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A system of interacting Brownian particles subject to short-range repulsive potentials is considered. A continuum description in the form of a nonlinear diffusion equation is derived systematically in the dilute limit using the method of…

Statistical Mechanics · Physics 2017-10-12 Maria Bruna , S. Jonathan Chapman , Martin Robinson

We consider the motion of interacting particles governed by a coupled system of ODEs with random initial conditions. Direct computations for such systems are prohibitively expensive due to a very large number of particles and randomness…

Computational Physics · Physics 2014-11-25 Leonid Berlyand , Pierre-Emmanuel Jabin , Mykhailo Potomkin

This paper develops a non-asymptotic approach to mean field approximations for systems of $n$ diffusive particles interacting pairwise. The interaction strengths are not identical, making the particle system non-exchangeable. The marginal…

Probability · Mathematics 2026-04-17 Daniel Lacker , Lane Chun Yeung , Fuzhong Zhou

The tight-coupling approximation (TCA) used to describe the early dynamics of the baryons-photons system is systematically built to higher orders in the inverse of the interaction rate. This expansion can be either used to grasp the…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 Cyril Pitrou

Obtaining a reduced description with particle and momentum flux densities outgoing from the microscopic equations of motion of the particles requires approximations. The usual method, we refer to as truncation method, is to zero Fourier…

Statistical Mechanics · Physics 2017-01-04 Hamid Seyed-Allaei , Lutz Schimansky-Geier , Mohammad Reza Ejtehadi

In this work, which is based on our previously derived theoretical framework [1], we apply the truncated Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy for ultracold bosonic systems with a fixed number of particles to two…

Quantum Physics · Physics 2018-08-08 Sven Krönke , Peter Schmelcher

We present the algorithmic details of the dynamical cluster approximation (DCA) algorithm. The DCA is a fully-causal approach which systematically restores non-local correlations to the dynamical mean field approximation (DMFA). The DCA is…

Strongly Correlated Electrons · Physics 2007-05-23 S. Moukouri , C. Huscroft , M. Jarrell

An accurate description of the nonequilibrium dynamics of systems with coupled spin and bosonic degrees of freedom remains theoretically challenging, especially for large system sizes and in higher than one dimension. Phase space methods…

Quantum Gases · Physics 2017-09-13 A. Piñeiro Orioli , A. Safavi-Naini , M. L. Wall , A. M. Rey

We present a general method by which linear quantum Hamiltonian dynamics with exponentially many degrees of freedom is replaced by approximate classical nonlinear dynamics with the number of degrees of freedom (phase space dimensionality)…

Quantum Physics · Physics 2018-08-01 Jonathan Wurtz , Anatoli Polkovnikov , Dries Sels

A new direct integration method is established to construct the solutions of the stationary BBGKY hierarchy, assuming the usual form of the equilibrium correlation functions, for infinite classical systems of particles interacting via a…

Mathematical Physics · Physics 2016-11-28 Giuseppe Genovese , Sergio Simonella

This paper develops a non-asymptotic, local approach to quantitative propagation of chaos for a wide class of mean field diffusive dynamics. For a system of $n$ interacting particles, the relative entropy between the marginal law of $k$…

Probability · Mathematics 2023-05-31 Daniel Lacker

We recently introduced the dynamical cluster approximation(DCA), a new technique that includes short-ranged dynamical correlations in addition to the local dynamics of the dynamical mean field approximation while preserving causality. The…

Strongly Correlated Electrons · Physics 2009-10-31 M. H. Hettler , M. Mukherjee , M. Jarrell , H. R. Krishnamurthy

We study approximations of evolving probability measures by an interacting particle system. The particle system dynamics is a combination of independent Markov chain moves and importance sampling/resampling steps. Under global regularity…

Probability · Mathematics 2011-12-12 Andreas Eberle , Carlo Marinelli

We discuss a general mean field plus random phase approximation (RPA) for describing composite systems at zero and finite temperature. We analyze in particular its implementation in finite systems invariant under translations, where for…

Quantum Physics · Physics 2011-04-20 Juan Mauricio Matera , Raul Rossignoli , Norma Canosa

Developing theoretical understanding of complex reactions and processes at interfaces requires using methods that go beyond semilocal density functional theory to accurately describe the interactions between solvent, reactants and…

We reformulate the Cavity Approximation (CA), a class of algorithms recently introduced for improving the Bethe approximation estimates of marginals in graphical models. In our new formulation, which allows for the treatment of multivalued…

Statistical Mechanics · Physics 2009-11-11 T. Rizzo , B. Wemmenhove , H. J. Kappen

Many machine learning and optimization algorithms can be cast as instances of stochastic approximation (SA). The convergence rate of these algorithms is known to be slow, with the optimal mean squared error (MSE) of order $O(n^{-1})$. In…

Optimization and Control · Mathematics 2024-09-13 Caio Kalil Lauand , Sean Meyn

We discuss a general treatment based on the mean field plus random phase approximation (RPA) for the evaluation of subsystem entropies and negativities in ground states of spin systems. The approach leads to a tractable general method,…

Quantum Physics · Physics 2011-04-21 J. M. Matera , R. Rossignoli , N. Canosa

The mean spherical approximation (MSA) is a closure relation for pair correlation functions (two-point functions) in statistical physics. It can be applied to a wide range of systems, is computationally fairly inexpensive, and when properly…

High Energy Physics - Theory · Physics 2016-11-07 Arturo Amador , Johan Skule Høye , Kåre Olaussen

The diffusion approximation (DA) is widely used in the analysis of stochastic population dynamics, from population genetics to ecology and evolution. DA is an uncontrolled approximation that assumes the smoothness of the calculated quantity…

Populations and Evolution · Quantitative Biology 2021-01-04 Jayant Pande , Nadav M. Shnerb
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