rho,\sigma)\leq 1, with equality if and only if ρ=σ\rho=\sigma.

Let ρ\rho be a mixed state with purity \trρ2≥p>1/2\tr\rho^{2}\geq p>1/2. Then there exists a pure state σ=∣ψ⟩⟨ψ∣\sigma=\lvert\psi\rangle\langle\psi\rvert with fidelity F(ρ,σ)≥pF(\rho,\sigma)\geq p such that

Consider the spectral decomposition ρ=∑iri∣ψi⟩⟨ψi∣\rho=\sum_{i}r_{i}\lvert\psi_{i}\rangle\langle\psi_{i}\rvert with eigenvalues ordered non-increasingly, ri≥ri+1r_{i}\geq r_{i+1}. Our assumption on the purity implies immediately that the maximal eigenvalue can also be lower-bounded by 1/21/2:

Thus if we set σ=∣ψ1⟩⟨ψ1∣\sigma=\lvert\psi_{1}\rangle\langle\psi_{1}\rvert then F(ρ,σ)=⟨ψ1∣ρ∣ψ1⟩=r1≥pF(\rho,\sigma)=\braket{\psi_{1}|\rho|\psi_{1}}=r_{1}\geq p.

On the other hand, using that rj≤∑i>1ri=1−r1r_{j}\leq\sum_{i>1}r_{i}=1-r_{1} for all j>1j>1, we find that

We solve this quadratic relation and obtain two possible solutions,

In the case of qubits, the bound (4.17) can be equivalently written in terms of the maximal local eigenvalues,

For small noise, the right-hand side is equal to nε/2n\varepsilon/2 in first order in ε=1−p≈0\varepsilon=1-p\approx 0.

We now illustrate the approach with a numerical example. Suppose that ρ\rho is an experimentally prepared quantum state of four qubits with purity no less than p=0.9p=0.9. Then by Section 4.6 above there exists a pure state σ=∣ψ⟩⟨ψ∣\sigma=\lvert\psi\rangle\langle\psi\rvert with fidelity F(ρ,σ)≥0.9F(\rho,\sigma)\geq 0.9 for which (4.21) reads

At this resolution, the differences between the various four-qubit entanglement polytopes are already well visible. For example, suppose that we would like to use the inequality

to deduce that σ\sigma is not entangled of W-type (cf. the summary of results in this chapter). For this, it suffices by (4.22) to verify that the local eigenvalues of the experimentally realized state ρ\rho satisfy the relation

For comparison, the left-hand side of this inequality is equal to 22 for a symmetric Dicke state (∣0011⟩+∣0101⟩+∣0110⟩+∣1001⟩+∣1010⟩+∣1100⟩)/6\left(\ket{0011}+\ket{0101}+\ket{0110}+\ket{1001}+\ket{1010}+\ket{1100}\right)/\sqrt{6}.

Convex Extension

A second, alternative approach for treating noise aims to show that the experimentally prepared mixed state ρ\rho cannot be written as a convex combination of pure states in the closure of an entanglement class X\mathcal{X}. For this, we consider the distance between a spectrum λ⃗\vec{\lambda} and an entanglement polytope ΔX\Delta_{\mathcal{X}} defined as

There exists a continuous function δ(p)≥0\delta(p)\geq 0 with δ(1)=0\delta(1)=0 such that

for all mixed states ρ\rho with purity \trρ2≥p>1/2\tr\rho^{2}\geq p>1/2.

Let δ(p):=n(1+21−p−2p−1)\delta(p):=n(1+2\sqrt{1-p}-\sqrt{2p-1}). Then δ\delta is continuous and non-negative on [1/2,1][1/2,1], and δ(1)=0\delta(1)=0. Now assume that ρ\rho is a mixed state with purity \trρ2≥p>1/2\tr\rho^{2}\geq p>1/2 and d(λ⃗(ρ),ΔX)>δ(p)d(\vec{\lambda}(\rho),\Delta_{\mathcal{X}})>\delta(p). As in the proof of Section 4.6, let σ=∣ψ1⟩⟨ψ1∣\sigma=\lvert\psi_{1}\rangle\langle\psi_{1}\rvert where ∣ψ1⟩\ket{\psi_{1}} is an eigenvector corresponding to the maximal eigenvalue of ρ\rho. For any χ=∣ϕ⟩⟨ϕ∣∈X‾\chi=\lvert\phi\rangle\langle\phi\rvert\in\overline{\mathcal{X}}, the triangle inequality gives

We may lower-bound the first summand by reversing the argument of (4.19) and using the assumption on ρ\rho,

while the second summand can be upper-bounded as in (4.20),

so that by using a standard upper bound for the fidelity in terms of the trace norm [FvdG99] we obtain the following estimate which holds for all χ=∣ϕ⟩⟨ϕ∣∈X‾\chi=\lvert\phi\rangle\langle\phi\rvert\in\overline{\mathcal{X}}:

Now assume for the sake of reaching a contradiction that ρ\rho can in fact be written as a convex combination ρ=∑jpj∣ϕj⟩⟨ϕj∣\rho=\sum_{j}p_{j}\lvert\phi_{j}\rangle\langle\phi_{j}\rvert of pure states from X‾\overline{\mathcal{X}}. Then,

But on the other hand, ⟨ψ1∣ρ∣ψ1⟩≥p\braket{\psi_{1}|\rho|\psi_{1}}\geq p by (4.18), which is the desired contradiction. ∎

7 Discussion

Section 4.3provides a complete description of the entanglement polytopes based on a generating set of covariants. While the latter can in principle be found using computational invariant theory, current algorithms based on Gröbner bases work best for low-dimensional scenarios. It would therefore be highly desirable to find an alternative characterization that does not rely on an explicit knowledge of the covariants—for example, based on the differential-geometric approach of Chapter 3 or by using semistability computations in geometric invariant theory. The fact that only the vanishing behavior of the covariants enters the description in Section 4.3 indicates that such a characterization could indeed be achievable.

While the distillation method in Section 4.5 is conceptually pleasing, it is not clear when its realization will become experimentally feasible. In contrast, Section 4.5 has already been successfully implemented and might provide a way of circumventing the combinatorial challenges faced by exact methods in higher dimensions. Apart from its immediate applications to the marginal problem and entanglement witnessing, the computation of moment polytopes is also relevant in other disciplines such as in mathematics and in geometric complexity theory [BLMW11] (cf. Chapter 6), and it might be worthwhile to study our algorithm in this context.

Chapter 5 Random Marginals

In this chapter we consider a quantitative version of the one-body quantum marginal problem. For a random pure state drawn from the unitarily invariant measure, we give an algorithm to compute the joint probability distribution of the eigenvalues of its one-body reduced density matrices. We obtain the exact probability distribution by reducing to the corresponding distribution of diagonal entries, which corresponds to a quantitative version of a classical marginal problem. This reduction is an instance of a more general principle that can be used to compute Duistermaat–Heckman measures in symplectic geometry.

The results in this chapter have been obtained in collaboration with Matthias Christandl, Brent Doran and Stavros Kousidis, and they have appeared in [CDKW14].

Let ρ\rho be a pure quantum state of nn particles, drawn at random according to the unitarily invariant probability measure on projective space. We consider the problem of determining the joint distribution of its one-body reduced density matrices ρ1,…,ρn\rho_{1},\dots,\rho_{n}, which are again random variables. This is a quantitative version of the one-body quantum marginal problem, Chapter 2, and strictly generalizes the latter – for a given collection of density matrices, we ask how likely it is to obtain them as the one-body marginals of a pure state rather than whether this is possible at all.

The starting point for our work is the observation that the joint distribution of the one-body reduced density matrices is invariant under the action of the local unitary group. In particular, this implies that we may equivalently consider the joint distribution of their eigenvalues, P\spec\mathbf{P}_{\spec}, which is a probability measure on the positive Weyl chamber it≥0∗i\mathfrak{t}^{*}_{\geq 0} with support equal to the moment polytope (i.e., the solution to the one-body quantum marginal problem). The crucial fact is that in general P\spec\mathbf{P}_{\spec} can be recovered from the corresponding distribution of local diagonal entries P\diag\mathbf{P}_{\diag} by taking a number of partial derivatives:

where d1,…,dkd_{1},\dots,d_{k} are the local dimensions and where pp is an explicitly given polynomial (namely, a product of Vandermonde determinants). This is an instance of a more general derivative principle that relates invariant measures for the coadjoint action of a compact Lie group to their projections onto a Cartan subalgebra, and follows from a result by Harish-Chandra [HC57] (Section 5.4). A similar reduction is not possible on the level of the moment polytopes. To compute the distribution of diagonal entries, we show in Section 5.3 that its density f\diagf_{\diag} can be written as the push-forward of Lebesgue measure on a simplex along a linear map. Concretely:

It is amusing to note that this corresponds precisely to a quantitative marginal problem for ordinary random variables. Any measure of the form (5.2) is given by piecewise homogeneous polynomials on convex chambers that can be explicitly computed. To do so algorithmically, we adapt a result of Boysal and Vergne that can be used to recursively compute closely related measures by evaluating residues [BV09]. By putting together all ingredients, we obtain an effective algorithm for computing P\spec\mathbf{P}_{\spec} for an arbitrary number of particles and statistics (Section 5.4). See Figure 5.1 for a summary of the method. This generalizes previous results in the literature significantly, where exact results were only obtained for two distinguishable particles [LP88, ZS01]. In [CDKW14] we also give a variant of the algorithm that can be directly applied to non-pure global spectrum (while the general case can always be reduced to the case of random pure states, such an algorithm can be useful for the manual computation of concrete examples).

From a mathematical perspective, the distributions that we compute are Duistermaat–Heckman measures, which are defined more generally using the push-forward of the Liouville measure on a symplectic manifold along the moment map [Hec82, GS82b, GS84b, GLS88, GLS96, GP90] (Section 5.2). For the purposes of this thesis, it will be convenient to restrict our attention to projective space; we refer to [CDKW14] for an exposition from the symplectic point of view.

2 Duistermaat–Heckman Measures

More generally, we may consider a random quantum state ρ\rho of fixed spectrum μ\mu and consider the corresponding Duistermaat–Heckman measures PK,μ\mathbf{P}_{K,\mu} and PT,μ\mathbf{P}_{T,\mu} constructed in the same way as before. We will see in (5.6) below that the computation of these measures can always be reduced to the case of random pure states.

We remark that there is a general definition of a Duistermaat–Heckman measure in symplectic geometry that goes as follows: Let (M,ω)(M,\omega) be a Hamiltonian KK-manifold of dimension 2n2n and μK ⁣:M→ik∗\mu_{K}\colon M\rightarrow i\mathfrak{k}^{*} its moment map. Then ωn/(2π)nn!\omega^{n}/(2\pi)^{n}n! is a volume form on MM that determines the Liouville measure of MM. By pushing forwarding along the moment map μK\mu_{K} and further along the map OK,λ↦λ\mathcal{O}_{K,\lambda}\mapsto\lambda we obtain the Duistermaat–Heckman measure for the KK-action on MM. If MM is compact then we can renormalize to obtain a probability measure PK,M\mathbf{P}_{K,M} on the moment polytope. We remark that in our definition of the non-Abelian Duistermaat–Heckman measure in [CDKW14] we had furthermore divided the push-forward measure at each point by the Liouville volume of the respective coadjoint orbit, given by

where ρK=12∑α∈RK,+α\rho_{K}=\frac{1}{2}\sum_{\alpha\in R_{K,+}}\alpha is the Weyl vector [BGV03, Proposition 7.26]. This is conceptually more appealing since it corresponds to “intersecting” with the positive Weyl chamber – just as in the definition of the moment polytope! – and it makes the formulas slightly cleaner. However, it comes at the expense of working with measures that are not probability measures, and we have chosen not to adopt this convention herein.

Let us now consider the groups and representations that correspond to the one-body quantum marginal problem and its variants (cf. Table 2.3). In the case of distinguishable particles, G=\SL(H1)×⋯×\SL(Hn)G=\SL(\mathcal{H}_{1})\times\dots\times\SL(\mathcal{H}_{n}), K=\SU(H1)×⋯×\SU(Hn)K=\SU(\mathcal{H}_{1})\times\dots\times\SU(\mathcal{H}_{n}), and H=H1⊗⋯⊗Hn\mathcal{H}=\mathcal{H}_{1}\otimes\dots\otimes\mathcal{H}_{n}. As in the preceding chapters, we may identify the collection of local eigenvalues with points in the positive Weyl chamber it+∗i\mathfrak{t}^{*}_{+}; likewise, the collection of local diagonal entries can be identified with points in it∗i\mathfrak{t}^{*} (Section 2.3). In this way, the eigenvalue distribution P\spec\mathbf{P}_{\spec} and the distribution of local diagonal entries P\diag\mathbf{P}_{\diag} introduced in Section 5.1 are identified with the Duistermaat–Heckman probability measures PK\mathbf{P}_{K} and PT\mathbf{P}_{T}, respectively.

for any test function f=f(λ⃗A,λ⃗B)f=f(\vec{\lambda}_{A},\vec{\lambda}_{B}). Here,

is the volume polynomial (5.3) for K=\SU(d)K=\SU(d), and Z>0Z>0 is a suitable normalization constant. Note that the measure P\spec\mathbf{P}_{\spec} is supported on the “diagonal” λ⃗A=λ⃗B\vec{\lambda}_{A}=\vec{\lambda}_{B}, in agreement with Chapter 2. We will later give a simple proof of (5.4) using the methods of this chapter (see (5.26)). The corresponding distribution of the one-body reduced density matrix ρA\rho_{A} is known as the Hilbert–Schmidt probability measure.

Just as Chapter 2 did for the one-body quantum marginal problem, its quantitative version (5.4) can be used to reduce the seemingly more general problem of computing the local eigenvalue distribution for random states with fixed global spectrum to the case of global pure states. More generally, let H0\mathcal{H}_{0} be a K0K_{0}-representation (e.g., one from Table 2.3) and H=H0⊗H0\mathcal{H}=\mathcal{H}_{0}\otimes\mathcal{H}_{0} the corresponding representation of K=K0×\SU(H0)K=K_{0}\times\SU(\mathcal{H}_{0}) (its “purification”). Then (5.4) implies that the probability measure PKP_{K} for pure states can be obtained as a direct integral of the measures PK0,μP_{K_{0},\mu} for fixed global spectrum μ\mu,

where d=dim⁡H0d=\dim\mathcal{H}_{0}. Conversely, since the probability distributions PK0,μ\mathbf{P}_{K_{0},\mu} vary continuously with the global spectrum μ\mu, they can be reconstructed from PK\mathbf{P}_{K} by taking limits.

Our assumption that the moment polytope ΔK\Delta_{K} has non-empty intersection with the interior of the positive Weyl chamber amounts to showing that there exists a global pure state ρ\rho whose reduced density matrices all have non-degenerate eigenvalue spectrum. We first give a criterion in the case of distinguishable particles:

where we set ∣j⟩⟨j∣k:=∣dk⟩⟨dk∣\lvert j\rangle\langle j\rvert_{k}:=\lvert d_{k}\rangle\langle d_{k}\rvert if j>dkj>d_{k}. It is not hard to see that each ρk\rho_{k} has non-degenerate spectrum. The same remains true if we perturb ρ1,…,n\rho_{1,\dots,n} slightly such that it has non-degenerate global spectrum with all eigenvalues positive. Let ρ\rho denote a purification of ρ1,…,n\rho_{1,\dots,n} on H\mathcal{H}. Then Chapter 2 shows ρn+1\rho_{n+1} and therefore all one-body reduced density matrices of ρ\rho have non-degenerate spectrum. ∎

Note that the conditions of Section 5.2 are always satisfied for the purification, where dn+1=d1⋯dnd_{n+1}=d_{1}\dotsm d_{n}. The following lemma shows that the same is true for the one-body nn-representability problem:

For bosons, we have already seen that any one-body reduced density matrix is consistent with a global pure state.

The Post-Selection Bound

where “≤\leq” denotes the positive semidefinite order of Hermitian matrices. Since the latter is preserved by the partial trace, we obtain the following bound, which holds for any permutation-invariant density operator σAk\sigma_{A^{k}}:

3 The Abelian Measure

denote the (D−1)(D-1)-dimensional standard simplex, where D=dim⁡HD=\dim\mathcal{H}. In the following, a Lebesgue measure on a closed convex body is the restriction of a translation-invariant measure on its affine hull (such a measure is unique up to normalization).

The Abelian Duistermaat–Heckman probability measure PT\mathbf{P}_{T} is equal to the push-forward of Lebesgue measure dpdp on the standard simplex ΔD\Delta_{D}, normalized to probability one, along the linear map Φ ⁣:(pk)↦∑kpkωk\Phi\colon(p_{k})\mapsto\sum_{k}p_{k}\omega_{k}.

Now fix a Lebesgue measure dλd\lambda on the affine hull of Abelian moment polytope ΔT=\convΩ\Delta_{T}=\conv\Omega. Away from the boundary of the standard simplex, the map (pk)↦∑kpkωk(p_{k})\mapsto\sum_{k}p_{k}\omega_{k} is a submersion onto this affine space, and therefore the measure PT\mathbf{P}_{T} is absolutely continuous with respect to dλd\lambda. In fact, its density function fT(λ)f_{T}(\lambda) is given by

i.e., as the volume of a parametrized polytope, measured with respect to a Lebesgue measure dp/dλdp/d\lambda on the fiber Φ−1(λ)∩ΔD\Phi^{-1}(\lambda)\cap\Delta_{D} that is normalized such that dp=dp/dλ∧dλdp=dp/d\lambda\wedge d\lambda (we freely identify differential pseudo-forms and the measures induced by them). For the one-body quantum marginal problem, (5.10) reduces to (5.2), the quantitative version of a classical marginal problem that we discussed in the introduction.

