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We consider deterministic dynamics, known as the slicer map (SM), which exhibits normal and anomalous diffusion by varying a single parameter. The statistics of the position moments and the low-order position autocorrelation function (PACF)…

Statistical Mechanics · Physics 2025-08-19 Muhammad Tayyab , Jahanzeb Tariq

In this article, we focus on extending the notion of lattice linearity to self-stabilizing programs. Lattice linearity allows a node to execute its actions with old information about the state of other nodes and still preserve correctness.…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-19 Arya Tanmay Gupta , Sandeep S Kulkarni

We uncover an unforeseen asymmetry in relaxation -- for a pair of thermodynamically equidistant temperature quenches, one from a lower and the other from a higher temperature, the relaxation at the ambient temperature is faster in case of…

Statistical Mechanics · Physics 2022-06-20 Alessio Lapolla , Aljaž Godec

We study the complexity of sampling from the stationary distribution of a mean-field SDE, or equivalently, the complexity of minimizing a functional over the space of probability measures which includes an interaction term. Our main insight…

Statistics Theory · Mathematics 2024-07-08 Yunbum Kook , Matthew S. Zhang , Sinho Chewi , Murat A. Erdogdu , Mufan Bill Li

We study a systematic improvement of perturbation theory for gauge fields on the lattice; the improvement entails resumming, to all orders in the coupling constant, a dominant subclass of tadpole diagrams. This method, originally proposed…

High Energy Physics - Lattice · Physics 2009-11-11 M. Constantinou , H. Panagopoulos , A. Skouroupathis

Recurrent neural networks (RNNs) are commonly applied to clinical time-series data with the goal of learning patient risk stratification models. Their effectiveness is due, in part, to their use of parameter sharing over time (i.e., cells…

Machine Learning · Computer Science 2020-01-03 Jeeheh Oh , Jiaxuan Wang , Shengpu Tang , Michael Sjoding , Jenna Wiens

Motivated by the large strain shear of loose granular materials we introduced a model which consists of consecutive optimization and restructuring steps leading to a self organization of a density field. The extensive connections to other…

Statistical Mechanics · Physics 2013-05-29 Janos Torok , Supriya Krishnamurthy , Janos Kertesz , Stephane Roux

We study the evolution of an initially random distribution of particles on a square lattice, under certain rules for `growing' and `culling' of particles. In one version we allow the particles to move laterally along the surface (mobile…

Soft Condensed Matter · Physics 2009-11-07 Tapati Dutta , Nikolai Lebovka , S. Tarafdar

As a continuation of the previously published work [Velychko O. V., Stasyuk I. V., Phase Transitions, 2019, 92, 420], a phenomenological framework for the relaxation dynamics of quantum lattice model with multi-well potentials is given in…

Statistical Mechanics · Physics 2023-01-05 R. Erdem , S. Özüm , N. Güçlü

Real time thermalization and relaxation phenomena are studied in the low energy density phase of the 2+1 dimensional classical O(2) symmetric scalar theory by solving numerically its dynamics. The near-equilibrium decay rate of on-shell…

High Energy Physics - Phenomenology · Physics 2014-11-17 Sz. Borsanyi , Zs. Szep

We use molecular dynamics computer simulations to study the relaxation dynamics of Na2O-2(SiO2) in its molten, highly viscous state. We find that at low temperatures the incoherent intermediate scattering function for Na relaxes about 100…

Statistical Mechanics · Physics 2009-11-07 Jurgen Horbach , Walter Kob

Sharpness-Aware Minimization (SAM) has emerged as a powerful method for improving generalization in machine learning models by minimizing the sharpness of the loss landscape. However, despite its success, several important questions…

Optimization and Control · Mathematics 2025-03-05 Dimitris Oikonomou , Nicolas Loizou

Among random sampling methods, Markov Chain Monte Carlo algorithms are foremost. Using a combination of analytical and numerical approaches, we study their convergence properties towards the steady state, within a random walk Metropolis…

Statistical Mechanics · Physics 2024-01-08 Alexei D. Chepelianskii , Satya N. Majumdar , Hendrik Schawe , Emmanuel Trizac

We study the non--equilibrium motion of an elastic string in a two dimensional pinning landscape using Langevin dynamics simulations. The relaxation of a line, initially flat, is characterized by a growing length, $L(t)$, separating the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alejandro Kolton , Alberto Rosso , Thierry Giamarchi

This paper proposes a novel analysis for the Scaffold algorithm, a popular method for dealing with data heterogeneity in federated learning. While its convergence in deterministic settings--where local control variates mitigate client…

Machine Learning · Statistics 2025-03-11 Paul Mangold , Alain Durmus , Aymeric Dieuleveut , Eric Moulines

Consider Least Squares Monte Carlo (LSM) algorithm, which is proposed by Longstaff and Schwartz (2001) for pricing American style securities. This algorithm is based on the projection of the value of continuation onto a certain set of basis…

Computational Finance · Quantitative Finance 2011-08-01 Oleksii Mostovyi

Optical tweezers setup is often used to probe the motion of individual tracer particle, which promotes the study of relaxation dynamics of a generic process confined in a harmonic potential. We uncover the dependence of ensemble- and…

Statistical Mechanics · Physics 2020-04-15 Xudong Wang , Yao Chen , Weihua Deng

We study the phase synchronization problem with noisy measurements $Y=z^*z^{*H}+\sigma W\in\mathbb{C}^{n\times n}$, where $z^*$ is an $n$-dimensional complex unit-modulus vector and $W$ is a complex-valued Gaussian random matrix. It is…

Statistics Theory · Mathematics 2022-03-21 Chao Gao , Anderson Y. Zhang

Following the Renormalization Group scheme recently developed by Pietronero {\it et al}, we introduce a simplifying strategy for the renormalization of the relaxation dynamics of sandpile models. In our scheme, five sub-cells at a generic…

Statistical Mechanics · Physics 2009-10-31 Y. Moreno , J. B. Gomez , A. F. Pacheco

The scaling and mass expansion (shortly 'sm-expansion') is a new axiom for causal perturbation theory, which is a stronger version of a frequently used renormalization condition in terms of Steinmann's scaling degree. If one quantizes the…

Mathematical Physics · Physics 2015-06-18 Michael Duetsch