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 -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 -complete and therefore -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 in the restriction of an irreducible representation of . 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 vs. 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 of the Hilbert spaces describing the individual particles. Given a density matrix on , the one-body reduced density matrices are defined by taking the partial trace of over all subsystems other than . In other words,
In physical terms, (2.1) asserts that reproduces faithfully the expectation values of all local observables . Hence describes the effective state of the -th particle. The one-body quantum marginal problem then is the following compatibility problem:
Let . Given density matrices on for all , does there exist a pure state on such that are its one-body reduced density matrices?
We will call such density matrices 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, , the one-body quantum marginal problem is rather straightforward to solve. For this, recall that any vector on a tensor product can be expanded in the form
for orthonormal sets of vectors in and in and positive numbers . 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 is a pure state then it follows that and have the same non-zero eigenvalues, including multiplicities (and indeed the same spectrum if and are of the same dimension). Conversely, for any two such density matrices and , 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 and are compatible with a global pure state if and only if and have the same non-zero eigenvalues (including multiplicities), i.e., if and only if .
In particular, any density matrix 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 .
An important consequence of Chapter 2 is that spectra , …, , are compatible with a pure state if and only if , …, are compatible with a global state of spectrum . 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 : A given collection of spectra is compatible if and only if there exists a spectrum such that both as well as are compatible, and this process can be iterated. This is immediate from the preceding and Chapter 2, which also shows that the rank of can be bounded by the minimum of and .
Identical Particles
In the case of identical particles, the system is described by the -th symmetric or antisymmetric tensor power of the single-particle Hilbert space, or depending on whether the particles are bosons or fermions. By considering as a subspace of , we can define the one-body reduced density matrices as in the case of distinguishable particles. Of course, , since for bosons as well as for fermions the global state is permutation-invariant. In summary,
where in the last expression and denote the creation and annihilation operators with respect to an arbitrary basis of the single-particle Hilbert space.
For fermions, we thus arrive at the following variant of Chapter 2:
Given a density matrix on , does there exist a pure state on such that is its one-body reduced density matrix?
We will call such a density matrix -representable. In the context of second quantization, it is often more convenient to normalize the one-body marginal to trace . Following quantum chemistry conventions, we correspondingly set 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 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 , or, equivalently, on the natural occupation numbers of . 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 . Equivalently, the largest eigenvalue of an -representable one-body density matrix is at most . However, there are many more constraints on the natural occupation numbers of a pure state of 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 arises as the one-body reduced density matrix of a pure state on the symmetric subspace, e.g., [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 acts on itself by conjugation, . By taking the derivative, we obtain the adjoint representation of on . Its differential is the representation of the Lie algebra on itself by the Lie bracket, . By decomposing the adjoint representation into weight spaces and observing that , we obtain
where 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 we have that ; in particular, . All root spaces are one-dimensional, and for each root , is also a root. We can find basis vectors and elements , called co-roots, such that
The “Pauli matrices” and are a basis of ; they satisfy the commutation relations
Now choose a decomposition of the set of roots into positive and negative roots. That is, and each subset is strictly contained in a half-space of the (real) span of the roots (which is equal to if is semisimple). Then we have a decomposition
where the are nilpotent Lie algebras; the corresponding Lie groups are called maximal unipotent subgroups.
Another consequence of the choice of positive roots is the following. Consider the dual of the adjoint representation of on , given by for all , and in . It is not hard to see that its restriction to preserves the real subspace
and we shall call it the coadjoint representation of on (our choice of factor is somewhat idiosyncratic but will be rather convenient in the sequel). We may consider and by extending each functional by zero on the root spaces . Then the positive Weyl chamber
is a cross-section for the coadjoint action of . In other words, each coadjoint orbit intersects the positive Weyl chamber in a single point . We write for the coadjoint orbit through . The positive Weyl chamber is a convex cone (pointed if is semisimple). Its (relative) interior is
For any , the -stabilizer is the maximal torus , so that .
The last piece of structure is the Weyl group , where denotes the normalizer of the maximal torus . It is a finite group that acts on . For any representation , 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 -orbit in has a unique point of intersection with the positive Weyl chamber , and there exists a Weyl group element, known as the longest Weyl group element , that exchanges the positive and negative roots and hence sends the “negative Weyl chamber” to . More generally, one can define the length of a Weyl group element as the minimal number of certain standard generators required to write , but we will not need this level of generality.
Representation Theory
Let be a finite-dimensional representation of , with infinitesimal representation and weight space decomposition . A weight vector is called a highest weight vector if , or, equivalently, if . The corresponding highest weight is necessarily dominant, i.e., an element of .
The fundamental theorem of the representation theory of compact connected Lie groups asserts that the irreducible representations of can be labeled by their highest weight: Any irreducible representation contains a highest weight vector , unique up to multiplication by a scalar. Conversely, for every there exists a unique irreducible representation with as the highest weight. The dual representation of an irreducible representation is again irreducible, and its highest weight is , where is the longest Weyl group element as defined above. Like any finite-dimensional representation of , extends to a rational representation of the algebraic group , i.e., a representation whose matrix elements are given by rational functions on the algebraic group (that is, by morphisms of algebraic varieties, which is the appropriate notion in this context). All irreducible rational representations of can be obtained in this way. Therefore, the representation theory of and of are essentially equivalent.
An arbitrary -representation can always be equipped with a -invariant inner product (choose an arbitrary inner product and average). In this case, , and so consist of anti-Hermitian and of Hermitian operators. Moreover, can always be decomposed into irreducible representations and the irreducible representations that occur in are in one-to-one correspondence with the highest weight vectors in (up to rescaling). In particular, the subspace of invariant vectors is the sum of all trivial representations that occur in .
The General Linear and Unitary Groups
The general linear group of invertible -matrices is a connected reductive algebraic group, with Lie algebra the space of complex -matrices. The Lie bracket is the usual commutator, , and the exponential map is the usual matrix exponential. The unitary group , whose elements are unitary -matrices, is a maximal compact subgroup, with Lie algebra the space of anti-Hermitian matrices. Thus is the set of Hermitian matrices, which we may identify with by using the Hilbert–Schmidt inner product.
The roots of are the functionals , and the corresponding root spaces are spanned by the elementary matrices that have a single non-zero entry in the -th row and -th column. Indeed, we have that for any diagonal matrix . A choice of positive roots is given by those roots with . Thus the nilpotent Lie algebras consist of the strictly upper and lower triangular matrices, respectively. The corresponding unipotent subgroups are upper and lower triangular with ones on the diagonal.
The adjoint action is by conjugation. If we identify then the coadjoint orbits of consist of Hermitian matrices with fixed spectrum. Then the positive Weyl chamber can be identified with the set of Hermitian diagonal matrices whose entries are weakly decreasing, or with their spectra . The assertion that is a cross-section for the coadjoint action of on corresponds to the plain fact that any Hermitian matrix can be diagonalized by a unitary. Its interior then corresponds to the set of non-degenerate spectra . The claim that the -stabilizer of any is 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 ; it acts on by permuting diagonal entries. The length of a permutation is the number of transpositions required to write the permutation , and the longest Weyl group element is the “order-reversing permutation” which sends any to .