In special case that D−1=dim⁡ΔTD-1=\dim\Delta_{T}, the map Φ\Phi maps the standard simplex bijectively onto the Abelian moment polytope ΔT\Delta_{T} (which in this case is itself a simplex). It follows that

where the denominator denotes the volume of the parallelotope spanned by the (ωj−ω1)(\omega_{j}-\omega_{1}) as measured by dλd\lambda. In particular, the Abelian Duistermaat–Heckman measure for the maximal torus of \U(H)\U(\mathcal{H}) is simply Lebesgue probability measure on the standard simplex, which is in agreement with Section 5.3.

In the general case, D−1>dim⁡ΔTD-1>\dim\Delta_{T}. Consider subsets of weights whose convex hull have codimension one in ΔT\Delta_{T}. These convex hulls are precisely the critical points of the Abelian moment map, viewed as a map onto the affine hull of ΔT\Delta_{T} (the proof of Section 3.2 works just as well if ΔT\Delta_{T} is of positive codimension). They cut ΔT\Delta_{T} into convex polytopes that we will call the regular chambers. We will also considered the complement of ΔT\Delta_{T} as a chamber, called the unbounded chamber, although it is not convex. If the closures of two chambers have a common boundary of maximal dimension (i.e., of codimension one) then we shall say that the two chambers are adjacent. The affine hyperplane spanned by their common boundary will be called a critical wall. The significance of these notions is the following: Inside each regular chamber, the vertices of the convex polytopes Φ−1(λ)∩ΔD\Phi^{-1}(\lambda)\cap\Delta_{D} can be parametrized as affine functions of λ\lambda (see, e.g., [CL98, VSB+07] for details). It follows that the density function fT(λ)f_{T}(\lambda) is given by a polynomial of degree at most (D−1)−rT(D-1)-r_{T} on (the interior of) each regular chamber, where we set rT=dim⁡ΔTr_{T}=\dim\Delta_{T}. Thus we say that fT(λ)f_{T}(\lambda) is a piecewise polynomial function. As we cross a critical wall, this polynomial will in general change, and we will now describe a way to compute these “jumps”.

Consider two adjacent chambers separated by a critical wall (−,H)=c(-,H)=c. Let Ω0:={ω∈Ω:(ω,H)=c}\Omega_{0}:=\{\omega\in\Omega:(\omega,H)=c\} denote the set of weights on the wall, H0=⨁ω∈Ω0Hω\mathcal{H}_{0}=\bigoplus_{\omega\in\Omega_{0}}\mathcal{H}_{\omega} the corresponding sum of weight spaces, and D0:=dim⁡H0D_{0}:=\dim\mathcal{H}_{0} its dimension. Let dλ0d\lambda_{0} be Lebesgue measure on the affine hyperplane (−,H)=c(-,H)=c, normalized such that

where \Resz=0g=a−1\Res_{z=0}g=a_{-1} denotes the residue of a formal Laurent series g=∑kakzkg=\sum_{k}a_{k}z^{k} (it appears as part of an inversion formula for the Laplace transform). In Section 5.5 we will give many illustrations of how to use (5.13).

The jump formula (5.13) can be simplified in case only a minimal number of weights lie on the wall (that is, if D0=rTD_{0}=r_{T}). In this case, it follows from (5.11) and (5.12) that the density on the wall is constant,

where ξ∈it∗\xi\in i\mathfrak{t}^{*} is again chosen such that (ξ,H)=1(\xi,H)=1, and (5.13) simplifies to

Algorithm

Equations (5.13), (5.14) and (5.15) together can be used to recursively compute the Abelian Duistermaat–Heckman measure PT\mathbf{P}_{T} for arbitrary projective spaces. We sketch the procedure in the following algorithm:

We remark that exist other algorithms that can be used to compute the volume of parametrized polytopes (see, e.g., [Ver14, CL98, VSB+07] and references therein). In this chapter we will not pursue this route any further. However, in Chapter 6 we will use Barvinok’s algorithm to solve the corresponding discrete problem of counting the number of integral points to give an efficient algorithm for computing multiplicities in Lie group representations.

4 The Derivative Principle

In this section we describe a way to obtain the non-Abelian Duistermaat–Heckman measure PK\mathbf{P}_{K} from the Abelian measure PT\mathbf{P}_{T} that we have studied in the preceding section.

We start by considering the following model problem: Let φ\varphi be a random point in OK,λ\mathcal{O}_{K,\lambda}, chosen according to the unique KK-invariant probability measure on the coadjoint orbit. Then its restriction φ∣it\varphi|_{i\mathfrak{t}} is a random variable that takes values in it∗i\mathfrak{t}^{*}, and we denote its distribution by PT,OK,λ\mathbf{P}_{T,\mathcal{O}_{K,\lambda}}. We remark that PT,OK,λ\mathbf{P}_{T,\mathcal{O}_{K,\lambda}} is a Duistermaat–Heckman measure in the more general sense sketched in Section 5.2. For K=\U(d)K=\U(d), it can be identified with the distribution of diagonal entries of a random Hermitian matrix with spectrum λ\lambda.

In the case where λ∈it>0∗\lambda\in i\mathfrak{t}^{*}_{>0}, Harish-Chandra has proved the following fundamental formula for the Fourier transform [HC57, Theorem 2]: For all X∈itX\in i\mathfrak{t} not orthogonal to a root,

where the factor pK(λ)p_{K}(\lambda) is defined in (5.3). Since partial derivatives in real space correspond to multiplication in Fourier space, (5.16) implies that [Hec82]

where δwλ\delta_{w\lambda} is the Dirac measure at a point wλw\lambda and where ∂−α\partial_{-\alpha} denotes the partial derivative in direction −α-\alpha in the sense of distributions. In other words, for any smooth and compactly supported test function gg on it∗i\mathfrak{t}^{*} we have that

In fact, PT,OK,λ\mathbf{P}_{T,\mathcal{O}_{K,\lambda}} is the unique compactly supported solution to the differential equation (5.17) [Hec82], and it can be explicitly written as an alternating sum of convolutions of Heaviside distributions in the directions of the positive roots [GLS96]. To lift Harish-Chandra’s result to general Duistermaat–Heckman measures, we need the following observation:

For all smooth, compactly supported test functions ff on it∗i\mathfrak{t}^{*},

for all test functions hh on ik∗i\mathfrak{k}^{*}, where dgdg denotes the Haar probability measure on the compact group KK. Now recall that PT\mathbf{P}_{T} is the push-forward of Q\mathbf{Q} along the restriction ik∗→it∗i\mathfrak{k}^{*}\rightarrow i\mathfrak{t}^{*}. It follows that

As similarly observed in [Hec82, GP90], Harish-Chandra’s formula implies the following fundamental derivative principle:

where the partial derivatives ∂−α\partial_{-\alpha}, the multiplication by pKp_{K} and the restrictions to it>0∗i\mathfrak{t}^{*}_{>0} are all in the sense of distributions. In other words, we have that

for any smooth test function ff on it∗i\mathfrak{t}^{*} that is compactly supported in the interior of the positive Weyl chamber.

Let ff be a smooth test function that is compactly supported in the interior of the positive Weyl chamber. Then the same is true for pKfp_{K}f, and we find that

for all λ∈it>0∗\lambda\in i\mathfrak{t}^{*}_{>0} by applying (5.18) to pKfp_{K}f and dividing by pK(λ)≠0p_{K}(\lambda)\neq 0. In fact, (5.21) can be extended to all λ∈it+\lambda\in i\mathfrak{t}_{+}, since both the left-hand side and the right-hand side are continuous in λ\lambda. Thus,

where the second equality is Section 5.4. ∎

In mathematics, Heckman has used a variant of Section 5.4 together with the Harish-Chandra formula to study the asymptotics of multiplicities in the subgroup restriction problem [Hec82] (cf. Section 6.6 in the next chapter). Guillemin and Prato have used the same idea to derive an alternating-sum formula for non-Abelian Duistermaat–Heckman measures in symplectic geometry, which however is not directly applicable to the pure-state problem [GP90] (cf. the discussion in [CDKW14]). Woodward also mentions Paradan as a source [Woo05]. There is also a version of Harish-Chandra’s formula (5.16) for lower-dimensional coadjoint orbits [BGV03, Theorem 7.24].

Our basic assumption that the moment polytope ΔK\Delta_{K} intersects the interior of the positive Weyl chamber implies that a random pure state is mapped into the interior of the positive Weyl chamber with probability one [GS82a, p. 504]. It follows that the non-Abelian Duistermaat–Heckman measure PK\mathbf{P}_{K} can be fully recovered from the Abelian measure PT\mathbf{P}_{T} by taking partial derivatives in the directions of the negative roots, multiplying by the polynomial pK(λ)p_{K}(\lambda), and restricting to the positive Weyl chamber. In the case of the one-body quantum marginal problem, this is just (5.1) in the introduction to this chapter, with p(λ⃗1,…,λ⃗n)=pd1(λ⃗1)⋯pdn(λ⃗n)p(\vec{\lambda}_{1},\dots,\vec{\lambda}_{n})=p_{d_{1}}(\vec{\lambda}_{1})\dotsm p_{d_{n}}(\vec{\lambda}_{n}) the product of the Vandermonde determinants (5.5). We note that for the computation of averages the non-Abelian measure does not necessarily have to be computed explicitly. Instead, we may use (5.20) to reduce to the calculation of an expectation value for the Abelian measure (see Section 5.5 for an example).

The derivative principle allows us to lift structural properties to the non-Abelian measure. For example, recall from Section 5.3 that the density of the Abelian measure is on each regular chamber given by a polynomial. Section 5.4 implies that, on the interior of each chamber, the same is true for the non-Abelian measure—indeed, the polynomials for PK\mathbf{P}_{K} can be obtained from the ones of PT\mathbf{P}_{T} by taking partial derivatives and multiplying with pK(λ)p_{K}(\lambda) according to (5.19). If the Abelian measure is #RG,+\#R_{G,+} times continuously differentiable then there cannot be any measure on the walls, so that PK\mathbf{P}_{K} is absolutely continuous with piecewise polynomial density. In this case it also follows that the support of the measure is equal to the union of those regular chambers where the non-Abelian polynomial is non-zero, i.e., that it is a finite union of convex polytopes. It is instructive to compare this observation with the main result of [GS82a] and with Section 3.2, where we had already seen that the facets of ΔK\Delta_{K} are always contained in critical walls. In fact, the support of PK\mathbf{P}_{K} is always equal to the non-Abelian moment polytope ΔK\Delta_{K}, and hence a single convex polytope. Moreover, PK\mathbf{P}_{K} is always absolutely continuous with respect to Lebesgue measure on ΔK\Delta_{K}. This is folklore and can be established, e.g., by using the symplectic cross section and the local submersion theorem. It also follows from [Oko96], where Okounkov shows how to construct an abstract convex body from which the non-Abelian measure can be obtained by pushing forward in a similar way as in Section 5.3.

Computation

By combining Section 5.3 with the derivative principle, we obtain a general algorithm for computing the non-Abelian Duistermaat–Heckman measure PK\mathbf{P}_{K} under our basic assumption that ΔK\Delta_{K} intersects the interior of the positive Weyl chamber. We note that this solves the problem of exactly computing the local eigenvalue distribution of random quantum states in complete generality, since we have shown in Section 5.2 that the assumption can always be satisfied by considering the purified scenario.

We conclude this section by explicitly stating the non-Abelian jump formula for critical walls that contain a minimal number of weights (D0=rTD_{0}=r_{T}), which will be useful for the computation of examples:

Equation (5.22) can be immediately obtained from its Abelian counterpart (5.14) and the derivative principle (5.19). It is applicable as long as D−D0−1≥#RG,+D-D_{0}-1\geq\#R_{G,+}, so that the non-Abelian Duistermaat–Heckman measure is absolutely continuous across the wall.

5 Examples

We will now illustrate the general method in some low-dimensional examples, where the polytopes and measures can be easily visualized.

where we have ordered the terms on the left-hand side in the same way as in the jump formula. Next, we cross the wall with equation λ⃗⋅(1,−1)=0\vec{\lambda}\cdot(1,-1)=0 that separates the upper and the right-hand side regular chamber (1 and 2 in the figure). Using (5.14) with ξ=(1,−1)/2\xi=(1,-1)/2 we find that the density changes by

Therefore, PT\mathbf{P}_{T} has the following piecewise polynomial density function on the positive Weyl chamber:

We now cross the critical wall λ⃗⋅(−1,−1,−1)=−1\vec{\lambda}\cdot(-1,-1,-1)=-1 that separates the blue and the green chambers in Figure 5.3. It is spanned by the weights (1,1,−1)(1,1,-1), (1,−1,1)(1,-1,1) and (−1,1,1)(-1,1,1) and is therefore again minimal. By (5.22) with ξ=(−1,−1,−1)/3\xi=(-1,-1,-1)/3, the density function of PK\mathbf{P}_{K} changes by the polynomial

as we cross the wall. It follows that the density function of PK\mathbf{P}_{K} is on the two green chambers that face the viewer in Figure 5.3 equal to 7!16λ1λ2λ3λ2\frac{7!}{16}\lambda_{1}\lambda_{2}\lambda_{3}\lambda_{2}. Note that the blue and green chambers together form the part of the three-qubit polytope where λ2=min⁡kλk\lambda_{2}=\min_{k}\lambda_{k}. By using permutation-symmetry to extend the formulas to all of ΔK\Delta_{K}, we conclude that the non-Abelian Duistermaat–Heckman measure is given by the following piecewise polynomial density function:

As in the case of two qubits, it is straightforward to deduce from this the marginal eigenvalue distribution of a random pure state of three qubits.

Bosons

We apply Section 5.3 starting from the left-hand side unbounded chamber {λ1≤−n}\{\lambda_{1}\leq-n\} and successively cross the critical walls, which are points and correspond to a single weight each. At each point m=−n,−n+2,…,nm=-n,-n+2,\dots,n, the jump formula (5.14) shows that the Abelian measure changes by

It follows that the Abelian Duistermaat–Heckman density has Lebesgue density

where we set (λ1−m)+n−1:=(λ1−m)n−1(\lambda_{1}-m)^{n-1}_{+}:=(\lambda_{1}-m)^{n-1} for λ1≥m\lambda_{1}\geq m and 00 otherwise. Amusingly, (5.23) is precisely the probability density of a sum of nn independent random variables that are each distributed uniformly in the interval $$ [Fel71, §I.9, Theorem 1a]. It follows from the derivative principle that the non-Abelian measure has Lebesgue density

on [0,∞)[0,\infty), which can be readily translated into, e.g., the distribution of the maximal local eigenvalue. See Figure 5.4 for an illustration.

As an application, we compute the average value of the linear entropy of entanglement (4.11) for a random pure state of nn bosonic qubits. For a bosonic state ρ\rho on H\mathcal{H}, it is given by

where ρ1\rho_{1} denotes the one-body reduced density matrix.

The average linear entropy of entanglement of a random pure state of nn bosonic qubits is equal to 1/2−1/(2n)1/2-1/(2n).

The average linear entropy of entanglement is given by

To evaluate the right-hand side, we observe that λ12\lambda_{1}^{2} vanishes at λ1=0\lambda_{1}=0, the boundary of the Weyl chamber; thus we may use (5.20) and take limits to reduce to an integral over the Abelian measure. We obtain

where we have used that PT\mathbf{P}_{T} is symmetric about the origin. The right-hand side integral is the variance of PT\mathbf{P}_{T}. But recall that PT\mathbf{P}_{T} is the distribution of a sum of independent random variables that are uniformly distributed on $.Sincethevarianceofeachsummandis. Since the variance of each summand is1/3anditisadditiveforindependentsums,wefindthat(5.24)ispreciselyequaltoand it is additive for independent sums, we find that (5.24) is precisely equal ton.Bypluggingthisintothefirstformula,weconcludethat,indeed,. By plugging this into the first formula, we conclude that, indeed,\int d\rho\,E(\rho)=1/2-1/(2n)$. ∎

Bipartite Systems

since each factor is the volume of a (b−1)(b-1)-dimensional simplex. We now consider the negative partial derivative in the direction in the positive roots: Since there are (a2)\binom{a}{2} positive roots,

is a polynomial of degree no more than a(b−1)−(a2)a(b-1)-\binom{a}{2}. Since we differentiate each variable at most a−1a-1 times, the result will be a multiple of the symmetric polynomial ∏i=1aλA,ib−a\prod_{i=1}^{a}\lambda_{A,i}^{b-a}. On the other hand, the result is evidently antisymmetric in the variables and so will be a multiple of the Vandermonde determinant pA(λ⃗A)p_{A}(\vec{\lambda}_{A}). Since the degrees add up, a(b−a)+(a2)=a(b−1)−(a2)a(b-a)+\binom{a}{2}=a(b-1)-\binom{a}{2} it follows at once that

Thus we conclude from the derivative principle (5.19) that the eigenvalue distribution of ρA\rho_{A} is proportional to

on Δa,+={λ⃗A∈Δa:λA,1≥⋯≥λA,a}\Delta_{a,+}=\{\vec{\lambda}_{A}\in\Delta_{a}:\lambda_{A,1}\geq\dots\geq\lambda_{A,a}\}, the intersection of Δa\Delta_{a} with the positive Weyl chamber, which is the non-Abelian moment polytope for the action of K=\U(a)K=\U(a). This is the well-known formula from [LP88, ZS01]. In mathematics, the distribution of ρA\rho_{A} is also known as a normalized Wishart ensemble (see, e.g., [ASY14]). Since ρA\rho_{A} and ρB\rho_{B} have the same non-zero eigenvalues (Chapter 2), it follows immediately from (5.25) that the joint distribution of the marginal eigenvalues of both ρA\rho_{A} and ρB\rho_{B} is given by

for all test functions f=f(λ⃗A,λ⃗B)f=f(\vec{\lambda}_{A},\vec{\lambda}_{B}). For a=b=da=b=d, this is precisely (5.4) in Section 5.2.

