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Kohnert’s rule for flagged Schur modules

Sam Armon [email protected] Sami Assaf Department of Mathematics, University of Southern California, 3620 S. Vermont Ave., Los Angeles, CA 90089-2532, U.S.A. [email protected] Grant Bowling [email protected]  and  Henry Ehrhard [email protected]
Abstract.

Flagged Schur modules generalize the irreducible representations of the general linear group under the action of the Borel subalgebra. Their characters include many important generalizations of Schur polynomials, such as Demazure characters, flagged skew Schur polynomials, and Schubert polynomials. In this paper, we prove the characters of flagged Schur modules can be computed using a simple combinatorial algorithm due to Kohnert if and only if the indexing diagram is northwest. This gives a new proof that characters of flagged Schur modules are nonnegative sums of Demazure characters and gives a representation theoretic interpretation for Kohnert polynomials.

Key words and phrases:
Flagged Schur modules, Kohnert polynomials, Demazure crystals
Work supported in part by NSF DMS-1763336.

1. Introduction

The irreducible representations of the general linear group were constructed explicitly by Weyl using the Ferrers diagrams of partitions. Similarly, for any diagram DD, a finite collection of cells in +×+\mathbb{Z}_{+}\times\mathbb{Z}_{+}, one can construct the Schur module 𝒮D\mathcal{S}_{D} for the general linear group. These modules have been widely studied, and their characters include generalizations of the Schur polynomials such as skew Schur polynomials and Stanley symmetric polynomials. More generally, one can construct the flagged Schur module 𝒮Dflag\mathcal{S}^{\mathrm{flag}}_{D}, which carries the action of the Borel subgroup of lower triangular matrices. These modules are also well-studied for certain families of diagrams, and their characters include type A Demazure characters [Dem74a], flagged skew Schur polynomials [RS95], and Schubert polynomials [LS82].

The Borel-Weyl theorem also realizes irreducible representations for the general linear group as spaces of sections of line bundles of the flag manifold. In a similar way, this classical construction can be generalized to configuration varieties 𝔉D\mathfrak{F}_{D} of families of subspaces of a fixed vector space with incidence relations specified by a diagram DD. When the diagram DD has the northwest property, Magyar [Mag98a] gave an explicit resolution proving 𝔉D\mathfrak{F}_{D} is normal with rational singularities. Since the corresponding line bundle has no higher cohomology, its space of sections recovers the Schur module 𝒮Dflag\mathcal{S}^{\mathrm{flag}}_{D}. Magyar [Mag98b] uses the geometry to give a recurrence for the character in terms of degree-preserving divided difference operators that arise in Demazure’s character formula [Dem74a]. Reiner and Shimozono [RS98] use this recurrence to show the characters of the corresponding flagged Schur modules expand nonnegatively into Demazure characters.

In this paper, we prove the characters of flagged Schur modules for northwest diagrams can be computed using Kohnert’s rule [Koh91], thus resolving a conjecture of Assaf and Searles [AS19]. They defined Kohnert polynomials 𝔎D\mathfrak{K}_{D} for diagrams DD using Kohnert’s rule [Koh91], giving a common generalization of Demazure characters [Koh91] and Schubert polynomials [Ass20a]. We prove the Kohnert polynomial 𝔎D\mathfrak{K}_{D} is the character of the flagged Schur module 𝒮Dflag\mathcal{S}^{\mathrm{flag}}_{D} for DD a northwest diagram by using the Demazure crystal structure for Kohnert polynomials [Ass20b] to show they also satisfy Magyar’s recurrence.

Our paper is structured as follows. In Section 2, we review flagged Schur modules and Kohnert polynomials, along with the associated combinatorics. We state Magyar’s recurrence for characters of flagged Schur modules, and begin to show it holds for Kohnert polynomials as well. In Section 3, we review crystals and reinterpret the last term in the desired recurrence for Kohnert polynomials as a statement about Demazure operators on crystals. In Section 4, we delve into the combinatorics of Kohnert diagrams to prove the desired result for Demazure operators on Kohnert crystals. Thus we prove Kohnert polynomials satisfy the same recurrence, and so coincide with characters of flagged Schur modules.

Our results have several corollaries. Using recent work of Assaf [Ass20b], we give a new proof that characters of flagged Schur modules decompose as a nonnegative sum of Demazure characters. Our results also give an explicit representation theoretic interpretation for Kohnert polynomials indexed by northwest diagrams. Since Schubert polynomials are known to be characters of flagged Schur modules indexed by northwest shapes [KP87, KP04], this also gives a new proof of Kohnert’s rule for Schubert polynomials [Ass20a].

Magyar considered the more general class of %\%-avoiding diagrams, which includes northwest diagrams. We show our result is tight in the sense that for %\%-avoiding diagrams DD that are not northwest, the Kohnert polynomial does not agree with characters of the flagged Schur modules.

2. Modules and polynomials

In this section, we define the basic objects of study for this paper: flagged Schur modules, Demazure characters, and Kohnert polynomials.

2.1. Schur modules for diagrams

Consider the infinite, doubly indexed family of indeterminates {zi,j}i,j=1\{z_{i,j}\}_{i,j=1}^{\infty}. A matrix AGLNA\in\mathrm{GL}_{N} act on [zi,j]\mathbb{C}[z_{i,j}] in the usual way,

Azk,l={i=1NAi,kzi,lkNzk,lk>N.A\cdot z_{k,l}=\begin{cases}\sum_{i=1}^{N}A_{i,k}z_{i,l}&k\leq N\\ z_{k,l}&k>N\end{cases}.

A diagram DD is a finite collection of cells in +×+\mathbb{Z}_{+}\times\mathbb{Z}_{+}. We use matrix convention, so that the northwest corner has index (1,1)(1,1). For example, Fig. 1 shows the Ferrers diagram for a partition, the skew diagram for nested partitions, the key diagram for a weak composition, the Rothe diagram for a permutation, and a generic diagram.

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Figure 1. Examples of diagrams.

A tableau or filling on DD is any map T:DT:D\rightarrow\mathbb{N}. Abusing notation, we let DD also denote the row tableau on the shape DD where each cell is assigned its row index. For example, Fig. 2 shows a generic tableau (left) and the row tableau (right).

T= 1 3 3 2 4 D= 1 2 2 3 3 T={\vline\vtop{ \halign{&\boxify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{1}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{2}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{4}$\hss}\vss\crcr}}}\hskip 20.00003ptD={\vline\vtop{ \halign{&\boxify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{1}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{2}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{2}$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(0.0,0.0){\line(1,0){8.0}} \put(0.0,0.0){\line(0,1){8.0}} \put(8.0,0.0){\line(0,1){8.0}} \put(0.0,8.0){\line(1,0){8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss\crcr}}}}}}}}}}}}}}}}}
Figure 2. Two tableaux for a diagram DD.
Definition 2.1.

For DD a diagram and TT a tableau of shape DD, set

(2.1) ΔT=j(T(j)D(j))\Delta_{T}=\prod_{j}(T^{(j)}\mid D^{(j)})

where T(j)T^{(j)} is the array of values in the jjth column of TT, and for arrays 𝐚,𝐛m\mathbf{a},\mathbf{b}\in\mathbb{N}^{m}, we set (𝐚𝐛)=det(zai,bj)[zi,j](\mathbf{a}\mid\mathbf{b})=\det(z_{a_{i},b_{j}})\in\mathbb{C}[z_{i,j}].

For example, taking TT to be the left tableau in Fig. 2, we have

ΔT=|z11z12z31z32||z23||z32z33z42z43|.\Delta_{T}=\begin{vmatrix}z_{11}&z_{12}\\ z_{31}&z_{32}\end{vmatrix}\begin{vmatrix}z_{23}\end{vmatrix}\begin{vmatrix}z_{32}&z_{33}\\ z_{42}&z_{43}\end{vmatrix}.

Notice ΔT=0\Delta_{T}=0 whenever TT has repeated column entries.

Definition 2.2.

The Schur module 𝒮D\mathcal{S}_{D} is the \mathbb{C}-span of {ΔTT:D[n]}\{\Delta_{T}\mid T:D\rightarrow[n]\}.

In particular, taking DD to be the Ferrers diagram of the partition λ\lambda as in the leftmost diagram of Fig. 1, the Schur module 𝒮D\mathcal{S}_{D} is the irreducible representation of GLn\mathrm{GL}_{n} indexed by λ\lambda, which we denote by 𝒮λ\mathcal{S}_{\lambda}.

For BGLnB\subset\mathrm{GL}_{n} the subalgebra of upper triangular matrices, there is a BB-stable ideal I=zi,ji>jI=\langle z_{i,j}\mid i>j\rangle. We consider the BB-module spanned by those fillings that respect this ideal. Say a filling TT is flagged if Ti,jiT_{i,j}\leq i.

Definition 2.3.

The flagged Schur module 𝒮Dflag\mathcal{S}^{\mathrm{flag}}_{D} is the BB-module 𝒮D/(𝒮DI)\mathcal{S}_{D}/(\mathcal{S}_{D}\cap I) spanned by {ΔTTi,ji}\{\Delta_{T}\mid T_{i,j}\leq i\}.

The character of a BB-module is the trace of the action of the matrix X=diag(x1,,xn)X=\mathrm{diag}(x_{1},\ldots,x_{n}). Many flagged Schur modules arise naturally in the context of geometry: for DD a key diagram, the module 𝒮Dflag\mathcal{S}^{\mathrm{flag}}_{D} coincides with those introduced by Demazure [Dem74b, Dem74a] that give a filtration of irreducible modules with respect to the Weyl group; and for DD a Rothe diagram, the module 𝒮Dflag\mathcal{S}^{\mathrm{flag}}_{D} coincides with the Schubert modules introduced by Kraskiewicz and Pragacz [KP87, KP04] whose characters are Schubert polynomials of Lascoux and Schützenberger [LS82] that compute intersection multiplicities for the flag manifold.

In what follows, we study these modules through their characters, to wit the following results are useful.

The weight of a filling TT is the weak composition 𝐰𝐭(T)\mathbf{wt}(T) whose iith part is the number of entries of TT with label ii. Given 𝐚\mathbf{a}, let x𝐚=x1a1xnanx^{\mathbf{a}}=x_{1}^{a_{1}}\cdots x_{n}^{a_{n}}.

Lemma 2.4.

For a flagged filling TT of DD, ΔT(modI)\Delta_{T}\pmod{I} is an eigenvector with eigenvalue x1𝐰𝐭(T)1xn𝐰𝐭(T)nx_{1}^{\mathbf{wt}(T)_{1}}\cdots x_{n}^{\mathbf{wt}(T)_{n}} under the action of X=diag(x1,,xn)X=\mathrm{diag}(x_{1},\ldots,x_{n}). In particular, the monomial x𝐰𝐭(T)x^{\mathbf{wt}(T)} appears with positive multiplicity in char(𝒮Dflag)\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D}).

Proof.

Since each entry in T(j)T^{(j)} is no greater than the corresponding entry in D(j)D^{(j)}, the diagonal of the matrix defining (T(j)D(j))(T^{(j)}\mid D^{(j)}) includes only indeterminates zk,z_{k,\ell} for which kk\leq\ell, ensuring that (T(j)D(j))I(T^{(j)}\mid D^{(j)})\notin I. Since II is prime we can be sure that ΔTI\Delta_{T}\notin I as well. Namely ΔT\Delta_{T} is not zero in 𝒮Dflag\mathcal{S}^{\mathrm{flag}}_{D}.