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 . We write for a Young diagram with boxes and at most 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 . In other words, the traceless part of each one-body reduced density matrix vanishes. We conclude that each one-body reduced density matrix is proportional to the identity matrix. In the language of quantum information theory, the quantum state 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 ,
is known as a complex projective space. It is a smooth submanifold of the real vector space of Hermitian operators on . The unitary group acts transitively by conjugation, , so that the tangent space at a point is spanned by the tangent vectors for all . Since the 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, , and its imaginary part is the Fubini–Study symplectic form
For tangent vectors generated by elements of the Lie algebra , this becomes
The action of can be extended to its complexification, the general linear group by the formula
The tangent vector generated by a Hermitian matrix is then given by , with the anti-commutator. It is easily verified that . 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 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 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 . Dually, we find that the range of the differential of the moment map at any point is given by the annihilator of , the Lie algebra of the -stabilizer of [GS82a]:
Thus its image consists of a union of coadjoint orbits, and so is characterized by its intersection with the positive Weyl chamber . 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 -orbit through is not closed. Then the Hilbert–Mumford criterion asserts that we can reach a point in the “boundary” by using a single one-parameter subgroup (e.g., [Kra85, p. 171]). More formally, it states that there exists such that
Let be the decomposition of into eigenvectors of the Hermitian operator , with an eigenvector with eigenvalue . Clearly, for all , since otherwise the limit (2.15) cannot exist. But then
so that also for all . It follows that , i.e. . 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 -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 and . Let . Then
It follows by using the second assertion in (2.16) and 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 , is contained in the affine subspace for all . It will usually be more convenient to instead use the special linear and unitary groups, and , so that 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 and acting by . With and using (2.3) we obtain that
where is the first-order density matrix from quantum chemistry with trace that we had defined below (2.3). Again we find that the one-body -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 is a -representation describing a pure-state problem then the corresponding mixed-state problem can be studied by taking and ; e.g., the mixed-state problem for fermions amounts to the moment polytope for the -representation . 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 . By -equivariance of the moment map, meets transversally, so that is a smooth manifold with tangent space [GS84b, Theorem 26.7]. Thus we may choose any curve in that starts with and . ∎
Let be a pure state such that is a point on a facet of the moment polytope corresponding to the inequality . Then
Since is an inequality for the moment polytope, it follows that —for otherwise we could walk through the facet! On the other hand, (2.14) shows that
Therefore, is necessarily an element of the Lie algebra of the -stabilizer of , i.e., . This implies that by (2.13), but also that is an eigenvector of , with corresponding eigenvalue . ∎
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 , which has a useful operational meaning (but this choice is completely arbitrary since the proof is based on a purely topological argument):
and as .
is well-defined. Clearly, is monotonic in , and by Section 2.3.
For concrete applications, it might be interesting to obtain explicit bounds of the form . 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 , and (but of course , and 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 vs. 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., [JK81, §2.1]. Therefore,
for the space of -equivariant linear maps, or -linear maps between two representations and . For irreducible and , Schur’s lemma asserts that
It follows that can also be defined as the multiplicity of in the tensor product of two irreducible representations of the symmetric group:
In particular, for the trivial representation of we obtain that . In view of Schur–Weyl duality, this implies that
This equation corresponds to the one-body quantum marginal problem for 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’’ 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 -representability problem—given a two-body density matrix, is it compatible with a state of 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 is compatible with a (not necessarily pure) state of fermions if and only if the natural occupation numbers do not exceed —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 and ). It is interesting to observe that the equality strengthens the Pauli principle .
(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 and [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 , where 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 is necessarily contained in a hyperplane spanned by weights of the representation . 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 of the moment polytope. To state it, let denote the direct sum of negative root spaces with and the sum of eigenspaces of with eigenvalue smaller than . Then we show that there necessarily exists an eigenvector of with eigenvalue such that the map
is an isomorphism. Conversely, we prove that any inequality 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 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 for some positive root . 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 meets the relative interior of the positive Weyl chamber.
Any facet of 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 for some positive root . If it was then the moment polytope would be strictly contained in the hyperplane , and therefore not of maximal dimension, in contradiction with our assumption. We conclude that the facet is of the form , and therefore trivial. ∎
We now consider the moment map for the action of the maximal torus ,
For the quantum marginal problem, this amounts to considering diagonal entries rather than eigenvalues. Let be the decomposition of into weight spaces, and a pure state with decomposed accordingly. Then has the following concrete description:
The set of critical values of 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 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 is non-empty. Each point in this intersection is a critical value for by selection rule (Section 2.3), hence of , 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 be the preimage of a point on the facet of the moment polytope. We have seen that the selection rule Section 2.3 shows that is a critical point of the component , 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 , which is a quadratic form on the tangent space at . Since is a critical point, we can compute it by
for all anti-Hermitian operators . It follows that [GS84b, (32.8)]
for all (which is indeed symmetric in and ). We now decompose
where is the sum of the eigenspaces of the Hermitian operator with eigenvalue less than , etc. Then we have the following interpretation of the index of the Hessian (the dimension of a maximal subspace on which the quadratic form is negative definite):
The index of the Hessian at is equal to the real dimension of .
Since itself is in by the selection rule, the claim follows. ∎
Since and , the Hessian is necessarily positive semidefinite on the subspace of those tangent vectors that get mapped to . Indeed, let and consider the curve from Section 2.3. Then,
which shows that, indeed, . The subspace of all such can be computed in a different way. For this, let 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 is positive semidefinite on the subspace
The first claim is a reformulation of the fact that the -stabilizer of any is , while . The second claim follows from the first, since and by equivariance of the moment map. ∎
The tangent space at decomposes as a direct sum
and the Hessian is block-diagonal with respect to this decomposition.
For the first claim we only need to show that , which is standard (see, e.g., [GS82a, Lemma 6.7]): Let . Suppose that . That is,
For the second claim, observe that (3.6) immediately implies that
for all and , since and hence . ∎
The index of the Hessian at is equal to twice the number of positive roots such that .
Since the tangent map is injective (Section 3.3), we may instead consider the form
on . For this, observe that is block-diagonal with respect to , since for all and , , while . And for each root space , we have that
where we have used the “Pauli matrices” and their commutation relations (2.6). Likewise, , while . Since , we conclude that the index of is equal to twice the number of positive roots with . ∎
Ressayre Elements
So far we have used the Lie algebra 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 of the negative unipotent subgroup, which plays a role analogous to for states that are mapped into the positive Weyl chamber (compare the following with Section 3.3).
The tangent map is injective.
Let be an arbitrary element in . Since , we find that with (the Cartan involution of ). Therefore,
so that by using we find that
In contrast to Section 3.3, which continues to hold true if is mapped to the relative interior of a different Weyl chamber (since 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 -representation with highest weight and highest weight vector . Then by Section 2.2, and the “lowering operators” in act indeed injectively (all live in different weight spaces and are non-zero, since ). On the other hand, the “raising operators” in the positive nilpotent Lie algebra annihilate the highest weight vector (by definition).
We now decompose the Lie algebra similarly to (3.7),
where is the sum of the complex root spaces with negative -weight , etc. By combining Lemmas 3.3 and 3.3 and using , we observe that
Note that , since for any and we have that
Thus we obtain the following important result:
The fact that is just a reformulation of the selection rule. By the preceding discussion, the tangent map is well-defined as a map from to ; 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 such that the tangent map
is surjective. Then is a valid inequality for the moment polytope.
Its differential at is the linear map
The assumption implies that this map is surjective. It follows that contains a small Euclidean ball around . In particular, any polynomial that is zero on is zero everywhere on .