6 Discussion

Random ensembles of states have long been studied in quantum statistical physics. In fact, Lloyd and Pagels had derived (5.25) out of thermodynamic considerations [LP88]. More recently, the typical behavior of canonical states, i.e., states that are obtained by computing the reduced density matrix of the uniform state on a subspace (encoding the energy constraint) of the system–bath Hilbert space, have been considered [PSW06, Llo06, GLTZ06], and the average von Neumann entropy of a subsystem [Lub78, Pag93] has featured in the analysis of the black hole entropy paradox [HP07]. Apart from their import from the perspective of the quantum marginal problem, random states of multipartite systems are also relevant in quantum information theory. For example, conditional entropies and mutual informations are central quantities in entanglement theory. Since they are functions of the eigenvalues only they can be studied in the framework of this chapter (e.g., in the case of tripartite pure states). Remarkable recent progress has been made by analyzing the entanglement properties of the two-body reduced density matrix ρAB\rho_{AB} of a randomly-chosen tripartite pure state [HLSW04, HLW06, ASY14, ASY12, CNY12]. In all these applications, most known results are for high-dimensional Hilbert spaces, where the powerful concentration of measure phenomenon occurs. In contrast, our exact algorithms require no such assumption and are instead well-suited for low-dimensional systems, which previously remained inaccessible. It would be highly desirable to find a common meeting ground for both techniques that would allow for an interpolation between the combinatorial and the analytical regime (cf. [BG12, BP14]).

Chapter 6 Interlude: Computing Multiplicities of Lie Group Representations

In this chapter we consider the classical branching or subgroup restriction problem in representation theory, which asks for the multiplicity of an irreducible representation of a subgroup K⊆K′K\subseteq K^{\prime} in the restriction of an irreducible representation of K′K^{\prime}. In the case of compact, connected Lie groups, we provide a polynomial-time algorithm for this problem—based on a finite-difference formula for the multiplicities and Barvinok’s algorithm for counting integral points in polytopes. Our algorithm is also applicable to the Kronecker coefficients of the symmetric group, which play an important role in the geometric complexity theory approach to the P\mathbf{P} vs. NP\mathbf{NP} problem. Whereas the computation of Kronecker coefficients is known to be #P\#\mathbf{P}-hard for Young diagrams with an arbitrary number of rows, our algorithm computes them in polynomial time if the number of rows is bounded. The finite-difference formula that we use is a discrete analogue of the derivative principle that was used in the preceding chapter. This connection can be made precise, as the asymptotic growth rates of multiplicities are directly related to the measures that we had computed in the preceding chapter. We complement our results by showing that in geometric complexity theory, such asymptotic information might not directly lead to complexity-theoretic obstructions beyond what can be obtained from moment polytopes. Non-asymptotic information on the multiplicities, such as provided by our algorithm, may therefore be essential in order to find new obstructions in geometric complexity theory.

The results in this chapter have been obtained in collaborations with Matthias Christandl and Brent Doran, and they have appeared in [CDW12]; the first part of Section 6.6 is adapted from the collaboration [CDKW14].

The decomposition of Lie group representations into irreducible sub-representations is a fundamental problem in mathematics with a variety of applications to the sciences. In atomic and molecular physics as well as in high-energy physics, this problem has been studied extensively in the context of symmetries [Wey50, WG59, Wig73], perhaps most famously in Ne’eman and Gell-Mann’s “eight-fold way” of elementary particles [Nee61, GM61, GM62]. In pure mathematics, the combinatorial resolution by Knutson and Tao of the problem of decomposing tensor products of irreducible representations of the unitary group has been a recent highlight with a long history of research [Ful00, KT99]. More recently, the representation theory of Lie groups has found novel applications in quantum information [KW01, CM06, Kly06, CSW10] and quantum computation [BCH07, BCH06, Jor08], as well as in the geometric complexity theory approach to the P\mathbf{P} vs. NP\mathbf{NP} problem in computer science [MS01, MS08, BLMW11]. In this chapter, we study the problem of computing multiplicities of Lie group representations:

Let Φ ⁣:K→K′\Phi\colon K\rightarrow K^{\prime} be a fixed homomorphism of compact, connected Lie groups. What is the multiplicity mμλm^{\lambda}_{\mu} of an irreducible KK-representation VK,μV_{K,\mu} in an irreducible KK-representation VK′,λV_{K^{\prime},\lambda}, when given as input the highest weights μ\mu and λ\lambda?

The term subgroup restriction problem comes from the archetypical case where the map Φ\Phi is the inclusion of a subgroup K⊆K′K\subseteq K^{\prime}.

The main result of this chapter is a polynomial-time algorithm for the subgroup restriction problem (Section 6.4). It takes as input bitstrings containing the coordinates of the highest weights with respect to fixed bases of fundamental weights. As a direct consequence, for any fixed λ\lambda and μ\mu the stretching function k↦mkμkλk\mapsto m^{k\lambda}_{k\mu} can be evaluated in polynomial time. Another immediate corollary is that the positivity of the coefficients mμλm^{\lambda}_{\mu} can be decided in polynomial time for any fixed homomorphism Φ ⁣:K→K′\Phi\colon K\rightarrow K^{\prime}. Mulmuley has conjectured that deciding positivity of the multiplicities mμλm^{\lambda}_{\mu} should be possible in polynomial time even if the group homomorphism Φ\Phi is also part of the input [Mul07]. This is known only for specific families of homomorphisms, such as those corresponding to the Littlewood–Richardson coefficients [KT99, MNS12], and our result can be regarded as supporting evidence for the conjecture. However, any approach to deciding positivity that proceeds by computing the actual multiplicities is of course expected to fail, since the latter problem is well-known to be #P\#\mathbf{P}-hard [Nar06, BI08]. Since representations of compact, connected Lie groups are in one-to-one correspondence with the rational representations of complex, reductive, connected algebraic groups (Section 2.1), our results can also be interpreted in the latter context.

Our polynomial-time algorithm is based on a formula for the multiplicities mμλm^{\lambda}_{\mu} (Section 6.4), which is obtained in three steps: First, we restrict from the group K′K^{\prime} to its maximal torus T′T^{\prime}. The corresponding weight multiplicities can be computed efficiently by using the classical multiplicity formula of Kostant [Kos59, Coc05] or, in fact, by evaluating a single vector partition function [BGR04, Bli08, Bli10] (Section 6.2). Second, we restrict all weights to a maximal torus TT of KK. Third, we recover the multiplicity of an irreducible KK-representation by using a finite-difference formula based on Weyl’s character formula: For any KK-representation VV, the highest weight multiplicity function mK,Vm_{K,V} of irreducible KK-representations and the weight multiplicity function mT,Vm_{T,V} are related by

where (Dαm)(λ)=m(λ+α)−m(λ)(D_{\alpha}m)(\lambda)=m(\lambda+\alpha)-m(\lambda) denotes the finite-difference operator in direction α\alpha (Section 6.3). By carefully combining the first two steps, we obtain a formula for the multiplicities that reduces Section 6.1 to the problem of counting integral points in rational convex polytopes of bounded dimension (Section 6.4). The latter can be done efficiently by using Barvinok’s algorithm [Bar94] (see also [Dye91, CHKM92, DK97, BP99, BBCV06]) and we thus obtain Section 6.4. The multiplicity formula itself has intrinsic interest beyond its application to algorithmics. One immediate insight is a piecewise quasi-polynomiality of the multiplicities and of the stretching function [Mul07].

In Section 6.5, we turn to the computation of the Kronecker coefficients gα,β,γg_{\alpha,\beta,\gamma}, which are commonly defined as the multiplicities in the decomposition of tensor products of irreducible representations of the symmetric group SkS_{k}. Kronecker coefficients are notoriously difficult to study, and finding an appropriate combinatorial interpretation is one of the outstanding problems of classical representation theory. Apart from the role for the quantum marginal problem, they appear naturally in geometric complexity theory, where their computation serves as a model problem which has been subject to a number of conjectures [Mul07]. In Section 2.4, we have seen that the Kronecker coefficients can be equivalently defined in terms of the special linear or unitary groups. For Young diagrams of bounded height, this amounts to an instance of Section 6.1 for a fixed group homomorphism Φ\Phi. Therefore the Kronecker coefficients can in this case be computed in polynomial time by using Section 6.4. We also get a clean closed-form expression for the Kronecker coefficients (Section 6.5), which not only nicely illustrates the algorithm’s effectiveness, but also implies directly that the problem of computing Kronecker coefficients with unbounded height is in GapP\mathbf{GapP}, as first proved in [BI08].

In practice, our algorithm appears to work rather well as long as the rank of the Lie group GG is not too large. In the case of Kronecker coefficients for Young diagrams with two rows, we can easily go up to k=108k=10^{8} boxes using commodity hardware. In contrast, all other software packages known to the authors cannot go beyond only a moderate number of boxes (k=102k=10^{2} on the same hardware as used above). Moreover, by distributing the computation of weight multiplicities onto several processors, we have been able to compute Kronecker coefficients for Young diagrams with three rows and k=105k=10^{5} boxes in a couple of minutes. A preliminary implementation of the algorithm is available at [Wal12b]. We hope that our algorithm will provide a useful tool in experimental mathematics, theoretical physics, and geometric complexity theory.

2 Weight Multiplicities

Throughout this chapter, we will use the notations and conventions of Section 2.1; however, we will label all objects such as weight lattices, irreducible representations, etc. by the compact connected Lie group KK, since we will mostly not need its complexification GG explicitly. Recall that the irreducible representations of KK are labeled by their highest weight in ΛK,+∗\Lambda^{*}_{K,+}. An arbitrary finite-dimensional representation VV can always be decomposed into irreducible sub-representations,

We will call the function mK,Vm_{K,V} thus defined the highest weight multiplicity function.

We may similar decompose VV into irreducible representations of the maximal torus T⊆KT\subseteq K, which we recall are one-dimensional and labeled by elements of the weight lattice ΛK∗\Lambda^{*}_{K}. We thus obtain the decomposition into weight spaces

We will call mT,V(ω)=dim⁡Vωm_{T,V}(\omega)=\dim V_{\omega} the weight multiplicity function. An equivalent way of encoding the weight multiplicities is in terms of the (formal) character,

The character of an irreducible representation VK,λV_{K,\lambda} is given by the famous Weyl character formula

where ρK=∑α∈RK,+α/2∈ΛK∗\rho_{K}=\sum_{\alpha\in R_{K,+}}\alpha/2\in\Lambda^{*}_{K} is known as the Weyl vector. To make sense of the right-hand side fraction, we need to work in the larger ring of functions that are supported in a finite number of “cones” of the form

This restriction ensures that multiplication is still well-defined [Kna02] (unlike for general functions!). We find that the denominator in (6.6) is indeed invertible, with inverse

In the last equation we have introduced the Kostant partition function

which counts the number of ways that a weight can be written as a sum of positive roots (this number is always finite since the positive roots span a proper cone). It follows directly from the above that

Thus the multiplicity of a weight ω\omega in an irreducible representation VK,λV_{K,\lambda} is given by the well-known Kostant multiplicity formula [Kos59],

For any fixed group KK, the Kostant partition function can be evaluated in polynomial time by using Barvinok’s algorithm [Bar94], since it amounts to counting integral points in a convex polytope in an ambient space of fixed dimension. Therefore, weight multiplicities for fixed groups KK can be computed efficiently. This idea has been implemented by Cochet [Coc05] to compute weight multiplicities for the classical Lie algebras (but using the method of [BBCV06] instead of Barvinok’s algorithm). We note that the problem of computing weight multiplicities is of course a special case of Section 6.1 where KK is the maximal torus of K′K^{\prime}.

Weight Multiplicities as a Single Partition Function

for all λ∈ΛK,+∗,ω∈ΛK∗\lambda\in\Lambda^{*}_{K,+},\omega\in\Lambda^{*}_{K}, where ϕA\phi_{A} is a vector partition function defined by

Note that this improves over the Kostant multiplicity formula (6.7), where weight multiplicities are expressed as an alternating sum over several invocations of a vector partition function. In particular, (6.8) is an evidently positive formula. Billey, Guillemin, and Rassart have constructed (6.8) for the Lie group K=\SU(d)K=\SU(d) [BGR04] by using Gelfand–Tsetlin patterns [GT88]; the general construction is due to Bliem [Bli08] based on Littelmann patterns [Lit98].

We note that the assumption of semisimplicity for (6.8) is not a restriction. If KK is a general compact connected Lie group then its Lie algebra can always decomposed as

where [k,k][\mathfrak{k},\mathfrak{k}] is the Lie algebra of a compact connected semisimple Lie group K\sesiK_{\sesi} and z\mathfrak{z} the Lie algebra of the center Z(K)Z(K) of KK. By Schur’s lemma (2.23), each element of the center acts by a scalar on an irreducible representation VK,λV_{K,\lambda}. Therefore, all weights that appear in VK,λV_{K,\lambda} have the same restriction to z\mathfrak{z}. It follows that

where we write ω=ω\sesi⊕ωz\omega=\omega_{\sesi}\oplus\omega_{z} according to the corresponding decomposition of weight lattices ΛK∗=ΛK\sesi∗⊕ΛZ(K)∗\Lambda^{*}_{K}=\Lambda^{*}_{K_{\sesi}}\oplus\Lambda^{*}_{Z(K)}, and likewise for λ\lambda. These multiplicities can thus be evaluated by using (6.8).

3 The Finite Difference Formula

Let VV be a finite-dimensional representation of the compact connected Lie group KK. In the preceding section we have seen that we can compute the weight multiplicity function mT,Vm_{T,V} from the highest weight multiplicity function mK,Vm_{K,V} by using one of the classical formulas (6.6) and (6.7), or by evaluating the vector partition function (6.8) of Bliem. By “inverting” the Weyl character formula, the converse can also be achieved:

For any finite-dimensional KK-representation VV, we have that

where (Dαm)(λ)=m(λ+α)−m(λ)(D_{\alpha}m)(\lambda)=m(\lambda+\alpha)-m(\lambda) is the finite-difference operator in direction α\alpha.

By linearity, it suffices to establish the lemma for an irreducible representation V=VK,λV=V_{K,\lambda}. The Weyl character formula (6.6) can be rewritten in the form

Now consider the right-hand side of (6.12). Since λ+ρK\lambda+\rho_{K} is a strictly dominant weight in ΛK,>0∗=ΛK∗∩it>0∗\Lambda^{*}_{K,>0}=\Lambda^{*}_{K}\cap i\mathfrak{t}^{*}_{>0}, it is sent by any Weyl group element w≠1w\neq 1 to the interior of a different Weyl chamber. That is, for any w≠1w\neq 1 there exists a positive root α∈RK,+\alpha\in R_{K,+} such that (w(λ+ρK),Hα)<0(w(\lambda+\rho_{K}),H_{\alpha})<0. Therefore w(λ+ρK)−ρKw(\lambda+\rho_{K})-\rho_{K} is a dominant weight if only if w=1w=1, in which case it is equal to λ\lambda. It follows that the right-hand side of (6.12) identifies with a function on the weight lattice whose restriction to ΛK,+∗\Lambda^{*}_{K,+} is equal to the indicator function of {λ}\{\lambda\}, i.e., to the highest weight multiplicity function mK,VK,λ=δλm_{K,V_{K,\lambda}}=\delta_{\lambda} of VK,λV_{K,\lambda}. ∎

The idea of using (6.6) for determining multiplicities of irreducible representations goes back at least to Steinberg [Ste61], who proved a formula for the multiplicity cλα,βc^{\alpha,\beta}_{\lambda} of an irreducible representation VK,λV_{K,\lambda} in the tensor product VK,α⊗VK,βV_{K,\alpha}\otimes V_{K,\beta}. These multiplicities cλα,βc^{\alpha,\beta}_{\lambda} are called the Littlewood–Richardson coefficients for KK (cf. Section 2.4). Steinberg’s formula involves an alternating sum over the Kostant partition function (6.7) and can therefore be evaluated efficiently as described by Cochet [Coc05]. De Loera and McAllister give another method for computing Littlewood–Richardson coefficients [DLM06], which applies Barvinok’s algorithm to a result by Berenstein and Zelevinsky [BZ01]. Since the tensor products of irreducible KK-representations are just the irreducible representations of K×KK\times K, the problem of computing Littlewood–Richardson coefficients is again a special case of Section 6.1. The Clebsch–Gordan series in quantum mechanics is routinely derived in a similar fashion (it corresponds to the case K=\SU(2)K=\SU(2)).

In fact, it is not hard to see that the coefficients can be defined by the expansion ∏α∈RK,+ ⁣(1−e−α)=∑γ∈ΓKcγe−γ\prod_{\alpha\in R_{K,+}}\!\left(1-e^{-\alpha}\right)=\sum_{\gamma\in\Gamma_{K}}c_{\gamma}e^{-\gamma}.

4 Multiplicities for the Subgroup Restriction Problem

Let VV be a representation of K′K^{\prime} and ∣ψ⟩∈V\ket{\psi}\in V a weight vector of weight ω∈ΛK′∗\omega\in\Lambda^{*}_{K^{\prime}}. If we restrict the action to KK via Φ ⁣:K→K′\Phi\colon K\rightarrow K^{\prime} then ∣ψ⟩\ket{\psi} is a weight vector of weight ϕ∗ω∈ΛK∗\phi^{*}\omega\in\Lambda^{*}_{K}.

