Rectangular Kronecker coefficients and plethysms in geometric complexity theory
Christian Ikenmeyer, Greta Panova
Geometric complexity theory and Kronecker positivity
is the permanent polynomial, a polynomial of interest in particular in graph theory and physics. From a complexity theory standpoint the determinant is complete for the complexity class VPs [Val79a, Tod92, MP08], while the permanent is complete for VNP [Val79a] and also for #P [Val79b]. By definition we have \textup{{VP{}_{s}}}\subseteq\textup{{VNP}} and a major conjecture in algebraic complexity theory related to the famous conjecture (see [Coo00]) is the following.
\textup{{VP{}_{s}}}\neq\textup{{VNP}}.
so . Conjecture 1.1 can be equivalently stated as follows:
The sequence grows superpolynomially in .
Finding lower bounds for is an important research area in algebraic complexity theory, see for example the recent progress in [MR04, CCL10, LMR13, HI16, ABV15, Yab15]. Mulmuley and Sohoni [MS01, MS08] proposed an approach to this problem using algebraic geometry and representation theory and coined the term geometric complexity theory.
In the following we outline how one can prove lower bounds on using rectangular Kronecker coefficients, see (1.5) below.
If , then .
Kronecker coefficients are #P-hard to compute as they are generalizations of the well-known Littlewood-Richardson coefficients [Nar06]. But the positivity of Littlewood-Richardson coefficients can be decided in polynomial time [DLM06, MNS12], even by a combinatorial max-flow algorithm [BI13]. Even though deciding positivity of Kronecker coefficients is NP-hard in general, see [IMW15], the same paper provides evidence that the rectangular Kronecker coefficient case is significantly simpler. Thus to implement Thm. 1.4 [MS08] proposed to focus on the positivity of representation theoretic multiplicities in order to use the weaker statement
to prove lower bounds, see also [Lan15, Sec. 6.6] and [Bür15, Problem 3.13], where this approach is explained. The results in [BCI11b, BHI15, Kum15] already indicate that vanishing of might be rare. In [IMW15] sequences of partition triples are constructed that satisfy . Unfortunately has not the necessary rectangular shape. Indeed, our main result Thm. 1.6 completely rules out the possibility that (1.5) could be used to prove superpolynomial lower bounds on .
Let , . If , then .
Thm. 1.6 holds in higher generality: In the proof of Thm. 1.6 we do not use any specific property of the permanent other than it is a family of polynomials whose degree and number of variables is polynomially bounded in . For all these families of polynomials no superpolynomial lower bounds on the determinantal complexity can be shown using the vanishing of .
To use (1.5) it is required by (1.3) that
An example is and , , where we have , see [Ike12, Appendix].
A natural generalization of our main theorem would be to consider symmetric rectangular Kronecker coefficients instead of just , because those are the multiplicities in the coordinate ring of the orbit . Our proof does not immediately work for those coefficients as they lack the important transposition symmetry, but an equivalent no-go result for these coefficients follows directly from [BIP16].
For a partition we write to denote with its first row removed, so . Vice versa, for a partition and we write to denote the partition with an additional new first row containing boxes. The following theorem gives a very strong restriction on the shape of the partitions that we have to consider.
We sometimes write instead of .
The main ingredients for the proof of Thm. 1.6 are the following Corollary 1.9 and Thm. 1.10.
If with , then .
Note that if and , then .
Let be the set of the following 6 exceptional partitions.
Thm. 1.10 is proved in Section 4. The proof cuts the partition into smaller pieces in several significantly different ways and makes heavy use of the following three properties:
The semigroup property: If for 6 partitions of we have that and , then also , where we interpret partitions as integer vectors in order to define the sum of two partitions.
The transposition property: .
The square positivity: For all positive we have .
The first property is easy to see if we interpret as the dimension of the -highest weight vector space in the coordinate ring of . Here the acting group is and the semigroup property follows from multiplying highest weight vectors. The second and third property follow from the character theory of the symmetric group. While the second property is immediate, the third property (in [BB04]) requires reduction to the alternating group and specific properties of characters of symmetric partitions, later generalized in [PPV16] and further in [PP14a].