Note that Xzk,=xkzk,X\cdot z_{k,\ell}=x_{k}z_{k,\ell} for any k,k,\ell. The iith row vector of the matrix of (T(j)D(j))(T^{(j)}\mid D^{(j)}) contains only indeterminates zk,z_{k,\ell} with k=Ti(j)k=T^{(j)}_{i}. Hence X(T(j)D(j))X\cdot(T^{(j)}\mid D^{(j)}) is the result of multiplying each row ii in (T(j)D(j))(T^{(j)}\mid D^{(j)}) by xTi(j)x_{T^{(j)}_{i}}. Multi-linearity of the determinant yields X(T(j)D(j))=x𝐰𝐭(T(j))(T(j)D(j))X\cdot(T^{(j)}\mid D^{(j)})=x^{\mathbf{wt}(T^{(j)})}(T^{(j)}\mid D^{(j)}). Therefore,

XΔT=jx𝐰𝐭(T(j))(T(j)D(j))=x𝐰𝐭(T)j(T(j)D(j))=x𝐰𝐭(T)ΔT.X\cdot\Delta_{T}=\prod_{j}x^{\mathbf{wt}(T^{(j)})}(T^{(j)}\mid D^{(j)})=x^{\mathbf{wt}(T)}\prod_{j}(T^{(j)}\mid D^{(j)})=x^{\mathbf{wt}(T)}\Delta_{T}.

Take a set of flagged fillings which indexes a basis for 𝒮Dflag\mathcal{S}^{\mathrm{flag}}_{D} in the natural way. The basis is in fact an eigenbasis for the action of a diagonal matrix and all eigenvalues are positive monomials. Since x𝐰𝐭(T)x^{\mathbf{wt}(T)} is an eigenvalue, the result follows. ∎

Th following is used to determine when the character of a flagged Schur module differs from the Kohnert polynomial (defined below). Given position integers r<sr<s, let αr,s\alpha_{r,s} be the weak composition with rrth entry 11, ssth entry 1-1, and all others 0.

Proposition 2.5.

Let DD be a diagram and CC a set of column indices in which row ss contains a cell but row r<sr<s does not. Then x𝐰𝐭(D)+|C|αr,sx^{\mathbf{wt}(D)+|C|\alpha_{r,s}} occurs in the monomial expansion of char(𝒮Dflag)\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D}).

Proof.

We will define a flagged filling TT on DD. For jCj\notin C we simply let T(j)=D(j)T^{(j)}=D^{(j)}. Otherwise, D(j)=(a1,,am)D^{(j)}=(a_{1},\ldots,a_{m}) contains the entry ss but not rr. Say kk is the least index so that ak>ra_{k}>r and a=sa_{\ell}=s. Then define

T(j)=(,ak1,r,ak,ak+1,,a1,a+1,).T^{(j)}=(\ldots,a_{k-1},r,a_{k},a_{k+1},\ldots,a_{\ell-1},a_{\ell+1},\ldots).

That is, the kkth entry becomes rr and entries of index ii with k<ik<i\leq\ell become ai1a_{i-1} with all other entries the same as in D(j)D^{(j)}. The second case is vacuous if k=k=\ell.

Since the entries in TT are no greater than the corresponding entries in DD, TT is indeed a flagged filling. It is clear to see that 𝐰𝐭(T(j))=𝐰𝐭(D(j))+αr,s\mathbf{wt}(T^{(j)})=\mathbf{wt}(D^{(j)})+\alpha_{r,s} if jCj\in C, and 𝐰𝐭(T(j))=𝐰𝐭(D(j))\mathbf{wt}(T^{(j)})=\mathbf{wt}(D^{(j)}) otherwise. Therefore 𝐰𝐭(T)=𝐰𝐭(D)+|C|αr,s\mathbf{wt}(T)=\mathbf{wt}(D)+|C|\alpha_{r,s}. The proof is completed by Lemma 2.4. ∎

2.2. Demazure modules and characters

Each irreducible GLn\mathrm{GL}_{n}-module 𝒮λ\mathcal{S}_{\lambda} decomposes into weight spaces as 𝒮λ=𝐚𝒮λ𝐚\mathcal{S}_{\lambda}=\bigoplus_{\mathbf{a}}\mathcal{S}_{\lambda}^{\mathbf{a}}. Demazure [Dem74a] considered the BB-action on the extremal weight spaces of SλS_{\lambda}, those whose weak composition weight 𝐚\mathbf{a} is a rearrangement of the highest weight λ\lambda. The extremal weights are naturally indexed by the pair (λ,w)(\lambda,w), where λ\lambda is the partition weight and ww is the minimum length permutation that rearranges λ\lambda to 𝐚\mathbf{a}.

Definition 2.6 ([Dem74a]).

For a partition λ\lambda and a permutation ww, the Demazure module 𝒮λw\mathcal{S}_{\lambda}^{w} is the BB-submodule of 𝒮λ\mathcal{S}_{\lambda} generated by the weight space 𝒮λwλ\mathcal{S}_{\lambda}^{w\cdot\lambda}.

At the one extreme, the Demazure module 𝒮λid\mathcal{S}_{\lambda}^{\mathrm{id}} for the identity permutation is the one-dimensional subspace of 𝒮λ\mathcal{S}_{\lambda} containing the highest weight element. At the other extreme, the Demazure module 𝒮λw0\mathcal{S}_{\lambda}^{w_{0}} for the long element of 𝒮n\mathcal{S}_{n} is the full module 𝒮λ\mathcal{S}_{\lambda}. In general, the Demazure modules give a filtration from the highest weight element, namely 𝒮λu𝒮λw\mathcal{S}_{\lambda}^{u}\subset\mathcal{S}_{\lambda}^{w} whenever uwu\prec w in Bruhat order.

The characters of Demazure modules can be computed by degree-preserving divided difference operators [Dem74b], as well as myriad combinatorial models.

For a positive integer ii, the divided difference operator i\partial_{i} is the linear operator that acts on polynomials f[x1,x2,]f\in\mathbb{Z}[x_{1},x_{2},\ldots] by

(2.2) i(f)=fsifxixi+1,\partial_{i}(f)=\frac{f-s_{i}\cdot f}{x_{i}-x_{i+1}},

where si𝒮s_{i}\in\mathcal{S}_{\infty} is the simple transposition that exchanges xix_{i} and xi+1x_{i+1}. Fulton [Ful92] connected the divided difference operators with modern intersection theory, providing a direct geometric context for Schubert polynomials [LS82]. An isobaric variation, sometimes called the Demazure operator, is defined by

(2.3) πi(f)=i(xif).\pi_{i}(f)=\partial_{i}(x_{i}f).

Given a permutation ww, we may define

w\displaystyle\partial_{w} =\displaystyle= siksi1,\displaystyle\partial_{s_{i_{k}}}\cdots\partial_{s_{i_{1}}},
πw\displaystyle\pi_{w} =\displaystyle= πsikπsi1,\displaystyle\pi_{s_{i_{k}}}\cdots\pi_{s_{i_{1}}},

for any expression siksi1=ws_{i_{k}}\cdots s_{i_{1}}=w with kk minimal. Such an expression is called a reduced expression for ww. Both i\partial_{i} and πi\pi_{i} satisfy the braid relations, and so are independent of the choice of reduced expression for ww. In fact, the expression for πw\pi_{w} need not be reduced, since πi(f)=f\pi_{i}(f)=f whenever sif=fs_{i}\cdot f=f.

Theorem 2.7 ([Dem74a]).

The character of the Demazure module 𝒮λw\mathcal{S}_{\lambda}^{w} is

(2.4) char(𝒮λw)=πw(x1λ1xnλn).\mathrm{char}(\mathcal{S}_{\lambda}^{w})=\pi_{w}(x_{1}^{\lambda_{1}}\cdots x_{n}^{\lambda_{n}}).

In particular, when siwws_{i}w\prec w in Bruhat order, we have the following identity,

(2.5) char(𝒮λw)=πi(char(𝒮λsiw)).\mathrm{char}(\mathcal{S}_{\lambda}^{w})=\pi_{i}\left(\mathrm{char}(\mathcal{S}_{\lambda}^{s_{i}w})\right).

For 𝔻(𝐚)\mathbb{D}(\mathbf{a}) the key (left-justified) diagram of a composition 𝐚=wλ\mathbf{a}=w\cdot\lambda, we have

(2.6) char(𝒮𝔻(𝐚)flag)=char(𝒮λw).\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{\mathbb{D}(\mathbf{a})})=\mathrm{char}(\mathcal{S}_{\lambda}^{w}).

In this sense, the flagged Schur modules generalize Demazure characters.

Both key diagrams indexing Demazure modules and Rothe diagrams indexing Kraskiewicz–Pragacz modules exhibit the following property.

Definition 2.8.

A diagram DD is northwest if whenever (j,k),(i,l)D(j,k),(i,l)\in D with i<ji<j and k<lk<l, then (i,k)D(i,k)\in D.

Northwest in this context is equivalent to southwest as used by Assaf and Searles [AS19, Ass20b] for Kohnert polynomials.

Magyar [Mag98b] gave a recurrence for computing characters of flagged Schur modules for %-avoiding shapes (see Definition 4.13). To state the recurrence, let CkC_{k} denote the diagram with cells in rows 1,2,,k1,2,\ldots,k of the first column. Given a diagram DD, let srDs_{r}D denote the diagram obtained from DD by permuting the cells in rows r,r+1r,r+1. Restricting Magyar’s result to northwest shapes gives the following.

Theorem 2.9.

The characters of the flagged Schur modules of northwest shapes satisfy the following recurrence:

  • (M1)

    char(𝒮flag)=1\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{\varnothing})=1;

  • (M2)

    if the first column of DD is exactly CkC_{k}, then

    (2.7) char(𝒮Dflag)=x1x2xkchar(𝒮DCkflag);\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D})=x_{1}x_{2}\cdots x_{k}\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D-C_{k}});
  • (M3)

    if every cell in row rr has a cell in row r+1r+1 in the same column, then

    (2.8) char(𝒮Dflag)=πr(char(𝒮srDflag)).\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D})=\pi_{r}\left(\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{s_{r}D})\right).
T5T4T3T2T1T0\begin{array}[]{cccccc}\vline\vtop{ \halign{&\circify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{\ }$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\crcr}}&\varnothing\\ T_{5}&T_{4}&T_{3}&T_{2}&T_{1}&T_{0}\end{array}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}
Figure 3. Applying Magyar’s recurrence to a northwest diagram (left) to compute the character of the flagged Schur module.