As alluded to in the introduction, our strategy for solving the subgroup restriction problem then is the following: Given an irreducible representation VK′,λV_{K^{\prime},\lambda} of K′K^{\prime}, we can determine its weight multiplicities with respect to the maximal torus TK′T_{K^{\prime}} by using any of the formulas from Section 6.2. We then obtain the weight multiplicities for TT by restricting as in Section 6.4. Finally, we reconstruct the multiplicity of an irreducible representation VK,μV_{K,\mu} by using the finite-difference formula from Section 6.3. If this procedure were to be translated directly into an algorithm, the runtime would be polynomial in the coefficients of λ\lambda, i.e., exponential in their bitlength (cf. the branching formula by Straumann [Str65]). Indeed, the number of weights generically grows polynomially and can even be of the order of the dimension of the irreducible representation VK′,λV_{K^{\prime},\lambda}, which according to the Weyl dimension formula is given by

It is however possible to combine (6.8) with the restriction map ϕ∗\phi^{*} in a way that will subsequently give rise to an algorithm that runs in polynomial time in the bitlength of the input:

We start with the finite-difference formula in the form (6.13),

According to Section 6.4, weight multiplicities for KK can be expressed in terms of weight multiplicities for K′K^{\prime}:

Finally, decompose B=B1⊕B2B=B_{1}\oplus B_{2} according to ΛK\sesi′∗⊕ΛK\sesi′∗\Lambda^{*}_{K^{\prime}_{\sesi}}\oplus\Lambda^{*}_{K^{\prime}_{\sesi}} and ϕ∗=ϕ\sesi∗⊕ϕz∗\phi^{*}=\phi^{*}_{\sesi}\oplus\phi^{*}_{z} according to ΛK∗=ΛK\sesi∗⊕ΛZ(K)∗\Lambda^{*}_{K}=\Lambda^{*}_{K_{\sesi}}\oplus\Lambda^{*}_{Z(K)}. Then we can rewrite the above in the following way:

We note that the proof of Section 6.4 is constructive: The maps A′A^{\prime} and B′B^{\prime}, whose existence is asserted by the proposition, are defined in (6.16) in terms of the maps AA and BB constructed explicitly in [Bli08, §4] (or [BGR04, Proof of Theorem 2.1] for k=su(d)\mathfrak{k}=\mathfrak{su}(d)). In Section 6.5 we give an illustration in the context of the Kronecker coefficients. If one uses the Kostant multiplicity formula (6.7) rather than Bliem’s formula (6.8) in the proof of Section 6.4 then one obtains at a similar formula for the multiplicities mμλm^{\lambda}_{\mu}. After completion of this work, we have learned of [Hec82, (3.5)], which is derived precisely in this spirit (and attributed to Kostant).

Polynomial-Time Algorithm for the Subgroup Restriction Problem

We will now formulate our polynomial-time algorithm for the subgroup restriction problem. As we have just explained, (6.15) reduces the computation of the multiplicities mμλm^{\lambda}_{\mu} to counting the number of integral points in rational convex polytopes of the form (6.18). We shall suppose that the highest weights λ\lambda and μ\mu, which are the input to our algorithm, are given in terms of bitstrings containing coordinates with respect to the identification (6.17). Clearly, for each of the finitely many γ∈ΓK\gamma\in\Gamma_{K}, the polytope ΔA′,B′(λ,μ+γ)\Delta_{A^{\prime},B^{\prime}}(\lambda,\mu+\gamma) defined in (6.18) can be described in polynomial size in the bitlength of the input (e.g., in terms of linear equalities and inequalities), and it can be produced from the input in polynomial time. Therefore we may use Barvinok’s algorithm to compute the number of integral points in each of these polytopes in polynomial time [Bar94]. We thus obtain the following algorithm:

There are at least two software packages which have implemented Barvinok’s algorithm, namely LattE [DLDK+11] and barvinok [Ver14, VSB+07]. In Section 6.1 we have reported on the performance of our preliminary implementation [Wal12b] of Section 6.4 for computing Kronecker coefficients using the latter package.

5 Kronecker Coefficients

In this section we will describe precisely how the Kronecker coefficients can be computed using the general method.

When computing Kronecker coefficients using our method, we are only interested in the subgroup restriction problem for the symmetric subspaces rather than for arbitrary irreducible representations VλabcV^{abc}_{\lambda}. By specializing the construction of Section 6.4 to this one-parameter family of representations, we obtain the following formulas:

Therefore, the Kronecker coefficient for Young diagrams λ,μ,ν\lambda,\mu,\nu with kk boxes and no more than aa, bb and cc rows, respectively, is given by the formula

and the corresponding weight spaces are all one-dimensional. On the other hand, the dual map between the weight lattices induced by the tensor product embedding

The formulas asserted in the proposition follow at once. ∎

6 Asymptotics

is equal to Lebesgue measure on the standard simplex, normalized to total volume

On the other hand, PT′\mathbf{P}_{T^{\prime}} is equal to Lebesgue measure on the standard simplex normalized to probability one, so that:

Now consider H\mathcal{H} as a representation of T⊆T′T\subseteq T^{\prime}, the maximal torus of KK. By pushing forward both the left and the right-hand side of (6.22) along the map (xi)↦∑k=1Dxiωi(x_{i})\mapsto\sum_{k=1}^{D}x_{i}\omega_{i}, we obtain that

(Section 5.3 and Section 6.4). Thus the Abelian Duistermaat–Heckman measure encodes the asymptotics of the weight multiplicities. In the case of the quantum marginal problem, this is plainly visible by comparing (5.2) and (6.20).

since the (suitably rescaled) finite differences converge to partial derivatives. It follows by using the definition of the measures (6.21) that

where pa,pb,pcp_{a},p_{b},p_{c} are the Vandermonde determinants (5.5), d=abc−1−(a2)−(b2)−(c3)d=abc-1-\binom{a}{2}-\binom{b}{2}-\binom{c}{3}, and where the sum runs over all Young diagrams α,β,γ\alpha,\beta,\gamma with kk boxes each and no more than aa, bb and cc rows, respectively (if ΔK∩it>0∗≠∅\Delta_{K}\cap i\mathfrak{t}^{*}_{>0}\neq\emptyset).

The link between representation theory and geometry is quite remarkable. Not only can one read off the existence of a pure state with given local eigenvalues from the non-vanishing of the corresponding Kronecker coefficients gkλ,kμ,kνg_{k\lambda,k\mu,k\nu}, but their asymptotic growth also encodes the probability of finding these eigenvalue spectra when the global state is chosen according to the invariant probability measure. See Figure 6.1 for an illustration of the convergence of the corresponding multiplicity measure.

Restricting to the action of K=\SU(a)K=\SU(a) on the first tensor factor, we find that

For large kk, it follows readily from Weyl’s dimension formula (6.14) that

for some constant Z>0Z>0. Together with (6.24), we recover (5.25), the formula for the density of the eigenvalue distribution of ρA\rho_{A} for a random bipartite pure state.

Order of Growth and Geometric Complexity Theory

where for the last equality we have used (6.2). By the Weyl dimension formula (6.14),

7 Discussion

In a recent preprint, our algorithm for computing Kronecker coefficients has been analyzed in some detail and it has also been shown that it is possible to decide positivity in linear time for Young diagrams of bounded height [PP14]. The problem of efficiently deciding the positivity of Kronecker coefficients for general Young diagrams, though, is still wide open, partly because we do not know of an effective combinatorial description akin to the honeycomb model for the Littlewood–Richardson coefficients [KT99].

In the past chapters, we have studied the one-body reduced density matrix in quantum mechanics from a variety of perspectives. In Chapter 3, we gave a new solution to the one-body quantum marginal in terms of “Ressayre-type inequalities”. In Chapter 4, we studied multipartite entanglement from the perspective of the one-body marginals. In Chapter 5, we showed how the joint distribution of the local eigenvalues can be computed by reducing to the distribution of diagonal entries; the discrete analogue of this reduction leads to an efficient algorithm for the subgroup restriction problem as we have seen in this Chapter 6. Common to all our results is the remarkable role played by the maximal unipotent subgroups and the interplay between highest weights and weights, which in each case allowed us to reduce from a non-Abelian quantum-mechanical problem to an Abelian one, and thus in essence to the classical combinatorics of weights.

Chapter 7 The Search for Further Entropy Inequalities

In the second part of this thesis, we go beyond the study of one-body reduced density matrices and consider general quantum marginals. Motivated by the fundamental role of entropy in physics and information theory, we start by introducing in this chapter the problem of determining the linear inequalities that constrain the von Neumann entropy of the marginals of a multipartite quantum state [Pip03]. The strong subadditivity of the von Neumann entropy is perhaps the most important such inequality [LR73], and an indispensable tool in quantum statistical physics and quantum information theory [OP93]. The discovery of any further entropy inequality would be considered a major breakthrough, and it would shed further light on the general quantum marginal problem.

The following introduction is partially adapted from [GW13]. We refer to [CT06, Yeu02] and [NC04] for comprehensive introductions to classical and quantum entropy.

Let us first consider the classical situation.

The Shannon entropy of a random variable XX with finitely many outcomes is given by

where p=(px)p=(p_{x}) is the probability distribution of XX (i.e., pxp_{x} is the probability of an outcome xx).

Given a collection of random variables X1,…,XnX_{1},\dots,X_{n} defined on a common probability space, we can then consider the Shannon entropy H(XI)H(X_{I}) of any non-empty subset XI=(Xi)i∈IX_{I}=(X_{i})_{i\in I} of the variables. These entropies are not independent: For example, monotonicity asserts that the Shannon entropy can never decrease if more random variables are taken into account:

A second example is the strong subadditivity of the Shannon entropy:

Equivalently, the conditional entropy and the conditional mutual information are always non-negative. To study the entropies of subsystems systematically, we define the classical entropy region

In general, the set Cn\mathcal{C}_{n} has a complicated geometrical structure [ZY97]. However, its closure Cn‾\overline{\mathcal{C}_{n}} is a convex cone [ZY97], which we call the classical entropy cone. Like any closed convex cone, Cn‾\overline{\mathcal{C}_{n}} can be described by linear inequalities. To see this, consider the dual cone

Each element (νI)∈Cn∗(\nu_{I})\in\mathcal{C}_{n}^{*} can be identified with an entropy inequality ∑IνIH(XI)≥0\sum_{I}\nu_{I}H(X_{I})\geq 0 that is satisfied by the Shannon entropy. The bipolar theorem now asserts that the bidual cone Cn∗∗\mathcal{C}_{n}^{**} is equal to Cn‾\overline{\mathcal{C}_{n}} (e.g., [Roc72]). Thus the set of entropy inequalities (or even just its extreme rays) determines the classical entropy region up to closure [Pip86]. Matús̆ has shown that the classical entropy region contains the relative interior of the classical entropy cone, so that \relintCn‾⊆Cn⊆Cn‾\relint\overline{\mathcal{C}_{n}}\subseteq\mathcal{C}_{n}\subseteq\overline{\mathcal{C}_{n}}.

Monotonicity (7.1) and strong subadditivity (7.2) together span the polyhedral cone of entropy inequalities of Shannon-type. For any given candidate inequality it can be automatically checked by using linear programming if it is an entropy inequality of Shannon-type [YY, Yeu97]. For a long time, these were the only known inequalities. Equivalently, it was not known if monotonicity and strong subadditivity were the only constraints on a non-negative vector (hI)(h_{I}) to be approximable by the Shannon entropies of random variables.

In the seminal work [ZY98], Zhang and Yeung have shown that for n≥4n\geq 4 random variables there exist entropy inequalities that are not of Shannon-type. In particular, they have proved that

is a linear entropy inequality that is not of Shannon-type. Here, I(XI:XJ)=S(XI)+S(XJ)−S(XI∪J)I(X_{I}:X_{J})=S(X_{I})+S(X_{J})-S(X_{I\cup J}) and I(XI:XJ∣XK):=H(XI∪K)+H(XJ∪K)−H(XI∪J∪K)−H(XK)I(X_{I}:X_{J}|X_{K}):=H(X_{I\cup K})+H(X_{J\cup K})-H(X_{I\cup J\cup K})-H(X_{K}) are the Shannon (conditional) mutual information. In fact, there are infinitely many independent inequalities that are not of Shannon-type. Thus the classical entropy cone Cn\mathcal{C}_{n} is not polyhedral for n≥4n\geq 4 [Mat07, DFZ11]. Its general structure is still only poorly understood, and any improved understanding should have direct applications to network information theory [Yeu02, SJ13].

The Quantum Entropy Cone

We now consider the situation in quantum mechanics. Here, the natural analogue of the Shannon entropy is the von Neumann entropy:

The von Neumann entropy of a density matrix ρ\rho on a finite-dimensional Hilbert space is given by

By the spectral theorem, the von Neumann entropy S(ρ)S(\rho) is equal to H(λ⃗)H(\vec{\lambda}), the Shannon entropy of the spectrum λ⃗\vec{\lambda} of ρ\rho, which is a probability distribution. It is a concave function of ρ\rho.

Now let ρ\rho be a density matrix describing the state of a quantum system of nn distinguishable particles with tensor-product Hilbert space H=⨂i=1nHi\mathcal{H}=\bigotimes_{i=1}^{n}\mathcal{H}_{i}. The state of any subset I⊆{1,…,n}I\subseteq\{1,\dots,n\} of the particles is described by the reduced density matrix ρI=\trIcρ\rho_{I}=\tr_{I^{c}}\rho formed by tracing out the Hilbert space of the other particles. We define the quantum entropy region to be [Pip03]

Clearly, Qn⊇Cn\mathcal{Q}_{n}\supseteq\mathcal{C}_{n}, since any joint probability distribution can be considered as a multipartite density matrix. In general, Qn\mathcal{Q}_{n} has a complex structure and in particular is neither closed nor convex [LW05b]. But its closure is again a convex cone, called the quantum entropy cone. We recall a proof of this important fact:

The quantum entropy cone Qn‾\overline{\mathcal{Q}_{n}} is indeed a convex cone.

(1) We first show that Qn+Qn⊆Qn\mathcal{Q}_{n}+\mathcal{Q}_{n}\subseteq\mathcal{Q}_{n}: Let ρ\rho, ρ′\rho^{\prime} be quantum states on ⨂i=1nHi\bigotimes_{i=1}^{n}\mathcal{H}_{i} and ⨂i=1nHi′\bigotimes_{i=1}^{n}\mathcal{H}^{\prime}_{i}, respectively. Then ρ′′:=ρ⊗ρ′\rho^{\prime\prime}:=\rho\otimes\rho^{\prime} is a quantum state on ⨂i=1nHi⊗Hi′\bigotimes_{i=1}^{n}\mathcal{H}_{i}\otimes\mathcal{H}^{\prime}_{i}, and ρI′′=ρI⊗ρI′\rho^{\prime\prime}_{I}=\rho_{I}\otimes\rho^{\prime}_{I} for each subset I⊆{1,…,n}I\subseteq\{1,\dots,n\}. By additivity of the von Neumann entropy, S(ρI′′)=S(ρI)+S(ρI′)S(\rho^{\prime\prime}_{I})=S(\rho_{I})+S(\rho^{\prime}_{I}), which shows the claim.

where h(p)=−plog⁡p−(1−p)log⁡(1−p)h(p)=-p\log p-(1-p)\log(1-p) is the binary entropy function. Let ε>0\varepsilon>0. Since h(p)h(p) is continuous and h(0)=0h(0)=0, we may choose kk large enough such that h(p)≤εh(p)\leq\varepsilon for p=λ/kp=\lambda/k, and hence

Since ε>0\varepsilon>0 was arbitrary, we may conclude that (λS(ρI))∈Qn‾(\lambda S(\rho_{I}))\in\overline{\mathcal{Q}_{n}}. This establishes the second claim.

By taking limits, points (1) and (2) together imply that Qn‾\overline{\mathcal{Q}_{n}} is a convex cone. ∎

The most immediate difference to the classical case is that the von Neumann entropy is no longer monotonic: Global quantum states can exhibit less entropy than their reductions (a signature of entanglement), which also shows that Qn⊋Cn\mathcal{Q}_{n}\supsetneq\mathcal{C}_{n}. Instead, the von Neumann entropy satisfies weak monotonicity:

Strong subadditivity, however, famously remains valid for quantum entropies [LR73]:

In fact, (7.4) and (7.5) are easily shown to be equivalent by the process of purification [Lie75]. Since purification is a non-linear construction, this does not imply equivalence on the level of the entropy regions; but see the discussion in [LMRW13].

Balanced Entropy Inequalities

Instead of directly determining the quantum entropy cone, it is natural to approach the problem by asking which of the classical entropy inequalities might continue to hold for the von Neumann entropy. Since the latter is no longer monotonic, we need to identify those classical entropy inequalities which do not “involve” monotonicity. An interesting class of entropy inequalities introduced by Chan does precisely that:

An entropy inequality ∑IνIH(XI)≥0\sum_{I}\nu_{I}H(X_{I})\geq 0 or ∑IνIS(ρI)≥0\sum_{I}\nu_{I}S(\rho_{I})\geq 0 is called balanced [Cha03] (also correlative [Han75]) if

For example, strong subadditivity is balanced, while monotonicity is not. Chan has shown that the classical entropy cone is determined by the set of balanced entropy inequalities together with monotonicity. More precisely, he has proved that any Shannon entropy inequality can be decomposed uniquely into the form

where the left-hand side is a balanced entropy inequality and the right-hand side a conic combination of conditional entropies, i.e. all ri≥0r_{i}\geq 0 [Cha03]. In other words, the dual cone Cn∗\mathcal{C}^{*}_{n} of Shannon entropy inequalities is a direct sum of the cone of balanced entropy inequalities and the cone spanned by monotonicity (7.1). It is thus natural to consider the following problem.