We now prove the inequality. By the description of the moment polytope of Theorem 2.11, it suffices to show that for all highest weights such that . Recall that the highest weight of is , where is the longest Weyl group element that flips the positive and negative roots. Consider a lowest weight vector, i.e., a homogeneous polynomial that is a weight vector of weight and stabilized by . Then and the restriction of to is non-zero by our discussion above. But this restriction is an element of , the space of homogeneous polynomials of degree on . Thus all -weights in are less or equal to . It follows that , hence , as we set out to prove. ∎
We remark that Section 3.3 holds unconditionally without any assumption on the dimension of the moment polytope . We summarize our findings in the following definition and theorem:
An inequality is said to be of Ressayre type if
is an affine hyperplane spanned by a subset of weights.
There exists 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 -representation (under the assumption that 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 , the second condition can be easily checked: Indeed, we only need to verify that 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 qubits is indeed given by the polygonal inequalities (3.2), which we recall are given by
By using that for each qubit, we find that (3.12) is equivalent to the following inequality for the moment polytope ,
which we will now prove by using the criterion of Section 3.3.
On the other hand, there is precisely one negative root with , namely . Therefore,
where the generator acts as the “lowering operator” on the -th tensor factor of . But then , so that the map
is indeed an isomorphism for . Thus Section 3.3 shows that the polygonal inequality (3.12) is indeed valid. We remark that the weights corresponding to (3.13) span the hyperplane 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 as well as for 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 . 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 acts by on the corresponding tensor factor, we readily find that it is given by
and thus is indeed non-zero. For example, 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 in [Fra02, Proposition 5.1].
The significance of this facet is that it is neither trivial nor does it contain the vertex of the moment polytope that corresponds to product states – unlike in the case of 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 and with their tensor product action on the Hilbert space . 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 . Now suppose that we know in addition that the global state is a pure state in the sector for total spin :
Then the problem of determining the relation between the orbital and spin occupation numbers amounts to computing the moment polytope for the -representation . 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 , as they verified for . Their first equation is
where denote the natural occupation numbers of the first-order orbital density matrix , normalized to trace , and the eigenvalues of the spin density matrix , normalized to trace .
We will now prove (3.19) for arbitrary . For this, we will use the following description of the irreducible -representation (see, e.g., [Ful97]): Let 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 . Then can be identified with the quotient of by the relations
It is not hard to see that a basis of 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 , (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 , and the generators of 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 by . For example,
where we have used the first relation in (3.20).
where we have used that . Furthermore,
But then (3.21) shows that the tangent map 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 . In the same way the other four inequalities asserted in [KA08, §6.1] can be proved for arbitrary ; 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 is said to be entangled if it cannot be written as a tensor product [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 , which exhibits a particularly strong form of quantum correlations [GHZ89]; the second contains the W state [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 vs. 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 or, equivalently, their eigenvalues 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 of the states in the closure of a given entanglement class . 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 of the class. Entanglement polytopes immediately lead to a local criterion for witnessing multipartite entanglement: If the collection of eigenvalues of the one-body reduced density matrices of a pure quantum state does not lie in an entanglement polytope, then the given state cannot belong to the closure of the corresponding entanglement class (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 can be approximated arbitrarily well by states from then . This reflects geometrically the fact that states in the second class are more powerful for quantum information processing.
To describe mathematically and establish these claims, we work in the framework of Chapter 2. Using the characterization of SLOCC operations as invertible local operators [DVC00], we find that the closure of an entanglement class is a projective subvariety of the space of pure states. Thus can be identified with its moment polytope, and the above-mentioned properties follow from the general theory. We explain how 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 has two eigenvalues, which are non-negative and sum to one; hence its spectrum is completely characterized by the maximal eigenvalue , which can take values in the interval . 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 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, , then by (4.1) the state cannot be contained in the closure of the 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 .
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 -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 [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 corresponds to the Euclidean length of the vector of local eigenvalues, shorter vectors imply more entanglement. In particular, quantum states of maximal entropy of entanglement in a class map to the point of minimal distance to the origin in the entanglement polytope . 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 of a multi-particle system with Hilbert space is called entangled if it cannot be written as a tensor product [NC04]
It is easy to see that is unentangled, or separable, if and only if each its one-body reduced density matrices 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 , one fruitful approach has been to compare the capability of for quantum information processing tasks with that of other quantum states [BPR+00]. Specifically, suppose that is a state that can be obtained from by some suitable class of operations. Then can be used as a replacement for 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 to be at least as entangled as . If, conversely, can also be obtained from 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 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 . 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 and are interconvertible using SLOCC if and only if there exist invertible operators acting on such that . Here, the non-trivial part is to show that invertible operators 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 be a tensor-product Hilbert space. The (SLOCC) entanglement class of a pure state is defined as
In this way, the group 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 implies . 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 grows only linearly with the particle number 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 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 of local eigenvalues of a state is not contained in a given entanglement polytope then by definition cannot be contained in the closure of the class . 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 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 , this description can be slightly simplified. For this, we consider the following definition from classical invariant theory [KP96].
A covariant of degree and weight is a -equivariant map
whose components are homogeneous polynomials of degree and where .
The covariants of degree are in bijection with the highest weight vectors in , the space of homogeneous polynomials of degree on . Indeed, if is a covariant of degree and weight then its component
is a highest weight vector in of highest weight , where is a fixed “lowest weight vector” of weight . What is more,
since the -orbit through spans the entire irreducible representation , while any polynomial that vanishes on must also vanish on the closure. The following lemma is already implicit in [Bri87]:
For an entanglement class , the following are equivalent:
There exists an irreducible representation .
There exists a covariant of degree and weight such that .
: Let denote a highest weight vector of the irreducible representation . Then we may consider as a polynomial in that does not vanish on , and (4.4) implies that the corresponding covariant is non-zero at .
: Conversely, any covariant with corresponds to a highest weight vector of highest weight in . By virtue of (4.4), does not fully vanish on . Therefore, determines a highest weight vector in and there exists a corresponding irreducible representation . ∎
To show that moment polytopes are not only convex but indeed polytopes, we had used the crucial fact that the algebra of -invariant polynomials – 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 such that all other highest weight vectors can be obtained as linear combinations of monomials in the . Let us call the corresponding covariants a generating set of covariants.
The entanglement polytope of an entanglement class is given by
where denotes a generating set of covariants with degrees and weights .
Recall from Section 4.3 that can be identified with the moment polytope of the -action on . By Theorem 2.11 and Section 4.3, the rational points of the entanglement polytope are thus given by the normalized weights corresponding to covariants that do not vanish at . In particular, the inclusion is immediate.
For , we closely follow the proof of Section 2.2. Let with corresponding covariant of degree and weight . We denote by the highest weight vector (4.3) corresponding to the covariant . Since the are generators of the algebra of highest weight vectors, we may write as a linear combination of monomials in the . If the linear combination is chosen minimally then the degrees and weights of each monomial add up to the degree and weight of . Thus,
We know from (4.4) that does not completely vanish on . 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 are all non-zero at . But then (4.5) shows that is indeed a convex combination of normalized weights 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 . 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 .
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 qubits by the tuple 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 and weight determines the point in the polytope of maximal local eigenvalues.
the other is the class of product states, represented by . Using Chapter 2, it is not hard to see that the entanglement polytope of the former class is given the convex hull of and , while the entanglement polytope of the product states is a single point . 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 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 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 of can be realized as the space of homogeneous polynomials of degree in two formal variables. Therefore, any covariant for three qubits can be written as a homogeneous polynomial in formal variables , and , whose coefficients are themselves homogeneous polynomials in the components of the quantum state (the degree in the 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 ; it is a generating covariant of degree 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 be a quantum state with maximal local eigenvalues .