For example, Magyar’s recurrence allows us to compute the character for the flagged Schur module indexed by the leftmost diagram T5T_{5} in Figure 3 as follows:

char(𝒮T5flag)=x1x2char(𝒮T4flag)(M2)=x1x2π1(char(𝒮T3flag))(M3)=x1x2π1(π2(char(𝒮T2flag)))(M3)=x1x2π1(π2(x1x2char(𝒮T1flag))))(M2)=x1x2π1(π2(x1x2(x1char(𝒮T0flag)))))(M2)=x1x2π1(π2(x12x2(1)))(M1)=x1x2π1(x12x2+x12x3)=x1x2(x12x2+x12x3+x1x22+x1x2x3+x22x3)=x13x22+x13x2x3+x12x23+x12x22x3+x1x23x3\begin{array}[]{rll}\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{T_{5}})=&x_{1}x_{2}\cdot\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{T_{4}})&\text{(M2)}\\ =&x_{1}x_{2}\cdot\pi_{1}(\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{T_{3}}))&\text{(M3)}\\ =&x_{1}x_{2}\cdot\pi_{1}(\pi_{2}(\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{T_{2}})))&\text{(M3)}\\ =&x_{1}x_{2}\cdot\pi_{1}(\pi_{2}(x_{1}x_{2}\cdot\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{T_{1}}))))&\text{(M2)}\\ =&x_{1}x_{2}\cdot\pi_{1}(\pi_{2}(x_{1}x_{2}\cdot(x_{1}\cdot\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{T_{0}})))))&\text{(M2)}\\ =&x_{1}x_{2}\cdot\pi_{1}(\pi_{2}(x_{1}^{2}x_{2}\cdot(1)))&\text{(M1)}\\ =&x_{1}x_{2}\cdot\pi_{1}(x_{1}^{2}x_{2}+x_{1}^{2}x_{3})&\\ =&x_{1}x_{2}\cdot(x_{1}^{2}x_{2}+x_{1}^{2}x_{3}+x_{1}x_{2}^{2}+x_{1}x_{2}x_{3}+x_{2}^{2}x_{3})&\\ =&x_{1}^{3}x_{2}^{2}+x_{1}^{3}x_{2}x_{3}+x_{1}^{2}x_{2}^{3}+x_{1}^{2}x_{2}^{2}x_{3}+x_{1}x_{2}^{3}x_{3}&\end{array}

Two Demazure modules 𝒮μu\mathcal{S}_{\mu}^{u} and 𝒮νv\mathcal{S}_{\nu}^{v} correspond precisely when uμ=vνu\cdot\mu=v\cdot\nu. While this implies μ=ν\mu=\nu, the permutations u,vu,v can differ. Therefore the more natural indexing set for Demazure characters is obtained by specifying the weak composition given by the permutation acting on the partition. Define

(2.9) κ𝐚=char(𝒮λw),\kappa_{\mathbf{a}}=\mathrm{char}(\mathcal{S}_{\lambda}^{w}),

where ww sorts the weak composition 𝐚\mathbf{a} to the weakly decreasing partition λ\lambda.

Perhaps unsurprising when comparing (2.5) and (2.8), Reiner and Shimozono [RS98] use Magyar’s recurrence for the character of flagged Schur modules [Mag98b] to prove the characters of flagged Schur modules decompose as a nonnegative sum of Demazure characters; see [RS98] for precise definitions.

Theorem 2.10 ([RS98]).

For DD a northwest diagram, we have

char(𝒮Dflag)=𝐚c𝐚Dκ𝐚,\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D})=\sum_{\mathbf{a}}c^{D}_{\mathbf{a}}\kappa_{\mathbf{a}},

where c𝐚Dc^{D}_{\mathbf{a}} is the number of DD-peelable tableaux whose left-nil key is 𝐚\mathbf{a}.

One consequence of our main result is a new proof of this positivity and a new combinatorial interpretation for the coefficients.

2.3. Kohnert polynomials

Kohnert gave a combinatorial model for Demazure characters [Koh91] in terms of the following operation on diagrams.

Definition 2.11 ([Koh91]).

A Kohnert move on a diagram selects the rightmost cell of a given row and moves the cell up, staying within its column, to the first available position above, if it exists, jumping over other cells in its way as needed.

Given a diagram DD, let KD(D)\mathrm{KD}(D) denote the set of diagrams that can be obtained by some sequence of Kohnert moves on DD. For example, Fig. 4 shows the Kohnert diagrams for the bottom diagram, where an edge from SS up to TT indicates TT can be obtained from SS by a single Kohnert move.

{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
Figure 4. The poset of Kohnert diagrams for the bottom diagram.
Theorem 2.12 ([Koh91]).

The Demazure character κ𝐚\kappa_{\mathbf{a}} is

κ𝐚=TKD(𝔻(𝐚))x1𝐰𝐭(T)1xn𝐰𝐭(T)n,\kappa_{\mathbf{a}}=\sum_{T\in\mathrm{KD}(\mathbb{D}(\mathbf{a}))}x_{1}^{\mathbf{wt}(T)_{1}}\cdots x_{n}^{\mathbf{wt}(T)_{n}},

where the weight of a diagram DD, denoted by 𝐰𝐭(D)\mathbf{wt}(D), is the weak composition whose iith part is the number of cells of DD in row ii.

Assaf and Searles define the Kohnert polynomial of any diagram as follows.

Definition 2.13 ([AS19]).

The Kohnert polynomial for a diagram DD is

𝔎D=TKD(D)x1𝐰𝐭(T)1xn𝐰𝐭(T)n.\mathfrak{K}_{D}=\sum_{T\in\mathrm{KD}(D)}x_{1}^{\mathbf{wt}(T)_{1}}\cdots x_{n}^{\mathbf{wt}(T)_{n}}.

By convention, set 𝔎=1\mathfrak{K}_{\varnothing}=1 for the empty diagram.

Assaf and Searles conjectured [AS19] and Assaf proved [Ass20b] that for DD northwest, the Kohnert polynomial expands nonnegatively into Demazure characters.

Theorem 2.14 ([Ass20b]).

For DD northwest, we have

𝔎D=𝐚c𝐚Dκa,\mathfrak{K}_{D}=\sum_{\mathbf{a}}c^{D}_{\mathbf{a}}\kappa_{a},

where c𝐚Dc^{D}_{\mathbf{a}} is the number of Yamanouchi Kohnert diagrams for DD of weight 𝐚\mathbf{a}.

For the example, the Kohnert polynomial expands into Demazure characters as

𝔎D=κ(0,1,2,1)+κ(0,2,2,0).\mathfrak{K}_{D}=\kappa_{(0,1,2,1)}+\kappa_{(0,2,2,0)}.

Comparing Theorem 2.10 with Theorem 2.14, one begins to suspect the following.

Conjecture 2.15 ([AS19]).

For DD a northwest diagram, we have

(2.10) char(𝒮Dflag)=𝔎D.\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D})=\mathfrak{K}_{D}.

We prove Conjecture 2.15 by showing Kohnert polynomials of northwest diagrams satisfy the recurrence in Theorem 2.9.

By definition, we have 𝔎=1\mathfrak{K}_{\varnothing}=1, establishing Theorem 2.9(M1). It is straightforward to establish Theorem 2.9(M2).

Lemma 2.16.

Let DD be a northwest diagram such that the first column is exactly CkC_{k}. Then DCkD-C_{k} is also northwest, and we have

(2.11) 𝔎D=x1x2xk𝔎DCk.\mathfrak{K}_{D}=x_{1}x_{2}\cdots x_{k}\mathfrak{K}_{D-C_{k}}.
Proof.

As Kohnert moves preserve the columns of cells and no moves are possible in column 11 of DD, all diagrams in KD(D)\mathrm{KD}(D) must coincide in column 11 with cells in rows 1,,k1,\ldots,k. In particular, since column 11 is the leftmost column and admits no Kohnert moves, there is a poset isomorphism between KD(D)\mathrm{KD}(D) and KD(DCk)\mathrm{KD}(D-C_{k}) obtained by deleting all cells in column 11. Since those cells contribute x1x2xkx_{1}x_{2}\cdots x_{k} to the weight, the result follows. ∎

We next consider DD and siDs_{i}D when row ii is a subset of row i+1i+1, meaning the set of occupied columns in row ii is a subset of the occupied columns of row i+1i+1. These conditions combined imply all cells in row i+1i+1 without cells above them in row ii lie to the right of all cells in row ii. Otherwise, the cell in row i+1i+1 without a cell above it in row ii and any cell to the right in row ii violate the northwest condition. This also implies siDs_{i}D is northwest. The only violation must take place in rows ii and i+1i+1, but we only move cells in row i+1i+1 to row ii where all cells to the left in row i+1i+1 have a cell in row ii above them.

Lemma 2.17.

If DD is a northwest diagram and row ii is contained in row i+1i+1, then siDs_{i}D is also northwest and siDKD(D)s_{i}D\in\mathrm{KD}(D). In particular, KD(siD)KD(D)\mathrm{KD}(s_{i}D)\subseteq\mathrm{KD}(D).

Proof.

Let cc be the rightmost occupied column in row ii of DD. Let mm be the number of cells in row i+1i+1 strictly to the right of column cc. By choice of cc, we may apply a sequence of mm Kohnert moves to row i+1i+1 of DD, resulting in all cells strictly to right of column cc moving from row i+1i+1 to row ii. Since row ii is a subset of row i+1i+1, any column weakly left of column cc either has no cells in rows i,i+1i,i+1 or cells in both rows i,i+1i,i+1. Thus this sequence of Kohnert moves yields siDs_{i}D. ∎

Since πi\pi_{i} acts on a polynomial by adding additional monomials, this makes Theorem 2.9(M3) plausible. However, in order to understand precisely how πi\pi_{i} acts on Kohnert polynomials, we must rely on Demazure crystals.

3. Crystal graphs

In order to understand the action of the degree-preserving divided difference operator on Kohnert polynomials, we shift our paradigm to Demazure operators on Demazure subsets of highest weight crystals.

3.1. Tableaux crystals

A crystal graph [Kas90] is a combinatorial model for a highest weight module, consisting of a vertex set \mathcal{B}, corresponding to the crystal base (see also the canonical basis [Lus90]), and directed, colored edges, corresponding to deformations of the Chevalley generators. For a highest weight λ\lambda for GLn\mathrm{GL}_{n}, the crystal base for 𝒮λ\mathcal{S}_{\lambda} is naturally indexed by SSYTn(λ)\mathrm{SSYT}_{n}(\lambda), the semistandard Young tableaux of shape λ\lambda with entries in {1,2,,n}\{1,2,\ldots,n\}. We adopt the French (coordinate) convention for SSYT\mathrm{SSYT} in which entries weakly increase left to right within rows and strictly increase bottom to top within columns. Kashiwara and Nakashima [KN94] and Littelmann [Lit95] defined the crystal edges on tableaux as follows.

Definition 3.1.

For TSSYTn(λ)T\in\mathrm{SSYT}_{n}(\lambda) and 1i<n1\leq i<n, we i-pair the cells of TT with entries ii or i+1i+1 iteratively by ii-pairing an unpaired i+1i+1 with an unpaired ii weakly to its right whenever all entries ii or i+1i+1 lying between them are already ii-paired.

The raising and lowering operators on crystals are maps ei,fi:{0}e_{i},f_{i}:\mathcal{B}\rightarrow\mathcal{B}\cup\{0\}.

Definition 3.2.

For 1i<n1\leq i<n, the crystal raising operator eie_{i} acts on TSSYTn(λ)T\in\mathrm{SSYT}_{n}(\lambda) as follows:

  • if all entries i+1i+1 of TT are ii-paired, then ei(T)=0e_{i}(T)=0;

  • otherwise, eie_{i} changes the leftmost unpaired i+1i+1 to ii.

Definition 3.3.

For 1i<n1\leq i<n, the crystal lowering operator fif_{i} acts on TSSYTn(λ)T\in\mathrm{SSYT}_{n}(\lambda) as follows:

  • if all entries ii of TT are ii-paired, then fi(T)=0f_{i}(T)=0;

  • otherwise, fif_{i} changes the rightmost unpaired ii to i+1i+1.

