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Consider standard first-passage percolation on $\mathbb Z^d$. We study the lower-tail large deviations of the rescaled random metric $\widehat{\mathbf T}_n$ restricted to a box. If all exponential moments are finite, we prove that…

Probability · Mathematics 2024-12-05 Julien Verges

In this paper, we study lower tail probabilities of the height function $\mathfrak{h}(M,N)$ of the stochastic six-vertex model. We introduce a novel combinatorial approach to demonstrate that the tail probabilities…

Probability · Mathematics 2025-08-26 Sayan Das , Yuchen Liao , Matteo Mucciconi

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

In this article we study a \emph{non-directed} polymer model in dimension $d\ge 2$: we consider a simple symmetric random walk on $\mathbb{Z}^d$ which interacts with a random environment, represented by i.i.d. random variables…

Probability · Mathematics 2022-09-26 Quentin Berger , Niccolò Torri , Ran Wei

In this mostly numerical study, we revisit the statistical properties of the ground state of a directed polymer in a $d=1+1$ "hilly" disorder landscape, i.e. when the quenched disorder has power-law tails. When disorder is Gaussian, the…

Disordered Systems and Neural Networks · Physics 2016-12-19 Thomas Gueudré , Pierre Le Doussal , Jean-Philippe Bouchaud , Alberto Rosso

Stochastic partial differential equations driven by Poisson random measures (PRM) have been proposed as models for many different physical systems, where they are viewed as a refinement of a corresponding noiseless partial differential…

Probability · Mathematics 2012-09-25 Amarjit Budhiraja , Jiang Chen , Paul Dupuis

We study cluster sizes in supercritical $d$-dimensional inhomogeneous percolation models with long-range edges -- such as long-range percolation -- and/or heavy-tailed degree distributions -- such as geometric inhomogeneous random graphs…

Probability · Mathematics 2025-11-12 Joost Jorritsma , Júlia Komjáthy , Dieter Mitsche

A central theoretical issue at the core of the current research on many-body localization (MBL) consists in characterizing the statistics of rare long-range resonances in many-body eigenstates. This is of paramount importance to understand:…

Disordered Systems and Neural Networks · Physics 2023-12-25 Giulio Biroli , Alexander K. Hartmann , Marco Tarzia

We consider a directed variant of the negative-weight percolation model in a two-dimensional, periodic, square lattice. The problem exhibits edge weights which are taken from a distribution that allows for both positive and negative values.…

Disordered Systems and Neural Networks · Physics 2019-08-21 Christoph Norrenbrock , Mitchell M. Mkrtchian , Alexander K. Hartmann

We study large deviation properties of probability distributions with either a compact support or a fat tail by comparing them with q-deformed exponential distributions. Our main result is a large deviation property for probability…

Mathematical Physics · Physics 2015-06-02 Jan Naudts , Hiroki Suyari

Recent work across many machine learning disciplines has highlighted that standard descent methods, even without explicit regularization, do not merely minimize the training error, but also exhibit an implicit bias. This bias is typically…

Machine Learning · Computer Science 2020-06-22 Ziwei Ji , Miroslav Dudík , Robert E. Schapire , Matus Telgarsky

In last passage percolation models lying in the KPZ universality class, the energy of long energy-maximizing paths may be studied as a function of the paths' pair of endpoint locations. Scaled coordinates may be introduced, so that these…

Probability · Mathematics 2019-04-17 Alan Hammond

The real-space renormalization procedures on hierarchical lattices have been much studied for many disordered systems in the past at the level of their typical fluctuations. In the present paper, the goal is to analyze instead the…

Disordered Systems and Neural Networks · Physics 2021-05-12 Cecile Monthus

This thesis deals with some $(1+1)$-dimensional lattice path models from the KPZ universality class: the directed random polymer with inverse-gamma weights (known as log-gamma polymer) and its zero temperature degeneration, i.e. the last…

Probability · Mathematics 2019-05-27 Elia Bisi

We consider the model of the directed polymer in a random medium of dimension 1+3, and investigate its multifractal properties at the localization/delocalization transition. In close analogy with models of the quantum Anderson localization…

Disordered Systems and Neural Networks · Physics 2007-06-13 Cecile Monthus , Thomas Garel

We study the behavior of the optimal path between two sites separated by a distance $r$ on a $d$-dimensional lattice of linear size $L$ with weight assigned to each site. We focus on the strong disorder limit, i.e., when the weight of a…

Disordered Systems and Neural Networks · Physics 2016-08-16 Eduardo López , Sergey V. Buldyrev , Lidia A. Braunstein , Shlomo Havlin , H. Eugene Stanley

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

Large deviations for sums of i.i.d.\ random variables with stretched-exponential tails (also called Weibull or semi-exponential tails) have been well understood since the 60's, going back to Nagaev's seminal work. Many extensions in the…

Probability · Mathematics 2026-02-04 Nina Gantert , Joscha Prochno , Philipp Tuchel

We develop a new probabilistic method for deriving deviation estimates in directed planar polymer and percolation models. The key estimates are for exit points of geodesics as they cross transversal down-right boundaries. These bounds are…

Probability · Mathematics 2023-08-30 Elnur Emrah , Christopher Janjigian , Timo Seppäläinen

Using the weak-noise theory, we evaluate the probability distribution $\mathcal{P}(H,t)$ of large deviations of height $H$ of the evolving surface height $h(x,t)$ in the Kardar-Parisi-Zhang (KPZ) equation in one dimension when starting from…

Statistical Mechanics · Physics 2016-02-23 Baruch Meerson , Eytan Katzav , Arkady Vilenkin