If the point 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 must be entangled of GHZ type.
More generally, if 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 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 , where
It is easy to verify by the method of covariants that the entanglement polytope of is full-dimensional. Thus it follows from the above classification that is of GHZ type. However, its collection of local eigenvalues 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 is either of GHZ or of W type. In Section 4.5 we will describe a distillation procedure that allows us to transform by SLOCC operations into another state whose local eigenvalues are arbitrarily close to the “origin” (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 , , etc. of the family. Deciding whether a normalized weight is included in the entanglement polytope of a state in the family then amounts to solving the explicit polynomial equation in the parameters , , 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 . It is a convex hull of 12 vertices, which can be easily described as follows: One vertex, corresponds to the class of product states; and its permutations correspond to the six possibilities of embedding an EPR pair into four qubits; and its permutations correspond to the four possibilities of embedding a GHZ state of three qubits; and the vertex 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 with respect to some proper bipartition of the four qubits. For example, the state 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 . 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 -state, , corresponds to polytope no. 5 in Table 4.3 and Figure 4.4. In analogy with the -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 can be converted into one whose linear entropy of entanglement is at least , which might be much higher than 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” . These reach the maximal value for the linear entropy of entanglement . 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 (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” . 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 . A pure state on is called producible using -partite entanglement if it is of the form
where and each subset is of size at most .
Otherwise, is called genuinely -partite entangled. In particular, the genuinely -partite entangled states are precisely those which are not biseparable.
We remark that some authors use the term “genuine -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 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 are given by
Mathematically, while this set of states does not form a single entanglement class, it is still a -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 and . For any , the local eigenvalues
can only originate from a genuinely -partite entangled state.
Conversely, if then there exists a corresponding pure state of qubits that is producible using -partite entanglement (i.e., that is not genuinely -partite entangled).
For the first claim, suppose that is a state with the displayed local eigenvalues. Without loss of generality, suppose that . Then (4.7) for reads
Since this holds for all partitions, we conclude that is genuinely -partite entangled.
For the second claim, consider the bipartition , . Then (4.8) is satisfied and all other inequalities in (4.7) are satisfied for since . For , which we need to consider only if , (4.7) is equivalent to . ∎
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 -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 attains at its maximal value over all states in the entanglement class [Kly07]. To see this, recall from (2.7) that for a locally maximally mixed state the norm square of the corresponding vector does not change to first order as we move along the -orbit in Hilbert space; that is is a critical point of on its -orbit. Kempf and Ness have shown that in fact any such vector has minimal length in its -orbit [KN79], so that for all . 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 as the origin of the coordinate systems in most of the figures in this chapter. Indeed, if we identify an entanglement polytope with the corresponding moment polytope then the origin corresponds to the point , which justifies the terminology (recall that we work with ). 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 be the entanglement class of a quantum state with non-degenerate local eigenvalues that is pinned to a facet (of the maximal entanglement polytope) that does not contain the origin. Then does not contain the origin.
for depending on the sign of . Therefore, . But then any -invariant homogeneous polynomial ought to vanish at . We conclude from (4.10) that does not contain the origin. ∎
Section 4.5can be strengthened by considering facets of the entanglement polytope 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 by following its gradient flow.
The gradient flow for 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 consists of tuples of traceless Hermitian matrices. We may equip with the -invariant inner product corresponding to the norm and use this to identify . This amounts to identifying 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 is given by [Kir84a, NM84]
where denotes as in Section 2.2 the tangent vector at generated by the infinitesimal action of , considered as an element of by using the -invariant inner product. This follows from the calculation
where we have used (2.13) and the relation (2.9) between the Riemannian metric and the Fubini–Study form . An important consequence of (4.13) is that the gradient flow
automatically stays in the -orbit of , i.e., in its entanglement class at all times . What is more, the gradient flow converges to a unique limit point [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 [GRS13]. We remark that such states are unique up to the -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 . 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 , which amounts to the SLOCC transformation
where 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 , 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 of the gradient flow can also be seen as a normal form of the state 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 denote the norm corresponding to a -invariant inner product on . We start with a simple observation:
Let . Then:
The right-hand side maximization can be understood as an optimization of the linear functional over the Abelian moment polytope of the coadjoint orbit . By Kostant’s convexity theorem [Kos73], the latter is equal to the convex hull of the orbit of under the Weyl group, which in turn is a subset of plus the cone spanned by the negative roots. We conclude that
By assumption and using that ,
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 this is immediate. If then the convexity of the moment polytope implies that it is contained in the half-space . ∎
One choice of outer approximation is given by the moment polytope for the action of the maximal torus , which is equal to the convex hull of the weights of the representation (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 (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 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 on the purity is available. One natural way of obtaining such an estimate is the well-known swap test [BCWdW01], which directly estimates using a series of two-body measurements on two copies of . We sketch an alternative procedure which may be simpler to implement for some experimental platforms. Suppose that has been prepared by acting on an initial product state with a quantum operation that approximates an entangling unitary gate (e.g., a spin squeezing operation). Act on by a quantum operation that approximates the corresponding “disentangling unitary” and denote by 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 , which can be obtained from tomography of the single-particle reduced density matrices . For small noise, 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 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 and an arbitrary pure state , which is defined by . Note that , with equality if and only if .
Let be a mixed state with purity . Then there exists a pure state with fidelity such that
Consider the spectral decomposition with eigenvalues ordered non-increasingly, . Our assumption on the purity implies immediately that the maximal eigenvalue can also be lower-bounded by :
Thus if we set then .
On the other hand, using that for all , 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 in first order in .
We now illustrate the approach with a numerical example. Suppose that is an experimentally prepared quantum state of four qubits with purity no less than . Then by Section 4.6 above there exists a pure state with fidelity 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 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 satisfy the relation
For comparison, the left-hand side of this inequality is equal to for a symmetric Dicke state .
Convex Extension
A second, alternative approach for treating noise aims to show that the experimentally prepared mixed state cannot be written as a convex combination of pure states in the closure of an entanglement class . For this, we consider the distance between a spectrum and an entanglement polytope defined as
There exists a continuous function with such that
for all mixed states with purity .
Let . Then is continuous and non-negative on , and . Now assume that is a mixed state with purity and . As in the proof of Section 4.6, let where is an eigenvector corresponding to the maximal eigenvalue of . For any , the triangle inequality gives
We may lower-bound the first summand by reversing the argument of (4.19) and using the assumption on ,
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 :
Now assume for the sake of reaching a contradiction that can in fact be written as a convex combination of pure states from . Then,
But on the other hand, 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 be a pure quantum state of 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 , 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, , which is a probability measure on the positive Weyl chamber 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 can be recovered from the corresponding distribution of local diagonal entries by taking a number of partial derivatives:
where are the local dimensions and where 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 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 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 of fixed spectrum and consider the corresponding Duistermaat–Heckman measures and 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 be a Hamiltonian -manifold of dimension and its moment map. Then is a volume form on that determines the Liouville measure of . By pushing forwarding along the moment map and further along the map we obtain the Duistermaat–Heckman measure for the -action on . If is compact then we can renormalize to obtain a probability measure 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 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, , , and . As in the preceding chapters, we may identify the collection of local eigenvalues with points in the positive Weyl chamber ; likewise, the collection of local diagonal entries can be identified with points in (Section 2.3). In this way, the eigenvalue distribution and the distribution of local diagonal entries introduced in Section 5.1 are identified with the Duistermaat–Heckman probability measures and , respectively.
for any test function . Here,
is the volume polynomial (5.3) for , and is a suitable normalization constant. Note that the measure is supported on the “diagonal” , 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 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 be a -representation (e.g., one from Table 2.3) and the corresponding representation of (its “purification”). Then (5.4) implies that the probability measure for pure states can be obtained as a direct integral of the measures for fixed global spectrum ,
where . Conversely, since the probability distributions vary continuously with the global spectrum , they can be reconstructed from by taking limits.