We draw a crystal graph with an ii-colored edge from bb to bb^{\prime} whenever b=fi(b)b^{\prime}=f_{i}(b), omitting edges to 0. For examples, see Fig. 5.

3 2 1 1
3 2 1 2
4 2 1 1
3 2 1 3
4 2 1 2
4 3 1 1
3 2 1 4
4 2 1 3
4 3 1 2
4 3 2 2
4 3 1 3
4 2 1 4
4 3 2 3
4 3 1 4
4 3 2 4
111111111111222222222222333333333333
3 3 2 2
2 3 1 2
3 3 1 2
3 4 2 2
3 4 2 3
2 2 1 1
2 3 1 1
3 3 1 1
2 4 1 2
2 4 1 3
3 4 1 2
3 4 1 3
4 4 2 2
4 4 2 3
4 4 3 3
2 4 1 1
3 4 1 1
4 4 1 2
4 4 1 3
4 4 1 1
111111111111111111112222222222222222222233333333333333333333
Figure 5. The tableaux crystals for GL4\mathrm{GL}_{4} with highest weights (2,1,1,0)(2,1,1,0) and (2,2,0,0)(2,2,0,0).

The crystal base is endowed with a map, 𝐰𝐭:n\mathbf{wt}:\mathcal{B}\rightarrow\mathbb{Z}^{n}, to the weight lattice. Using this, we define the character of a crystal \mathcal{B} by

(3.1) char()=bx1𝐰𝐭(b)1xn𝐰𝐭(b)n.\mathrm{char}(\mathcal{B})=\sum_{b\in\mathcal{B}}x_{1}^{\mathbf{wt}(b)_{1}}\cdots x_{n}^{\mathbf{wt}(b)_{n}}.

Thus if \mathcal{B} is the crystal for a module VV, then we have char()=char(V)\mathrm{char}(\mathcal{B})=\mathrm{char}(V). In particular, for λ\mathcal{B}_{\lambda} the crystal on SSYTn(λ)\mathrm{SSYT}_{n}(\lambda), we have

(3.2) char(λ)=char(𝒮λ)=sλ(x1,,xn),\mathrm{char}(\mathcal{B}_{\lambda})=\mathrm{char}(\mathcal{S}_{\lambda})=s_{\lambda}(x_{1},\ldots,x_{n}),

where the latter is the Schur polynomial indexed by λ\lambda in nn variables.

Definition 3.4.

An element uu\in\mathcal{B} of a highest weight crystal \mathcal{B} is a highest weight element if ei(u)=0e_{i}(u)=0 for all 1i<n1\leq i<n.

Each connected crystal λ\mathcal{B}_{\lambda} has a unique highest weight element bb, and we have 𝐰𝐭(b)=λ\mathbf{wt}(b)=\lambda. Part of the beauty of highest weight elements, and indeed of crystals, lies in the following decomposition combining (3.1) and (3.2),

(3.3) char()=uei(u)=0is𝐰𝐭(u)(x1,,xn).\mathrm{char}(\mathcal{B})=\sum_{\begin{subarray}{c}u\in\mathcal{B}\\ e_{i}(u)=0\forall i\end{subarray}}s_{\mathbf{wt}(u)}(x_{1},\ldots,x_{n}).

3.2. Demazure crystals

Littelmann [Lit95] conjectured a crystal structure for Demazure modules as certain truncations of highest weight crystals. Kashiwara [Kas93] proved the result, giving a new proof of the Demazure character formula.

Definition 3.5.

Given a subset XX of a highest weight crystal \mathcal{B} and an index 1i<n1\leq i<n, the Demazure operator 𝔇i\mathfrak{D}_{i} is given by

(3.4) 𝔇i(X)={beik(b)X for some k0}.\mathfrak{D}_{i}(X)=\{b\in\mathcal{B}\mid e_{i}^{k}(b)\in X\text{ for some }k\geq 0\}.

These operators satisfy the braid relations, and so we may define

(3.5) 𝔇w=𝔇im𝔇i1\mathfrak{D}_{w}=\mathfrak{D}_{i_{m}}\cdots\mathfrak{D}_{i_{1}}

for any expression simsi1s_{i_{m}}\cdots s_{i_{1}} for the permutation ww. As with πw\pi_{w}, the indexing expression for 𝔇w\mathfrak{D}_{w} need not be reduced, since 𝔇i2=𝔇i\mathfrak{D}_{i}^{2}=\mathfrak{D}_{i}.

Definition 3.6 ([Lit95]).

Given a highest weight crystal (λ)\mathcal{B}(\lambda) and a permutation ww, the Demazure crystal λw\mathcal{B}^{w}_{\lambda} is given by

(3.6) λw=𝔇w({uλ}),\mathcal{B}^{w}_{\lambda}=\mathfrak{D}_{w}(\{u_{\lambda}\}),

where uλu_{\lambda} is the highest weight element of λ\mathcal{B}_{\lambda}.

(2,1,1,0)id\mathcal{B}^{\mathrm{id}}_{(2,1,1,0)}
3 2 1 1
(2,1,1,0)s1\mathcal{B}^{s_{1}}_{(2,1,1,0)}
3 2 1 1
3 2 1 2
11(2,1,1,0)s3s1\mathcal{B}^{s_{3}s_{1}}_{(2,1,1,0)}
3 2 1 1
3 2 1 2
4 2 1 1
4 2 1 2
11113333(2,1,1,0)s2s3s1\mathcal{B}^{s_{2}s_{3}s_{1}}_{(2,1,1,0)}
3 2 1 1
3 2 1 2
4 2 1 1
3 2 1 3
4 2 1 2
4 3 1 1
4 2 1 3
4 3 1 3
1111222222223333(2,1,1,0)s1s2s3s1\mathcal{B}^{s_{1}s_{2}s_{3}s_{1}}_{(2,1,1,0)}
3 2 1 1
3 2 1 2
4 2 1 1
3 2 1 3
4 2 1 2
4 3 1 1
4 2 1 3
4 3 1 2
4 3 2 2
4 3 1 3
4 3 2 3
111111111122222222223333
Figure 6. The Demazure crystals (2,1,1,0)w\mathcal{B}^{w}_{(2,1,1,0)} for the permutations w=id,s1,s3s1,s2s3s1w=\mathrm{id},s_{1},s_{3}s_{1},s_{2}s_{3}s_{1}, and s1s2s3s1s_{1}s_{2}s_{3}s_{1}.

For example, Fig. 6 constructs the Demazure crystal (2,1,1,0)4213\mathcal{B}^{4213}_{(2,1,1,0)} using the expression 4213=s1s2s3s14213=s_{1}s_{2}s_{3}s_{1} together with the left hand crystal in Fig. 5. Beginning with the topmost tableau, traverse the single f1f_{1} edge, followed by the two f3f_{3} edges (taking the induced subgraph gives us an additional f1f_{1} edge as well), followed by three vertical f2f_{2} paths (the outer two of length 11 and the middle of length 22), and finally take two f1f_{1} paths (and the one induced f2f_{2} edge).

Just as Demazure crystals combinatorialize Demazure characters, the Demazure operator combinatorializes the isobaric divided difference operator.

Proposition 3.7.

Let XX be a Demazure subset of a highest weight crystal \mathcal{B}. Then on the level of characters, we have

(3.7) char(𝔇i(X))=πi(char(X)).\mathrm{char}(\mathfrak{D}_{i}(X))=\pi_{i}(\mathrm{char}(X)).
Proof.

For a subset XX\subseteq\mathcal{B} to be a Demazure crystal, we must have a decomposition

X\displaystyle X \displaystyle\cong λ(1)w(1)λ(k)w(k)\displaystyle\mathcal{B}^{w^{(1)}}_{\lambda^{(1)}}\sqcup\cdots\sqcup\mathcal{B}^{w^{(k)}}_{\lambda^{(k)}}
char(X)\displaystyle\mathrm{char}(X) =\displaystyle= char(λ(1)w(1))++char(λ(k)w(k))\displaystyle\mathrm{char}(\mathcal{B}^{w^{(1)}}_{\lambda^{(1)}})+\cdots+\mathrm{char}(\mathcal{B}^{w^{(k)}}_{\lambda^{(k)}})

for some partitions λ(1),,λ(k)\lambda^{(1)},\ldots,\lambda^{(k)} and permutations w(1),,w(k)w^{(1)},\ldots,w^{(k)}, where kk is the number of connected components of the crystal. The Demazure operator 𝔇i\mathfrak{D}_{i} acts on each connected component separately, and so factors through the decomposition. Thus it suffices to show for λ\lambda a partition and ww a permutation, we have

char(𝔇i(λw))=πi(char(λw)).\mathrm{char}(\mathfrak{D}_{i}(\mathcal{B}^{w}_{\lambda}))=\pi_{i}(\mathrm{char}(\mathcal{B}^{w}_{\lambda})).

If wsiww\prec s_{i}\cdot w in Bruhat order, then by (3.6), we have 𝔇i(λw)=siw(λ)\mathfrak{D}_{i}(\mathcal{B}^{w}_{\lambda})=\mathcal{B}_{s_{i}w}(\lambda), and so by (2.5), we have

char(𝔇i(λw))=char(λsiw)=πi(char(λw)).\mathrm{char}(\mathfrak{D}_{i}(\mathcal{B}^{w}_{\lambda}))=\mathrm{char}(\mathcal{B}^{s_{i}w}_{\lambda})=\pi_{i}(\mathrm{char}(\mathcal{B}^{w}_{\lambda})).

On the other hand, if siwws_{i}\cdot w\prec w in Bruhat order, then ww has a reduced expression of the form sisimsi1s_{i}s_{i_{m}}\cdots s_{i_{1}}. Thus by (3.6), we have λw=𝔇i(λsiw)\mathcal{B}^{w}_{\lambda}=\mathfrak{D}_{i}(\mathcal{B}^{s_{i}w}_{\lambda}), and so

𝔇i(λw)=𝔇i(𝔇i(λsiw))=𝔇i(λsiw)=λw.\mathfrak{D}_{i}(\mathcal{B}^{w}_{\lambda})=\mathfrak{D}_{i}(\mathfrak{D}_{i}(\mathcal{B}^{s_{i}w}_{\lambda}))=\mathfrak{D}_{i}(\mathcal{B}^{s_{i}w}_{\lambda})=\mathcal{B}^{w}_{\lambda}.

In this case, by symmetry of crystal strings, we also have sichar(λw)=char(λw)s_{i}\cdot\mathrm{char}(\mathcal{B}^{w}_{\lambda})=\mathrm{char}(\mathcal{B}^{w}_{\lambda}), and so πi(char(λw))=char(λw)\pi_{i}(\mathrm{char}(\mathcal{B}^{w}_{\lambda}))=\mathrm{char}(\mathcal{B}^{w}_{\lambda}). Thus in this case, we have

char(𝔇i(λw))=char(λw)=πi(char(λw)).\mathrm{char}(\mathfrak{D}_{i}(\mathcal{B}^{w}_{\lambda}))=\mathrm{char}(\mathcal{B}^{w}_{\lambda})=\pi_{i}(\mathrm{char}(\mathcal{B}^{w}_{\lambda})).

The result follows. ∎

3.3. Kohnert crystals

Assaf [Ass20b] defined a crystal structure on diagrams that intertwines the crystal operators on tableaux via the injective, weight-reversing map from KD(𝐚)\mathrm{KD}(\mathbf{a}) to SSYTn(sort(𝐚))\mathrm{SSYT}_{n}(\mathrm{sort}(\mathbf{a})) defined by Assaf and Searles [AS18, Def 4.5].