Which balanced Shannon entropy inequalities also hold true for the von Neumann entropy?

We remark that the Zhang–Yeung inequality (7.3) as well as the infinite families in [Mat07, DFZ11] are balanced, since they are linear combinations of conditional mutual informations. On the other hand, we note that there are unbalanced entropy inequalities that hold for the von Neumann entropy, e.g. weak monotonicity. It can be argued that there is no direct quantum counterpart of the decomposition (7.6) [Maj14], which perhaps makes it unlikely that the problem of determining all linear entropy inequalities satisfied by the von Neumann entropy can be reduced to Chapter 7.

Discussion

We conclude this introduction by mentioning some related avenues of investigation. Entropic constraints are of interest not only for the Shannon and von Neumann entropy, but also for other kinds of entropies, e.g. differential entropies [Cha03] and Rényi entropies [LMW13, CHLW14]. Another interesting direction is to relax the notion of subsystems beyond the tensor-product case. Instead of only considering partial traces over the factors of a tensor-product Hilbert space, we may consider marginals with respect to more general subalgebras of observables [OP93]. This leads directly to the study of entropic uncertainty relations [BCC+10, MU88], entropy power inequalities [KS14], and entropy in space-time and might thus serve as a unifying framework for studying entropy in general quantum systems.

Chapter 8 Entropy Inequalities from Phase Space

In this chapter we study the entropy inequalities satisfied by two classes of quantum states—namely, stabilizer states and Gaussian states (the latter can be seen as continuous-variable counterparts of the former). Both classes of states can exhibit intrinsically quantum features, such as multi-particle entanglement, but they possess enough structure to allow for a concise and computationally efficient description and so have proven to be extremely useful in quantum information theory and beyond. For example, the stabilizer formalism is a basic tool for constructing quantum error-correcting codes, while Gaussian states and transformations are routinely used in quantum optics (see, e.g., [NC04, WPGP+12]). Quantum phase-space methods have been built around both classes of states, and it is this point of view we will exploit here.

The results in this chapter have been obtained in collaboration with David Gross, and they have appeared in [GW13].

Our crucial observation then is that certain quantum entropies are simple functions of corresponding classical entropies. More precisely, in the case of stabilizer states (Section 8.4), we find that

Therefore, if ∑IνIH(XI)≥0\sum_{I}\nu_{I}H(X_{I})\geq 0 is a balanced entropy inequality satisfied by the Shannon entropies of the random variables XIX_{I} then the same inequality is also satisfied by the von Neumann entropies of the quantum states ρI\rho_{I}:

In particular, the von Neumann entropy of stabilizer states respects all balanced Shannon entropy inequalities, such as the inequalities of non-Shannon type found in [ZY98, Mat07, DFZ11]. This completely solves Chapter 7 for the class of stabilizer states.

Our construction can also be understood in the group-theoretical framework of [CY02]. Here it is well-known that there are inequalities for the Shannon entropy which do not hold for arbitrary random variables, but only for random variables constructed from certain classes of subgroups [LC07]. By analyzing the construction above, we show that the von Neumann entropy for stabilizer states similarly respects a further entropy inequality which does not hold for arbitrary random variables (and hence quantum states)—namely the Ingleton inequality [LC07], which is the balanced inequality

Here, Iρ(I:J)=S(ρI)+S(ρJ)−S(ρI∪J)I_{\rho}(I:J)=S(\rho_{I})+S(\rho_{J})-S(\rho_{I\cup J}) and Iρ(I:J∣K)=S(ρI∪K)+S(ρJ∪K)−S(ρK)−S(ρI∪J∪K)I_{\rho}(I:J|K)=S(\rho_{I\cup K})+S(\rho_{J\cup K})-S(\rho_{K})-S(\rho_{I\cup J\cup K}) are the quantum (conditional) mutual information.

We find it instructive to understand how the above classical model manages to respect monotonicity (7.1), while the quantum state may violate it. For example, since stabilizer states can be entangled (even maximally so, see Section 8.3 below), S(ρ1)=S(ρ2)=1S(\rho_{1})=S(\rho_{2})=1 and S(ρ12)=0S(\rho_{12})=0 are perfectly valid entropies of a stabilizer state which certainly violate monotonicity. Equation (8.1) states that the classical model is more highly mixed than the quantum one, in the sense that the entropy associated with a subset II is higher by an amount of ∣I∣\lvert I\rvert ddits. That is precisely the maximal amount by which quantum mechanics can violate monotonicity.

where S2(ρ)=−log⁡\trρ2S_{2}(\rho)=-\log\tr\rho^{2} is the quantum Rényi-2 entropy; hαh_{\alpha} is the differential Rényi-α\alpha entropy, defined by hα(X)=(1−α)−1log⁡∫p(x)αdxh_{\alpha}(X)=(1-\alpha)^{-1}\log\int p(x)^{\alpha}dx for any positive α≠1\alpha\neq 1, with p(x)p(x) the probability density of the random variable XX with respect to Lebesgue measure. In the limiting case α→1\alpha\rightarrow 1, we recover a formula involving the differential Shannon entropy h(X)=−∫p(x)log⁡p(x)h(X)=-\int p(x)\log p(x), which has previously appeared in [AGS12], attributed to Stratonovich:

Thus, Rényi-2 entropies of Gaussian states respect all balanced entropy inequalities that hold for the Shannon entropies of multivariate normal distributions. The latter have been investigated in the literature (see, e.g., [HS07, SH11]).

In Section 8.6 we discuss the relation between our results for stabilizer states and Gaussian states and point towards further avenues of investigations.

Independently of the work presented in this chapter, Linden, Ruskai, and Winter have published an analysis of the entropy cone generated by stabilizer states [LMRW13]. Their methods – focusing on group-theoretical constructions – are conceptually complementary to our phase-space approach. [LMRW13] contains a complete characterization of the entropy cone generated by four-party stabilizer states. The paper also lists further examples of inequalities which, like the Ingleton Inequality, are respected by stabilizer states, even though there are classical distributions violating it. While not originally stated explicitly, their results also imply that all balanced inequalities remain valid for stabilizer states (see Theorem 11 in [LMRW13] and discussion thereafter).

2 Discrete Phase Space

In this section, we present a self-contained account of Weyl operators and stabilizer states in the discrete phase-space picture. This section does not contain original results. All statements could be found in some form in [Got96, App05, Gro06, Bea13, KG13], albeit not in a unified language.

The characters of the additive group of the phase space VV are V^={χd(ω(v,−)):v∈V}≅V\widehat{V}=\{\chi_{d}(\omega(v,-)):v\in V\}\cong V.

The symplectic complement of a submodule M⊆VM\subseteq V is the submodule Mω={v∈V:ω(v,m)=0  (∀m∈M)}M^{\omega}=\{v\in V:\omega(v,m)=0\;(\forall m\in M)\}. In the case of prime dd, it is well-known that dim⁡M+dim⁡Mω=dim⁡V\dim M+\dim M^{\omega}=\dim V—however, in general the dimension (or rank) might not even be well-defined. Still there is an important analogue that holds in the general case:

∣M∣∣Mω∣=∣V∣\lvert M\rvert\lvert M^{\omega}\rvert=\lvert V\rvert.

is both injective and surjective (it is certainly well-defined). Injectivity follows immediately from the non-degeneracy of the symplectic form. For surjectivity, let τ∈V/M^\tau\in\widehat{V/M}. Then w↦τ([w])w\mapsto\tau([w]) is a character of VV. By Section 8.2, there exists v∈Vv\in V such that τ([w])=χd(ω(v,w))\tau([w])=\chi_{d}(\omega(v,w)). Since τ\tau vanishes on MM, v∈Mωv\in M^{\omega}. Thus Φ\Phi is an isomorphism, and we find that

The following important corollary follows from Section 8.2 and M⊆(Mω)ωM\subseteq(M^{\omega})^{\omega}:

We call a submodule M⊆VM\subseteq V an isotropic submodule if M⊆MωM\subseteq M^{\omega}, i.e. if ω(m,m′)=0\omega(m,m^{\prime})=0 for all m,m′∈Mm,m^{\prime}\in M. Finally consider VI=⨁i∈IViV_{I}=\bigoplus_{i\in I}V_{i}, the phase space of particles I⊆{1,…,n}I\subseteq\{1,\dots,n\}. There is a natural way of restricting a submodule MM to VIV_{I}: we set

where VIV_{I} is identified with a submodule of VV in the natural way.

Weyl Representation

In both the even and the odd case, it now follows from (8.4) and (8.5) that

3 Stabilizer States in Phase Space

From the fact that GG is a group, we deduce that P2=PP^{2}=P; since all elements of GG are unitaries, P=P†P=P^{\dagger}; and (8.9) implies that \trP=dn/∣G∣\tr P=d^{n}/|G|. Hence PP projects onto a (dn/∣G∣)\big(d^{n}/|G|\big)-dimensional subspace, called the stabilizer code of GG. Note that the stabilizer code is the subspace of all vectors that are stabilized by GG. The corresponding stabilizer state is ρ=1dn∑gg\rho=\frac{1}{d^{n}}\sum_{g}g. We refer to [NC04, §10.5] for an introduction to the stabilizer formalism from the perspective of quantum information theory.

We now prove the central theorem that provides a description of stabilizer states in terms of discrete phase space:

for all subsets I⊆{1,…,n}I\subseteq\{1,\dots,n\}. If dd is odd then there is a canonical element ρ(M)\rho(M) in each equivalence class, given by

It is compatible with reductions, i.e. ρ(M)I=ρ(MI)\rho(M)_{I}=\rho(M_{I}).

Consequently, ρ(M,ν)\rho(M,\nu) and ρ(M,μ)\rho(M,\mu) are related by conjugation with the Weyl operator w(v)w(v).

If dd is odd, then (8.6) implies that w(m)w(m′)=w(m+m′)w(m)w(m^{\prime})=w(m+m^{\prime}). It follows that G:={w(m):m∈M}G:=\{w(m):m\in M\} is a stabilizer group of cardinality ∣M∣\lvert M\rvert, with corresponding stabilizer state ρ(M)=1dn∑m∈Mw(m).\rho(M)=\frac{1}{d^{n}}\sum_{m\in M}w(m). This is the canonical representative (8.12) of the equivalence class of states associated with MM.

(3) Injectivity: Suppose that ρ(M,μ)\rho(M,\mu) and ρ(M′,μ′)\rho(M^{\prime},\mu^{\prime}) are two equivalent stabilizer states. As we saw, conjugating with a Weyl operator only changes the phases, so we may in fact assume that states are equal. Now assume that M≠M′M\neq M^{\prime}, so that there exists, e.g., m∈M∖M′m\in M\setminus M^{\prime}. Then, (8.9) shows that

(4) Reduction: We now show that our construction is compatible with reduction. For this, observe that

Since any valid assignment of phases μm\mu_{m} restricts to the submodule MI=M∩VIM_{I}=M\cap V_{I}, it follows that [ρ(M)I]=[ρ(MI)][\rho(M)_{I}]=[\rho(M_{I})]. It is also immediate that the canonical element (8.12) is compatible with reduction.

(5) Entropy: In view of the preceding point, it suffices to show (8.11) for I={1,…,n}I=\{1,\dots,n\}. Recall that the cardinalities of MM and of the corresponding stabilizer group GG agree. We have already seen that the dimension of the stabilizer code is equal to dn/∣G∣d^{n}/\lvert G\rvert. Thus,

(observe the judicious choice of signs). The stabilizer code is one-dimensional, since dn/∣G∣=22/4=1d^{n}/\lvert G\rvert=2^{2}/4=1, and spanned by the vector ∣Ψ+⟩=(∣00⟩+∣11⟩)/2\ket{\Psi^{+}}=\left(\ket{00}+\ket{11}\right)/\sqrt{2} which is stabilized by all operators in GG. Thus the stabilizer state ρ\rho is the maximally entangled state ∣Ψ+⟩⟨Ψ+∣\lvert\Psi^{+}\rangle\langle\Psi^{+}\rvert. In accordance with Theorem 8.4, its entropies are given by

since M1=M2={0}M_{1}=M_{2}=\{0\}. Another choice of stabilizer subgroup is

4 A Classical Model for Stabilizer Entropies

If the local dimension dd is odd, there exists a discrete Wigner function that replicates many properties of its better-known continuous-variable counterpart [Gro06]. It is the function on phase space defined by

The central observation is that in the case of stabilizer states, the Wigner function Wρ(M)W_{\rho(M)} is a probability distribution on phase space, i.e. it attains only non-negative values which sum to one. In fact [Gro05, Gro06],

Thus the Wigner function of the stabilizer state with isotropic submodule M⊆VM\subseteq V is given by the uniform distribution on Mω⊆VM^{\omega}\subseteq V.

We now show that this construction defines a classical model which reproduces the entropies of the given stabilizer state and its reduced states, up to a certain constant. In fact, by phrasing the construction solely in terms of the symplectic complement (hence without recourse to the Wigner function), this result can be established for arbitrary local dimension, even or odd:

and the same conclusion holds if we replace the Shannon and von Neumann entropy by any Rényi entropy. If dd is odd then the above construction can also be obtained by interpreting the Wigner function WρW_{\rho} as the probability distribution of the random variable XX.

To prove (8.15), denote by πI ⁣:V→VI\pi_{I}\colon V\rightarrow V_{I} the projection onto the phase space of parties I⊆{1,…,n}I\subseteq\{1,\dots,n\}. It will be convenient to consider VIV_{I} as a symplectic submodule of VV in the natural way. To avoid any notational ambiguity, we denote by ωI\omega_{I} the restriction of the symplectic form to VIV_{I} and by XωIX^{\omega_{I}} the symplectic complement of a subspace XX taken correspondingly within VIV_{I}. Observe that

Indeed, if v∈Mωv\in M^{\omega} and mI∈MIm_{I}\in M_{I}, then ωI(πI(v),mI)=ω(v,mI)=0\omega_{I}(\pi_{I}(v),m_{I})=\omega(v,m_{I})=0. On the other hand, we find that

To see this, consider a vector vI∈VIv_{I}\in V_{I} and note that if ωI(vI,πI(Mω))=0\omega_{I}(v_{I},\pi_{I}(M^{\omega}))=0 then ω(vI,Mω)=0\omega(v_{I},M^{\omega})=0, hence vI∈M∩VI=MIv_{I}\in M\cap V_{I}=M_{I} since (Mω)ω=M(M^{\omega})^{\omega}=M. We conclude from (8.16) and (8.17) that

Note that XI=πI(X)X_{I}=\pi_{I}(X). Since πI\pi_{I} is a group homomorphism, it follows that XIX_{I} is distributed uniformly on its range, so that

where we have used (8.11) in the last step. We have thus established (8.15). The same result holds if we replace the Shannon and von Neumann entropy by a classical and quantum Rényi entropy, respectively. This is because the random variables XIX_{I} are distributed uniformly on their range and the stabilizer states ρ(M)I\rho(M)_{I} are normalized projectors, so that the respective entropies coincide.

Finally, it is clear from (8.14) that for odd dd the distribution of XX coincides with the Wigner function Wρ(M)W_{\rho(M)} of the stabilizer state. It remains to show that the Wigner function WρIW_{\rho_{I}} of a reduced state ρI\rho_{I} is obtained by marginalizing the full Wigner function (in other words: the quantum and the classical way of reducing to subsystems commute):

for all v∈VIv\in V_{I}. While this can easily be proved in full generality from the definition of the Wigner function, it is also true that for the special case of stabilizer states (8.19) follows directly from (8.14) and (8.18). ∎

The following corollary completely solves Chapter 7 in the case of stabilizer states:

The von Neumann entropies of stabilizer states satisfy all balanced entropy inequalities satisfied by the Shannon entropy. Moreover, they satisfy the Ingleton inequality (8.2).

As described in the introduction, the first claim follows immediately from (8.15). This is because for any balanced information inequality ∑IνIH(XI)≥0\sum_{I}\nu_{I}H(X_{I})\geq 0 we necessarily have that [SH11]

Hence the correction term in (8.15) cancels as we sum over all subsystems:

For the second claim, we recall that the random variable XX is uniformly distributed on MωM^{\omega}, which is a group, and that the projections πI ⁣:V→VI\pi_{I}\colon V\rightarrow V_{I} are group homomorphisms (also when restricted to MωM^{\omega}). In this situation, it was shown in [LC07] that the Ingleton inequality (8.2) holds for the random variables XI=πI(X)X_{I}=\pi_{I}(X). (In the language of [CY02], the entropy vector (H(XI))(H(X_{I})) can be characterized by the normal subgroups ker⁡(πI)∩Mω⊆Mω\ker(\pi_{I})\cap M^{\omega}\subseteq M^{\omega}.) Since the Ingleton inequality is balanced, the same argument that we used above shows that the Ingleton inequality also holds for the von Neumann entropies of stabilizer states. ∎

Pure stabilizer states correspond to maximally isotropic submodules M⊆VM\subseteq V. Such submodules are called Lagrangian, and they satisfy ∣M∣=dn\lvert M\rvert=d^{n} and M=MωM=M^{\omega}. Thus in this case our classical model can also be defined by choosing X∈MX\in M uniformly at random. Furthermore, since πI(M)≅M/(ker⁡πI∩M)\pi_{I}(M)\cong M/(\ker\pi_{I}\cap M), we may also define XIX_{I} to be the coset of XX modulo ker⁡(πI)∩M=M∩VIc=MIc\ker(\pi_{I})\cap M=M\cap V_{I^{c}}=M_{I^{c}}. In this way, we recover the construction of Theorem 11 in [LMRW13].

