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In recent years dynamical systems (of deterministic and stochastic nature), describing many models in mathematics, physics, engineering and finances, become more and more complex. Numerical analysis narrowed only to deterministic algorithms…

Numerical Analysis · Mathematics 2024-02-13 Paweł Przybyłowicz

The intuition that a long history is required for the emergence of complexity in natural systems is formalized using the notion of depth. The depth of a system is defined in terms of the number of parallel computational steps needed to…

Statistical Mechanics · Physics 2011-11-09 J. Machta

This paper explores how far the scientific discovery process can be automated. Using the identification of causally significant flow structures in two-dimensional turbulence as an example, it probes how far the usual procedure of planning…

Fluid Dynamics · Physics 2020-12-02 Javier Jimenez

The process of equilibration of a colliding hard-disks system is studied in the framework of classical mechanic. The method consists of dividing the nonequilibrium system into the interacting subsystems; the evolution one of these…

Statistical Mechanics · Physics 2014-11-17 V. M. Somsikov

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and…

Computational Physics · Physics 2018-01-08 Markus Wallerberger , Emanuel Gull

Successful computer studies of glass-forming materials need to overcome both the natural tendency to structural ordering and the dramatic increase of relaxation times at low temperatures. We present a comprehensive analysis of eleven…

Statistical Mechanics · Physics 2017-06-09 Andrea Ninarello , Ludovic Berthier , Daniele Coslovich

Event-driven molecular dynamics is a valuable tool in condensed and soft matter physics when particles can be modeled as hard objects or more generally if their interaction potential can be modeled in a stepwise fashion. Hard spheres model…

Computational Physics · Physics 2015-05-19 Cristiano De Michele

The quest for quantum computers is motivated by their potential for solving problems that defy existing, classical, computers. The theory of computational complexity, one of the crown jewels of computer science, provides a rigorous…

Statistical Mechanics · Physics 2010-09-10 C. R. Laumann , R. Moessner , A. Scardicchio , S. L. Sondhi

Predictive statistical mechanics is a form of inference from available data, without additional assumptions, for predicting reproducible phenomena. By applying it to systems with Hamiltonian dynamics, a problem of predicting the macroscopic…

Statistical Mechanics · Physics 2015-09-22 Domagoj Kuic

Computation of gas dispersal in urban places or hilly grounds requires a large amount of computer time when addressed with conventional multidimensional models. Those are usually based on two-phase flow or Navier-Stokes equations. Different…

Analysis of PDEs · Mathematics 2021-01-13 Alexandre Chiapolino , Sébastien Courtiaud , Emmanuel Lapebie , Richard Saurel

Melting in two spatial dimensions, as realized in thin films or at interfaces, represents one of the most fascinating phase transitions in nature, but it remains poorly understood. Even for the fundamental hard-disk model, the melting…

Soft Condensed Matter · Physics 2015-03-13 Etienne P. Bernard , Werner Krauth

Predicting crystal nucleation is among the most significant long--standing challenges in condensed matter. In the system most studied (hard sphere colloids), the comparison between experiments performed using static light scattering and…

Soft Condensed Matter · Physics 2025-06-04 Lars Kürten , Antoine Castagnède , Frank Smallenburg , C. Patrick Royall

The hard-sphere model is one of the most extensively studied models in statistical physics. It describes the continuous distribution of spherical particles, governed by hard-core interactions. An important quantity of this model is the…

Probability · Mathematics 2021-02-16 Tobias Friedrich , Andreas Göbel , Martin S. Krejca , Marcus Pappik

The basic problem in equilibrium statistical mechanics is to compute phase space average, in which Monte Carlo method plays a very important role. We begin with a review of nonlocal algorithms for Markov chain Monte Carlo simulation in…

Statistical Mechanics · Physics 2007-05-23 Jian-Sheng Wang

Accurate simulation of complex physical systems enables the development, testing, and certification of control strategies before they are deployed into the real systems. As simulators become more advanced, the analytical tractability of the…

Robotics · Computer Science 2020-05-27 Lucas Barcelos , Rafael Oliveira , Rafael Possas , Lionel Ott , Fabio Ramos

In this review article, we discuss connections between the physics of disordered systems, phase transitions in inference problems, and computational hardness. We introduce two models representing the behavior of glassy systems, the spiked…

Disordered Systems and Neural Networks · Physics 2022-12-07 David Gamarnik , Cristopher Moore , Lenka Zdeborová

There are many interesting physical processes which involve the generation of high density plasmas in large volumes. However, when modeling these systems numerically, the large densities and volumes present a significant computational…

Computational Physics · Physics 2007-05-23 A. E. Schulz , A. D. Greenwood , K. L. Cartwright , P. J. Mardahl

Computer simulations of inhomogeneous soft matter systems often require accurate methods for computing the local pressure. We present a simple derivation, based on the virial relation, of two equivalent expressions for the local (atomistic)…

Soft Condensed Matter · Physics 2015-06-03 Thomas Lion , Rosalind J. Allen

Advanced algorithms are necessary to obtain faster-than-real-time dynamic simulations in a number of different physical problems that are characterized by widely disparate time scales. Recent advanced dynamic Monte Carlo algorithms that…

Materials Science · Physics 2016-11-23 M. A. Novotny

Recent experiments demonstrated quantum computational advantage in random circuit sampling and Gaussian boson sampling. However, it is unclear whether these experiments can lead to practical applications even after considerable research…

Quantum Physics · Physics 2023-12-14 Chae-Yeun Park , Pablo A. M. Casares , Juan Miguel Arrazola , Joonsuk Huh