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The relaxation in complex systems is in general nonexponential. After an initial rapid decay the system relax slowly following a long time tail. In the present paper a sandpile modelation of the relaxation in complex systems is analysed.…

Condensed Matter · Physics 2007-05-23 A. Vazquez , O. Sotolongo-Costa , F. Brouers

An elegant and uniform relaxation-rate formula is presented for the entropic lattice Boltzmann method (ELBM). The formula not only guarantees the discrete time H-theorem at numerical level but also gives full consideration to the…

Computational Physics · Physics 2020-01-08 Weifeng Zhao , Wen-An Yong

Using different segmental dynamics and relaxation, characteristics of the interface growth is examined in an electrophoretic deposition of polymer chains on a three (2+1) dimensional discrete lattice with a Monte Carlo simulation.…

Soft Condensed Matter · Physics 2007-05-23 Frank W. Bentrem , Jun Xie , R. B. Pandey

This study examines the statistical nature of instantaneous scalar concentration in an elevated point-source plume (neutral or buoyant) dispersing within a turbulent boundary layer. Using high-frequency long-duration experimental…

Fluid Dynamics · Physics 2026-01-29 Miaoyan Pang , Krishna M Talluru , Kapil Chauhan

In entangled polymer systems, there are several characteristic time scales, such as the entanglement time and the disengagement time. In molecular simulations, the longest relaxation time (the disengagement time) can be determined by the…

Soft Condensed Matter · Physics 2015-06-11 Takashi Uneyama , Takuma Akimoto , Tomoshige Miyaguchi

The long-time relaxation of the average conductance in a 2D mesoscopic sample is studied within the method recently suggested by Muzykantskii and Khmelnitskii and based on a saddle-point approximation to the supermatrix $\sigma$--model. The…

Condensed Matter · Physics 2007-05-23 Alexander D. Mirlin

Spatially-distributed, nonequilibrium chemical systems described by a Markov chain model are considered. The evolution of such systems arises from a combination of local birth-death reactive events and random walks executed by the particles…

chao-dyn · Physics 2009-10-31 Mikhail V. Velikanov , Raymond Kapral

Statistical inference problems arising within signal processing, data mining, and machine learning naturally give rise to hard combinatorial optimization problems. These problems become intractable when the dimensionality of the data is…

Statistical Mechanics · Physics 2017-04-27 Adel Javanmard , Andrea Montanari , Federico Ricci-Tersenghi

We study enhancement of diffusive mixing by fast incompressible time-periodic flows. The class of relaxation-enhancing flows that are especially efficient in speeding up mixing has been introduced in [2]. The relaxation-enhancing property…

Analysis of PDEs · Mathematics 2007-07-02 Alexander Kiselev , Roman Shterenberg , Andrej Zlatos

Like other critical phenomena, the jamming transition accompanies the divergence of the relaxation time $\tau$. A recent numerical study of frictionless spherical particles proves that $\tau$ is inversely proportional to the lowest non-zero…

Soft Condensed Matter · Physics 2020-09-23 Harukuni Ikeda

Out-of-time ordered correlators (OTOCs) help characterize the scrambling of quantum information and are usually studied in the context of nonintegrable systems. In this work, we compare the relaxation dynamics of OTOCs in interacting…

Statistical Mechanics · Physics 2023-06-29 Vinitha Balachandran , Lea F. Santos , Marcos Rigol , Dario Poletti

We develop tractable convex relaxations for rank-constrained quadratic optimization problems over $n \times m$ matrices, a setting for which tractable relaxations are typically only available when the objective or constraints admit spectral…

Optimization and Control · Mathematics 2026-05-22 Ryan Cory-Wright , Jean Pauphilet

We adapted the SWAP molecular dynamics algorithm for use in lattice Ising spin models. We dressed the spins with a randomly distributed length and we alternated long-range spin exchanges with conventional single spin flip Monte Carlo…

Statistical Mechanics · Physics 2025-10-14 Greivin Alfaro Miranda , Leticia F. Cugliandolo , Marco Tarzia

We investigate the long-term relaxation of one-dimensional (${1D}$) self-gravitating systems, using both kinetic theory and $N$-body simulations. We consider thermal and Plummer equilibria, with and without collective effects. All…

Statistical Mechanics · Physics 2023-08-11 Mathieu Roule , Jean-Baptiste Fouvry , Christophe Pichon , Pierre-Henri Chavanis

We introduce a simple one-dimensional sandpile model that undergoes relaxation oscillations. A single model can account for self-organized critical behavior and relaxation oscillations, depending on the manner in which it is driven,…

Condensed Matter · Physics 2007-05-23 J. E. S. Socolar , M. E. Bleich

We extend the conventional mode-coupling theory of supercooled liquids to systems under stationary shear flow. Starting from generalized fluctuating hydrodynamics, a nonlinear equation for the intermediate scattering function is…

Statistical Mechanics · Physics 2009-11-10 Kunimasa Miyazaki , David R. Reichman

We study droplet dynamics and breakup in generic time-dependent flows via a multicomponent Lattice Boltzmann algorithm, with emphasis on flow start up conditions. We first study droplet breakup in a confined oscillatory shear flow via two…

Fluid Dynamics · Physics 2020-03-18 Felix Milan , Luca Biferale , Mauro Sbragaglia , Federico Toschi

This paper proposes a bilevel hierarchy of strengthened complex moment relaxations for complex polynomial optimization. The key trick entails considering a class of positive semidefinite conditions that arise naturally in characterizing the…

Optimization and Control · Mathematics 2025-05-12 Jie Wang

Estimating the entropy based on data is one of the prototypical problems in distribution property testing and estimation. For estimating the Shannon entropy of a distribution on $S$ elements with independent samples, [Paninski2004] showed…

Machine Learning · Computer Science 2018-09-25 Yanjun Han , Jiantao Jiao , Chuan-Zheng Lee , Tsachy Weissman , Yihong Wu , Tiancheng Yu

Stochastic gradient descent (SGD) exhibits strong algorithmic regularization effects in practice, which has been hypothesized to play an important role in the generalization of modern machine learning approaches. In this work, we seek to…

Machine Learning · Computer Science 2022-07-12 Difan Zou , Jingfeng Wu , Vladimir Braverman , Quanquan Gu , Dean P. Foster , Sham M. Kakade