5 Gaussian States

Here, Σ\Sigma is a real, positive definite n×nn\times n-matrix called the covariance matrix, and μ\mu is the vector of first moments. Conversely, for every covariance matrix Σ\Sigma that satisfies the uncertainty relation Σ+iΩ≥0\Sigma+i\Omega\geq 0, where Ω\Omega is the symplectic matrix, there exists a corresponding Gaussian quantum state. Note that (8.21) is the probability density of a random vector X=(X1,…,X2n)X=(X_{1},\dots,X_{2n}) with multivariate normal distribution of mean μ\mu and covariance matrix Σ\Sigma. Using (8.20), it follows that the Rényi-2 entropy of the quantum state, S2(ρ)=−log⁡\trρ2S_{2}(\rho)=-\log\tr\rho^{2}, is directly related to the differential Rényi-2 entropy of the continuous random variable XX, h2(X)=−log⁡∫Wρ2(x) dxh_{2}(X)=-\log\int W^{2}_{\rho}(x)\ dx:

The reduced state ρI\rho_{I} for some subset of modes I⊆{1,…,n}I\subseteq\{1,\dots,n\} is again a Gaussian state, and its covariance matrix is equal to the corresponding submatrix of Σ\Sigma. Thus the Wigner function of ρI\rho_{I} is given by the marginal probability density of the variables XI=(Xi)i∈IX_{I}=(X_{i})_{i\in I}, and using (8.22) we find that

Equation (8.23) states that the Rényi-2 entropy of a Gaussian quantum state is always lower than the phase space entropy of its classical model, as given by the Wigner function. It is so by a precise amount, namely by log⁡(2π)\log(2\pi) bits per mode.

Let ρ\rho be a Gaussian state with covariance matrix Σ\Sigma, and define a random variable X=(X1,…,Xn)X=(X_{1},\dots,X_{n}) with probability density given by the Wigner function Wρ(x)W_{\rho}(x). Then, for any positive α≠1\alpha\neq 1,

where hα(X)=(1−α)−1log⁡∫Wρα(x) dxh_{\alpha}(X)=(1-\alpha)^{-1}\log\int W_{\rho}^{\alpha}(x)\ dx is the differential Rényi-α\alpha entropy. In the limit α→1\alpha\rightarrow 1, we recover

where h(X)=−∫Wρ(x)log⁡Wρ(x) dxh(X)=-\int W_{\rho}(x)\log W_{\rho}(x)\ dx is the differential Shannon entropy.

By Gaussian integration, the differential Rényi-α\alpha entropy of the random variable XIX_{I} is given by

The assertions of the theorem follow from this and (8.23). ∎

Equation (8.24) has been previously used in [AGS12], where the formula is attributed to Stratonovich. Just as in the discrete case, we immediately get the following corollary:

The Rényi-2 entropies of Gaussian states satisfy all balanced entropy inequalities that are valid for the differential Shannon entropies of multivariate normal distributions.

Interestingly, it is not clear whether Section 8.5 holds for the von Neumann entropy. We remark that Gaussian states can violate the Ingleton inequality (8.2) (in contrast to stabilizer states, cf. Section 8.4). Indeed, this is well-known for multivariate normal distributions [SH11], and the counterexample presented in [SH11] can be readily adapted:

is a covariance matrix on the four-particle phase space that satisfies the uncertainty relation Σ+iΩ≥0\Sigma+i\Omega\geq 0, and the corresponding four-partite Gaussian quantum state violates the Ingleton inequality.

6 Discussion

Theorems 8.6 and 8.8 can be phrased in a unified language by observing that all reductions ρI\rho_{I} of a stabilizer state are proportional to projectors, while the corresponding random variables XIX_{I} are uniformly distributed on their support. As noted in Theorem 8.6, this implies that we may replace the von Neumann and Shannon entropy in (8.15) by any quantum and classical Rényi-α\alpha entropy, respectively. For discrete random variables the latter are defined by Hα(X):=(1−α)−1log⁡∑xpxαH_{\alpha}(X):=(1-\alpha)^{-1}\log\sum_{x}p_{x}^{\alpha}. In particular, we find that

We conclude this chapter with a few remarks. Our work uses the classical model provided by the Wigner function as a tool for proving statements that do not, a priori, seem to be connected to phase-space distributions. This point of view has been employed before, e.g. to construct quantum expanders [GE08], to establish simulation algorithms [VFGE12, ME12, VWFE13], and to demonstrate the onset of contextuality [HWVE14]. It would be interesting to see further applications. While it is known that the Wigner function approach cannot be straight-forwardly translated to non-stabilizer states [Hud74, Gro06, Gro07], our discussion suggests searching for other maps from quantum states to probability distributions that reproduce entropies faithfully, up to state-independent additive constants.

In order to establish the Ingleton inequality (8.2), we have used the group-theoretical approach to classical information inequalities [CY02]. It would be highly desirable to find a quantum-mechanical analogue of this work (see [CM06] and Chapter 9 for partial results towards this goal, motivated by the quantum marginal problem).

Chapter 9 Entropy Inequalities from Recoupling Coefficients

In this chapter we consider entropy inequalities for general quantum states. This requires us to go beyond the mathematical techniques of the first part of this thesis, which only gave us control over non-overlapping marginals. To this end, we unveil a novel link between the existence of multipartite quantum states with given marginal eigenvalues and the representation theory of the symmetric group SkS_{k}. We use this link to give a new proof of the strong subadditivity and weak monotonicity of the von Neumann entropy, and propose an approach to finding further entropy inequalities based on studying representation-theoretic symbols and their symmetry properties.

The results in this chapter have been obtained in collaboration with Matthias Christandl and Burak Şahinoğlu, and they have appeared in the preprint [CŞW12] (cf. [Şah12] for an earlier version).

To establish the link to representation theory, we consider the recoupling coefficients of the symmetric group SkS_{k}, which measure the overlap of two ways of decomposing a triple tensor product of irreducible representations of SkS_{k} (Section 9.2). We find that in the “semiclassical limit” k→∞k\rightarrow\infty, the recoupling coefficients’ norm decreases at most polynomially for a sequence of Young diagrams of kk boxes converging to the eigenvalues of a given tripartite quantum state ρABC\rho_{ABC} and its reduced states ρA\rho_{A}, ρB\rho_{B}, ρC\rho_{C}, ρAB\rho_{AB}, ρBC\rho_{BC}; conversely, if there exists no such quantum state then the coefficients decrease exponentially in norm (Theorem 9.6 in Section 9.3). This is a first general result for the quantum marginal problem with overlaps. It extends significantly the characterization of the triples ρA\rho_{A}, ρB\rho_{B}, ρAB\rho_{AB} by the Kronecker coefficient of the symmetric group that we had reviewed in Section 2.4 [CM06, Kly04, DH04, CHM07, CDKW14]. Our result can be generalized to an arbitrary number of particles and linearly many reduced states, and may thus be regarded as a first step towards a quantum-mechanical version of Chan and Yeung’s description of the set of compatible Shannon entropies in terms of group theory [CY02].

To illustrate the power of this characterization, we show that symmetry properties of the recoupling coefficients alone imply the strong subadditivity and weak monotonicity of the von Neumann entropy (Section 9.5). This symmetry is particularly transparent when the coefficients are expressed in a graphical calculus for tensor categories (Section 9.4). Our strategy of proof suggests a hitherto unexplored route towards establishing further entropy inequalities by exploiting the symmetries of higher-order representation-theoretic objects (Section 9.8).

Our result is inspired by Wigner’s seminal work on the semiclassical behavior of quantum spins, which are described by the representation theory of the group \SU(2)\SU(2) [WG59]. The recoupling coefficients of \SU(2)\SU(2), known as the Wigner 6j6j-symbols in their rescaled, more symmetric form [WG59], describe the relation between individual spins jAj_{A}, jBj_{B}, jCj_{C}, their total spin jABCj_{ABC} and the intermediate spins jABj_{AB} and jBCj_{BC} (the Racah W-coefficients [Rac42] are also closely related). As first noted by Wigner, there is a dichotomy in the semiclassical limit where all spins are simultaneously large: the 6j6j-symbol decays polynomially if there exists a tetrahedron with side lengths jAj_{A}, jBj_{B}, jCj_{C}, jABj_{AB}, jBCj_{BC}, jABCj_{ABC}, and exponentially otherwise [WG59, §27] (Figure 9.1).

That the asymptotics are in both cases guided by the existence of a geometric object—for Wigner, a tetrahedron with certain side lengths, for us, a quantum state with certain spectral properties—is not an accident. Via Schur–Weyl duality, our limit k→∞k\rightarrow\infty can similarly be understood as a semiclassical limit of representation-theoretic coefficients of unitary groups (Section 9.6). In Section 9.7 we show that Wigner’s scenario is in fact a special case of the quantum marginal problem considered above: For every tetrahedron, we construct a tripartite quantum state in a faithful, i.e., side length-encoding way, and for every recoupling coefficient for \SU(2)\SU(2) we construct a corresponding recoupling coefficient of the symmetric group. The existence of Wigner’s tetrahedron can be understood as an instance of the more general problem of characterizing the eigenvalues of certain partial sums of matrices [Bac10], and our construction generalizes readily. This extends the connection between the non-overlapping quantum marginal problem and Horn’s conjecture mentioned in Section 2.4 [Kly04].

2 Recoupling Coefficients

Recall from Section 2.4 that the finite-dimensional irreducible representations of the symmetric group SkS_{k} are labeled by Young diagrams with kk boxes, that is, ordered partitions λ1≥⋯≥λl>0\lambda_{1}\geq\dots\geq\lambda_{l}>0 of ∑iλi=k\sum_{i}\lambda_{i}=k. As before, we write λ⊢k\lambda\vdash k for such a partition and [λ][\lambda] for the associated irreducible unitary representation of SkS_{k}; we denote its dimension by dλ:=dim⁡[λ]d_{\lambda}:=\dim[\lambda]. Any finite-dimensional representation VV of SkS_{k} can be decomposed into a direct sum of irreducible representations, and if VV is a unitary representation then this decomposition can also be made unitary. Concretely, consider the space of SkS_{k}-linear maps \HaλV:=\HomSk([λ],V)\Ha^{V}_{\lambda}:=\Hom_{S_{k}}([\lambda],V) defined as in (2.22) and equip \HaλV\Ha^{V}_{\lambda} with the re-scaled Hilbert–Schmidt inner product

(1) Any unit vector in \HaλV\Ha^{V}_{\lambda} is an SkS_{k}-linear isometry, and any two orthogonal vectors have orthogonal range.

(2) The direct sum of the SkS_{k}-linear maps

defines an SkS_{k}-linear unitary isomorphism ⨁λ⊢k[λ]⊗\HaλV≅V\bigoplus_{\lambda\vdash k}[\lambda]\otimes\Ha^{V}_{\lambda}\cong V.

(2) This follows from (1) and Schur’s lemma. ∎

In particular, we may decompose a tensor product [α]⊗[β][\alpha]\otimes[\beta] of two irreducible representations:

The Clebsch–Gordan isomorphism of the symmetric group is the SkS_{k}-linear unitary isomorphism

defined as in Section 9.2. Its components are SkS_{k}-linear isometric embeddings; they will be denoted by Φλαβ ⁣:[λ]⊗\Haλαβ→[α]⊗[β]\Phi^{\alpha\beta}_{\lambda}\colon[\lambda]\otimes\Ha^{\alpha\beta}_{\lambda}\rightarrow[\alpha]\otimes[\beta]. According to (2.24), the dimension of \Haλαβ\Ha^{\alpha\beta}_{\lambda} is equal to the Kronecker coefficient gα,β,λg_{\alpha,\beta,\lambda}.

Now we consider a triple tensor product. Since the tensor product is associative, we have

Decomposing accordingly using (9.2), we get an isomorphism

By Schur’s lemma, this allows us to identify the multiplicity spaces for each fixed λ\lambda,

The recoupling coefficients of the symmetric group are the components of the isomorphism (9.4) for fixed μ\mu and ν\nu, denoted by

In other words, they are defined by the relation

in terms of the Clebsch–Gordan maps from Section 9.2.

In contrast to the case of \SU(2)\SU(2), these recoupling coefficients are linear maps rather than scalars, since the “Clebsch–Gordan series” for SkS_{k} is not multiplicity-free. Their size is thus measured by an operator norm, and it will be convenient to employ the Hilbert–Schmidt norm ∥X∥HS⁡2:=\trX†X\lVert X\rVert_{\operatorname{HS}}^{2}:=\tr X^{\dagger}X as well as the operator norm ∥X∥∞:=sup⁡∥ψ∥=1∥Xψ∥\lVert X\rVert_{\infty}:=\sup_{\lVert\psi\rVert=1}\lVert X\psi\rVert (cf. Section 9.2).

where the direct sum runs over all Young diagram with kk boxes and at most dd rows. In the following we shall denote by PλP_{\lambda} the orthogonal projector onto a direct summand [λ]⊗Vλd[\lambda]\otimes V^{d}_{\lambda} in (9.6).

the orthogonal projectors onto the respective direct summands in the second and third line of (9.7) (observe that each is defined as a product of commuting projectors). The following lemma connects the operator norm of their product to the operator norm of the corresponding recoupling coefficient.

Recall from (9.5) that the recoupling coefficients are defined by the identity

where the last equality holds because both EE and FF are isometries. Now note that EE†EE^{\dagger} is precisely equal to the orthogonal projector onto

On the other hand, PP as defined in (9.8) is the orthogonal projector onto

For the following it will be useful to relate the recoupling coefficients’ operator norm to their Hilbert–Schmidt norm:

Schur–Weyl duality also leads to an alternative definition of the recoupling coefficients in terms of unitary groups (Section 9.6).

3 Overlapping Marginals and Recoupling Coefficients

If there exists a quantum state ρABC\rho_{ABC} with eigenvalues r⃗A\vec{r{}}_{A}, r⃗B\vec{r{}}_{B}, r⃗C\vec{r{}}_{C}, r⃗AB\vec{r{}}_{AB}, r⃗BC\vec{r{}}_{BC}, r⃗ABC\vec{r{}}_{ABC} then there exists a sequence of Young diagrams α,β,γ,μ,ν,λ⊢k\alpha,\beta,\gamma,\mu,\nu,\lambda\vdash k with k→∞k\rightarrow\infty boxes and at most aa, bb, etc. rows such that

Conversely, if (r⃗A,r⃗B,r⃗C,r⃗AB,r⃗BC,r⃗ABC)(\vec{r{}}_{A},\vec{r{}}_{B},\vec{r{}}_{C},\vec{r{}}_{AB},\vec{r{}}_{BC},\vec{r{}}_{ABC}) is not associated to any tripartite density matrix then for every sequence of Young diagrams satisfying (9.11) we have

We start with the proof of the “if” statement. Define P~\widetilde{P} as the sum of the projectors Pαβγλ,μP_{\alpha\beta\gamma}^{\lambda,\mu} – defined as in (9.8) – for which ∥αˉ−r⃗A∥1≤δ\lVert\bar{\alpha}-\vec{r{}}_{A}\rVert_{1}\leq\delta, ∥βˉ−r⃗B∥1≤δ\lVert\bar{\beta}-\vec{r{}}_{B}\rVert_{1}\leq\delta, etc.; Q~\widetilde{Q} is defined accordingly. By (9.13) and the fact that there are only \poly(k)\poly(k) many Young diagrams with a bounded number of rows,

where ε=\poly(k)exp⁡(−kδ2/2)\varepsilon=\poly(k)\exp(-k\delta^{2}/2). Now we use

which holds for arbitrary projectors P~\widetilde{P}, Q~\widetilde{Q} and quantum states σ\sigma, For pure states σ=∣ϕ⟩⟨ϕ∣\sigma=\lvert\phi\rangle\langle\phi\rvert, \tr(PQσ)=⟨ϕ∣PQ∣ϕ⟩≥⟨ϕ∣P∣ϕ⟩−∣⟨ϕ∣P(1−Q)∣ϕ⟩∣≥⟨ϕ∣P∣ϕ⟩−∥(1−Q)∣ϕ⟩∥=\tr(Pσ)−1−\tr(Qσ)\tr(PQ\sigma)=\braket{\phi|PQ|\phi}\geq\braket{\phi|P|\phi}-\lvert\braket{\phi|P(1-Q)|\phi}\rvert\geq\braket{\phi|P|\phi}-\lVert(1-Q)\ket{\phi}\rVert=\tr(P\sigma)-\sqrt{1-\tr(Q\sigma)} by the Cauchy–Schwarz inequality; the general statement follows by considering a purification of σ\sigma. and obtain

Using (9.9), (9.10) and the triangle inequality, we find that

where the sum extends over Young diagrams whose normalization is δ\delta-close to the eigenvalues associated to ρABC\rho_{ABC} and its marginals, respectively (as specified above). Since the number of terms in this sum is again upper-bounded by \poly(k)\poly(k), we can find sequences of Young diagrams satisfying (9.11) and (9.12).

Using the Cauchy–Schwarz inequality, the right-hand side can be upper-bounded by the square roots of each of the six traces \tr(PαρA⊗k)\tr(P_{\alpha}\rho_{A}^{\otimes k}), \tr(PβρB⊗k)\tr(P_{\beta}\rho_{B}^{\otimes k}), etc., which in turn can be upper-bounded via (9.13). Thus we find

For pure quantum states ρABC\rho_{ABC}, the Schmidt decomposition (2.2) implies that necessarily r⃗AB=r⃗C\vec{r{}}_{AB}=\vec{r{}}_{C} and r⃗A=r⃗BC\vec{r{}}_{A}=\vec{r{}}_{BC}. Therefore, we can discard the two-body spectra, and the problem reduces to a one-body quantum marginal problem. On the level of representation theory, it suffices to consider single-row Young diagrams λ=(k)\lambda=(k), corresponding to the trivial representation; hence, μ=γ\mu=\gamma and α=ν\alpha=\nu according to (2.25), and it can be shown easily that \lVert\mbox{\scriptsize\begin{bmatrix}\alpha&\beta&\mu\\ \gamma&\lambda&\nu\end{bmatrix}}\rVert_{\operatorname{HS}}^{2}=\dim\Ha^{\alpha\beta}_{\gamma}, which is the Kronecker coefficient of the symmetric group. In this way, Theorem 9.6 specializes to the results of [CM06, Kly04, CHM07] discussed in Section 2.4. This also shows that recoupling coefficients can grow with kk.

