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On the Distribution of the Length of the Longest Increasing Subsequence of Random Permutations
Combinatorics · Submitted 16 Oct 1998
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim The main result in this paper is a proof that the distribution function for $l_N$, suitably centered and scaled, converges to the Tracy-Widom distribution [TW1] of the largest eigenvalue of a random GUE matrix.
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The abstract, sentence by sentence
The authors consider the length, $l_N$, of the length of the longest increasing subsequence of a random permutation of $N$ numbers. The main result in this paper is a proof that the distribution function for $l_N$, suitably centered and scaled, converges to the Tracy-Widom distribution [TW1] of the largest eigenvalue of a random GUE matrix. The authors also prove convergence of moments. The proof is based on the steepest decent method for Riemann-Hilbert problems, introduced by Deift and Zhou in 1993 [DZ1] in the context of integrable systems. The applicability of the Riemann-Hilbert technique depends, in turn, on the determinantal formula of Gessel [Ge] for the Poissonization of the distribution function of $l_N$.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | The authors consider the length, $l_N$, of the length of the longest increasing subsequence of a random permutation of $N$ numbers. | background 0.87 | 0.56 | 0.02 | asserted 0.85 |
| s1 | The main result in this paper is a proof that the distribution function for $l_N$, suitably centered and scaled, converges to the Tracy-Widom distribution [TW1] of the largest eigenvalue of a random GUE matrix. | result 0.97 | 0.94 | 0.98 | asserted 1.00 |
| s2 | The authors also prove convergence of moments. | result 0.94 | 0.95 | 0.03 | asserted 1.00 |
| s3 | The proof is based on the steepest decent method for Riemann-Hilbert problems, introduced by Deift and Zhou in 1993 [DZ1] in the context of integrable systems. | method 0.99 | 0.14 | 0.02 | asserted 1.00 |
| s4 | The applicability of the Riemann-Hilbert technique depends, in turn, on the determinantal formula of Gessel [Ge] for the Poissonization of the distribution function of $l_N$. | method 0.92 | 0.16 | 0.02 | asserted 1.00 |
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The paper
Original abstract
The authors consider the length, $l_N$, of the length of the longest increasing subsequence of a random permutation of $N$ numbers. The main result in this paper is a proof that the distribution function for $l_N$, suitably centered and scaled, converges to the Tracy-Widom distribution [TW1] of the largest eigenvalue of a random GUE matrix. The authors also prove convergence of moments. The proof is based on the steepest decent method for Riemann-Hilbert problems, introduced by Deift and Zhou in 1993 [DZ1] in the context of integrable systems. The applicability of the Riemann-Hilbert technique depends, in turn, on the determinantal formula of Gessel [Ge] for the Poissonization of the distribution function of $l_N$.
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References
How the literature uses it
39 arXiv papers cite this in 64 sentences
Papers citing it · 33 sentences without a confident label
Uses its method or tool 2 papers
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Consequently, with these characterizations in terms of bi-orthogonal polynomials and their reproducing kernel, we can employ the Riemann–Hilbert approach to BOPUC [ref] to attain the sought-after asymptotics for multi-bordered, framed, and multi-framed Toeplitz determinants.
Strong Szeg\H{o} Limit Theorems for Multi-Bordered, Framed, and Multi-Framed Toeplitz Determinants · Introduction · 1.00
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The same result may also be proved through a more powerful procedure, namely solving a Riemann-Hilbert problem [ref] .
Phase transition in complex-time Loschmidt echo of short and long range spin chain · Determinants of Bessel functions · 0.84
Compares with it 1 paper
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Finally, we note that the approach of Baik, Deift and Johansson [ref] for the edge behavior of Plancherel random partitions was based on Riemann-Hilbert techniques, while the approach that we follow here is much closer in spirit to that developed by Borodin, Okounkov and Olshanski [ref] .
The periodic Schur process and free fermions at finite temperature · Conclusion · 0.82
Cites it as support 1 paper
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This condition is satisfied with high probability due to arguments such as [ref] about the typical Young diagrams concentrating towards $Θ(√(t))$ rows and columns.
The state hidden subgroup problem and an efficient algorithm for locating unentanglement · The full permutational symmetries defy Fourier sampling · 0.97
Cites it as background 24 papers
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Of particular interest is the case $β= 2$ ($$ Tracy-Widom distribution) that initially appeared in the fluctuations of the largest eigenvalue of a $$ random matrix [ref] and that meanwhile exhibited a universal feature in a variety of models: longuest increasing subsequence of a random uniform permutation [ref] , last passage percolation [ref] , log-Gamma polymer partition function [ref] , asymmetric simple exclusion process [ref] , value in $0$ of the Hopf-Cole solution to the KPZ equation [ref] , O'Connell-Yor semidiscrete directed polymer partition function [ref] , etc.
Remarkable structures in integrable probability, I: max-independence structures · Motivations · 0.95
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Moreover, as shown by Baik, Deift, and Johansson [ref] , Borodin, Okounkov, and Olshanski [ref] and Johansson [ref] , the edge scaling limit of the random permutations and the Plancherel measure yields the Tracy-Widom distribution, originally introduced to describe the fluctuation of the largest eigenvalue of the Gaussian Unitary Ensemble [ref] .
Multicritical Scaling Limit of Shifted Schur Measure · Introduction · 0.88
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The RSK was first applied in this context by Johansson [ref] and Baik–Deift–Johansson [ref] , and the dynamical perspective has been substantially developed by O'Connell [ref] , [ref] , [ref] , Biane–Bougerol–O'Connell [ref] (see also Chhaibi [ref] ), Corwin–O'Connell–Seppäläinen–Zygouras [ref] , O'Connell–Pei [ref] , see also O'Connell–Seppäläinen–Zygouras [ref] .
Nearest neighbor Markov dynamics on Macdonald processes · Introduction · 0.95
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