Definition 3.8.

[Ass20b] For TT a diagram and 1i<n1\leq i<n, we i-pair the cells of TT in rows i,i+1i,i+1 iteratively by ii-pairing an unpaired cell in row i+1i+1 with an unpaired cell in row ii weakly to its left whenever all cell in rows ii or i+1i+1 lying between them are already ii-paired.

Definition 3.9.

[Ass20b] For 1i<n1\leq i<n, the Kohnert raising operator eie_{i} acts on a diagram TT as follows:

  • if all cells in row i+1i+1 of TT are ii-paired, then ei(T)=0e_{i}(T)=0;

  • otherwise, eie_{i} moves the rightmost unpaired cell in row i+1i+1 to row ii.

Given the asymmetry between raising and lowering operators for Demazure crystals, we define Kohnert crystals using the former. For example, Fig. 7 shows the Kohnert crystal structure on the set of Kohnert diagrams generated in Fig. 4.

Definition 3.10.

[Ass20b] For 1i<n1\leq i<n, the Kohnert lowering operator fif_{i} acts on a diagram TT as follows:

  • if all cells in row ii of TT are ii-paired, then fi(T)=0f_{i}(T)=0;

  • otherwise, eie_{i} moves the leftmost unpaired cell in row ii to row i+1i+1.

{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
111111111122222222223333
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
{}_{~{}} {}_{~{}} {}_{~{}} {}_{~{}}
111111222222
Figure 7. The Kohnert crystal on Kohnert diagrams for the bottom diagram, which is northwest.

Assaf [Ass20b, Thm 4.1.1] proves the Kohnert raising operators are closed within the set of Kohnert diagrams, provided the initial diagram is northwest.

Theorem 3.11.

[Ass20b] For DD a northwest diagram, if TKD(D)T\in\mathrm{KD}(D) and ei(T)0e_{i}(T)\neq 0, then ei(T)KD(D)e_{i}(T)\in\mathrm{KD}(D).

We remark the analog of Theorem 3.11 for Kohnert lowering operators is false in general, though true under certain circumstances considered in Lemma 3.17 below. However, for DD northwest, Theorem 3.11 makes the following well-defined.

Definition 3.12.

[Ass20b] For DD a northwest diagram, the Kohnert crystal on DD is the set KD(D)\mathrm{KD}(D) together with the Kohnert raising operators.

For example Fig. 7 shows the Kohnert crystal for the bottom most diagram. Notice there are two connected components, and the leftmost corresponds precisely with the rightmost Demazure crystal in Fig. 6. One can easily verify the rightmost component is also a Demazure crystal, and Theorem 5.3.4 of [Ass20b] proves the Kohnert crystal for northwest diagrams is always a union of Demazure crystals.

Theorem 3.13 ([Ass20b]).

For DD a northwest diagram, the Kohnert crystal on KD(D)\mathrm{KD}(D) is a disjoint union of Demazure crystals. That is, there exist partitions λ(1),,λ(m)\lambda^{(1)},\ldots,\lambda^{(m)} and permutations w(1),,w(m)w^{(1)},\ldots,w^{(m)} such that

KD(D)λ(1)w(1)λ(m)w(m).\mathrm{KD}(D)\cong\mathcal{B}^{w^{(1)}}_{\lambda^{(1)}}\sqcup\cdots\sqcup\mathcal{B}^{w^{(m)}}_{\lambda^{(m)}}.

To establish Theorem 2.9(M3) and prove our main result, by Proposition 3.7, it is enough to show that for DD northwest with row rr a subset of row r+1r+1, we have

(3.8) KD(D)=𝔇r(KD(srD)).\mathrm{KD}(D)=\mathfrak{D}_{r}(\mathrm{KD}(s_{r}D)).

By Lemma 2.17, we have KD(srD)KD(D)\mathrm{KD}(s_{r}D)\subseteq\mathrm{KD}(D). To begin to relate KD(D)\mathrm{KD}(D) with 𝔇r(KD(srD))\mathfrak{D}_{r}(\mathrm{KD}(s_{r}D)), we have the following.

Lemma 3.14.

Let DD be a diagram, and rr a row index such that row rr is contained in row r+1r+1. Given TKD(D)T\in\mathrm{KD}(D), there exists SKD(srD)S\in\mathrm{KD}(s_{r}D) such that

  1. (1)

    SS and TT agree in all rows tr,r+1t\neq r,r+1;

  2. (2)

    if S,TS,T differ in some column cc at row rr or r+1r+1, then TT has a cell only in row r+1r+1 and SS has a cell only in row rr.

  3. (3)

    if, at rows r,r+1r,r+1, S,TS,T differ in column cc and agree in some column b<cb<c, and if, in column bb, row rr has a cell, so does row r+1r+1.

Proof.

We proceed by induction on the number of Kohnert moves used to obtain TT from DD. For the base case, we observe srDs_{r}D is obtained by applying raising operators ere_{r} to DD by the proof of Lemma 2.17, and so for T=DT=D we may take S=srDS=s_{r}D. Thus suppose for some TKD(D)T\in\mathrm{KD}(D), we have constructed SKD(srD)S\in\mathrm{KD}(s_{r}D) satisfying conditions (1)-(3). Suppose TT^{\prime} is obtained by a Kohnert move on TT, say moving a cell xx which lies in column cc. We will construct SS^{\prime} by a (possibly trivial) sequence of Kohnert moves on SS such that conditions (1)-(3) are satisfied for SS^{\prime} and TT^{\prime}.

Case A: xx not in rows r,r+1r,r+1.

  • Case A1: TT^{\prime} is obtained by moving xx between rows that lie either strictly above row rr or strictly below row r+1r+1.

    By condition (1), SS and TT agree in all rows tr,r+1t\neq r,r+1, so we can perform the same Kohnert move on SS to obtain SS^{\prime}. Since this Kohnert move does not move any cells in rows rr or r+1r+1, conditions (1)-(3) hold by induction.

  • Case A2: TT^{\prime} is obtained by moving xx from row s>r+1s>r+1 to row q<rq<r.

    In order to perform this Kohnert move, TT must have cells in rows rr and r+1r+1 of column cc. By condition (2) SS and TT must then agree in rows rr and r+1r+1 of column cc. Thus by condition (1) we can perform the same Kohnert move on SS to obtain SS^{\prime}, and conditions (1)-(3) once again hold by induction since this Kohnert move does affect any cells in rows rr or r+1r+1.

  • Case A3: TT^{\prime} is obtained by moving xx from row s>r+1s>r+1 to row r+1r+1.

    Since xx moves into row r+1r+1 from TT to TT^{\prime}, condition (2) implies that SS and TT agree in column cc; otherwise, TT would have a cell in row r+1r+1, column cc, which would block xx from moving into row r+1r+1. Then by condition (1) we can again perform the same Kohnert move on SS to obtain SS^{\prime}. In particular, SS^{\prime} and TT^{\prime} agree in column cc, so conditions (1) and (2) immediately follow by induction. Since SS^{\prime} and TT^{\prime} both have a cell in row r+1r+1, column cc, the implication of condition (3) is satisfied as well.

  • Case A4: TT^{\prime} is obtained by moving xx from row s>r+1s>r+1 to row rr.

    Here, SS and TT may not agree in column cc by condition (2). If this is the case, then in rows rr and r+1r+1 of column cc, TT has a cell only in row r+1r+1 while SS has a cell only in row rr. However, after moving xx, TT^{\prime} has cells in rows rr and r+1r+1 of column cc. Thus in SS, we can move xx up to row r+1r+1 so that SS^{\prime} and TT^{\prime} both have cells in rows rr and r+1r+1 of column cc.

    If, on the other hand, SS and TT do agree in column cc, then we can perform the same Kohnert move on SS which we performed on TT to obtain the same result: SS^{\prime} and TT^{\prime} both have cells in rows rr and r+1r+1 of column cc, and therefore the columns are identical in either case by condition (1). Conditions (1) and (2) again follow by induction, and condition (3) holds because SS^{\prime} and TT^{\prime} both have cells in rows rr and r+1r+1 of column cc.

Case B: xx in row r+1r+1.

  • Case B1: SS and TT agree in column cc.

    In this case we can perform the same Kohnert move on SS to obtain SS^{\prime}. Conditions (1) and (2) then hold by induction. For condition (3), notice that since xx is able to move out of row r+1r+1 from TT to TT^{\prime}, there can be no columns right of cc in which SS and TT differ; otherwise by condition (2) there would be a cell in row r+1r+1 of TT which blocks xx from moving. Thus condition (3) holds vacuously for every column weakly right of cc, and holds by induction for every column left of cc.

  • Case B2: SS and TT differ in column cc.

    By condition (2), TT has a cell only in row r+1r+1, while SS only has a cell in row rr, in column cc. In this case xx lies in row rr in TT^{\prime}, and we define S=SS^{\prime}=S so that SS and TT agree in column cc. Conditions (1) and (2) hold by induction. Condition (3) also holds by induction because, as we noted above, there can be no columns right of cc in which SS and TT differ.

Case C: xx in row rr. By condition (2), SS and TT must agree in column cc.

  • Case C1: SS and TT agree in all columns right of cc.

    In this case, we can perform the same Kohnert move on SS to obtain SS^{\prime} so that SS^{\prime} and TT^{\prime} agree in column cc. Then conditions (1) and (2) hold by induction. By assumption column cc is right of all columns in which SS and TT differ, so condition (3) also holds by induction.

  • Case C2: SS and TT differ in some column right of cc.

    Here SS and TT both have cells in row rr, column cc and there exists some column d>cd>c in which SS and TT differ. By condition (3), SS and TT must both have cells in rows rr and r+1r+1 of column cc. Furthermore TT has no cells in row rr right of column cc — otherwise xx is blocked from moving — and this implies that there is at most one cell in rows rr and r+1r+1 per column right of cc in SS. Indeed, for any column d>cd>c either

    1. (i)

      SS and TT differ in rows rr and r+1r+1 of column dd, and condition (2) implies that SS has a single cell in row rr, column dd, or

    2. (ii)

      SS and TT agree in rows rr and r+1r+1 of column dd, in which case SS has no cells in row rr, column dd, since TT does not either.

    We define SS^{\prime} as follows: first, move every cell in row r+1r+1 of SS which lies in a column strictly right of cc into row rr via a sequence of Kohnert moves to obtain an intermediate diagram S~\tilde{S}. Let yy be the cell in row r+1r+1, column cc of SS (which is in the same position in S~\tilde{S}). Then perform a Kohnert move on S~\tilde{S} by moving yy to obtain SS^{\prime}. By construction, yy lands in the same position in SS^{\prime} as xx lands in TT^{\prime}.

    Condition (1) holds as the only new cell introduced outside of rows rr and r+1r+1 lies in the same position in SS^{\prime} and TT^{\prime}. Condition (2) holds in all columns left of cc by induction, and we now show it holds in all columns weakly right of cc. In rows rr and r+1r+1 of column cc, TT^{\prime} has a cell only in row r+1r+1 and SS^{\prime} has a cell only in row rr, so condition (2) holds. For any column d>cd>c, we have two possibilities:

    1. (i)

      SS and TT differ in rows rr and r+1r+1. Then SS has a cell in row rr, column dd, and this cell is in the same place in SS^{\prime}. Since TT and TT^{\prime} agree right of column cc, condition (2) holds.