Our result can be generalized to more than three parties by considering the following quantity: as in (9.3), successively decompose a tensor product of irreducible representations in two inequivalent ways; the corresponding “generalized recoupling coefficients” then are the components of the resulting isomorphism for fixed intermediate labels μj\mu_{j} and νk\nu_{k}, and an analogous result can be established for these coefficients. They are in the same way related to Wigner’s 3nj3nj-symbols for \SU(2)\SU(2) as the recoupling coefficients are related to the 6j6j-symbol. Just as Theorem 9.6 does not cover the eigenvalues of ρAC\rho_{AC}, in general only a linear number of the exponentially many reduced states can be controlled in this fashion (e.g., the nearest-neighbor reduced states in a linear chain of particles). However, the “if” part of Theorem 9.6 immediately generalizes to an arbitrary number of marginals, since it only relies on the spectrum estimation theorem (9.13) and the “union bound” (9.14). What the representation-theoretic quantities involved in controlling all marginal spectra should be is an intriguing question, with possible ramifications for the search for new entropy inequalities of the von Neumann entropy, as we detail in the next section.

4 Symmetry Properties of the Recoupling Coefficients

In the following we use a graphical calculus for symmetric monoidal categories to deduce symmetry properties of the recoupling coefficients for the symmetric group (see, e.g., the reviews [Coe10] and [Sel11], [Tur10, §2], or [Pre04] for a more physical introduction). An alternative, purely algebraic proof is given at the end of this section. Both the strong subadditivity of the von Neumann entropy as well as its weak monotonicity can then be understood in terms of the coefficients’ symmetries (Section 9.5).

Recall from Section 9.2 that the multiplicity spaces \Haλαβ\Ha^{\alpha\beta}_{\lambda} are given by the space of SkS_{k}-linear maps from [λ][\lambda] to [α]⊗[β][\alpha]\otimes[\beta]. In each multiplicity space, let us choose maps Φλ,iαβ\Phi^{\alpha\beta}_{\lambda,i} that form an orthonormal basis with respect to the inner product (9.1). We will represent them by

in the graphical calculus. The maps Φλ,iαβ\Phi^{\alpha\beta}_{\lambda,i} are nothing but components of the Clebsch–Gordan isometries Φλαβ\Phi_{\lambda}^{\alpha\beta} (Section 9.2). It follows from (9.5) that

By taking the trace over [λ][\lambda] and deforming the above graphic, we obtain the following graphical expression for the matrix elements of the recoupling coefficients.

Our goal is to transform the right-hand side expression in (9.17) into a form that renders its symmetries apparent. For this, recall from Section 2.4 that the irreducible representations of the symmetric group are self-dual, i.e., [λ]≅[λ]∗[\lambda]\cong[\lambda]^{*}, because they can be defined over the reals. We saw that this implied that \Ha1λλ\Ha^{\lambda\lambda}_{\mathbf{1}} is one-dimensional, i.e., there exists a single copy of the trivial representation 1\mathbf{1} in each tensor product [λ]⊗[λ][\lambda]\otimes[\lambda]. We shall denote the corresponding basis vector by

omitting the leg corresponding to the identity object 1\mathbf{1} as is usual in the graphical calculus. It can be concretely written as a maximally entangled state ∑i∣λ,i⟩⊗∣λ,i⟩/dλ\sum_{i}\ket{\lambda,i}\otimes\ket{\lambda,i}/{\sqrt{d_{\lambda}}} in any real orthonormal basis ∣λ,i⟩\ket{\lambda,i} of [λ][\lambda] (i.e., in a basis such that SkS_{k} acts by real orthogonal matrices). We denote the adjoint of (9.18) by reversing arrows. It is then easy to see that we have the “teleportation identity”

We can use (9.18) and its adjoint to raise and lower indices, i.e., to reverse the direction of arrows. We thus obtain the following important property of the Clebsch–Gordan isometries (cf. [Ham89, (7-205a)]):

form orthonormal bases of the space ([α]⊗[β]⊗[λ])Sk([\alpha]\otimes[\beta]\otimes[\lambda])^{S_{k}} of SkS_{k}-invariant vectors in the triple tensor product.

Since the dimensions of ([α]⊗[β]⊗[λ])Sk([\alpha]\otimes[\beta]\otimes[\lambda])^{S_{k}} and of \Haλαβ\Ha^{\alpha\beta}_{\lambda} agree by self-duality of [λ][\lambda], it suffices to show that both sets of vectors are orthonormal. For the first set, observe that it follows from the teleportation identity (9.19) that

since ϕi\phi_{i} is an orthonormal basis with respect to the inner product (9.1).

For the second set, we find similarly that

We finally introduce the symmetric notation:

We note that the vectors (9.20) depend on the choice of arrow that was reversed. However, by Section 9.4 any such choice gives rise to unitarily equivalent bases of the space of SkS_{k}-invariants! We thus obtain the following result:

By inserting the teleportation identity (9.19) once for each of the six arrows, we obtain

By first applying the unitary transformation that relates the second orthonormal basis in Section 9.4 to the first (at the vertices kk and ll) and then using definition (9.20) (at all four vertices), this is in turn equal to

The right-hand side of (9.21) is the symmetric group analogue of Wigner’s 6j6j-symbol, which can be obtained in the same way from the recoupling coefficients of \SU(2)\SU(2). It is immediately apparent from the graphical calculus that it has the symmetries of a tetrahedron. We remark that for our purposes it was important to study the recoupling coefficients in Section 9.3, since the dimensions of irreducible SkS_{k}-representations grow exponentially with kk and thus affect the asymptotics. We record the following consequence, which has a well-known counterpart for \SU(2)\SU(2); cf. [LW05a, (B4)].

are invariant under exchanging the columns (β,λ)↔(μ,ν)(\beta,\lambda)\leftrightarrow(\mu,\nu) as well as (α,γ)↔(μ,ν)(\alpha,\gamma)\leftrightarrow(\mu,\nu).

This is an immediate consequence of Section 9.4, since the right-hand side norm in (9.21) is invariant under reflection of the diagram by the axes through the edges labeled by α\alpha and β\beta, respectively. ∎

We now give an alternative, algebraic proof of Section 9.4 and Section 9.4 that follows along the same lines as the graphical proof.

In quantum information theory, maximally entangled states on a Hilbert space H⊗H\mathcal{H}\otimes\mathcal{H} are defined by the formula

with respect to an orthonormal basis ∣i⟩\ket{i}. They satisfy the fundamental identity

for any operator XX on H\mathcal{H}, where XTX^{T} denotes the transpose in the basis ∣i⟩\ket{i}. Thus they are invariant under operations of the form U⊗U‾U\otimes\overline{U}, where U∈\U(H)U\in\U(\mathcal{H}) is a unitary and where U‾\overline{U} denotes its complex conjugate with respect to the basis ∣i⟩\ket{i} [HH99]. In particular, this implies that for any basis ∣λ,i⟩\ket{\lambda,i} of [λ][\lambda] in which SkS_{k} acts by orthogonal transformations,

is the (unique up to phase) invariant vector in [λ]⊗[λ][\lambda]\otimes[\lambda]—as we had asserted before (cf. (9.18)). By using (9.24) it is straightforward to verify that the following two well-known properties hold:

This is the algebraic version of (9.19). It follows that for any two operators X ⁣:K→K′⊗HX\colon\mathcal{K}\rightarrow\mathcal{K}^{\prime}\otimes\mathcal{H} and Y ⁣:H⊗L→L′Y\colon\mathcal{H}\otimes\mathcal{L}\rightarrow\mathcal{L}^{\prime} we have the relation

The normalized trace of any operator XX can be written as

For any α\alpha, β\beta and λ\lambda, we shall consider the following sets of vectors in ([α]⊗[β]⊗[λ])Sk([\alpha]\otimes[\beta]\otimes[\lambda])^{S_{k}},

constructed as in Section 9.4. We now prove algebraically that each set forms an orthonormal basis. For the first,

by (9.27) and the definition of the inner product (9.1). For the second set of vectors,

We now consider the recoupling coefficients. First, (9.5) and (9.27) give

We may now apply (9.26) to X=∣μγλ,i⟩X=\ket{\mu\gamma\lambda,i} and Y=Φμ,jαβY=\Phi^{\alpha\beta}_{\mu,j} in order to rewrite

Continuing in this way and using definition (9.28), we obtain the following expression for the matrix elements of the recoupling coefficient:

The sum of their absolute values squared over all indices ii, jj, kk and ll is equal to

where PαβμP^{\alpha\beta\mu} denotes the orthogonal projection onto ([α]⊗[β]⊗[μ])Sk([\alpha]\otimes[\beta]\otimes[\mu])^{S_{k}}, Pαα=∣Ψα+⟩⟨Ψα+∣P^{\alpha\alpha}=\lvert\Psi^{+}_{\alpha}\rangle\langle\Psi^{+}_{\alpha}\rvert, etc. Equation (9.29) is the algebraic analogue of Section 9.4. As before, Section 9.4 is a direct consequence of its symmetries.

5 Application: Strong Subadditivity of the von Neumann Entropy

We now prove the strong subadditivity and weak monotonicity of the von Neumann entropy as direct consequences of Theorem 8.6 and the symmetry properties of the recoupling coefficients. We refer to Section 9.8 for a discussion of the general technique in the context of the search for new entropy inequalities. We start by noting that it follows from the first invariance asserted in Section 9.4 and the polynomial upper bound (9.10) that

Hence, if ρABC\rho_{ABC} is a tripartite quantum state then Theorem 9.6 implies that

for sequences of normalized Young diagrams that converge to the respective spectra of the reduced density matrices. Since for large kk, 1klog⁡2dim⁡[λ]→H(λˉ)=∑i−λˉilog⁡2λˉi\frac{1}{k}\log_{2}\dim[\lambda]\rightarrow H(\bar{\lambda})=\sum_{i}-\bar{\lambda}_{i}\log_{2}\bar{\lambda}_{i} [CM06], we conclude that the von Neumann entropy is strongly subadditive:

For [β][\beta] the trivial representation, this proof of strong subadditivity reduces to the proof of subadditivity given in [CM06]. Weak monotonicity,

follows similarly by swapping the columns (α,γ)↔(μ,ν)(\alpha,\gamma)\leftrightarrow(\mu,\nu) in accordance with Section 9.4.

6 Semiclassicality

In [WG59], Wigner studied the asymptotics of the recoupling coefficients of \SU(2)\SU(2) which can be defined in complete analogy to Section 9.2. Given three particles of spin jAj_{A}, jBj_{B}, jCj_{C} such that the total spin of the first two particles is jABj_{AB} and of all three particles jABCj_{ABC}, the absolute value squared of the \SU(2)\SU(2) recoupling coefficient can be interpreted as the probability of observing that particles two and three have total spin jBCj_{BC}. In the semiclassical limit of simultaneously large spins, Wigner showed that this probability oscillates around the inverse volume of the tetrahedron whose edges have length equal to the six spins—if such a tetrahedron exists (Figure 9.1). In particular, it then decays polynomially with jj. If no such tetrahedron exists then the 6j6j-symbol decays exponentially. This result is understood to mean that “classical” configurations are exponentially more likely than all others in the limit of large quantum numbers. A more precise formula has been given by Ponzano and Regge [PR68] and only fully proved in [Rob99]. We remark that the labeling of Wigner’s tetrahedron in Figure 9.1 is dual to the \SU(2)\SU(2) analogue of the diagram (9.17) [Rob99].

7 Sums of Matrices and Quantum Marginals

Do there exist Hermitian d×dd\times d-matrices AA, BB and CC with given prescribed eigenvalues for AA, BB, CC, A+BA+B, B+CB+C and A+B+CA+B+C?

This is a natural generalization of the problem of determining the relation between the eigenvalues of AA, BB and A+BA+B that goes back at least to Weyl (Section 2.4). In [Kly04], it was shown how the one-body quantum marginal problem degenerates to Weyl’s problem in an appropriate limit (cf. [Rus07b] for another connection in the context of the NN-representability problem). We will now show that Section 9.7 can similarly be considered as a special case of the quantum marginal problem with overlapping marginals as discussed in this chapter—both on the level of geometry and on the level of representation theory.

Let AA, BB, CC be Hermitian d×dd\times d-matrices. Without loss of generality, we may assume that A,B,C≥0A,B,C\geq 0 and that 1−\tr(A+B+C)≥∥A+B+C∥∞1-\tr(A+B+C)\geq\lVert A+B+C\rVert_{\infty} (else, we may add suitable multiples of the identity and rescale). Generalizing a construction from [Chr08], we define a tripartite quantum state ρABC\rho_{ABC} in terms of its purification

Let ρABC\rho_{ABC} be the quantum state with purification (9.31). Then the non-zero eigenvalues of ρABC\rho_{ABC} and all its reduced density matrices are given by

Observe that ∣ψABCD⟩\ket{\psi_{ABCD}} is built from a sum of (unnormalized) maximally entangled states (9.23) on ADAD, BDBD and CDCD, respectively. By using (9.24) and the orthogonality properties of the construction (9.31), we thus find that

If we only trace out the first two systems, then we instead get a block decomposition of the form

where ∣ϕ⟩CD=∑k=1dC∣k⟩C⊗∣k⟩D+1−\tr(A+B+C)∣00⟩CD\ket{\phi}_{CD}=\sum_{k=1}^{d}\sqrt{C}\ket{k}_{C}\otimes\ket{k}_{D}+\sqrt{1-\tr(A+B+C)}\ket{00}_{CD}. Using (9.27), we find that ⟨ϕCD∣ϕCD⟩=1−\tr(A+B)\braket{\phi_{CD}|\phi_{CD}}=1-\tr(A+B), so that the second claim follows as above. The last claim follows from

which is established similarly. All other marginal spectra can be computed in the same way. ∎

We have thus obtained an embedding of triples of matrices into the space of tripartite quantum states that preserves the eigenvalue information. We remark that Section 9.7 can be used to obtain entropy inequalities for sums of Hermitian matrices from entropy inequalities for multipartite quantum states.

The state ρABC\rho_{ABC} has rank at most d+1d+1 and it satisfies the polygonal inequality (3.2) with equality:

where rI,1r_{I,1} denotes the maximal eigenvalue of the reduced density matrix ρI\rho_{I}.

Note that (9.32) implies that the polygonal inequalities for AB:CAB:C, A:BCA:BC and AC:BAC:B are likewise satisfied with equality (i.e., rAB,1+rC,1=1+rABC,1r_{AB,1}+r_{C,1}=1+r_{ABC,1}, etc.). We now show the following converse statement.

The first inequality is obtained by omitting the terms with negative signs, and the second by using the variational principle for the maximal eigenvalue of ρABC\rho_{ABC}. It is thus immediate that we have equality if and only if ∣000⟩ABC\ket{000}_{ABC} is a maximal eigenvector of ρABC\rho_{ABC} and

A priori, the right-hand side can run over all indices (i,j,k)≠(0,0,0)(i,j,k)\neq(0,0,0) and l≠0l\neq 0 by orthogonality of the bases in the Schmidt decomposition. But (9.33) implies that in fact precisely two out of the three indices (i,j,k)(i,j,k) have to be zero, so that we obtain

Thus we may define d×dd\times d-matrices XAX_{A}, XBX_{B} and XCX_{C} such that

Finally, we use the polar decomposition to write XA=UA∣XA∣X_{A}=U_{A}\lvert X_{A}\rvert, etc., and set A:=∣XA∣\sqrt{A}:=\lvert X_{A}\rvert, etc. Then (9.31) is indeed a purification of the quantum state (UA†⊗UB†⊗UC†)ρABC(UA⊗UB⊗UC)(U^{\dagger}_{A}\otimes U^{\dagger}_{B}\otimes U^{\dagger}_{C})\rho_{ABC}(U_{A}\otimes U_{B}\otimes U_{C}), which is locally unitarily equivalent to ρABC\rho_{ABC}. ∎

The following theorem shows that Section 9.7 – in particular, the existence of Wigner’s tetrahedra – is in a precise mathematical sense a special case of the quantum marginal problem with overlapping marginals covered by Theorem 9.6. This generalizes the corresponding result for the one-body quantum marginal problem in [Kly04, §6.2], and in particular gives a geometric proof of the latter.

There exist Hermitian d×dd\times d-matrices AA, BB, and CC with \spec(A+B+C)=s⃗A+B+C\spec(A+B+C)=\vec{s{}}_{A+B+C}, \spec(A+B)=s⃗A+B\spec(A+B)=\vec{s{}}_{A+B}, \specA=s⃗A\spec A=\vec{s{}}_{A}, etc. as their partial sums.

(1)⇒(2)(1)\Rightarrow(2) is the content of Section 9.7. For (2)⇒(1)(2)\Rightarrow(1), Section 9.7 implies that there exist Hermitian d×dd\times d-matrices AA, BB, CC such that ρABC\rho_{ABC} is locally unitarily equivalent to the state ρABC′\rho^{\prime}_{ABC} with purification (9.31). Since the spectra of ρABC\rho_{ABC} and its reduced density matrices are left invariant by local unitaries, Section 9.7 implies that the partial sums of these matrices AA, BB and CC have the desired spectra. ∎

Similar statements can be proved for all marginal spectra (i.e., including s⃗A+C\vec{s{}}_{A+C}, since Section 9.7 holds for all reduced density matrices) as well as for an arbitrary number of summands. Thus the quantum marginal problem with overlaps is a precise generalization of the problem of characterizing the eigenvalues of partial sums of Hermitian matrices.