Our assumption that the moment polytope has non-empty intersection with the interior of the positive Weyl chamber amounts to showing that there exists a global pure state whose reduced density matrices all have non-degenerate eigenvalue spectrum. We first give a criterion in the case of distinguishable particles:
where we set if . It is not hard to see that each has non-degenerate spectrum. The same remains true if we perturb slightly such that it has non-degenerate global spectrum with all eigenvalues positive. Let denote a purification of on . Then Chapter 2 shows and therefore all one-body reduced density matrices of have non-degenerate spectrum. ∎
Note that the conditions of Section 5.2 are always satisfied for the purification, where . The following lemma shows that the same is true for the one-body -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 “” 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 :
3 The Abelian Measure
denote the -dimensional standard simplex, where . 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 is equal to the push-forward of Lebesgue measure on the standard simplex , normalized to probability one, along the linear map .
Now fix a Lebesgue measure on the affine hull of Abelian moment polytope . Away from the boundary of the standard simplex, the map is a submersion onto this affine space, and therefore the measure is absolutely continuous with respect to . In fact, its density function is given by
i.e., as the volume of a parametrized polytope, measured with respect to a Lebesgue measure on the fiber that is normalized such that (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 , the map maps the standard simplex bijectively onto the Abelian moment polytope (which in this case is itself a simplex). It follows that
where the denominator denotes the volume of the parallelotope spanned by the as measured by . In particular, the Abelian Duistermaat–Heckman measure for the maximal torus of is simply Lebesgue probability measure on the standard simplex, which is in agreement with Section 5.3.
In the general case, . Consider subsets of weights whose convex hull have codimension one in . These convex hulls are precisely the critical points of the Abelian moment map, viewed as a map onto the affine hull of (the proof of Section 3.2 works just as well if is of positive codimension). They cut into convex polytopes that we will call the regular chambers. We will also considered the complement of 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 can be parametrized as affine functions of (see, e.g., [CL98, VSB+07] for details). It follows that the density function is given by a polynomial of degree at most on (the interior of) each regular chamber, where we set . Thus we say that 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 . Let denote the set of weights on the wall, the corresponding sum of weight spaces, and its dimension. Let be Lebesgue measure on the affine hyperplane , normalized such that
where denotes the residue of a formal Laurent series (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 ). In this case, it follows from (5.11) and (5.12) that the density on the wall is constant,
where is again chosen such that , 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 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 from the Abelian measure that we have studied in the preceding section.
We start by considering the following model problem: Let be a random point in , chosen according to the unique -invariant probability measure on the coadjoint orbit. Then its restriction is a random variable that takes values in , and we denote its distribution by . We remark that is a Duistermaat–Heckman measure in the more general sense sketched in Section 5.2. For , it can be identified with the distribution of diagonal entries of a random Hermitian matrix with spectrum .
In the case where , Harish-Chandra has proved the following fundamental formula for the Fourier transform [HC57, Theorem 2]: For all not orthogonal to a root,
where the factor is defined in (5.3). Since partial derivatives in real space correspond to multiplication in Fourier space, (5.16) implies that [Hec82]
where is the Dirac measure at a point and where denotes the partial derivative in direction in the sense of distributions. In other words, for any smooth and compactly supported test function on we have that
In fact, 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 on ,
for all test functions on , where denotes the Haar probability measure on the compact group . Now recall that is the push-forward of along the restriction . It follows that
As similarly observed in [Hec82, GP90], Harish-Chandra’s formula implies the following fundamental derivative principle:
where the partial derivatives , the multiplication by and the restrictions to are all in the sense of distributions. In other words, we have that
for any smooth test function on that is compactly supported in the interior of the positive Weyl chamber.
Let be a smooth test function that is compactly supported in the interior of the positive Weyl chamber. Then the same is true for , and we find that
for all by applying (5.18) to and dividing by . In fact, (5.21) can be extended to all , since both the left-hand side and the right-hand side are continuous in . 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 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 can be fully recovered from the Abelian measure by taking partial derivatives in the directions of the negative roots, multiplying by the polynomial , 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 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 can be obtained from the ones of by taking partial derivatives and multiplying with according to (5.19). If the Abelian measure is times continuously differentiable then there cannot be any measure on the walls, so that 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 are always contained in critical walls. In fact, the support of is always equal to the non-Abelian moment polytope , and hence a single convex polytope. Moreover, is always absolutely continuous with respect to Lebesgue measure on . 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 under our basic assumption that 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 (), 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 , 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 that separates the upper and the right-hand side regular chamber (1 and 2 in the figure). Using (5.14) with we find that the density changes by
Therefore, has the following piecewise polynomial density function on the positive Weyl chamber:
We now cross the critical wall that separates the blue and the green chambers in Figure 5.3. It is spanned by the weights , and and is therefore again minimal. By (5.22) with , the density function of changes by the polynomial
as we cross the wall. It follows that the density function of is on the two green chambers that face the viewer in Figure 5.3 equal to . Note that the blue and green chambers together form the part of the three-qubit polytope where . By using permutation-symmetry to extend the formulas to all of , 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 and successively cross the critical walls, which are points and correspond to a single weight each. At each point , 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 for and otherwise. Amusingly, (5.23) is precisely the probability density of a sum of 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 , 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 bosonic qubits. For a bosonic state on , it is given by
where denotes the one-body reduced density matrix.
The average linear entropy of entanglement of a random pure state of bosonic qubits is equal to .
The average linear entropy of entanglement is given by
To evaluate the right-hand side, we observe that vanishes at , 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 is symmetric about the origin. The right-hand side integral is the variance of . But recall that is the distribution of a sum of independent random variables that are uniformly distributed on $1/3n\int d\rho\,E(\rho)=1/2-1/(2n)$. ∎
Bipartite Systems
since each factor is the volume of a -dimensional simplex. We now consider the negative partial derivative in the direction in the positive roots: Since there are positive roots,
is a polynomial of degree no more than . Since we differentiate each variable at most times, the result will be a multiple of the symmetric polynomial . On the other hand, the result is evidently antisymmetric in the variables and so will be a multiple of the Vandermonde determinant . Since the degrees add up, it follows at once that
Thus we conclude from the derivative principle (5.19) that the eigenvalue distribution of is proportional to
on , the intersection of with the positive Weyl chamber, which is the non-Abelian moment polytope for the action of . This is the well-known formula from [LP88, ZS01]. In mathematics, the distribution of is also known as a normalized Wishart ensemble (see, e.g., [ASY14]). Since and have the same non-zero eigenvalues (Chapter 2), it follows immediately from (5.25) that the joint distribution of the marginal eigenvalues of both and is given by
for all test functions . For , 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 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 in the restriction of an irreducible representation of . 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 vs. problem. Whereas the computation of Kronecker coefficients is known to be -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 vs. problem in computer science [MS01, MS08, BLMW11]. In this chapter, we study the problem of computing multiplicities of Lie group representations:
Let be a fixed homomorphism of compact, connected Lie groups. What is the multiplicity of an irreducible -representation in an irreducible -representation , when given as input the highest weights and ?