    2. (ii)

      SS and TT agree in rows rr and r+1r+1. Without loss of generality column dd is nonempty, so that SS and TT have a cell only in row r+1r+1 of column dd. Then in SS^{\prime} this cell is moved to row rr, column dd, while it stays fixed in TT^{\prime}. Therefore SS^{\prime} and TT^{\prime} differ in column dd in rows rr and r+1r+1; TT^{\prime} has a cell only in row r+1r+1 and SS^{\prime} has a cell only in row rr, so condition (2) is satisfied.

    We have just shown that SS^{\prime} and TT^{\prime} differ in rows rr and r+1r+1 in all columns right of cc in accordance with condition (2). Since we assumed that SS and TT differ in some column right of cc, condition (3) holds by induction.

Thus SS^{\prime} is constructed so that (1)-(3) hold. The result follows by induction. ∎

We now establish that KD(srD)\mathrm{KD}(s_{r}D) and KD(D)\mathrm{KD}(D) have the same number of connected components, each with the same highest weight.

Theorem 3.15.

Let DD be a northwest diagram and rr a row index such that row rr is contained in row r+1r+1. By Theorem 3.13, suppose the Kohnert crystals decompose into Demazure crystals (with minimal length permutations) as

KD(srD)i=1sμ(i)u(i)andKD(D)i=1tν(i)v(i).\mathrm{KD}(s_{r}D)\cong\bigsqcup_{i=1}^{s}\mathcal{B}^{u^{(i)}}_{\mu^{(i)}}\hskip 10.00002pt\text{and}\hskip 10.00002pt\mathrm{KD}(D)\cong\bigsqcup_{i=1}^{t}\mathcal{B}^{v^{(i)}}_{\nu^{(i)}}.

Then s=ts=t, and for all ii, we have μ(i)=ν(i)\mu^{(i)}=\nu^{(i)} and u(i)v(i)u^{(i)}\preceq v^{(i)} in Bruhat order.

Proof.

Each connected Demazure crystal λw\mathcal{B}^{w}_{\lambda} has a unique highest weight element, say TT, and TT satisfies 𝐰𝐭(T)=λ\mathbf{wt}(T)=\lambda. Thus there exist elements T1,,TsKD(srD)T_{1},\ldots,T_{s}\in\mathrm{KD}(s_{r}D) such that ei(Tj)=0e_{i}(T_{j})=0 for all i,ji,j, and 𝐰𝐭(Tj)=μ(j)\mathbf{wt}(T_{j})=\mu^{(j)}. By Lemma 2.17, we have TjKD(D)T_{j}\in\mathrm{KD}(D), and since the crystal operators are independent of the ambient diagram, each TjT_{j} is also a highest weight for KD(D)\mathrm{KD}(D).

Conversely, let TT be a highest weight element of KD(D)\mathrm{KD}(D), and let SKD(srD)S\in\mathrm{KD}(s_{r}D) be as in Lemma 3.14. Suppose there exists a column cc where TT and SS disagree. By condition (2), TT has a cell xx in row r+1r+1 but not in row rr of this column. Any column b<cb<c that has a cell yy in row rr agrees with SS by condition (2), hence by condition (3) also has a cell in row r+1r+1 to which yy must be rr-paired, and so xx cannot be rr-paired to yy. This contradicts the premise that er(T)=0e_{r}(T)=0 so we conclude TT and SS are identical, that is TKD(srD)T\in\mathrm{KD}(s_{r}D). In particular, KD(srD)\mathrm{KD}(s_{r}D) contains the highest weight diagrams of KD(D)\mathrm{KD}(D).

That u(i)w(i)u^{(i)}\preceq w^{(i)} follows because λ(i)u(i)λ(i)w(i)\mathcal{B}^{u^{(i)}}_{\lambda^{(i)}}\subseteq\mathcal{B}^{w^{(i)}}_{\lambda^{(i)}} by Lemma 2.17. ∎

We reformulate Theorem 3.15 in terms of the Demazure operators as follows.

Corollary 3.16.

For DD northwest with row rr a subset of row r+1r+1, we have frk(srD)=Df_{r}^{k}(s_{r}D)=D, where kk is the maximum integer ii such that fri(srD)0f_{r}^{i}(s_{r}D)\neq 0. In particular, we have nested crystals

KD(srD)KD(D)𝔇r(KD(srD)),\mathrm{KD}(s_{r}D)\subseteq\mathrm{KD}(D)\subseteq\mathfrak{D}_{r}(\mathrm{KD}(s_{r}D)),

and each has the same number of connected components.

In order to prove the latter containment is an equality, thus establishing (3.8), we will show 𝔇r(KD(D))=KD(D)\mathfrak{D}_{r}(\mathrm{KD}(D))=\mathrm{KD}(D) whenever DD is northwest with row rr a subset of row r+1r+1. This amounts to showing the lowering analog of [Ass20b, Thm 4.1.1].

Lemma 3.17.

Let DD be a left-justified diagram such that row rr\subseteq row r+1r+1. Then 𝔇r(KD(D))=KD(D)\mathfrak{D}_{r}(\mathrm{KD}(D))=\mathrm{KD}(D). In particular, for any TKD(D)T\in\mathrm{KD}(D) such that fr(T)0f_{r}(T)\neq 0, we have fr(T)KD(D)f_{r}(T)\in\mathrm{KD}(D).

Proof.

Let 𝐚=𝐰𝐭(D)\mathbf{a}=\mathbf{wt}(D), and let ww be the minimal length permutation that sorts 𝐚\mathbf{a} to a partition, say λ\lambda. Then KD(D)λw\mathrm{KD}(D)\cong\mathcal{B}^{w}_{\lambda}. The row containment condition on DD translates to 𝐚\mathbf{a} as arar+1a_{r}\leq a_{r+1}, and so srwws_{r}\cdot w\prec w in Bruhat order. In particular, ww has a reduced expression of the form srsiksi1s_{r}s_{i_{k}}\cdots s_{i_{1}}. Then we have

KD(D)λw𝔇r𝔇ik𝔇i1({uλ}).\mathrm{KD}(D)\cong\mathcal{B}^{w}_{\lambda}\cong\mathfrak{D}_{r}\mathfrak{D}_{i_{k}}\cdots\mathfrak{D}_{i_{1}}(\{u_{\lambda}\}).

The result now follows from the observation 𝔇r2(X)=𝔇r(X)\mathfrak{D}_{r}^{2}(X)=\mathfrak{D}_{r}(X) for any XX. ∎

To establish this for DD northwest, we leverage labelings of Kohnert diagrams introduced in [AS18] and generalized in [Ass20b].

4. Labelings of diagrams

Unlike tableaux, Kohnert diagrams do not, by default, have labels their cells. However, in this section we consider a canonical labeling of the cells of a diagram that allows one to determine if a given diagram belongs to a set KD(D)\mathrm{KD}(D) for a particular northwest diagram DD. Thus it will be essential for showing fr(T)KD(D)f_{r}(T)\in\mathrm{KD}(D) for TKD(D)T\in\mathrm{KD}(D) when DD is northwest with row rr a subset of row r+1r+1.

4.1. Kohnert tableaux

Assaf and Searles [AS18, Def 2.5] give an algorithm by which the cells of a diagram TT are labeled with respect to a weak composition 𝐚\mathbf{a} in order to determine whether or not TKD(𝔻(𝐚))T\in\mathrm{KD}(\mathbb{D}(\mathbf{a})).

Definition 4.1 ([AS18]).

For a weak composition 𝐚\mathbf{a} and a diagram TKD(𝔻(𝐚))T\in\mathrm{KD}(\mathbb{D}(\mathbf{a})), the Kohnert labeling of TT with respect to a\mathbf{a}, denoted by 𝐚(T)\mathcal{L}_{\mathbf{a}}(T), assigns labels to cells of TT as follows. Assuming all columns right of column cc have been labeled, assign labels {iaic}\{i\mid a_{i}\geq c\} to cells of column cc from top to bottom by choosing the smallest label ii such that the ii in column c+1c+1, if it exists, is weakly higher.

For example, the columns of the diagram in Figure 8 are labeled with respect to (3,0,5,1,4)(3,0,5,1,4), from right to left, with entries {3}\{3\}, {3,5}\{3,5\}, {1,3,5}\{1,3,5\}, {1,3,5}\{1,3,5\}, {1,3,4,5}\{1,3,4,5\}.

3 5 3 3 1 5 3 3 3 5 1 1 5 3 3 3 3 5 5 1 1 1 5 4 3 3 3 3 3 5 5 5 \begin{array}[]{cccccc}\vline\vtop{ \halign{&\circify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{1}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{1}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{1}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{~{}}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\crcr}}&\vline\vtop{ \halign{&\circify{#}\cr\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{1}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{1}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{1}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{4}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{3}$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss\\\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\vrule width=0.0pt,height=8.0pt,depth=0.0pt\vbox to8.0pt{\vss\hbox to8.0pt{\hss$$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\\\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss&\hbox to0.0pt{\leavevmode\hbox{\set@color\begin{picture}(8.0,8.0)\put(4.0,4.0){\circle{8.0}} \end{picture}}\hss}\vbox to8.0pt{\vss\hbox to8.0pt{\hss${}_{5}$\hss}\vss\crcr}}\end{array}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}
Figure 8. The labeling algorithm applied to a Kohnert diagram for (3,0,5,1,4)(3,0,5,1,4).

To handle the ambiguity where a given diagram is a Kohnert diagram for multiple weak compositions, Assaf and Searles [AS18, Def 2.3] define a Kohnert tableaux to be labelings that carry the information of the weak composition as well.

Definition 4.2 ([AS18]).

For a weak composition 𝐚\mathbf{a} of length nn, a Kohnert tableau of content a\mathbf{a} is a diagram labeled with 1a1,2a2,,nan1^{a_{1}},2^{a_{2}},\ldots,n^{a_{n}} satisfying

  1. (i)

    there is exactly one ii in each column from 11 through aia_{i};

  2. (ii)

    each entry in row ii is at least ii;

  3. (iii)

    the cells with entry ii weakly ascend from left to right;

  4. (iv)

    if i<ji<j appear in a column with ii below jj, then there is an ii in the column immediately to the right of and strictly below jj.

For example, Figure 9 shows the 1111 Kohnert tableaux of content (0,1,2,1)(0,1,2,1).

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Figure 9. The Kohnert tableaux of content (0,1,2,1)(0,1,2,1).

Assaf and Searles [AS18, Thm 2.8] prove for any diagram TT and weak composition 𝐚\mathbf{a} for which TT and 𝔻(𝐚)\mathbb{D}(\mathbf{a}) have the same column weight, TKD(𝔻(𝐚))T\in\mathrm{KD}(\mathbb{D}(\mathbf{a})) if and only if 𝐚(T)\mathcal{L}_{\mathbf{a}}(T) is a Kohnert tableau. Thus the labeling algorithm provides the bijection between Kohnert tableaux of content 𝐚\mathbf{a} and Kohnert diagrams for 𝐚\mathbf{a}.

In fact, the algorithm ensures conditions (i), (iii), and (iv) always hold, so we can restate this result as follows.

Proposition 4.3 ([AS18]).

Given a diagram TT and weak composition 𝐚\mathbf{a} for which TT and 𝔻(𝐚)\mathbb{D}(\mathbf{a}) have the same column weight, TKD(𝔻(𝐚))T\in\mathrm{KD}(\mathbb{D}(\mathbf{a})) if and only if each entry in row ii of 𝐚(T)\mathcal{L}_{\mathbf{a}}(T) is at least ii.