(b) Consequences for geometric complexity theory
We remark that the overall proof structure in [BIP16] closely mimics the proof structure of our Thm. 1.6: [KL14] is used to prove a degree lower bound and then an analog to Thm. 1.10 is proved, also by cutting the partition into smaller pieces. The details and the methods used in [BIP16] are very different from our paper though.
(c) Positivity results for Kronecker coefficients
In Section 4 we prove the rectangular Kronecker positivity for a large class of partitions: If the side lengths of the rectangles are at least quadratic in the partition length we have positivity, see Theorem 4.7 for the precise statement. More exact Kronecker positivity results are given in Section 6.
Combinatorial conjectures like the Saxl conjecture [PPV16, Ike15, LS15] are also concerned with the positivity of Kronecker coefficients.
In Section 5 we we prove that the saturation of the rectangular Kronecker semigroup is trivial, we show that the rectangular Kronecker positivity stretching factor is 2 for a long first row, and we completely classify the positivity of rectangular limit Kronecker coefficients.
We gratefully acknowledge the helpful comments of the anonymous reviewers. GP was partially supported by NSF grant DMS-1500834.
Proof of the degree lower bound
In this section we prove the degree lower bound Cor. 1.9. The main ingredients are Manivel’s result about limit rectangular Kronecker coefficients (Section 2 (a)) and Valiant’s insights about finite determinantal complexity (Section 2 (b)).
The main contribution to the specific limits of Kronecker coefficients that we are interested in in this paper comes from Manivel.
Since is symmetric in and , if both and , then and depends only on .
Analogously, the 1-stable range is defined as
The following tables show the Kronecker coefficients for , , and , from left to right.
(b) Complexity lower bounds literally too good to be true: inequality of multiplicities and degree lower bound
In this section we prove Corollary 1.9 by using the finiteness of the determinantal complexity.
As the following proposition shows, the existence of an -obstruction of quality proves the existence of an that cannot be written as an determinant.
If there exists an -obstruction of quality , then for some .
Given , if , then .
Given , we have .
Part (a) is the first part of [KL14, Thm 1.3]. Part (b) follows from the proof of the second part of [KL14, Thm 1.3]: From a highest weight vector of weight in they construct a highest weight vector of weight in such that the evaluations coincide. Take a basis of the highest weight vector space of weight in and take general points from . Then the evaluation matrix has full rank. Thus has full rank, which implies the statement. ∎
Let {\textup{dc{}_{\textup{max}}}}(m) denote the maximum . The following lemma shows that {\textup{dc{}_{\textup{max}}}}(m) is a well-defined finite number.
From [Val79a] it follows that if has monomials, then . In particular, since every has at most monomials, it follows that . ∎
Fix , and let , which is true in particular if . Let . Then
Interestingly the proof of this purely representation theoretic statement uses the finiteness of the determinantal complexity.
Assume the contrary, i.e., there exists a and with Since , the Kronecker coefficient is the same for all with . Thus we have for all with . By Prop. 2.6(b) we have for all . This implies is an -obstruction of quality for all . By Prop. 2.5 there exist functions such that for every . In particular we have \textup{dc}(f_{{\textup{dc{}_{\textup{max}}}}(m)})>{\textup{dc{}_{\textup{max}}}}(m), in contradiction to Lem. 2.7. ∎
The proof is now immediate. By assumption we have . By Prop. 2.8 we have , so . Thus and therefore . ∎
Kronecker positivity: A simplified version
In this section we prepare the reader for the combinatorially intricate arguments to come in the proof of Thm. 1.10. This section is a purely didactical one. We prove a weaker statement (Thm. 3.1) than Thm. 1.10 in the following sense. The bound we obtain is weaker and we exclude column lengths 2, 3, 5, and 7 from , which are the column lengths that cause most of the technical issues. The paper is self-contained without this section 3. Neither Thm. 3.1 nor its proof are referenced later. On the contrary, to prove Thm. 3.1 we use two positivity results (Lem. 4.2 and Cor. 4.5) that will be proved in section 4.
Let denote the hook partition of with boxes in the first column.
Let and . Let , . Then .
