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Related papers: Upper-tail large deviation principle for the ASEP

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We obtain a new relation between the distributions $\mu_t$ at different times $t\ge 0$ of the continuous-time TASEP (Totally Asymmetric Simple Exclusion Process) started from the step initial configuration. Namely, we present a…

Probability · Mathematics 2021-02-18 Leonid Petrov , Axel Saenz

In this paper we consider the first passage percolation with identical and independent exponentially distributions, called the Eden growth model, and we study the upper tail large deviations for the first passage time ${\rm T}$. Our main…

Probability · Mathematics 2020-01-01 Shuta Nakajima

To consider a high-dimensional random process, we propose a notion about stochastic tensor-valued random process (TRP). In this work, we first attempt to apply a generic chaining method to derive tail bounds for all p-th moments of the…

Probability · Mathematics 2023-02-02 Shih-Yu Chang

In this paper we present a Doob type maximal inequality for stochastic processes satisfying the conditional increment control condition. If we assume, in addition, that the margins of the process have uniform exponential tail decay, we…

Probability · Mathematics 2019-12-17 Xuan Liu , Guangyu Xi

We consider the totally asymmetric simple exclusion process (TASEP) on the periodic chain in the presence of a single impurity site that is inaccessible to other particles and therefore acts as a static defect. Particles are allowed to…

Statistical Mechanics · Physics 2010-01-04 J. Szavits-Nossan , K. Uzelac

We show that the stationary measure for the totally asymmetric simple exclusion process on a segment with open boundaries is given by a marginal of a two-line measure with a simple and explicit description. We use this representation to…

Probability · Mathematics 2025-02-11 Wlodek Bryc , Pavel Zatitskii

The totally asymmetric simple exclusion principle (TASEP) is a fundamental model in nonequilibrium statistical mechanics. It describes the stochastic unidirectional movement of particles along a 1D chain of ordered sites. We consider the…

Optimization and Control · Mathematics 2025-01-29 Lars Grüne , Kilian Pioch , Thomas Kriecherbauer , Michael Margaliot

Consider the continuous greedy paths model: given a $d$-dimensional Poisson point process with positive marks interpreted as masses, let $\mathrm P(\ell)$ denote the maximum mass gathered by a path of length $\ell$ starting from the origin.…

Probability · Mathematics 2025-03-04 Julien Verges

The TASEP (totally asymmetric simple exclusion process) is a basic model for an one-dimensional interacting particle system with non-reversible dynamics. Despite the simplicity of the model it shows a very rich and interesting behaviour. In…

Probability · Mathematics 2010-03-30 James Martin , Philipp Schmidt

This paper presents a new, short proof of the computation of the upper tail large deviation rate function for the Brownian directed percolation model. Through a distributional equivalence between the last passage time in this model and the…

Probability · Mathematics 2019-07-08 Christopher Janjigian

A large deviations principle is established for the joint law of the empirical measure and the flow measure of a renewal Markov process on a finite graph. We do not assume any bound on the arrival times, allowing heavy tailed distributions.…

Probability · Mathematics 2014-02-18 Mauro Mariani , Lorenzo Zambotti

The event of large losses plays an important role in credit risk. As these large losses are typically rare, and portfolios usually consist of a large number of positions, large deviation theory is the natural tool to analyze the tail…

Probability · Mathematics 2014-07-03 Vincent Leijdekker , Michel Mandjes , Peter Spreij

We consider a modulated process S which, conditional on a background process X, has independent increments. Assuming that S drifts to -infinity and that its increments (jumps) are heavy-tailed (in a sense made precise in the paper), we…

Probability · Mathematics 2017-11-29 Sergey Foss , Takis Konstantopoulos , Stan Zachary

The large deviations theory for heavy-tailed processes has seen significant advances in the recent past. In particular, Rhee et al. (2019) and Bazhba et al. (2020) established large deviation asymptotics at the sample-path level for L\'evy…

Probability · Mathematics 2024-10-29 Zhe Su , Chang-Han Rhee

Consider the partition function of a directed polymer in an IID field. We assume that both tails of the negative and the positive part of the field are at least as light as exponential. It is a well-known fact that the free energy of the…

Probability · Mathematics 2012-10-04 Iddo Ben-Ari

We study the totally asymmetric simple exclusion process (TASEP) on $\mathbb{Z}$ with step initial condition, in which all particles have distinct types. Our main object of interest is the type of the rightmost particle -- the leader -- at…

Probability · Mathematics 2026-01-30 Alexei Borodin , Alexey Bufetov

We study large deviation probabilities for a sum of dependent random variables from a heavy-tailed factor model, assuming that the components are regularly varying. We identify conditions where both the factor and the idiosyncratic terms…

Probability · Mathematics 2007-12-05 Boualem Djehiche , Jens Svensson

We theoretically study the Totally Asymmetric Exclusion Process (TASEP) with quenched jumping rates disorder and finite lifetime chain. TASEP is widely used to model the translation of messenger RNAs by Ribosomes in protein synthesis. Since…

Let $(X_n:n\geq 0)$ be a sequence of i.i.d. r.v.'s with negative mean. Set $S_0=0$ and define $S_n=X_1+... +X_n$. We propose an importance sampling algorithm to estimate the tail of $M=\max \{S_n:n\geq 0\}$ that is strongly efficient for…

Probability · Mathematics 2008-08-21 Jose Blanchet , Peter Glynn

The upper tail problem in the Erd\H{o}s--R\'enyi random graph $G\sim\mathcal{G}_{n,p}$ asks to estimate the probability that the number of copies of a graph $H$ in $G$ exceeds its expectation by a factor $1+\delta$. Chatterjee and Dembo…

Combinatorics · Mathematics 2019-11-12 Bhaswar B. Bhattacharya , Shirshendu Ganguly , Eyal Lubetzky , Yufei Zhao
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