The term subgroup restriction problem comes from the archetypical case where the map is the inclusion of a subgroup .
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 and the stretching function can be evaluated in polynomial time. Another immediate corollary is that the positivity of the coefficients can be decided in polynomial time for any fixed homomorphism . Mulmuley has conjectured that deciding positivity of the multiplicities should be possible in polynomial time even if the group homomorphism 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 -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 (Section 6.4), which is obtained in three steps: First, we restrict from the group to its maximal torus . 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 of . Third, we recover the multiplicity of an irreducible -representation by using a finite-difference formula based on Weyl’s character formula: For any -representation , the highest weight multiplicity function of irreducible -representations and the weight multiplicity function are related by
where denotes the finite-difference operator in direction (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 , which are commonly defined as the multiplicities in the decomposition of tensor products of irreducible representations of the symmetric group . 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 . 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 , as first proved in [BI08].
In practice, our algorithm appears to work rather well as long as the rank of the Lie group is not too large. In the case of Kronecker coefficients for Young diagrams with two rows, we can easily go up to boxes using commodity hardware. In contrast, all other software packages known to the authors cannot go beyond only a moderate number of boxes ( 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 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 , since we will mostly not need its complexification explicitly. Recall that the irreducible representations of are labeled by their highest weight in . An arbitrary finite-dimensional representation can always be decomposed into irreducible sub-representations,
We will call the function thus defined the highest weight multiplicity function.
We may similar decompose into irreducible representations of the maximal torus , which we recall are one-dimensional and labeled by elements of the weight lattice . We thus obtain the decomposition into weight spaces
We will call 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 is given by the famous Weyl character formula
where 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 in an irreducible representation is given by the well-known Kostant multiplicity formula [Kos59],
For any fixed group , 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 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 is the maximal torus of .
Weight Multiplicities as a Single Partition Function
for all , where 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 [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 is a general compact connected Lie group then its Lie algebra can always decomposed as
where is the Lie algebra of a compact connected semisimple Lie group and the Lie algebra of the center of . By Schur’s lemma (2.23), each element of the center acts by a scalar on an irreducible representation . Therefore, all weights that appear in have the same restriction to . It follows that
where we write according to the corresponding decomposition of weight lattices , and likewise for . These multiplicities can thus be evaluated by using (6.8).
3 The Finite Difference Formula
Let be a finite-dimensional representation of the compact connected Lie group . In the preceding section we have seen that we can compute the weight multiplicity function from the highest weight multiplicity function 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 -representation , we have that
where is the finite-difference operator in direction .
By linearity, it suffices to establish the lemma for an irreducible representation . The Weyl character formula (6.6) can be rewritten in the form
Now consider the right-hand side of (6.12). Since is a strictly dominant weight in , it is sent by any Weyl group element to the interior of a different Weyl chamber. That is, for any there exists a positive root such that . Therefore is a dominant weight if only if , in which case it is equal to . It follows that the right-hand side of (6.12) identifies with a function on the weight lattice whose restriction to is equal to the indicator function of , i.e., to the highest weight multiplicity function of . ∎
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 of an irreducible representation in the tensor product . These multiplicities are called the Littlewood–Richardson coefficients for (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 -representations are just the irreducible representations of , 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 ).
In fact, it is not hard to see that the coefficients can be defined by the expansion .
4 Multiplicities for the Subgroup Restriction Problem
Let be a representation of and a weight vector of weight . If we restrict the action to via then is a weight vector of weight .
As alluded to in the introduction, our strategy for solving the subgroup restriction problem then is the following: Given an irreducible representation of , we can determine its weight multiplicities with respect to the maximal torus by using any of the formulas from Section 6.2. We then obtain the weight multiplicities for by restricting as in Section 6.4. Finally, we reconstruct the multiplicity of an irreducible representation 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 , 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 , which according to the Weyl dimension formula is given by
It is however possible to combine (6.8) with the restriction map 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 can be expressed in terms of weight multiplicities for :
Finally, decompose according to and according to . Then we can rewrite the above in the following way:
We note that the proof of Section 6.4 is constructive: The maps and , whose existence is asserted by the proposition, are defined in (6.16) in terms of the maps and constructed explicitly in [Bli08, §4] (or [BGR04, Proof of Theorem 2.1] for ). 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 . 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 to counting the number of integral points in rational convex polytopes of the form (6.18). We shall suppose that the highest weights and , 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 , the polytope 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 . 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 with boxes and no more than , and 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, is equal to Lebesgue measure on the standard simplex normalized to probability one, so that:
Now consider as a representation of , the maximal torus of . By pushing forward both the left and the right-hand side of (6.22) along the map , 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 are the Vandermonde determinants (5.5), , and where the sum runs over all Young diagrams with boxes each and no more than , and rows, respectively (if ).
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 , 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 on the first tensor factor, we find that
For large , it follows readily from Weyl’s dimension formula (6.14) that
for some constant . Together with (6.24), we recover (5.25), the formula for the density of the eigenvalue distribution of 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 with finitely many outcomes is given by
where is the probability distribution of (i.e., is the probability of an outcome ).
Given a collection of random variables defined on a common probability space, we can then consider the Shannon entropy of any non-empty subset 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 has a complicated geometrical structure [ZY97]. However, its closure is a convex cone [ZY97], which we call the classical entropy cone. Like any closed convex cone, can be described by linear inequalities. To see this, consider the dual cone
Each element can be identified with an entropy inequality that is satisfied by the Shannon entropy. The bipolar theorem now asserts that the bidual cone is equal to (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 .
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 to be approximable by the Shannon entropies of random variables.
In the seminal work [ZY98], Zhang and Yeung have shown that for 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, and 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 is not polyhedral for [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 on a finite-dimensional Hilbert space is given by
By the spectral theorem, the von Neumann entropy is equal to , the Shannon entropy of the spectrum of , which is a probability distribution. It is a concave function of .
Now let be a density matrix describing the state of a quantum system of distinguishable particles with tensor-product Hilbert space . The state of any subset of the particles is described by the reduced density matrix formed by tracing out the Hilbert space of the other particles. We define the quantum entropy region to be [Pip03]
Clearly, , since any joint probability distribution can be considered as a multipartite density matrix. In general, 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 is indeed a convex cone.
(1) We first show that : Let , be quantum states on and , respectively. Then is a quantum state on , and for each subset . By additivity of the von Neumann entropy, , which shows the claim.
where is the binary entropy function. Let . Since is continuous and , we may choose large enough such that for , and hence
Since was arbitrary, we may conclude that . This establishes the second claim.
By taking limits, points (1) and (2) together imply that 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 . 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 or 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 [Cha03]. In other words, the dual cone 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 is a balanced entropy inequality satisfied by the Shannon entropies of the random variables then the same inequality is also satisfied by the von Neumann entropies of the quantum states :
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, and 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), and 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 is higher by an amount of its. That is precisely the maximal amount by which quantum mechanics can violate monotonicity.
where is the quantum Rényi-2 entropy; is the differential Rényi- entropy, defined by for any positive , with the probability density of the random variable with respect to Lebesgue measure. In the limiting case , we recover a formula involving the differential Shannon entropy , 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 are .