This follows from Cor. 4.5, because . ∎
Together with Lem. 4.2 we now have all the building blocks to prove Thm. 3.1.
We forget about the first row of and treat each column length in separately. For the ease of notation let . For each let be the number of columns of length in . We divide by , formally with . The partition decomposes as follows:
Note that by assumption on both sums exclude the four values . We now group together the rectangles into groups of roughly , so that the result is roughly of size . Formally we define and divide with . Now decomposes as follows:
We prove Kronecker positivity for the summands separately. For the leftmost sum, by Lem. 4.2 with . For the middle sum, with the same argument. For the rightmost sum, by Lem. 3.2. According to these observations we add a new first row to . Formally
Using the semigroup property the above three positivity considerations we show that
Proof of Kronecker positivity
In this section we prove Thm. 1.10. If , a finite calculation reveals . Combining this with Prop. 2.8 gives . Thus we are left to analyze the case .
Given a partition we want to decompose it into smaller partitions and use the semigroup property to show the positivity of . We use the following decomposition theorem to write as a sum of partitions that are not in .
with and where all columns in have distinct lengths and no column in has length 1, 2, 4, or 6, and where is of one of the following shapes:
has only columns of length 1, 2, 4, 6, all column lengths are distinct, and .
, where and .
, where .
.
We start by treating each independently. Let denote the number of columns of length in . In a greedy manner cut off from as many rectangles of size as possible. Formally, we divide with . We are left with a rectangle. We now join (if possible) one of the rectangles with the rectangle: If , define and . If , define and . We obtain a rectangle and call it . Note that .
Cut off from rectangle as many rectangles of size as possible. Formally, define , so as required in the claim. After cutting we are left with either the empty partition or a column . In the former case (i.e., is even) define , otherwise .
as required in the statement of the claim. Moreover, has the correct shape. Clearly has only columns of length 1, 2, 4, 6 and all column lengths are distinct. If , then we are done by property (1).
The rest of the proof is devoted to the case where . We will use that if , then has at most 1 column of length , by definition of . Note that , because no two columns in have the same length. If has a column of length different from 1, 2, 4, 6, then such a column appears in or we have that and has no column of length . If it appears in , then we remove it from and add it to and we are done by property (2). If it does not appear in but , then we decrease by 1 and add a column of length to both and , so that we are done by property (2).
So from now on we assume that only has columns of length 1, 2, 4, or 6 (and thus for all ).
If for some , then we can decrease by 1 and set , so we are done by property (3).
Thus from now on we assume for all . Note that corresponds to the columns of length 1 in . If , then we can decrease by 2 and set , so we are done by property (4).
At this point the possible shapes of are quite limited: for all , for , .
If , then by construction, which is impossible because and .
Recall . If , then , so Since it follows Now we set and and we are done by property (5). ∎
All summands in the partition decomposition will yield a positive rectangular Kronecker coefficient, but we will need to group large blocks of rectangles. This is done with the following lemma.
Let and , then .
For all we have as shown in [BB04]. By the semigroup property we can add these square triples times and obtain Let denote the single row partition of . Clearly . Adding these two triples with the semigroup property we get Finally, transposing the last two partitions we obtain the statement. ∎
The following proposition will be used to prove positivity for building blocks of partitions like hooks and fat hooks. Here, for a set and a number we denote by the set .
Note that is the size of the partition obtained from by adding a shortest possible top row and one extra box at the top left corner, so that the largest possible column we can add is to still have a valid partition.
Claim: Suppose that , then .
Next, to show that we first transpose and one of the squares, apply the argument from above to it, and then transpose again:
The claim implies that .
and we see that , in contradiction to . Thus the assumption is wrong and we conclude , so the induction is complete. ∎
Let denote the rectangular partition . Let denote the hook partition of with boxes in the first row and boxes in the first column. So has boxes. The next corollary says that most hooks have positive rectangular Kronecker coefficient.
Let , then for all .
We apply Prop. 4.3 with , , and and . The values at are readily verified by direct computation. Then we have for all that for . Let and use the semigroup property once to add the positive triple in order to obtain the statement. ∎
Let denote the partition that results from by first adding an additional column with boxes and then adding a top row with boxes. The next corollary treats the positivity of hooks that are not covered by Cor. 4.5.
