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Efficiently generating statistically independent samples from an unnormalized probability distribution, such as equilibrium samples of many-body systems, is a foundational problem in science. In this paper, we propose Iterated Denoising…

The theory of persistence, which arises from topological data analysis, has been intensively studied in the one-parameter case both theoretically and in its applications. However, its extension to the multi-parameter case raises numerous…

Algebraic Topology · Mathematics 2019-01-29 Nicolas Berkouk

In this paper, we propose a network model, the multiclass classification-based reduced order model (MC-ROM), for solving time-dependent parametric partial differential equations (PPDEs). This work is inspired by the observation of applying…

Numerical Analysis · Mathematics 2022-10-11 Chen Cui , Kai Jiang , Shi Shu

The equation which describes a particle diffusing in a logarithmic potential arises in diverse physical problems such as momentum diffusion of atoms in optical traps, condensation processes, and denaturation of DNA molecules. A detailed…

Statistical Mechanics · Physics 2015-06-03 Ori Hirschberg , David Mukamel , Gunter M. Schütz

We prove global existence of a solution to an initial and boundary value problem for a highly nonlinear PDE system. The problem arises from a thermomechanical dissipative model describing hydrogen storage by use of metal hydrides. In order…

Analysis of PDEs · Mathematics 2015-05-18 Elisabetta Chiodaroli

We analyze the random sequential dynamics of a message passing algorithm for Ising models with random interactions in the large system limit. We derive exact results for the two-time correlation functions and the speed of convergence. The…

Disordered Systems and Neural Networks · Physics 2021-03-10 Burak Çakmak , Manfred Opper

In recent years, the embedding approach for solving switched optimal control problems has been developed in a series of papers. However, the embedding approach, which advantageously converts the hybrid optimal control problem to a classical…

Optimization and Control · Mathematics 2018-04-04 Richard Meyer , Miloš Žefran , Raymond A. DeCarlo

Electro-energy-reaction-diffusion systems are thermodynamically consistent continuum models for reaction-diffusion processes that account for temperature and electrostatic effects in a way that total charge and energy are conserved. The…

Analysis of PDEs · Mathematics 2026-04-09 Katharina Hopf , Michael Kniely , Alexander Mielke

We analyze energy spreading for a system that features mixed chaotic phase-space, whose control parameters (or slow degrees of freedom) vary quasi-statically. For demonstration purpose we consider the restricted 3~body problem, where the…

Statistical Mechanics · Physics 2022-05-10 Yehoshua Winsten , Doron Cohen

Distribution-dependent stochastic dynamical systems arise widely in engineering and science. We consider a class of such systems which model the limit behaviors of interacting particles moving in a vector field with random fluctuations. We…

Numerical Analysis · Mathematics 2023-09-15 Wei Wei , Jianyu Hu

Inexpensive numerical methods are key to enable simulations of systems of a large number of particles of different shapes in Stokes flow. Several approximate methods have been introduced for this purpose. We study the accuracy of the…

Fluid Dynamics · Physics 2023-05-24 Anna Broms , Mattias Sandberg , Anna-Karin Tornberg

This paper focuses on establishing the existence of a class of steady solutions, termed least total curvature solutions, to the incompressible Euler system in a strip. The solutions obtained in this paper complement the least total…

Analysis of PDEs · Mathematics 2025-07-17 Changfeng Gui , David Ruiz , Chunjing Xie , Huan Xu

Low-discrepancy points are designed to efficiently fill the space in a uniform manner. This uniformity is highly advantageous in many problems in science and engineering, including in numerical integration, computer vision, machine…

Machine Learning · Computer Science 2025-10-07 Michael Etienne Van Huffel , Nathan Kirk , Makram Chahine , Daniela Rus , T. Konstantin Rusch

Many-body chaos is a default property of many-body systems; at the same time, near-integrable behaviour due to weakly interacting quasiparticles is ubiquitous throughout condensed matter at low temperature. There must therefore be a,…

Statistical Mechanics · Physics 2026-01-09 Sibaram Ruidas , Sthitadhi Roy , Subhro Bhattacharjee , Roderich Moessner

This work concerns the evolutionary approaches to distributed stochastic black-box optimization, in which each worker can individually solve an approximation of the problem with nature-inspired algorithms. We propose a distributed evolution…

Neural and Evolutionary Computing · Computer Science 2022-04-12 Xiaoyu He , Zibin Zheng , Chuan Chen , Yuren Zhou , Chuan Luo , Qingwei Lin

We show that the dynamical symmetry exists in dissipative quantum many-body systems. Under constraints on both Hamiltonian and dissipation parts, the time evolution of particular observables can be symmetric between repulsive and attractive…

Strongly Correlated Electrons · Physics 2022-06-01 Yi Zheng , Shuo Yang

In stochastic optimal control, change of measure arguments have been crucial for stochastic analysis. Such an approach is often called static reduction in dynamic team theory (or decentralized stochastic control) and has been an effective…

Optimization and Control · Mathematics 2021-11-30 Sina Sanjari , Tamer Başar , Serdar Yüksel

This paper investigates the problem of efficient computation of physically consistent multi-contact behaviors. Recent work showed that under mild assumptions, the problem could be decomposed into simpler kinematic and centroidal dynamic…

Robotics · Computer Science 2021-02-19 Brahayam Ponton , Majid Khadiv , Avadesh Meduri , Ludovic Righetti

Low complexity of a system model is essential for its use in real-time applications. However, sparse identification methods commonly have stringent requirements that exclude them from being applied in an industrial setting. In this paper,…

Systems and Control · Electrical Eng. & Systems 2022-03-24 Mark Haring , Esten Ingar Grøtli , Signe Riemer-Sørensen , Katrine Seel , Kristian Gaustad Hanssen

This work studies the linear approximation of high-dimensional dynamical systems using low-rank dynamic mode decomposition (DMD). Searching this approximation in a data-driven approach is formalised as attempting to solve a low-rank…

Machine Learning · Statistics 2021-08-23 Patrick Héas , Cédric Herzet