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Large deviations for additive path functionals of stochastic processes have attracted significant research interest, in particular in the context of stochastic particle systems and statistical physics. Efficient numerical `cloning'…

Probability · Mathematics 2021-07-21 Letizia Angeli , Stefan Grosskinsky , Adam M. Johansen

The prediction of the equation of state and the phase behavior of simple fluids (noble gases, carbon dioxide, benzene, methane, short alkane chains) and their mixtures by Monte Carlo computer simulation and analytic approximations based on…

Statistical Mechanics · Physics 2009-11-13 B. M. Mognetti , P. Virnau , L. Yelash , W. Paul , K. Binder , M. Mueller , L. G. MacDowell

We consider the problem of coarse-graining in the context of finite-volume fluid models. If a variable is defined on a high-resolution grid it may be coarse-grained so that it is defined on a grid of lower resolution. In general this will…

Atmospheric and Oceanic Physics · Physics 2022-01-26 Stuart Patching

Tissue dynamics and collective cell motion are crucial biological processes. Their biological machinery is mostly known, and simulation models such as the "active vertex model" (AVM) exist and yield reasonable agreement with experimental…

Soft Condensed Matter · Physics 2023-11-16 Gloria Triguero-Platero , Falko Ziebert , Luis L. Bonilla

In this paper, we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular dynamics. The latter are ubiquitous in physicochemical and biological…

Numerical Analysis · Mathematics 2016-04-20 Vagelis Harmandaris , Evangelia Kalligiannaki , Markos A. Katsoulakis , Petr Plecháč

Understanding and predicting microstructure evolution is fundamental to materials science, as it governs the resulting properties and performance of materials. Traditional simulation methods, such as phase-field models, offer high-fidelity…

Machine Learning · Computer Science 2026-02-24 Michael Trimboli , Mohammed Alsubaie , Sirani M. Perera , Ke-Gang Wang , Xianqi Li

Simulating physical systems has been an important application of classical and quantum computers. In this article we present an efficient classical algorithm for simulating time-dependent quantum mechanical Hamiltonians over constant…

Quantum Physics · Physics 2023-01-30 Reyhaneh Aghaei Saem , Ali Hamed Moosavian

Physics-based, atom-centered machine learning (ML) representations have been instrumental to the effective integration of ML within the atomistic simulation community. Many of these representations build off the idea of atoms as having…

Computational Physics · Physics 2024-03-29 Arthur Y. Lin , Kevin K. Huguenin-Dumittan , Yong-Cheol Cho , Jigyasa Nigam , Rose K. Cersonsky

Soft condensed matter structures often challenge us with complex many-body phenomena governed by collective modes spanning wide spatial and temporal domains. In order to successfully tackle such problems mesoscopic coarse-grained (CG)…

Soft Condensed Matter · Physics 2023-07-12 Vlad P Sokhan , Michael A Seaton , Ilian T Todorov

We present an effective evolution equation for a coarse-grained distribution function of a long-range-interacting system preserving the symplectic structure of the non-collisional Boltzmann, or Vlasov, equation. We first derive a general…

Statistical Mechanics · Physics 2020-07-01 Guido Giachetti , Alessandro Santini , Lapo Casetti

The data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the context of multiscale problems. The present paper offers a…

Computational Physics · Physics 2021-02-10 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis

Relationships between sediment flux and geomorphic processes are combined with statements of mass conservation, in order to create continuum models of hillslope evolution. These models have parameters which can be calibrated using available…

Geophysics · Physics 2019-01-30 Jacob Calvert , Márton Balázs , Katerina Michaelides

A cellular automaton is a deterministic and exactly computable dynamical system which mimics certain fundamental aspects of physical dynamics such as spatial locality and finite entropy. CA systems can be constructed which have additional…

comp-gas · Physics 2007-05-23 Norman Margolus

Many practical techniques for probabilistic inference require a sequence of distributions that interpolate between a tractable distribution and an intractable distribution of interest. Usually, the sequences used are simple, e.g., based on…

Artificial Intelligence · Computer Science 2015-09-11 Andreas Stuhlmüller , Robert X. D. Hawkins , N. Siddharth , Noah D. Goodman

The present paper introduces a mathematical model for studying dynamic grain growth. In particular, we show how characteristic measurements, grain volumes, centroids, and central second-order moments at discrete moments in time can be…

Computational Physics · Physics 2023-05-31 Andreas Alpers , Maximilian Fiedler , Peter Gritzmann , Fabian Klemm

We introduce a method for global optimization of the structure of atomic systems that uses additional atoms with fractional existence. The method allows for movement of atoms over long distances bypassing energy barriers encountered in the…

The integral equation coarse-graining (IECG) approach is a promising high-level coarse-graining (CG) method for polymer melts, with variable resolution from soft spheres to multi CG sites, which preserves the structural and thermodynamical…

Soft Condensed Matter · Physics 2018-07-24 Mohammadhasan Dinpajooh , Marina G. Guenza

An expression for the stress tensor near an external boundary of a discrete mechanical system is derived explicitly in terms of the constituents' degrees of freedom and interaction forces. Starting point is the exact and general coarse…

Soft Condensed Matter · Physics 2011-08-26 Thomas Weinhart , Anthony R. Thornton , Stefan Luding , Onno Bokhove

The volume of data that will be produced by the next generation of astrophysical instruments represents a significant opportunity for making unplanned and unexpected discoveries. Conversely, finding unexpected objects or phenomena within…

Instrumentation and Methods for Astrophysics · Physics 2019-09-11 Gary Segal , David Parkinson , Ray P. Norris , Jesse Swan

In this paper, we propose a primal-dual splitting algorithm for a broad class of structured composite monotone inclusions that involve finitely many set-valued operators, compositions of set-valued operators with bounded linear operators,…

Optimization and Control · Mathematics 2026-05-14 Minh N. Dao , Hung M. Phan , Matthew K. Tam , Thang D. Truong
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