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Learning dynamics governing physical and spatiotemporal processes is a challenging problem, especially in scenarios where states are partially measured. In this work, we tackle the problem of learning dynamics governing these systems when…

Machine Learning · Computer Science 2024-12-13 Paul Ghanem , Ahmet Demirkaya , Tales Imbiriba , Alireza Ramezani , Zachary Danziger , Deniz Erdogmus

In this paper, uniformly unconditionally stable first and second order finite difference schemes are developed for kinetic transport equations in the diffusive scaling. We first derive an approximate evolution equation for the macroscopic…

Numerical Analysis · Mathematics 2022-11-10 Guoliang Zhang , Hongqiang Zhu , Tao Xiong

In this paper we discuss the numerical solution of elliptic distributed optimal control problems with state or control constraints when the control is considered in the energy norm. As in the unconstrained case we can relate the…

Numerical Analysis · Mathematics 2023-06-28 Peter Gangl , Richard Löscher , Olaf Steinbach

We study step-wise time approximations of non-linear hyperbolic initial value problems. The technique used here is a generalization of the minimizing movements method, using two time-scales: one for velocity, the other (potentially much…

Numerical Analysis · Mathematics 2024-04-05 Antonín Češík , Sebastian Schwarzacher

By means of a novel variational approach we study ergodic properties of a model of a multi lane traffic flow, considered as a (deterministic) wandering of interacting particles on an infinite lattice. For a class of initial configurations…

Chaotic Dynamics · Physics 2007-05-23 Michael Blank

A time dependent variational approach is considered to derive the equations of movement for the $\lambda \phi^4$ model. The temporal evolution of the model is performed numerically in the frame of the Gaussian approximation in a lattice of…

High Energy Physics - Phenomenology · Physics 2009-11-07 Fabio L. Braghin

Multi-system interaction is an important and difficult problem in physics. Motivated by the experimental result of an electronic circuit element "Fractor", we introduce the concept of dynamic-order fractional dynamic system, in which the…

Mathematical Physics · Physics 2013-04-10 HongGuang Sun , Hu Sheng , YangQuan Chen , Wen Chen , ZhongBo Yu

We analyze the convergence rate of various momentum-based optimization algorithms from a dynamical systems point of view. Our analysis exploits fundamental topological properties, such as the continuous dependence of iterates on their…

Optimization and Control · Mathematics 2021-04-13 Michael Muehlebach , Michael I. Jordan

We solve the equations of motion of a complex $\phi^4$ theory coupled to some given gauge field background. The solutions are given in both cylindrical and spherical coordinates and have finite energy.

High Energy Physics - Theory · Physics 2021-02-03 Noureddine Mohammedi

Preliminary results of our investigations on solving indefinite qua\-dra\-tic programs by dynamical systems are given. First, dynamical systems corresponding to two fundamental DC programming algorithms to deal with indefinite quadratic…

Optimization and Control · Mathematics 2025-04-01 Massimo Pappalardo , Nguyen Nang Thieu , Nguyen Dong Yen

We consider a one dimensional elliptic distributed optimal control problem with pointwise constraints on the derivative of the state. By exploiting the variational inequality satisfied by the derivative of the optimal state, we obtain…

Numerical Analysis · Mathematics 2021-06-18 Susanne C. Brenner , Li-yeng Sung , Winnifried Wollner

We study general aspects of active motion with fluctuations in the speed and the direction of motion in two dimensions. We consider the case in which fluctuations in the speed are not correlated to fluctuations in the direction of motion,…

Biological Physics · Physics 2009-11-13 Fernando Peruani , Luis G. Morelli

Particle filtering is a popular method for inferring latent states in stochastic dynamical systems, whose theoretical properties have been well studied in machine learning and statistics communities. In many control problems, e.g.,…

Machine Learning · Computer Science 2021-07-12 Simon S. Du , Wei Hu , Zhiyuan Li , Ruoqi Shen , Zhao Song , Jiajun Wu

These short notes present to the reader (students, in particular) a concise approach to the derivation of the propagator of Hamiltonians with position-dependent kinetic energy. The formalism is applied to the von Roos Hamiltonian with…

Quantum Physics · Physics 2016-11-30 Yamen Hamdouni

Determinantal Point Processes (DPPs) are a family of probabilistic models that have a repulsive behavior, and lend themselves naturally to many tasks in machine learning where returning a diverse set of objects is important. While there are…

Statistics Theory · Mathematics 2017-03-03 John Urschel , Victor-Emmanuel Brunel , Ankur Moitra , Philippe Rigollet

In this paper we investigate the ability of some recently introduced discrete kinetic models of vehicular traffic to catch, in their large time behavior, typical features of theoretical fundamental diagrams. Specifically, we address the…

Mathematical Physics · Physics 2014-03-25 Luisa Fermo , Andrea Tosin

Motivated by applications to mathematical biology, we study the averaging problem for slow-fast systems, {\em in the case in which the fast dynamics is a stochastic process with multiple invariant measures}. We consider both the case in…

Probability · Mathematics 2023-08-17 B. D. Goddard , M. Ottobre , K. J. Painter , I. Souttar

Many biological processes are supported by special molecules, called motor proteins or molecular motors, that transport cellular cargoes along linear protein filaments and can reversibly associate to their tracks. Stimulated by these…

Statistical Mechanics · Physics 2021-11-17 Akriti Jindal , Anatoly B. Kolomeisky , Arvind Kumar Gupta

The motion of topological defects is an important feature of the dynamics of all liquid crystals, and is especially conspicuous in active liquid crystals. Understanding defect motion is a challenging theoretical problem, because the…

Soft Condensed Matter · Physics 2019-01-24 Xingzhou Tang , Jonathan V. Selinger

We develop a fully microscopic, statistical mechanics approach to study phase transitions in Ising systems with competing interactions at different scales. Our aim is to consider orientational and positional order parameters in a unified…

Statistical Mechanics · Physics 2011-09-28 Daniel G. Barci , Daniel A. Stariolo
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