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Related papers: Large deviation bounds for the Airy point process

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We prove that the spectrum of the stochastic Airy operator is rigid in the sense of Ghosh and Peres (Duke Math. J., 166(10):1789--1858, 2017) for Dirichlet and Robin boundary conditions. This proves the rigidity of the Airy-$\beta$ point…

Probability · Mathematics 2022-09-27 Pierre Yves Gaudreau Lamarre , Promit Ghosal , Wenxuan Li , Yuchen Liao

We consider the weakly asymmetric exclusion process on a bounded interval with particle reservoirs at the endpoints. The hydrodynamic limit for the empirical density, obtained in the diffusive scaling, is given by the viscous Burgers…

Probability · Mathematics 2009-12-14 Lorenzo Bertini , Claudio Landim , Mustapha Mourragui

We present a new lower bound on the differential entropy rate of stationary processes whose sequences of probability density functions fulfill certain regularity conditions. This bound is obtained by showing that the gap between the…

Information Theory · Computer Science 2017-08-30 Meik Dörpinghaus

We consider the upper and lower tail probabilities for the centered (by time$/24$) and scaled (according to KPZ time$^{1/3}$ scaling) one-point distribution of the Cole-Hopf solution of the KPZ equation when started with initial data drawn…

Probability · Mathematics 2020-03-04 Ivan Corwin , Promit Ghosal

We study moderate deviations in the exponential corner growth model, both in the bulk setting and the increment-stationary setting. The main results are sharp right-tail bounds on the last-passage time and the exit point of the…

Probability · Mathematics 2020-04-10 Elnur Emrah , Chris Janjigian , Timo Seppäläinen

The Airy distribution (AD) describes the probability distribution of the area under a Brownian excursion. The AD is prominent in several areas of physics, mathematics and computer science. Here we use a dilute colloidal system to directly…

Statistical Mechanics · Physics 2020-02-26 Tal Agranov , Pini Zilber , Naftali R. Smith , Tamir Admon , Yael Roichman , Baruch Meerson

We present a large deviation principle at speed N for the largest eigenvalue of some additively deformed Wigner matrices. In particular this includes Gaussian ensembles with full-rank general deformation. For the non-Gaussian ensembles, the…

Probability · Mathematics 2023-03-22 Benjamin McKenna

We consider the stationary measure of the asymmetric simple exclusion process (ASEP) on a finite interval in $\mathbb{Z}$ with open boundaries. Fixing all the jump rates and letting the system size approach infinity, the height profile of…

Probability · Mathematics 2024-12-18 Milind Hegde , Zongrui Yang

It was shown in [J. A. Ram\'irez, B. Rider and B. Vir\'ag. J. Amer. Math. Soc. 24, 919-944 (2011)] that the edge of the spectrum of $\beta$ ensembles converges in the large $N$ limit to the bottom of the spectrum of the stochastic Airy…

Probability · Mathematics 2020-11-19 Laure Dumaz , Cyril Labbé

We study the multipoint distribution of stationary half-space last passage percolation with exponentially weighted times. We derive both finite-size and asymptotic results for this distribution. In the latter case we observe a new…

Probability · Mathematics 2021-01-19 Dan Betea , Patrik Ferrari , Alessandra Occelli

Affine point processes are a class of simple point processes with self- and mutually-exciting properties, and they have found useful applications in several areas. In this paper, we obtain large-time asymptotic expansions in large…

Probability · Mathematics 2019-07-26 Xuefeng Gao , Lingjiong Zhu

This paper studies quantitative deviation bounds for statistical ensembles evolving under the one-parameter flow of a nearly integrable Hamiltonian system. Combining Nekhoroshev-type stability estimates with phase-mixing arguments, we…

Dynamical Systems · Mathematics 2026-02-23 Xinyu Liu , Yong Li

In this work, we derive sharp non-asymptotic deviation bounds for weighted sums of Dirichlet random variables. These bounds are based on a novel integral representation of the density of a weighted Dirichlet sum. This representation allows…

Probability · Mathematics 2023-04-07 Denis Belomestny , Pierre Menard , Alexey Naumov , Daniil Tiapkin , Michal Valko

The hard edge Pearcey process is universal in random matrix theory and many other stochastic models. This paper deals with the gap probability for the thinned/unthinned hard edge Pearcey process over the interval $(0,s)$ by working on the…

Mathematical Physics · Physics 2023-05-24 Dan Dai , Shuai-Xia Xu , Lun Zhang

Starting from one-point tail bounds, we establish an upper tail large deviation principle for the directed landscape at the metric level. Metrics of finite rate are in one-to-one correspondence with measures supported on a set of countably…

Probability · Mathematics 2024-05-27 Sayan Das , Duncan Dauvergne , Bálint Virág

We prove the first margin-based generalization bound for voting classifiers, that is asymptotically tight in the tradeoff between the size of the hypothesis set, the margin, the fraction of training points with the given margin, the number…

Machine Learning · Computer Science 2025-11-26 Kasper Green Larsen , Natascha Schalburg

We study the distribution of the supremum of the Airy process with $m$ wanderers minus a parabola, or equivalently the limit of the rescaled maximal height of a system of $N$ non-intersecting Brownian bridges as $N\to\infty$, where the…

Probability · Mathematics 2023-04-26 Karl Liechty , Gia Bao Nguyen , Daniel Remenik

This work is concerned with the derivation of a robust a posteriori error estimator for a discontinuous Galerkin method discretisation of linear non-stationary convection-diffusion initial/boundary value problems and with the implementation…

Numerical Analysis · Mathematics 2012-11-16 Andrea Cangiani , Emmanuil H. Georgoulis , Stephen Metcalfe

This paper provides a precise error analysis for the maximum likelihood estimate $\hat{a}_{\text{ML}}(u_1^n)$ of the parameter $a$ given samples $u_1^n = (u_1, \ldots, u_n)'$ drawn from a nonstationary Gauss-Markov process $U_i = a U_{i-1}…

Information Theory · Computer Science 2021-03-29 Peida Tian , Victoria Kostina

We present an estimate of the Wasserstein distance between the data distribution and the generation of score-based generative models. The sampling complexity with respect to dimension is $\mathcal{O}(\sqrt{d})$, with a logarithmic constant.…

Machine Learning · Computer Science 2025-10-06 Xixian Wang , Zhongjian Wang