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We propose discrete Langevin proposal (DLP), a simple and scalable gradient-based proposal for sampling complex high-dimensional discrete distributions. In contrast to Gibbs sampling-based methods, DLP is able to update all coordinates in…

Machine Learning · Computer Science 2022-06-22 Ruqi Zhang , Xingchao Liu , Qiang Liu

We propose a novel blocked version of the continuous-time bouncy particle sampler of [Bouchard-C\^ot\'e et al., 2018] which is applicable to any differentiable probability density. This alternative implementation is motivated by blocked…

Computation · Statistics 2021-07-12 Jacob Vorstrup Goldman , Sumeetpal Sidhu Singh

We propose a theory of ripples in suspended graphene sheets based on two-dimensional elasticity equations that are made discrete on the honeycomb lattice and then periodized. At each point carbon atoms are coupled to Ising spins whose…

Mesoscale and Nanoscale Physics · Physics 2012-11-06 L. L. Bonilla , A. Carpio

Diffusion models provide a principled framework for generative modeling via stochastic differential equations and time-reversed dynamics. Extending spectral diffusion approaches to spherical data, however, raises nontrivial geometric and…

Probability · Mathematics 2026-01-29 Pierpaolo Brutti , Claudio Durastanti , Francesco Mari

We investigate the nonequilibrium dynamics of active matter using a two-dimensional active Brownian particles model. In these systems, self-propelled particles undergo motility-induced phase separation (MIPS), spontaneously segregating into…

Soft Condensed Matter · Physics 2026-02-26 Toranosuke Umemura , Issei Sakai , Takuma Akimoto

Dynamic space packing (DSP) is a random process with sequential addition and removal of identical objects into space. In the lattice version, objects are particles occupying single lattice sites, and adding a particle to a lattice site…

Statistical Mechanics · Physics 2024-09-10 Rahul Dandekar , P. L. Krapivsky

Model Predictive Control (MPC) is a versatile approach capable of accommodating diverse control requirements that holds significant promise for a broad spectrum of industrial applications. Noteworthy challenges associated with MPC include…

Systems and Control · Electrical Eng. & Systems 2025-04-28 Ryuta Moriyasu , Sho Kawaguchi , Kenji Kashima

This paper deals with Gibbs samplers that include high dimensional conditional Gaussian distributions. It proposes an efficient algorithm that avoids the high dimensional Gaussian sampling and relies on a random excursion along a small set…

Computation · Statistics 2016-04-20 Olivier Féron , François Orieux , Jean-François Giovannelli

Glauber dynamics are a natural model of dynamics of dependent systems. While originally introduced in statistical physics, they have found important applications in the study of social networks, computer vision and other domains. In this…

Probability · Mathematics 2023-05-02 Byron Chin , Ankur Moitra , Elchanan Mossel , Colin Sandon

It is well known that Glauber dynamics on spin systems typically suffer exponential slowdowns at low temperatures. This is due to the emergence of multiple metastable phases in the state space, separated by narrow bottlenecks that are hard…

Probability · Mathematics 2024-12-24 Reza Gheissari , Alistair Sinclair

Pendulum-like dynamics is a universal motif across many areas of physics, underlying systems ranging from classical nonlinear oscillators to superconducting qubits and cold-atom tunneling platforms. Here we present an exact frequency-domain…

Classical Physics · Physics 2026-03-12 Teepanis Chachiyo

We introduce the Glauber Generative Model (GGM), a new class of discrete diffusion models, to obtain new samples from a distribution given samples from a discrete space. GGM deploys a discrete Markov chain called the heat bath dynamics (or…

Machine Learning · Computer Science 2025-03-18 Harshit Varma , Dheeraj Nagaraj , Karthikeyan Shanmugam

Simulating particle dynamics with high fidelity is crucial for solving real-world interaction and control tasks involving liquids in design, graphics, and robotics. Recently, data-driven approaches, particularly those based on graph neural…

Machine Learning · Computer Science 2025-12-01 Niteesh Midlagajni , Constantin A. Rothkopf

We show that mixing for local, reversible dynamics of mean field spin glasses is exponentially slow in the low temperature regime. We introduce a notion of free energy barriers for the overlap, and prove that their existence imply that the…

Probability · Mathematics 2020-04-17 Gérard Ben Arous , Aukosh Jagannath

We study the stochastic dynamics of Ising spin models with random bonds, interacting on finitely connected Poissonnian random graphs. We use the dynamical replica method to derive closed dynamical equations for the joint spin-field…

Disordered Systems and Neural Networks · Physics 2009-11-13 A. Mozeika , A. C. C. Coolen

We extend the spectral method for proving limit theorems to random non-uniformly expanding dynamical systems. This yields the CLT and moderate deviations principles (MDP). We show that as the amount of non-uniformity decreases the CLT rates…

Dynamical Systems · Mathematics 2024-08-14 Yeor Hafouta

The local computation of Linial [FOCS'87] and Naor and Stockmeyer [STOC'93] concerns with the question of whether a locally definable distributed computing problem can be solved locally: for a given local CSP whether a CSP solution can be…

Data Structures and Algorithms · Computer Science 2022-09-09 Weiming Feng , Yuxin Sun , Yitong Yin

For general spin systems, we prove that a contractive coupling for any local Markov chain implies optimal bounds on the mixing time and the modified log-Sobolev constant for a large class of Markov chains including the Glauber dynamics,…

Understanding the influence of activity on dense amorphous assemblies is crucial for biological processes such as wound healing, embryogenesis, or cancer progression. Here, we study the effect of self-propulsion forces of amplitude $f_0$…

Soft Condensed Matter · Physics 2026-01-27 Puneet Pareek , Peter Sollich , Saroj Kumar Nandi , Ludovic Berthier

A simple model for simulating flows of active suspensions is investigated. The approach is based on dissipative particle dynamics. While the model is potentially applicable to a wide range of self-propelled particle systems, the specific…

Fluid Dynamics · Physics 2015-10-08 Denis F. Hinz , Alexander Panchenko , Tae-Yeon Kim , Eliot Fried