To state the analogous definitions for northwest diagrams, we must use rectification [Ass20b, Def 4.2.4]. Rectification maps any diagram to one that is a Kohnert diagram for a composition. Essentially, rectification is the result of transposing a diagram, applying all possible Kohnert lowering operators (in any order), and then transposing back.

Definition 4.4 ([Ass20b]).

For TT a diagram and i1i\geq 1 an integer, we column ii-pair cells of TT in columns i,i+1i,i+1 iteratively by column ii-pairing an unpair cell in column i+1i+1 with an unpaired cell in column ii weakly above it whenever all cells in columns ii and i+1i+1 that lie strictly between them are already column ii-paired.

It follows from the column pairing rule and [AS18, Lemma 2.2] that a diagram is a Kohnert diagram for some weak composition if and only if for all ii, all cells in column i+1i+1 are column ii-paired.

Definition 4.5 ([Ass20b]).

For TT a diagram and i1i\geq 1 an integer, the rectification operator recti\operatorname{rect}_{i} acts on TT as follows:

  • if all cells in column i+1i+1 of TT are column ii-paired, then recti(T)=T\operatorname{rect}_{i}(T)=T;

  • otherwise, recti\operatorname{rect}_{i} moves the lowest unpaired cell in column i+1i+1 to column ii.

Just as applying any terminal sequence of raising operators results in a unique highest weight element on a crystal, Assaf [Ass20b, Lemma 4.3.3] proves the following is well-defined.

Definition 4.6 ([Ass20b]).

Given a diagram TT, the rectification of TT, denoted by rect(T)\operatorname{rect}(T), is the unique diagram obtained by applying any terminal sequence of rectification operators to TT.

Rectification is a powerful tool for studying Kohnert crystals precisely because it intertwines the crystal operators [Ass20b, Thm 4.2.5]. Moreover, it facilitates a generalization of the labeling algorithm and Kohnert tableaux.

Given diagrams T,DT,D of the same column weight, following [Ass20b, Def 5.1.8], we label TT with respect to DD by a greedy algorithm that uses rectification to follow the Assaf–Searles labeling algorithm. For this, given a diagram TT and a column cc, partition TT at column cc by TcT>cT_{\leq c}\sqcup T_{>c}, where the former contains cells in columns weakly left of cc, and the latter contains cells in columns strictly right of cc.

Definition 4.7 ([Ass20b]).

For diagrams T,DT,D of the same column weight, construct the Kohnert labeling of TT with respect to DD, denoted by D(T)\mathcal{L}_{D}(T), as follows. Once all columns of TT right of column cc have been labeled, set T=Tcrect(T>c)\displaystyle T^{\prime}=T_{\leq c}\ \sqcup\ \operatorname{rect}(T_{>c}), where the leftmost occupied column of the latter is c+1c+1. Bijectively assign labels

{rD has a cell in column c, row r }\{r\mid D\text{ has a cell in column $c$, row $r$ }\}

to cells in column cc of TT from smallest to largest by assigning label rr to the lowest unlabeled cell xx such that if there exists a cell zz in column c+1c+1 of rect(T>c)\operatorname{rect}(T_{>c}) with label rr, then xx lies weakly above zz.

Generalizing the characterization for left-justified diagrams to northwest diagrams, combining Theorems 5.2.2 and 5.2.4 from [Ass20b] proves the following.

Theorem 4.8 ([Ass20b]).

For DD a northwest diagram, D\mathcal{L}_{D} is well-defined and flagged for TT if and only if TKD(D)T\in\mathrm{KD}(D).

4.2. Closure under lowering operators

By Theorem 4.8, we can prove our main result by showing D\mathcal{L}_{D} is well-defined and flagged for fr(T)f_{r}(T) whenever TKD(D)T\in\mathrm{KD}(D) for DD northwest with row rr a subset of row r+1r+1. For this we focus on the labels r,r+1r,r+1.

Lemma 4.9.

Let DD be a northwest diagram, and let rr be a row index such that for every cell in row rr there is a cell directly below it row r+1r+1. Let TT be a diagram with the same column weights as DD. Then in the Kohnert labeling D(T)\mathcal{L}_{D}(T) of TT with respect to DD, the label rr always appears above the label r+1r+1 within columns.

Proof.

We proceed by induction on the columns of TT. Let cc be the largest index for which the original diagram DD has a cell in row rr, column cc. Then in column cc of D(T)\mathcal{L}_{D}(T), the label rr must appear above the label r+1r+1 by definition, as there are no cells labeled rr right of column cc.

Since DD is northwest, every column left of cc in DD either has no cells in row rr or row r+1r+1, or has cells in both rows rr and r+1r+1. Thus for each column b<cb<c in D(T)\mathcal{L}_{D}(T), either column bb will contain both labels rr and r+1r+1, or it will contain neither label. Assume that, if column bb does contain both labels, then the label rr appears above the label r+1r+1.

Consider column b1b-1 and assume it contains both labels rr and r+1r+1; otherwise, the result follows trivially. If column bb does not contain the labels rr and r+1r+1, then in column b1b-1, the candidate cells for the labels rr and r+1r+1 are the same. Thus since we assign labels from smallest to largest, the label rr will be placed above the label r+1r+1 in column b1b-1.

If, on the other hand, column bb does contain these labels, then the label rr appears above the label r+1r+1. In column b1b-1, the label rr is placed in the highest available cell which is weakly below the cell with label rr in column bb, and then the label r+1r+1 is placed in the analogous manner. For the label r+1r+1 to end up above the label rr in column b1b-1 would mean that there was a cell in column b1b-1 weakly below the cell labeled r+1r+1 in column bb which was not weakly below the cell labeled rr in column bb. However, this would force the cell labeled r+1r+1 in column bb to lie above the cell labeled rr, contradicting the assumption. ∎

Lemma 4.9 shows cells labeled rr are bounded by those labeled r+1r+1 in D(T)\mathcal{L}_{D}(T). We next show this persists under rectification. Thus Kohnert tableaux condition (iv) on the rectification will establish the flagged condition on D(T)\mathcal{L}_{D}(T).

Lemma 4.10.

Let DD be a northwest diagram, and let rr be a row index such that for every cell in row rr there is a cell directly below it row r+1r+1. Let TT be a diagram with the same column weights as DD. Then rect(D(T))\operatorname{rect}(\mathcal{L}_{D}(T)) has at least as many cells labeled r+1r+1 as cells labeled rr.

Proof.

Say that a column cc of TT has property ()(*) if, whenever column cc contains a cell with label rr, then column cc also contains a cell with label r+1r+1 weakly below the cell with label rr. We now proceed by induction on the columns of TT, showing that after we label rectify column cc, both columns cc and c+1c+1 satisfy ()(*).

First observe that in the original Kohnert labeling D(T)\mathcal{L}_{D}(T) of TT with respect to DD, the result certainly holds since DD has more cells in row r+1r+1 than in row rr. Now assume we have label rectified up to column c+1c+1, so that ()(*) holds in all columns weakly right of c+1c+1. In column cc, we can have that neither rr not r+1r+1 appears as a label (C0), that only r+1r+1 appears as a label (C1), or that both rr and r+1r+1 appear as labels (C2). We have the same three possibilities in column c+1c+1; designate these cases as (D0), (D1), and (D2), respectively.

Case (C0).

  • Subcase (D0). Nothing to check; never gain the label rr in either column.

  • Subcase (D1). Nothing to check; never gain the label rr in either column.

  • Subcase (D2). In column cc, ()(*) can fail if the cell labeled rr in column c+1c+1 moves into column cc, while the cell labeled r+1r+1 in column c+1c+1 does not. In column c+1c+1, ()(*) may fail if the cell labeled rr is not label paired, while the cell labeled r+1r+1 is label paired with a cell in column cc. By [Ass20b, Lemma 5.2.3], these cases are in fact equivalent. Furthermore note that in this case, the original diagram DD must have cells in rows rr and r+1r+1 of column c+1c+1, and have no cells in rows rr or r+1r+1 of column cc. This implies that DD cannot have cells anywhere in column cc below row rr, since DD is northwest. As a result, the labels in column cc of TT are all <r<r.

    Now let x0x_{0} denote the cell in column c+1c+1 labeled rr and let x1x_{1} denote the cell in column c+1c+1 labeled r+1r+1. Assume x0x_{0} is unpaired, and assume x1x_{1} is label paired with some cell in column cc. As noted above, the label on this latter cell is <r<r.

    Then by the first label rectifying “rule,” we find a cell yy in column cc which is label paired to a cell zz in column c+1c+1 such that (y)(x0)<(z)\mathcal{L}(y)\leq\mathcal{L}(x_{0})<\mathcal{L}(z) and such that (z)\mathcal{L}(z) is maximal. (This is possible since we found such a pair in the previous paragraph.) We then swap the labels on x0x_{0} and zz as we push x0x_{0} into column cc. As a result, column cc gains a cell with label (x0)=(z)r+1\mathcal{L}^{\prime}(x_{0})=\mathcal{L}(z)\geq r+1, so ()(*) is satisfied. In column c+1c+1, x0x_{0} has moved out and zz inherits (y)<r\mathcal{L}(y)<r, so the column has no cell labeled rr and ()(*) again holds.

Case (C1).

  • Subcase (D0). Nothing to check; never gain the label rr in either column.

  • Subcase (D1). Nothing to check; never gain the label rr in either column.

  • Subcase (D2). Not possible, since DD is northwest.

Case (C2). In all of the following subcases, ()(*) will hold in column cc since the column has both labels rr and r+1r+1, and rr appears above r+1r+1 by Lemma 4.9.

  • Subcase (D0). We could violate ()(*) in column c+1c+1 is if the cell in column cc with label rr is label paired with a cell, say xx, in column c+1c+1, but the cell in column cc with label r+1r+1 is not label paired with a cell in column c+1c+1. In this case (x)r+2\mathcal{L}(x)\geq r+2, since we must have (x)r\mathcal{L}(x)\geq r and we assumed that the labels rr and r+1r+1 do not appear in column c+1c+1. But the cell labeled r+1r+1 in column cc lies below the cell labeled rr by Lemma 4.9, showing that xx would have preferred to pair with the cell labeled r+1r+1. Therefore, there must have been some other cell below xx that was already paired with the cell labeled r+1r+1 in column cc — otherwise xx would pair to the cell labeled r+1r+1, instead — and it follows that ()(*) is satisfied in column c+1c+1 after we label rectify.

  • Subcase (D1). The only way we could run into trouble here is if the cell labeled r+1r+1 in column c+1c+1 pairs with the cell labeled rr in column cc. However, in this situation, the cell labeled r+1r+1 in column cc must have already paired with a cell in column c+1c+1. Again, ()(*) holds in column c+1c+1 after label rectifying.

  • Subcase (D2). Here, the cells labeled rr and r+1r+1 — denote them as y0y_{0} and y1y_{1}, respectively — in column cc must be label paired to cells in column c+1c+1, since both labels appear in column c+1c+1 weakly above the corresponding label in column cc.