Fix . We have that for all with and for all , where , except in the following cases: (i) with or ; (ii) with ; (iii) and or ; (iv) and .
For all values of we have finitely many partitions of length at most 6 and width at most 7, for which we verify computationally the statement with and then by the semigroup property deduce it for with .
(i) When then , and , we obtain for .
(ii) When then , and .
(iv) When and , then we apply Proposition 4.3 with , and the case was excluded computationally.
Last, we add the positive triple to to obtain the statement. ∎
Now we are ready to prove the main positivity theorem.
We will treat these 5 summands independently.
Using Lem. 4.2 with (recall ) we see that Using the semigroup property for the summands we get
Using Lem. 4.2 again, this time with we see that
Using Corollary 4.5 twice with the semigroup property (in the case ) or using Corollary 4.6 we see that for all , , .
For we make the case distinction from Lemma 4.1. In cases , , , and a finite calculation shows that . In case we invoke Cor. 4.6 to see that . In both cases we have
Using the semigroup property on equations (4.8), (4.9), (4.10), (4.11), and (4.12) we obtain
Further positivity results: limit coefficients, stretching factor, and semigroup saturation
In the rest of the appendix we prove the positivity of rectangular Kronecker coefficients for a large class of partitions where the side lengths of the rectangle are at least quadratic in the length of the partition. Moreover, we prove that the saturation of the rectangular Kronecker semigroup is trivial, we show that the rectangular Kronecker positivity stretching factor is 2 for a long first row, and we completely classify the positivity of rectangular limit Kronecker coefficients that were introduced by Manivel in 2011.
Recall the definition from Thm. 1.10. Using Thm. 1.10 we get a complete classification of all cases in which .
Given , can be seen by choosing large and and applying Thm. 1.10. For , is a small finite calculation. ∎
(b) Double and triple column hooks
Here we study Kronecker coefficients for partitions and the Kronecker coefficients when and . In the case of these were exactly the hooks which were already classified. By that classification and the semigroup property it is readily seen that since , for we have for large enough. We now prove that this positivity holds in fact for all when .
Let . For any and we have that .
First, note that proposition follows from the hook positivity as long as . In the case when finite calculations for and give positive values. For we have that for some , and then we apply the semigroup property for many double hooks plus many triple hooks. By that argument, we can always assume that .
So we can assume that , i.e. is finite.
Let be its transpose partition. Note that , so by transposing one of the rectangles the statement to prove is equivalent to showing that
This will follow from the following claim applied when :
Claim: We have that for all , and
We prove this claim by induction on , with initial condition computationally verified for for the given finite set of values for and . Suppose that the claim holds for some values , i.e. we have . Consider the triple . Since after transposing the first two partitions and rearranging them we also have that . Add this triple to , applying the semigroup property, we have that
This show that the claim holds for as well. By the symmetry between and , we also have the statement for , so by induction the claim holds for all , s.t. .
Applying the claim with completes the proof.
(c) Stretching factor 2
Cut columnwise and group pairs of columns of the same length so that you get partitions . By Prop. 5.2 we have . Using the semigroup property we get the result. ∎
(d) Trivial saturation of the rectangular Kronecker semigroup
Let . The group contains all partitions for which divides .
By Prop. 5.2 for all we have and . Subtracting these we obtain . For we subtract from to obtain , where the is at position . Given a partition we define and obtain a vector that coincides with in every entry but the first: . We calculate with . Since divides it follows that is an integer. Since we have . ∎
Exact results for Kronecker coefficients
Here we provide a complete classification of triples with – hook or two-column partition, for which the Kronecker coefficient is positive and in the course of the proof give certain stronger quantitative relationships between these coefficients.
Assume that . Let . We then have that and is 0 for all other values of .
For we have that if or in the following cases:
Moreover, we have that for and the coefficients form a symmetric sequence in .
It is immediate to characterize the triples for which the Kronecker coefficient is 1.
Fix and let be a partition with columns of length . Then if for and for .
