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Related papers: Pinning Model with Heavy Tailed Disorder

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Recent theoretical and empirical successes in deep learning, including the celebrated neural scaling laws, are punctuated by the observation that many objects of interest tend to exhibit some form of heavy-tailed or power law behavior. In…

Machine Learning · Statistics 2025-06-05 Liam Hodgkinson , Zhichao Wang , Michael W. Mahoney

We study the path properties of a random polymer attracted to a defect line by a potential with disorder, and we prove that in the delocalized regime, at any temperature, the number of contacts with the defect line remains in a certain…

Probability · Mathematics 2014-03-21 Kenneth S. Alexander , Nikos Zygouras

Suppose an online platform wants to compare a treatment and control policy, e.g., two different matching algorithms in a ridesharing system, or two different inventory management algorithms in an online retail site. Standard randomized…

Methodology · Statistics 2022-12-27 Peter Glynn , Ramesh Johari , Mohammad Rasouli

We consider an arbitrarily charged polymer driven by a weak field through a gel according to the rules of the Rubinstein-Duke model. The probability distribution in the stationary state is related to that of the model in which only the head…

Statistical Mechanics · Physics 2007-05-23 Andrzej Drzewinski , J. M. J. van Leeuwen

We investigate a simple tight-binding Hamiltonian to understand the stability of spin-polarized transport of states with an arbitrary spin content in the presence of disorder. The general spin state is made to pass through a linear chain of…

Disordered Systems and Neural Networks · Physics 2019-04-12 Leonardo Benini , Amrita Mukherjee , Arunava Chakrabarti , Rudolf A. Roemer

We consider a statistical mechanics model for biopolymers. Sophisticated polymer chains, such as DNA, have stiffness when they stretch chains. The Laplacian interaction is used to describe the stiffness. Also, the surface between two media…

Probability · Mathematics 2014-08-05 Chien-Hao Huang

Systems of interacting continuous-time Markov chains are a powerful model class, but inference is typically intractable in high dimensional settings. Auxiliary information, such as noisy observations, is typically only available at discrete…

Machine Learning · Statistics 2026-04-21 Giosue Migliorini , Padhraic Smyth

We consider a multivariate heavy-tailed stochastic volatility model and analyze the large-sample behavior of its sample covariance matrix. We study the limiting behavior of its entries in the infinite-variance case and derive results for…

Probability · Mathematics 2016-05-10 Anja Janßen , Thomas Mikosch , Mohsen Rezapour , Xiaolei Xie

We study anomalous transport arising in disordered one-dimensional spin chains, specifically focusing on the subdiffusive transport typically found in a phase preceding the many-body localization transition. Different types of transport can…

Disordered Systems and Neural Networks · Physics 2020-03-09 Maximilian Schulz , Scott R. Taylor , Antonello Scardicchio , Marko Žnidarič

This paper presents a novel theoretical Monte Carlo Markov chain procedure in the framework of graphs. It specifically deals with the construction of a Markov chain whose empirical distribution converges to a given reference one. The Markov…

Probability · Mathematics 2019-07-02 Roy Cerqueti , Emilio De Santis

We numerically study the effect of adding quenched disorder in the form of randomly placed pinning sites on jamming transitions in systems that jam at a well defined point J in the clean limit. Quenched disorder decreases the jamming…

Soft Condensed Matter · Physics 2015-06-04 C. J. Olson Reichhardt , E. Groopman , Z. Nussinov , C. Reichhardt

It has been widely believed that almost all states in one-dimensional (1d) disordered systems with short-range hopping and uncorrelated random potential are localized. Here, we consider the fate of these localized states by coupling between…

Disordered Systems and Neural Networks · Physics 2024-03-19 Xiaoshui Lin , Ming Gong

Interevent times in temporal contact data from humans and animals typically obey heavy-tailed distributions, and this property impacts contagion and other dynamical processes on networks. We theoretically show that distributions of…

Physics and Society · Physics 2022-02-08 Elohim Fonseca dos Reis , Naoki Masuda

We study the configurations of the nearest neighbor Ising ferromagnetic chain with IID centered and square integrable external random field in the limit in which the pairwise interaction tends to infinity. The available free energy…

Probability · Mathematics 2025-03-03 Orphée Collin , Giambattista Giacomin , Yueyun Hu

We study a discrete-time interacting particle system with continuous state space which is motivated by a mathematical model for turnover through branching in actin filament networks. It gives rise to transient clusters reminiscent of actin…

Probability · Mathematics 2024-10-01 Cecilia González-Tokman , Dietmar B. Oelz

We prove a Chernoff-type bound for sums of matrix-valued random variables sampled via a regular (aperiodic and irreducible) finite Markov chain. Specially, consider a random walk on a regular Markov chain and a Hermitian matrix-valued…

Machine Learning · Statistics 2020-10-30 Jiezhong Qiu , Chi Wang , Ben Liao , Richard Peng , Jie Tang

We study the unitary relaxation dynamics of disordered spin chains following a sudden quench of the Hamiltonian. We give analytical arguments, corroborated by specific numerical examples, to show that the existence of a stationary state…

Disordered Systems and Neural Networks · Physics 2012-12-21 Simone Ziraldo , Alessandro Silva , Giuseppe E. Santoro

Extreme events and the heavy tail distributions driven by them are ubiquitous in various scientific, engineering and financial research. They are typically associated with stochastic instability caused by hidden unresolved processes.…

Probability · Mathematics 2019-05-22 Andrew J. Majda , Xin T. Tong

This article investigates the effect for random pinning models of long range power-law decaying correlations in the environment. For a particular type of environment based on a renewal construction, we are able to sharply describe the phase…

Probability · Mathematics 2025-08-15 Quentin Berger , Hubert Lacoin

In this work the diffusion in the quenched trap model with diverging mean waiting times is examined. The approach of randomly stopped time is extensively applied in order to obtain asymptotically exact representation of the disorder…

Statistical Mechanics · Physics 2020-07-21 Stanislav Burov
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