    It suffices to show that the cell in column c+1c+1 with which y0y_{0} pairs is strictly above the cell with which y1y_{1} pairs. Thus assume for a contradiction that a cell xx in column c+1c+1 pairs with y0y_{0}, while y1y_{1} is yet unpaired. Then since y0y_{0} lies above y1y_{1} in column cc by Lemma 4.9, we must have (y)=r\mathcal{L}(y)=r. However, by the inductive hypothesis, xx must lie above the cell in column c+1c+1 labeled r+1r+1, meaning y1y_{1} must have in fact been paired already, a contradiction. Thus y0y_{0} always pairs with a cell strictly above the cell with which y1y_{1} pairs, and it follows that ()(*) is satisfied in column c+1c+1.

Thus property (*) holds throughout rectification and so, too, at the end. ∎

We use results about the generalized labeling algorithm to complete our proof.

Theorem 4.11.

Let DD be a northwest diagram, and let rr be a row index such that for every cell in row rr there is a cell directly below it row r+1r+1. Then for any TKD(D)T\in\mathrm{KD}(D) we have fr(T)KD(D)f_{r}(T)\in\mathrm{KD}(D). In particular 𝔇r(KD(D))=KD(D)\mathfrak{D}_{r}(\mathrm{KD}(D))=\mathrm{KD}(D).

Proof.

Let U=fr(T)U=f_{r}(T) and assume UTU\neq T or we are done. By [Ass20b, Thm 5.2.2] we have D(T)\mathcal{L}_{D}(T) is well-defined and flagged. By [Ass20b, Lemma 5.3.3], we know D(U)\mathcal{L}_{D}(U) is well-defined as well. By [Ass20b, Thm 5.3.2] rect(D(T))=𝐚(rect(T))\operatorname{rect}(\mathcal{L}_{D}(T))=\mathcal{L}_{\mathbf{a}}(\operatorname{rect}(T)) and rect(D(U))=𝐛(rect(U))\operatorname{rect}(\mathcal{L}_{D}(U))=\mathcal{L}_{\mathbf{b}}(\operatorname{rect}(U)) for some compositions 𝐚\mathbf{a} and 𝐛\mathbf{b}, with the former a Kohnert tableau with respect to 𝐚\mathbf{a} since D(T)\mathcal{L}_{D}(T) is flagged. This is to say that rect(T)𝔻(𝐚)\operatorname{rect}(T)\in\mathbb{D}(\mathbf{a}). Using [Ass20b, Lemma 5.3.3] once more we also note that 𝐚=𝐛\mathbf{a}=\mathbf{b}.

From Lemma 4.10 we know ar+1ara_{r+1}\geq a_{r} and from the left-justified case shown in Lemma 3.17 we have fr(rect(T))KD(𝐚)f_{r}(\operatorname{rect}(T))\in\mathrm{KD}(\mathbf{a}). Since crystals moves commute with rectification [Ass20b, Thm 4.2.5] we write rect(U)KD(𝐚)\operatorname{rect}(U)\in\mathrm{KD}(\mathbf{a}) which implies 𝐚(rect(U))=rect(D(U))\mathcal{L}_{\mathbf{a}}(\operatorname{rect}(U))=\operatorname{rect}(\mathcal{L}_{D}(U)) is flagged. Rectification does not affect the flagged condition [Ass20b, Lemma 5.3.1] so we finally have that D(U)\mathcal{L}_{D}(U) is flagged and therefore UKD(D)U\in\mathrm{KD}(D) by [Ass20b, Thm 5.2.4]. ∎

4.3. Recurrence for Kohnert polynomials

We can now establish the third and final term in Magyar’s recurrence, giving our main result.

Theorem 4.12.

The Kohnert polynomials of northwest diagrams satisfy the following recurrence:

  • (K1)

    𝔎=1\mathfrak{K}_{\varnothing}=1;

  • (K2)

    if the first column of DD is exactly CkC_{k}, then

    (4.1) 𝔎D=x1x2xk𝔎DCk;\mathfrak{K}_{D}=x_{1}x_{2}\cdots x_{k}\mathfrak{K}_{D-C_{k}};
  • (K3)

    if every cell in row rr has a cell in row r+1r+1 in the same column, then

    (4.2) 𝔎D=πr(𝔎srD).\mathfrak{K}_{D}=\pi_{r}\left(\mathfrak{K}_{s_{r}D}\right).

In particular, 𝔎D=char(𝒮Dflag)\mathfrak{K}_{D}=\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D}) for DD any northwest diagram.

Proof.

We have observed (K1) by definition, and (K2) is proved in Lemma 2.16. Assume, then that DD is northwest and every cell in row rr of DD, there is a cell in row r+1r+1 in the same column. By Theorem 4.11, we have 𝔇r(KD(D))=KD(D)\mathfrak{D}_{r}(\mathrm{KD}(D))=\mathrm{KD}(D). Thus applying the Demazure operator to the nested sequence in Corollary 3.16 gives

𝔇r(KD(srD))𝔇r(KD(D))𝔇r(𝔇r(KD(srD)))=𝔇r(KD(srD)),\mathfrak{D}_{r}(\mathrm{KD}(s_{r}D))\ \subseteq\ \mathfrak{D}_{r}(\mathrm{KD}(D))\ \subseteq\ \mathfrak{D}_{r}(\mathfrak{D}_{r}(\mathrm{KD}(s_{r}D)))\ =\ \mathfrak{D}_{r}(\mathrm{KD}(s_{r}D)),

and so 𝔇r(KD(srD))=KD(D)\mathfrak{D}_{r}(\mathrm{KD}(s_{r}D))=\mathrm{KD}(D). By Proposition 3.7, we have

𝔎D=char(KD(D))=char(𝔇r(KD(srD)))=πr(char(KD(srD)))=πr(𝔎srD).\mathfrak{K}_{D}=\mathrm{char}(\mathrm{KD}(D))=\mathrm{char}(\mathfrak{D}_{r}(\mathrm{KD}(s_{r}D)))=\pi_{r}(\mathrm{char}(\mathrm{KD}(s_{r}D)))=\pi_{r}(\mathfrak{K}_{s_{r}D}).

Thus (K3) holds. By Theorem 2.9, Kohnert polynomials and characters of flagged Schur modules satisfy the same recurrence, and so must be equal. ∎

It is worth remarking that Magyar’s recurrence, Theorem 2.9, holds for a more general class of shapes, namely %\%-avoiding diagrams. A natural question is whether our result holds for this more general class. The answer is a resounding no.

Definition 4.13.

A diagram DD is %\%-avoiding if whenever (j,k),(i,l)D(j,k),(i,l)\in D with i<ji<j and k<lk<l, then either (i,k)D(i,k)\in D or (j,l)D(j,l)\in D.

Notice every northwest shape is, in particular, %-avoiding.

Lemma 4.14.

Let zz be a cell in row ss of a diagram DD. Let UU be the diagram consisting of the rows strictly above ss weakly below some r<sr<s plus the cells right of zz inclusive in row ss. If UU is northwest and there exists a cell in row rr in the same column as zz, then there exists no TKD(D)T\in\mathrm{KD}(D) with 𝐰𝐭(T)=𝐰𝐭(D)+Kαr,s\mathbf{wt}(T)=\mathbf{wt}(D)+K\alpha_{r,s} where KK is the number of cells right of zz inclusive in row ss.

Proof.

Assume we can in fact construct such a diagram TT by performing Kohnert moves on DD. Note that no Kohnert moves could have moved a cell to a row strictly above rr or from a row strictly below row ss since we must preserve the weights of rows strictly above rr and also those strictly below ss. Therefore those two regions do not change between DD and TT.

Let cc denote the column containing zz. Suppose there is a cell xx in row kk column bcb\leq c of UU but that this position is vacant in TT. Then xx must have been moved by a Kohnert move so the number of cells in column bb strictly above kk must be strictly greater in TT than in DD. In particular, there must be some cell yy in row kk^{\prime} with rk<kr\leq k^{\prime}<k column bb of TT whose position is vacant in DD. The northwest condition on xx and the cell in row rr column cc, both lying in UU, imply there is a cell in row rr column bb of DD, so in fact r<k<kr<k^{\prime}<k. Furthermore, the presence of xx along with the vacancy of row kk^{\prime} column bb in DD imply that row kk^{\prime} has no cells right of bb in UU, hence in DD which has an identical row kk^{\prime}.

In order to preserve the row weight of row kk^{\prime} between DD and TT we then must have that there is a column b<bb^{\prime}<b such that row kk^{\prime} column bb^{\prime} has a cell xx^{\prime} in DD but not in TT. If we replace x,k,x,k, and bb with xx^{\prime}, kk^{\prime}, and bb^{\prime} respectively and we repeat the argument then it never terminates which would imply our diagram TT does not actually exist.

We know that in order to get from DD to TT, precisely KK cells must be removed from row ss with none more entering. These must be the rightmost KK cells in ss which includes zz. Thus, we begin the above contradictory process by letting x=zx=z. ∎

We prove Theorem 4.12 is tight with the following result.

Theorem 4.15.

If DD is %-avoiding but not northwest, then char(𝒮Dflag)𝔎D\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D})\neq\mathfrak{K}_{D}.

Proof.

Pick rows rr and ss with r<sr<s that exhibit a violation of the northwest condition and are minimally separated. That is, the only violations of the northwest condition in the diagram consisting of rows weakly between rr and ss occur with cells in the rows rr and ss themselves. Let yy be the rightmost cell in row ss for which there is a cell strictly right of its column cc in row rr, but not in column cc of row rr. Let KK be the number of cells of DD in row ss weakly right of yy for which there is not a corresponding cell in the same column of row rr. By Proposition 2.5 we have that x𝐰𝐭(D)+Kαr,sx^{\mathbf{wt}(D)+K\alpha_{r,s}} is a monomial in the monomial expansion of char(𝒮Dflag)\mathrm{char}(\mathcal{S}^{\mathrm{flag}}_{D}). It now suffices to show that x𝐰𝐭(D)+Kαr,sx^{\mathbf{wt}(D)+K\alpha_{r,s}} is not a monomial in 𝔎D\mathfrak{K}_{D}.

Let zz be KKth cell from the right in row ss. Due to the %-avoiding condition and the fact that there is not a cell in the same column as yy of row rr, we know that for any cell in row rr right of yy, of which there is at least one by assumption, there is a corresponding cell in the same column of row ss. This corresponding cell in row ss is not one of those counted in the definition of KK. Therefore the number of cells weakly right of yy in row ss is strictly greater than KK which is to say that zz lies strictly to the right of yy.

Now let UU be the diagram of DD consisting only of the rows strictly above ss weakly below rr, and additionally the cells weakly right of zz in row ss. By choice of r,sr,s and yy we know that UU is northwest. Moreover, if there were no cell in row rr of the same column as zz, then since UU is northwest there would be no cells right of this column in row rr in either UU or DD. However, this would mean that the KK cells weakly right of zz are precisely those cells weakly right of yy that do not have a corresponding cell in the same column of row rr, which is impossible because yy is included in this count but lies left of zz. So instead there must be a cell in row rr in the same column as zz. By Lemma 4.14 there is then no TKD(D)T\in\mathrm{KD}(D) with 𝐰𝐭(T)=𝐰𝐭(D)+Kαr,s\mathbf{wt}(T)=\mathbf{wt}(D)+K\alpha_{r,s} and therefore x𝐰𝐭(D)+Kαr,sx^{\mathbf{wt}(D)+K\alpha_{r,s}} does not appear in the monomial expansion of 𝔎D\mathfrak{K}_{D}. ∎

Acknowledgments

The authors are grateful to Peter Kagey for sharing insights on this project.

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