Direct computation shows that for , so by the semigroup property we have for all . Since every is either even, or , we have that is an even partition or is the sum of . By the semigroup property for Kronecker coefficients then we must have for all when . By Theorem 6.1 for any for the remaining values of .
Since , the statement follows by the Kronecker semigroup property.∎
In order to prove this theorem, we will derive a simple formula for these Kronecker coefficients, following the approaches set in [Bla12, Liu14, PP14b]. For brevity we set .
We have that the Kronecker coefficients are equal to the number of partitions of into distinct parts from , where without loss of generality by the symmetry of the Kronecker coefficients we assume . In other words, we have the following generating function identity:
Let denote the Schur function indexed by a partition and let denote the Kronecker product on the ring of symmetric functions, i.e. given by
For the sake of self-containment we repeat some calculations appearing in [Bla12, Liu14, PP14b].
We invoke Littlewood’s identity, stating that
In the case when and we have that and , where is the transposed (conjugate) partition of . Observe that . Rewriting the above identity in this case leads to
Take inner product with on both sides. Observe that the left-hand side gives two Kronecker coefficients and on the right side we have by the Littlewood-Richardson rule, so
Note that when we have that if and otherwise, and the above identity holds assuming that the term with is 0 when .
Let . As it is not hard to see by the Littlewood-Richardson rule in this case (see e.g. [PP14b]), we have that
In other words, the rectangular Littlewood-Richardson coefficient are equal to 1 only when the partitions and complement each other inside the rectangle. This is also easy to see from the fact that and in the case of , the skew shape, rotated is a straight shape, so the corresponding Schur function should be the same as to give nonzero inner product.
Applying these observation to equation (6.5) when , we see that the summands on the right-hand side will be nonzero if and only if and are both the complement of in the rectangle, so , and . Since in this case the product of the Littelwood-Richardson coefficients is just 1, the right-hand side is the number of such partitions , i.e.
where and we set , and for all so the above identity holds for all .
It is a classical result in combinatorics that self-conjugate partitions are in direct bijection with partitions into distinct odd parts, via . The condition in this case is equivalent to . Thus we can rewrite identity (6.6) as the following generating function identity
Let , then after an index shift the identity implies
Dividing both sides by we obtain the generating function for the hook Kronecker coefficients as desired.
We invoke the following result from [PP14b] which extends a result in [Alm85].
Let , i.e.
Then, for all , the sequence is symmetric and strictly unimodal.
Here strict unimodality means for all and for .
Let . Since , we have that is equivalent to for . No term for can contribute to the coefficient of for , so we have that the terms in of order are equal to the corresponding terms in
So we see that for . By the inequality for the values of , and the positivity for we obtain the positivity of all other ’s.
Now let . In this case the generating function can be computed explicitly summarized in the following table:
While the rectangles so far have been the same, we observe that in most cases when and are two different rectangles and is a two-row, then the Kronecker coefficients is almost always 0.
Let and , where and . Then
Using Littlewood’s identity for and , since and , we have that
As in [PP14b], the Jacobi-Trudi identity for a two row gives
and combining with with the previous identity we have
We now consider when . It is easy to see, and has been elaborated in [PP14b], if and only if is the complement of within , and is otherwise. In other words, for . At the same time, we need and so . Assume that , so . Since , we have for . So for .Together, the constraints for give for all . This now determines uniquely as for and . Since, further, and so , we must have and . Under these conditions it is easy to see that , so that and then . ∎
By transposing the two row partition and one of the rectangles above we reach the following.
Let and be a two-column partition of size . If and , then , otherwise .
Appendix: padding with the first variable
Let denote the space of matrices. In the literature sometimes is called the padded permanent instead of . We present now a simple interpolation argument that shows that it does not matter much which notion we use. Clearly if , then also by setting . The following claim proves the other direction.
There exists a function that is polynomially bounded in such that if , then then .
Let have skew circuits of size with polynomially bounded in . Let . Then there exists a size skew circuit computing . The polynomial is multilinear and we collect terms that involve using the notation , where does not appear in or . Setting in we obtain and setting we obtain . We see that and , which gives size skew circuits for and . Thus we get a size skew circuit for . Homogenizing with as the padding variable we see . ∎