Greene's theorem

greene_theorem robinson_schensted pitman_transform robinson_schensted_knuth directed_last_passage_percolation

The Greene's theorem associates the shape of the output Young tableau via the RS algorithm with the length of increasing (nondecreasing, to be more precise) subsequences of the input words.

An RSK version can be immediately obtained by the matrix-to-word transformation that defines the RSK algorithm. It turns out to be the directed last passage percolation.

As the Pitman's transform generalises the RS(K) algorithms, they also have Greene's theorems which call for a direct proof.

In this entry we describe all four versions (RS, RSK, discrete and continuous Pitman) of the Greene's theorem.

Version 1: RS algorithm

Theorem 1. Let $$w$$ be a word with alphabet $$\pint_{>0}$$, and $$\lambda$$ the shape of the output tableau after RS row-inserting $$w$$. Then

$\lambda_1 + \lambda_2 + ... + \lambda_k = \text{length of a longest }k\text{-increasing subsequence of }w.$

A proof can be found in e.g. [{sagan00}] using the Knuth equivalence.

Version 2: RSK algorithm

Definition. Given $$(n, k)$$ and $$(n', k')$$ two different coordinates in the 2-d integer lattice. A directed path $$\pi: (n', k') \to (n', k')$$ is a collection of coordinates $$(n_1, k_1) = (n, k), (n_2, k_2), ..., (n_{r - 1}, k_{r - 1}), (n_r, k_r) = (n', k')$$ such that

$(n_i - n_{i - 1}, k_i - k_{i - 1}) \in \{(\text{sgn}(n' - n), 0), (0, \text{sgn}(k' - k))\} \setminus \{(0, 0)\}.$

That is, from $$(n_{i - 1}, k_{i - 1})$$ to $$(n_i, k_i)$$ the coordinate moves towards $$(n, k)$$ following the lattice edges.

By Theorem 1 and the matrix-to-word transformation, we have

Theorem 2. Let $$A = (a_{ij})$$ be an $$n \times \ell$$ matrix, and $$\lambda$$ the shape of the output tableau after RSK row-inserting $$A$$. Then

$\lambda_1 + \lambda_2 + ... + \lambda_k = \max_{(*)} \sum_{(i, j) \in \bigcup_i \pi_i} a_{ij}.$

where the max is over

\begin{align} (*): \pi_{1 : k} \text{ are } k &\text{ disjoint directed paths where } \\ &\pi_1: (1, 1) \to (n, \ell - k + 1), \\ &\pi_2: (1, 2) \to (n, \ell - k + 2), \\ &... \\ &\pi_k: (1, k) \to (n, \ell). \end{align}

When $$k = 1$$, $$\lambda_1$$ coincides with the directed last passage percolation.

Version 3 & 4: discrete and continuous Pitman's transforms

Let $$(i_{pq})_{q = 1 : k - j}$$ correspond to $$\pi_p$$ in $$(*)$$ in the RSK version, we can write down the Pitman version:

Theorem 3. Let $$S_1, S_2, ...$$ be paths on $$\pint$$ such that $$S_i(0) = 0 \forall i$$, and $$(\lambda^k_j)$$ be the output tableau after applying the discrete Pitman's transform (with row insertion) to the $$S$$'s. Then

$\lambda^k_1(n) + ... + \lambda^k_j(n) = S_{k - j + 1} (n) + ... + S_k (n) + \max_{(i_{pq}): i_{p, q} \le i_{p - 1, q}, i_{p, q} \le n \forall p, q} \sum_{p = 1 : j, q = 1 : k - j} (S_{p + q - 1} (i_{p q}) - S_{p + q} (i_{p q})).$

The Proof of Theorem 3 (and similarly Theorem 3', 3c and 3'c below) is either open or folklore.

Theorem 3'. Let $$S_1, S_2, ...$$ be continuous paths on $$\real_{\ge 0}$$ such that $$S_i(0) = 0 \forall i$$, and $$(\lambda^k_j)$$ be the output tableau after applying the Pitman's transform (with row insertion) to the $$S$$'s. Then

$\lambda^k_1(t) + ... + \lambda^k_j(t) = S_{k - j + 1} (t) + ... + S_k (t) + \sup_{(t_{pq}): t_{p, q} \le t_{p - 1, q}, t_{pq} \le t \forall p, q} \sum_{p = 1 : j, q = 1 : k - j} (S_{p + q - 1} (t_{p q}) - S_{p + q} (t_{p q})).$

Difference between Pitman's transform and RSK

Recall that the $$\odot$$ and $$\otimes$$ are defined differently in rs_pitman_type_a and rsk_path_transformation. This can be seen in the following Greene's theorem example.