The symplectic complement of a submodule is the submodule . In the case of prime , it is well-known that —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:
.
is both injective and surjective (it is certainly well-defined). Injectivity follows immediately from the non-degeneracy of the symplectic form. For surjectivity, let . Then is a character of . By Section 8.2, there exists such that . Since vanishes on , . Thus is an isomorphism, and we find that
The following important corollary follows from Section 8.2 and :
We call a submodule an isotropic submodule if , i.e. if for all . Finally consider , the phase space of particles . There is a natural way of restricting a submodule to : we set
where is identified with a submodule of 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 is a group, we deduce that ; since all elements of are unitaries, ; and (8.9) implies that . Hence projects onto a -dimensional subspace, called the stabilizer code of . Note that the stabilizer code is the subspace of all vectors that are stabilized by . The corresponding stabilizer state is . 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 . If is odd then there is a canonical element in each equivalence class, given by
It is compatible with reductions, i.e. .
Consequently, and are related by conjugation with the Weyl operator .
If is odd, then (8.6) implies that . It follows that is a stabilizer group of cardinality , with corresponding stabilizer state This is the canonical representative (8.12) of the equivalence class of states associated with .
(3) Injectivity: Suppose that and 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 , so that there exists, e.g., . 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 restricts to the submodule , it follows that . 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 . Recall that the cardinalities of and of the corresponding stabilizer group agree. We have already seen that the dimension of the stabilizer code is equal to . Thus,
(observe the judicious choice of signs). The stabilizer code is one-dimensional, since , and spanned by the vector which is stabilized by all operators in . Thus the stabilizer state is the maximally entangled state . In accordance with Theorem 8.4, its entropies are given by
since . Another choice of stabilizer subgroup is
4 A Classical Model for Stabilizer Entropies
If the local dimension 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 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 is given by the uniform distribution on .
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 is odd then the above construction can also be obtained by interpreting the Wigner function as the probability distribution of the random variable .
To prove (8.15), denote by the projection onto the phase space of parties . It will be convenient to consider as a symplectic submodule of in the natural way. To avoid any notational ambiguity, we denote by the restriction of the symplectic form to and by the symplectic complement of a subspace taken correspondingly within . Observe that
Indeed, if and , then . On the other hand, we find that
To see this, consider a vector and note that if then , hence since . We conclude from (8.16) and (8.17) that
Note that . Since is a group homomorphism, it follows that 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 are distributed uniformly on their range and the stabilizer states are normalized projectors, so that the respective entropies coincide.
Finally, it is clear from (8.14) that for odd the distribution of coincides with the Wigner function of the stabilizer state. It remains to show that the Wigner function of a reduced state is obtained by marginalizing the full Wigner function (in other words: the quantum and the classical way of reducing to subsystems commute):
for all . 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 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 is uniformly distributed on , which is a group, and that the projections are group homomorphisms (also when restricted to ). In this situation, it was shown in [LC07] that the Ingleton inequality (8.2) holds for the random variables . (In the language of [CY02], the entropy vector can be characterized by the normal subgroups .) 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 . Such submodules are called Lagrangian, and they satisfy and . Thus in this case our classical model can also be defined by choosing uniformly at random. Furthermore, since , we may also define to be the coset of modulo . In this way, we recover the construction of Theorem 11 in [LMRW13].
5 Gaussian States
Here, is a real, positive definite -matrix called the covariance matrix, and is the vector of first moments. Conversely, for every covariance matrix that satisfies the uncertainty relation , where is the symplectic matrix, there exists a corresponding Gaussian quantum state. Note that (8.21) is the probability density of a random vector with multivariate normal distribution of mean and covariance matrix . Using (8.20), it follows that the Rényi-2 entropy of the quantum state, , is directly related to the differential Rényi-2 entropy of the continuous random variable , :
The reduced state for some subset of modes is again a Gaussian state, and its covariance matrix is equal to the corresponding submatrix of . Thus the Wigner function of is given by the marginal probability density of the variables , 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 bits per mode.
Let be a Gaussian state with covariance matrix , and define a random variable with probability density given by the Wigner function . Then, for any positive ,
where is the differential Rényi- entropy. In the limit , we recover
where is the differential Shannon entropy.
By Gaussian integration, the differential Rényi- entropy of the random variable 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 , 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 of a stabilizer state are proportional to projectors, while the corresponding random variables 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- entropy, respectively. For discrete random variables the latter are defined by . 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 . 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 , which measure the overlap of two ways of decomposing a triple tensor product of irreducible representations of (Section 9.2). We find that in the “semiclassical limit” , the recoupling coefficients’ norm decreases at most polynomially for a sequence of Young diagrams of boxes converging to the eigenvalues of a given tripartite quantum state and its reduced states , , , , ; 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 , , 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 [WG59]. The recoupling coefficients of , known as the Wigner -symbols in their rescaled, more symmetric form [WG59], describe the relation between individual spins , , , their total spin and the intermediate spins and (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 -symbol decays polynomially if there exists a tetrahedron with side lengths , , , , , , 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 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 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 are labeled by Young diagrams with boxes, that is, ordered partitions of . As before, we write for such a partition and for the associated irreducible unitary representation of ; we denote its dimension by . Any finite-dimensional representation of can be decomposed into a direct sum of irreducible representations, and if is a unitary representation then this decomposition can also be made unitary. Concretely, consider the space of -linear maps defined as in (2.22) and equip with the re-scaled Hilbert–Schmidt inner product
(1) Any unit vector in is an -linear isometry, and any two orthogonal vectors have orthogonal range.
(2) The direct sum of the -linear maps
defines an -linear unitary isomorphism .
(2) This follows from (1) and Schur’s lemma. ∎
In particular, we may decompose a tensor product of two irreducible representations:
The Clebsch–Gordan isomorphism of the symmetric group is the -linear unitary isomorphism
defined as in Section 9.2. Its components are -linear isometric embeddings; they will be denoted by . According to (2.24), the dimension of is equal to the Kronecker coefficient .
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 ,
The recoupling coefficients of the symmetric group are the components of the isomorphism (9.4) for fixed and , 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 , these recoupling coefficients are linear maps rather than scalars, since the “Clebsch–Gordan series” for is not multiplicity-free. Their size is thus measured by an operator norm, and it will be convenient to employ the Hilbert–Schmidt norm as well as the operator norm (cf. Section 9.2).
where the direct sum runs over all Young diagram with boxes and at most rows. In the following we shall denote by the orthogonal projector onto a direct summand 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 and are isometries. Now note that is precisely equal to the orthogonal projector onto
On the other hand, 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 with eigenvalues , , , , , then there exists a sequence of Young diagrams with boxes and at most , , etc. rows such that
Conversely, if 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 as the sum of the projectors – defined as in (9.8) – for which , , etc.; is defined accordingly. By (9.13) and the fact that there are only many Young diagrams with a bounded number of rows,
where . Now we use
which holds for arbitrary projectors , and quantum states , For pure states , by the Cauchy–Schwarz inequality; the general statement follows by considering a purification of . and obtain
Using (9.9), (9.10) and the triangle inequality, we find that
where the sum extends over Young diagrams whose normalization is -close to the eigenvalues associated to and its marginals, respectively (as specified above). Since the number of terms in this sum is again upper-bounded by , 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 , , etc., which in turn can be upper-bounded via (9.13). Thus we find
For pure quantum states , the Schmidt decomposition (2.2) implies that necessarily and . 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 , corresponding to the trivial representation; hence, and 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 .