We now show an analogous statement to Theorem 9.16 on the level of representation theory—namely, that the recoupling coefficients of the unitary group can be obtained as special recoupling coefficients of the symmetric group.

To see this, let λ\lambda be a Young diagram. In [Nis00], the restriction of an irreducible \U(k)\U(k)-representation VλkV^{k}_{\lambda} to the subgroup of permutation matrices Sk⊆U(k)S_{k}\subseteq U(k) has been computed:

In the right-hand side of (9.34), \Ind\Ind denotes an induced representation and α\alpha is the unique Young diagram with number of boxes equal to the number of rows of μ\mu such that

where Sμ:=Sμ1×Sμ2×⋯⊆S∣μ∣S_{\mu}:=S_{\mu_{1}}\times S_{\mu_{2}}\times\dots\subseteq S_{\lvert\mu\rvert} is the Young subgroup corresponding to μ\mu, NS∣μ∣(Sμ)N_{S_{\lvert\mu\rvert}}(S_{\mu}) its normalizer in S∣μ∣S_{\lvert\mu\rvert}, and Sα⊆S∣α∣S_{\alpha}\subseteq S_{\lvert\alpha\rvert} the Young subgroup of α\alpha. Note that SαS_{\alpha} indeed acts on the subspace [λ]Sμ[\lambda]^{S_{\mu}}.

If k−∣λ∣≥λ1k-\lvert\lambda\rvert\geq\lambda_{1}, then λ′:=(k−∣λ∣,λ)\lambda^{\prime}:=(k-\lvert\lambda\rvert,\lambda) is again a Young diagram, and

Here and in the following, we write “…” for a sum of irreducible SkS_{k}-representations whose Young diagrams have longer first rows than all the preceding ones.

Otherwise, if k−∣λ∣<λ1k-\lvert\lambda\rvert<\lambda_{1} then the first row of any Young diagram that appears in the restriction of VλkV^{k}_{\lambda} is longer than k−∣λ∣k-\lvert\lambda\rvert.

Since induction is transitive, we can rewrite (9.34) as

The Pieri formula asserts that the SkS_{k}-representation induced from a tensor product of an irreducible S∣α∣S_{\lvert\alpha\rvert}-representation [ν][\nu] with the trivial Sk−∣α∣S_{k-\lvert\alpha\rvert}-representation 1\mathbf{1} is given by the sum over all irreducible SkS_{k}-representations with a Young diagram that can be obtained by adding k−∣α∣k-\lvert\alpha\rvert boxes to ν\nu, with no two in the same column (see, e.g., [Ful97, §2.2, (4)]). The first row of any such Young diagram is of length at least k−∣α∣k-\lvert\alpha\rvert. As ∣α∣\lvert\alpha\rvert is equal to the number of rows of μ\mu, we obtain the lower bound

on the length of the first row of any irreducible SkS_{k}-representation that occurs in the restriction of VλkV^{k}_{\lambda}.

Equality in (9.37) can occur only if each row of μ\mu contains a single box, i.e., for μ=(1,…,1,0,…,0)\mu=(1,\ldots,1,0,\ldots,0), such that ∣α∣=∣μ∣=∣λ∣\lvert\alpha\rvert=\lvert\mu\rvert=\lvert\lambda\rvert. Then SμS_{\mu} is the trivial group, Sα=S∣α∣=S∣λ∣S_{\alpha}=S_{\lvert\alpha\rvert}=S_{\lvert\lambda\rvert}, and the corresponding summand in (9.36) is equal to

By the Pieri formula, (9.38) contains an irreducible SkS_{k}-representation with first row of length k−∣λ∣k-\lvert\lambda\rvert if and only if λ1≤k−∣λ∣\lambda_{1}\leq k-\lvert\lambda\rvert (since we only add boxes to λ\lambda). Moreover, if this condition is satisfied then there is only a single option, namely to place one box in each of the k−∣λ∣k-\lvert\lambda\rvert leftmost columns, resulting in the Young diagram λ′=(k−∣λ∣,λ)\lambda^{\prime}=(k-\lvert\lambda\rvert,\lambda). ∎

We now consider the decomposition of a tensor product of irreducible \U(k)\U(k)-representations,

where we assume that k−∣α∣≥α1k-\lvert\alpha\rvert\geq\alpha_{1} and k−∣β∣≥β1k-\lvert\beta\rvert\geq\beta_{1}. The multiplicities cλα,βc^{\alpha,\beta}_{\lambda} are known as the Littlewood–Richardson coefficients, and they are independent of the choice of kk (if kk is at least as large as the number of rows in the Young diagrams involved) [JK81]. Moreover, cλα,βc^{\alpha,\beta}_{\lambda} is non-zero only if ∣α∣+∣β∣=∣λ∣\lvert\alpha\rvert+\lvert\beta\rvert=\lvert\lambda\rvert. It follows from the points above that

On the other hand, by applying (9.35) to the individual tensor factors we find that

where gα′,β′,λ′g_{\alpha^{\prime},\beta^{\prime},\lambda^{\prime}} are the Kronecker coefficients. In the last inequality, we have used that gα′,β′,λ′>0g_{\alpha^{\prime},\beta^{\prime},\lambda^{\prime}}>0 only if ∣λ∣≤∣α∣+∣β∣\lvert\lambda\rvert\leq\lvert\alpha\rvert+\lvert\beta\rvert [JK81, Theorem 2.9.22]. By comparing coefficients we find that cλα,β=gα′,β′,λ′c^{\alpha,\beta}_{\lambda}=g_{\alpha^{\prime},\beta^{\prime},\lambda^{\prime}} for all triples of Young diagrams with ∣α∣+∣β∣=∣γ∣\lvert\alpha\rvert+\lvert\beta\rvert=\lvert\gamma\rvert and kk large enough. We thus recover a well-known result due to Littlewood and Murnaghan that states that the Littlewood–Richardson coefficients are a special case of the Kronecker coefficients [Lit58, Mur55]. What is more, the argument shows that the Clebsch–Gordan embeddings Φλ′α′β′\Phi^{\alpha^{\prime}\beta^{\prime}}_{\lambda^{\prime}} for SkS_{k} can be obtained by restricting the ones of \U(k)\U(k). In view of (9.5), this implies directly that the recoupling coefficients are the same, since they are built solely from the action on the multiplicity spaces. Again, the recoupling coefficients for \U(k)\U(k) do not depend on the choice of kk (if kk is at least as large as the number of rows in the Young diagrams involved).

8 Discussion

From the perspective of representation theory, the one-body quantum marginal problem can be characterized in terms of the decomposition of tensor products of irreducible representations of the symmetric group. Theorem 9.6 generalizes this description: It shows that the overlap between two such decompositions – as captured by the recoupling coefficients – similarly characterizes the quantum marginal problem with two overlapping marginals. It would be of great interest to find a geometric explanation of this result in the framework of Section 2.2, which might also lead to a more refined understanding of the asymptotics (along the lines of [Rob99] for Wigner’s 6j6j-symbols). Mathematically, this is related to the “intersection” of moment maps or to simultaneous Hamiltonian reduction for non-commuting group actions.

In Section 9.5, we have given a novel proof of the strong subadditivity and weak monotonicity of the von Neumann entropy. It is markedly different from previous proofs in the literature, which are built on operator convexity [LR73, NP05, Rus07a, Eff09] or asymptotic equipartition [Ren05, Gro13] (cf. the review [Rus05]). In our approach, we interpret an entropy inequality as the asymptotic shadow of a dimensional relation such as (9.30). We establish the latter by exploiting the symmetries of a corresponding representation-theoretic object – the recoupling coefficients – together with a lower bound from spectrum estimation. The generality of this approach suggests an intriguing route towards establishing new entropy inequalities—namely, by constructing novel representation-theoretic objects (e.g., by composing Clebsch–Gordan maps) and uncovering their symmetries (as can conveniently be done using the graphical calculus).

Finally, we speculate that the surprising connection established in Section 9.7 between tetrahedra and quantum states as well as between the corresponding recoupling coefficients may help to understand and connect the study of spin foams and spin networks in the context of quantum gravity [Oog92, RR97, FL03, BS03, Gur08, AHH+12] and condensed matter physics [LW05a] to quantum information theory.

References

List of Symbols

inner product of two vectors in Hilbert space

trace norm, or Schatten-1 norm of operator XX, \hyperpage26

Hilbert–Schmidt norm, or Schatten-2 norm of operator XX, \hyperpage144

operator norm, or Schatten-∞\infty norm of operator XX, \hyperpage144

dual cone of linear entropy inequalities, \hyperpage122

entanglement polytope of a class X\mathcal{X}, \hyperpage56

Hilbert–Schmidt probability measure, \hyperpage84

linear entropy of entanglement, \hyperpage70

fidelity between ρ\rho and σ\sigma, \hyperpage76

first-order density matrix of fermionic state, \hyperpage7

Shannon entropy of random variable XX, \hyperpage121

differential Rényi-α\alpha entropy of random variable XX, \hyperpage129

Hilbert space of kk-th particle, \hyperpage5

maximally entangled state on H⊗H\mathcal{H}\otimes\cal H, \hyperpage153

vector of eigenvalues λk,1≥λk,2≥…\lambda_{k,1}\geq\lambda_{k,2}\geq\dots of kk-th one-body reduced density matrix, \hyperpage6

joint distribution of local diagonal entries of random pure state, \hyperpage81

joint distribution of local eigenvalues of random pure state, \hyperpage81

vector of eigenvalues rI,1≥rI,2≥…r_{I,1}\geq r_{I,2}\geq\dots of reduced density matrix ρI\rho_{I}, \hyperpage146

reduced density matrix of subsystems II, \hyperpage128

one-body reduced density matrix of kk-th particle, \hyperpage5

stabilizer state corresponding to isotropic submodule MM, \hyperpage132

von Neumann entropy of quantum state ρ\rho, \hyperpage123

Rényi-2 entropy of quantum state ρ\rho, \hyperpage129

spectrum of Hermitian operator XX, \hyperpage5

symmetric subspace of H1⊗n\mathcal{H}_{1}^{\otimes n}, \hyperpage7

continuous-variable Wigner function of quantum state ρ\rho, \hyperpage137

discrete Wigner function of quantum state ρ\rho, \hyperpage134

antisymmetric subspace of H1⊗n\mathcal{H}_{1}^{\otimes n}, \hyperpage7

Weyl operator for integers PP, QQ, \hyperpage131

subset of random variables with indices in II, \hyperpage121

entanglement class of a pure state ρ\rho, \hyperpage55

dual pairing of g∗\mathfrak{g}^{*} and g\mathfrak{g}, \hyperpage17

adjoint representation of GG on g\mathfrak{g} and its differential, \hyperpage9

coadjoint representation of KK on ik∗i\mathfrak{k}^{*}, \hyperpage10

root of \GL(d)\GL(d) and \SL(d)\SL(d), \hyperpage11

Littlewood–Richardson coefficients, \hyperpage161

formal character of representation VV, \hyperpage105

finite-difference operator in direction α\alpha, \hyperpage108

partial derivative in direction −α-\alpha, \hyperpage90

connected reductive algebraic group and its Lie algebra, \hyperpage8

root spaces of g\mathfrak{g}, \hyperpage9

Pontryagin dual of finite Abelian group GG, \hyperpage130

general linear group and its Lie algebra, \hyperpage11

general linear group of Hilbert space H\mathcal{H}, and its Lie algebra, \hyperpage15

sum of π(H)\pi(H)-eigenspaces with eigenvalue less than cc, …, \hyperpage37

multiplicity spaces in the Clebsch–Gordan decomposition for the symmetric group, \hyperpage143

space of GG-linear maps between two representations VV and WW, \hyperpage28

complex-linear functionals on h\mathfrak{h}, \hyperpage8

positive Weyl chamber and its (relative) interior, \hyperpage10

compact connected Lie group and its Lie algebra, \hyperpage8

root spaces of k\mathfrak{k}, \hyperpage9

length of a Weyl group element, \hyperpage10

number of boxes of a Young diagram, \hyperpage14

Young diagram with kk boxes and at most dd rows, \hyperpage14

irreducible representations of the symmetric group, \hyperpage27

elements of it+∗i\mathfrak{t}^{*}_{+}, \hyperpage10

normalization of Young diagram λ\lambda, \hyperpage146

highest weight of the dual representation VG,λ∗V_{G,\lambda}^{*}, \hyperpage11

multiplicity of VK,μV_{K,\mu} in VK,λV_{K,\lambda}, \hyperpage102

highest weight multiplicity function, \hyperpage105

weight multiplicity function, \hyperpage105

maximal unipotent subgroups of GG and its Lie algebras, \hyperpage10

sum of negative root spaces with (α,H)<0(\alpha,H)<0, …, \hyperpage40

coadjoint KK-orbit through λ\lambda, \hyperpage10

element of it∗i\mathfrak{t}^{*}, \hyperpage8

homomorphism of Lie groups, corresponding homomorphism of Lie algebras, dual map between weight lattices, \hyperpage109

Clebsch–Gordan embeddings for the symmetric group, \hyperpage143

representation of GG and corresponding representation of g\mathfrak{g}, \hyperpage8

SkS_{k}-invariant vector in [λ]⊗[λ][\lambda]\otimes[\lambda], \hyperpage153

recoupling coefficients of the symmetric group, \hyperpage144

special linear group and its Lie algebra, \hyperpage15

special linear group of Hilbert space H\mathcal{H}, and its Lie algebra, \hyperpage15

special unitary group and its Lie algebra, \hyperpage15

special unitary group of Hilbert space H\mathcal{H}, and its Lie algebra, \hyperpage15

maximal torus of KK and its Lie algebra, \hyperpage8

complexification of TT and its Lie algebra, \hyperpage8

unitary group and its Lie algebra, \hyperpage11

unitary group of Hilbert space H\mathcal{H}, and its Lie algebra, \hyperpage15

irreducible representations of \GL(d)\GL(d), \U(d)\U(d), \SL(d)\SL(d), \SU(d)\SU(d), \hyperpage14

subspace of invariant vectors in representation VV, \hyperpage11

irreducible GG-representation with highest weight λ\lambda, \hyperpage11

weight spaces of a representation VV, \hyperpage9

Pauli matrices corresponding to root α\alpha, \hyperpage9

non-increasingly ordered chamber in Δd\Delta_{d}, \hyperpage84

moment polytope for the KK-action on projective space, \hyperpage34

moment polytope for the TT-action on projective space, \hyperpage36

Lebesgue measure on ΔT\Delta_{T}, \hyperpage87

closure of GG-orbit through ρ\rho, \hyperpage19

Riemannian metric of projective space, \hyperpage16

complex structure of projective space, \hyperpage16

KK-stabilizer of ρ\rho, and its Lie algebra, \hyperpage17

moment map for the KK-action, \hyperpage17

moment map for the TT-action, \hyperpage35

Fubini–Study symplectic form of projective space, \hyperpage16

Liouville volume of coadjoint orbit, \hyperpage83

non-Abelian Duistermaat–Heckman measure, \hyperpage83

Abelian Duistermaat–Heckman measure, \hyperpage83

Abelian Duistermaat–Heckman measure for coadjoint orbit, \hyperpage90

Hessian of moment map component at critical point, \hyperpage37

regular functions (of degree kk) on affine cone C\mathcal{C}, \hyperpage19

residue of formal Laurent series, \hyperpage88

volume of parametrized polytope, \hyperpage87

complex projective space of pure states on H\mathcal{H}, \hyperpage16

projective subvariety corresponding to an affine cone C\mathcal{C}, \hyperpage19

GG-orbit through projector onto highest weight vector (projective subvariety isomorphic to the coadjoint orbit OK,λ\mathcal{O}_{K,\lambda}), \hyperpage20

tangent vector at ρ\rho generated by infinitesimal action of XX, \hyperpage16

List of Publications

A Heisenberg Limit for Quantum Region Estimation, with J. M. Renes. Proc. IEEE Inter. Symp. Inform. Theory (ISIT’14), 1126–1130 (2014).

Lower Bounds for Quantum Parameter Estimation, with J. M. Renes. Preprint arXiv:1310.2155; accepted for publication in IEEE Trans. Inf. Theory.

Stabilizer information inequalities from phase space distributions, with D. Gross. J. Math. Phys. 54 (8), 082201 (2013).

Recoupling Coefficients and Quantum Entropies, with M. Christandl and M. B. Şahinoğlu. Preprint arXiv:1210.0463; presented at QIP’13.

Entanglement Polytopes: Multiparticle Entanglement from Single-Particle Information, with B. Doran, D. Gross, and M. Christandl. Science 340 (6137), 1205–1208 (2013); presented at QIP’13.

When is a pure state of three qubits determined by its single-particle reduced density matrices?, with A. Sawicki and M. Kuś. J. Phys. A 46, 055304 (2013).

Computing Lie Group Multiplicities, with M. Christandl and B. Doran. Proc. IEEE Ann. Symp. Found. Comput. Sci. (FOCS’12), 639–648 (2012).

Eigenvalue Distributions of Reduced Density Matrices, with M. Christandl, B. Doran, and S. Kousidis. Commun. Math. Phys. 332, 1–52 (2014).

Equivariant geometric KK-homology for compact Lie group actions, with P. Baum, H. Oyono-Oyono, and T. Schick. Abh. Math. Sem. Univ. Hamburg 80, 149–173 (2010).