Example. Let $$A$$ and $$S$$ be the following matrix and paths corresponding to each other according to (1) in rsk_path_transformation:

\begin{align} A &= \begin{pmatrix} 1 &0 &3 \\ 2 & 2 & 4 \\ 0 & 2 &1 \end{pmatrix}\\ S_1 (1 : 3) &= (1, 3, 3)\\ S_2 (1 : 3) &= (0, 2, 4)\\ S_3 (1 : 3) &= (3, 7, 8) \end{align}

Then the length of the first row $$\lambda_1$$ of the output tableaux are

\begin{align} \text{Pitman}: & \lambda_1 = 8 \\ \text{RSK}: & \lambda_1 = 10 \end{align}

And they correspond to the following directed paths (entries along the paths are highlighted in boldface) in the Greene's theorems:

\begin{align} \text{Pitman}: & \begin{pmatrix} 1 &0 &\mathbf{3} \\ 2 & 2 & \mathbf{4} \\ 0 & 2 &\mathbf{1} \end{pmatrix}\\ \text{RSK}: & \begin{pmatrix} \mathbf 1 &0 &{3} \\ \mathbf 2 & \mathbf 2 & \mathbf{4} \\ 0 & 2 &\mathbf{1} \end{pmatrix} \end{align}

Column insertion versions

The column insertion versions of the Greene's theorem can be derived from the row insertion versions and the duality / symmetry between the row and the column insertions (see e.g. Remark in dynamics_pitman_transform_type_a).

Theorem 1c. Let $$w$$ be a word with alphabet $$\pint_{>0}$$, and $$\lambda$$ the shape of the output tableau after RS column-inserting $$w$$. Then

$\lambda_1 + \lambda_2 + ... + \lambda_k = \text{length of a longest }k\text{-decreasing subsequence of }w.$

Theorem 2c. Let $$A = (a_{ij})$$ be an $$n \times \ell$$ matrix, and $$\lambda$$ the shape of the output tableau after RSK column-inserting $$A$$. Then

$\lambda_1 + \lambda_2 + ... + \lambda_k = \max_{(*)} \sum_{(i, j) \in \bigcup_i \pi_i} a_{ij}.$

where the max is over

\begin{align} (*): \pi_{1 : k} \text{ are } k &\text{ disjoint directed paths where } \\ &\pi_1: (1, \ell) \to (n, k), \\ &\pi_2: (1, \ell - 1) \to (n, k - 1), \\ &... \\ &\pi_k: (1, \ell - k + 1) \to (n, 1). \end{align}

Theorem 3c. Let $$S_1, S_2, ...$$ be paths on $$\pint$$ such that $$S_i(0) = 0 \forall i$$, and $$(\lambda^k_j)$$ be the output tableau after applying the discrete Pitman's transform (with column insertion) to the $$S$$'s. Then

$\lambda^k_1(n) + ... + \lambda^k_j(n) = S_{1} (n) + ... + S_j (n) + \max_{(i_{pq}): i_{p, q} \le i_{p - 1, q}, i_{p, q} \le n \forall p, q} \sum_{p = 1 : j, q = 1 : k - j} (S_{k - p - q + 2} (i_{p q}) - S_{k - p - q + 1} (i_{p q})).$

Theorem 3'c. Let $$S_1, S_2, ...$$ be continuous paths on $$\real_{\ge 0}$$ such that $$S_i(0) = 0 \forall i$$, and $$(\lambda^k_j)$$ be the output tableau after applying the Pitman's transform (with column insertion) to the $$S$$'s. Then

$\lambda^k_1(t) + ... + \lambda^k_j(t) = S_{1} (t) + ... + S_j (t) + \sup_{(t_{pq}): t_{p, q} \le t_{p - 1, q}, t_{pq} \le t \forall p, q} \sum_{p = 1 : j, q = 1 : k - j} (S_{k - p - q + 2} (t_{p q}) - S_{k - p - q + 1} (t_{p q})).$

References

• [sagan00] The Symmetric Group, , 2000.