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 and , and an analogous result can be established for these coefficients. They are in the same way related to Wigner’s -symbols for as the recoupling coefficients are related to the -symbol. Just as Theorem 9.6 does not cover the eigenvalues of , 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 are given by the space of -linear maps from to . In each multiplicity space, let us choose maps that form an orthonormal basis with respect to the inner product (9.1). We will represent them by
in the graphical calculus. The maps are nothing but components of the Clebsch–Gordan isometries (Section 9.2). It follows from (9.5) that
By taking the trace over 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., , because they can be defined over the reals. We saw that this implied that is one-dimensional, i.e., there exists a single copy of the trivial representation in each tensor product . We shall denote the corresponding basis vector by
omitting the leg corresponding to the identity object as is usual in the graphical calculus. It can be concretely written as a maximally entangled state in any real orthonormal basis of (i.e., in a basis such that 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 of -invariant vectors in the triple tensor product.
Since the dimensions of and of agree by self-duality of , 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 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 -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 and ) 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 -symbol, which can be obtained in the same way from the recoupling coefficients of . 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 -representations grow exponentially with and thus affect the asymptotics. We record the following consequence, which has a well-known counterpart for ; cf. [LW05a, (B4)].
are invariant under exchanging the columns as well as .
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 and , 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 are defined by the formula
with respect to an orthonormal basis . They satisfy the fundamental identity
for any operator on , where denotes the transpose in the basis . Thus they are invariant under operations of the form , where is a unitary and where denotes its complex conjugate with respect to the basis [HH99]. In particular, this implies that for any basis of in which acts by orthogonal transformations,
is the (unique up to phase) invariant vector in —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 and we have the relation
The normalized trace of any operator can be written as
For any , and , we shall consider the following sets of vectors in ,
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 and 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 , , and is equal to
where denotes the orthogonal projection onto , , 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 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 , [CM06], we conclude that the von Neumann entropy is strongly subadditive:
For 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 in accordance with Section 9.4.
6 Semiclassicality
In [WG59], Wigner studied the asymptotics of the recoupling coefficients of which can be defined in complete analogy to Section 9.2. Given three particles of spin , , such that the total spin of the first two particles is and of all three particles , the absolute value squared of the recoupling coefficient can be interpreted as the probability of observing that particles two and three have total spin . 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 . If no such tetrahedron exists then the -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 analogue of the diagram (9.17) [Rob99].
7 Sums of Matrices and Quantum Marginals
Do there exist Hermitian -matrices , and with given prescribed eigenvalues for , , , , and ?
This is a natural generalization of the problem of determining the relation between the eigenvalues of , and 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 -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 , , be Hermitian -matrices. Without loss of generality, we may assume that and that (else, we may add suitable multiples of the identity and rescale). Generalizing a construction from [Chr08], we define a tripartite quantum state in terms of its purification
Let be the quantum state with purification (9.31). Then the non-zero eigenvalues of and all its reduced density matrices are given by
Observe that is built from a sum of (unnormalized) maximally entangled states (9.23) on , and , 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 . Using (9.27), we find that , 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 has rank at most and it satisfies the polygonal inequality (3.2) with equality:
where denotes the maximal eigenvalue of the reduced density matrix .
Note that (9.32) implies that the polygonal inequalities for , and are likewise satisfied with equality (i.e., , 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 . It is thus immediate that we have equality if and only if is a maximal eigenvector of and
A priori, the right-hand side can run over all indices and by orthogonality of the bases in the Schmidt decomposition. But (9.33) implies that in fact precisely two out of the three indices have to be zero, so that we obtain
Thus we may define -matrices , and such that
Finally, we use the polar decomposition to write , etc., and set , etc. Then (9.31) is indeed a purification of the quantum state , which is locally unitarily equivalent to . ∎
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 -matrices , , and with , , , etc. as their partial sums.
is the content of Section 9.7. For , Section 9.7 implies that there exist Hermitian -matrices , , such that is locally unitarily equivalent to the state with purification (9.31). Since the spectra of and its reduced density matrices are left invariant by local unitaries, Section 9.7 implies that the partial sums of these matrices , and have the desired spectra. ∎
Similar statements can be proved for all marginal spectra (i.e., including , 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 be a Young diagram. In [Nis00], the restriction of an irreducible -representation to the subgroup of permutation matrices has been computed:
In the right-hand side of (9.34), denotes an induced representation and is the unique Young diagram with number of boxes equal to the number of rows of such that
where is the Young subgroup corresponding to , its normalizer in , and the Young subgroup of . Note that indeed acts on the subspace .
If , then is again a Young diagram, and
Here and in the following, we write “…” for a sum of irreducible -representations whose Young diagrams have longer first rows than all the preceding ones.
Otherwise, if then the first row of any Young diagram that appears in the restriction of is longer than .
Since induction is transitive, we can rewrite (9.34) as
The Pieri formula asserts that the -representation induced from a tensor product of an irreducible -representation with the trivial -representation is given by the sum over all irreducible -representations with a Young diagram that can be obtained by adding boxes to , 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 . As is equal to the number of rows of , we obtain the lower bound
on the length of the first row of any irreducible -representation that occurs in the restriction of .
Equality in (9.37) can occur only if each row of contains a single box, i.e., for , such that . Then is the trivial group, , and the corresponding summand in (9.36) is equal to
By the Pieri formula, (9.38) contains an irreducible -representation with first row of length if and only if (since we only add boxes to ). Moreover, if this condition is satisfied then there is only a single option, namely to place one box in each of the leftmost columns, resulting in the Young diagram . ∎
We now consider the decomposition of a tensor product of irreducible -representations,
where we assume that and . The multiplicities are known as the Littlewood–Richardson coefficients, and they are independent of the choice of (if is at least as large as the number of rows in the Young diagrams involved) [JK81]. Moreover, is non-zero only if . It follows from the points above that
On the other hand, by applying (9.35) to the individual tensor factors we find that
where are the Kronecker coefficients. In the last inequality, we have used that only if [JK81, Theorem 2.9.22]. By comparing coefficients we find that for all triples of Young diagrams with and 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 for can be obtained by restricting the ones of . 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 do not depend on the choice of (if 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 -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.
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special linear group of Hilbert space , and its Lie algebra, \hyperpage15
special unitary group and its Lie algebra, \hyperpage15
special unitary group of Hilbert space , and its Lie algebra, \hyperpage15
maximal torus of and its Lie algebra, \hyperpage8
complexification of and its Lie algebra, \hyperpage8
unitary group and its Lie algebra, \hyperpage11
unitary group of Hilbert space , and its Lie algebra, \hyperpage15
irreducible representations of , , , , \hyperpage14
subspace of invariant vectors in representation , \hyperpage11
irreducible -representation with highest weight , \hyperpage11
weight spaces of a representation , \hyperpage9
Pauli matrices corresponding to root , \hyperpage9
non-increasingly ordered chamber in , \hyperpage84
moment polytope for the -action on projective space, \hyperpage34
moment polytope for the -action on projective space, \hyperpage36
Lebesgue measure on , \hyperpage87
closure of -orbit through , \hyperpage19
Riemannian metric of projective space, \hyperpage16
complex structure of projective space, \hyperpage16
-stabilizer of , and its Lie algebra, \hyperpage17
moment map for the -action, \hyperpage17
moment map for the -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 ) on affine cone , \hyperpage19
residue of formal Laurent series, \hyperpage88
volume of parametrized polytope, \hyperpage87
complex projective space of pure states on , \hyperpage16
projective subvariety corresponding to an affine cone , \hyperpage19
-orbit through projector onto highest weight vector (projective subvariety isomorphic to the coadjoint orbit ), \hyperpage20
tangent vector at generated by infinitesimal action of , \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 -homology for compact Lie group actions, with P. Baum, H. Oyono-Oyono, and T. Schick. Abh. Math. Sem. Univ. Hamburg 80, 149–173 (2010).