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Enhanced sampling algorithms have emerged as powerful methods to extend the utility of molecular dynamics simulations and allow the sampling of larger portions of the configuration space of complex systems in a given amount of simulation…

Statistical Mechanics · Physics 2022-12-19 Jérôme Hénin , Tony Lelièvre , Michael R. Shirts , Omar Valsson , Lucie Delemotte

This paper introduces a framework for simulating finite dimensional representations of (jump) diffusion sample paths over finite intervals, without discretisation error (exactly), in such a way that the sample path can be restored at any…

Methodology · Statistics 2016-02-10 Murray Pollock , Adam M. Johansen , Gareth O. Roberts

The unknown parameters of simulation models often need to be calibrated using observed data. When simulation models are expensive, calibration is usually carried out with an emulator. The effectiveness of the calibration process can be…

Computation · Statistics 2024-12-03 Özge Sürer , Stefan M. Wild

We propose a novel witness of temporal quantum entanglement using the imaginary component of the complex heat capacity - a measurable thermodynamic quantity in temperature-modulated calorimetry. By establishing a direct correspondence…

Quantum Physics · Physics 2025-08-22 Mia Stamatova , Vlatko Vedral

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a novel…

Statistical Mechanics · Physics 2017-12-27 Tameem Albash , Gene Wagenbreth , Itay Hen

We consider a system formed by two different segments of particles, coupled to thermal baths, one at each end, modeled by Langevin thermostats. The particles in each segment interact harmonically and are subject to an on-site potential, for…

Statistical Mechanics · Physics 2025-11-18 Lucianno Defaveri , Alexandre A. A. Almeida , Celia Anteneodo

Entanglement entropy in topologically ordered matter phases has been computed extensively using various methods. In this paper, we study the entanglement entropy of topological phases in two-spaces from a new perspective---the perspective…

Strongly Correlated Electrons · Physics 2019-06-14 Yuting Hu , Yidun Wan

There are enormous amount of examples of Computation in nature, exemplified across multiple species in biology. One crucial aim for these computations across all life forms their ability to learn and thereby increase the chance of their…

Machine Learning · Computer Science 2013-12-30 Nabarun Mondal , Partha P. Ghosh

We investigate a quasi-adiabatic thermal process for preparing finite-temperature ensembles in the thermodynamic limit. The process gradually transforms a thermal ensemble of a noninteracting system into that of an interacting system of…

Statistical Mechanics · Physics 2026-05-12 Tatsuhiko Shirai

Geometric tempering is a popular approach to sampling from challenging multi-modal probability distributions by instead sampling from a sequence of distributions which interpolate, using the geometric mean, between an easier proposal…

Machine Learning · Statistics 2025-04-09 Omar Chehab , Anna Korba , Austin Stromme , Adrien Vacher

For quantum fermion problems, many accurate solvers are limited by the temperature regime in which they can be usefully applied. The Mermin theorem implies the uniqueness of an effective potential from which both the exact density and free…

Chemical Physics · Physics 2018-09-12 Justin Clifford Smith , Kieron Burke

Experiment directed simulation is a technique to minimally bias molecular dynamics simulations to match experimentally observed results. The method improves accuracy but does not address the sampling problem of molecular dynamics…

Chemical Physics · Physics 2019-02-07 Dilnoza B Amirkulova , Andrew D White

We perform large scale simulations to characterize the transition in quenched QCD. It is shown by a rigorous finite size scaling that the transition is of first order. After this qualitative feature quantitative results are obtained with…

High Energy Physics - Lattice · Physics 2022-04-19 S. Borsanyi , Z. Fodor , D. A. Godzieba , R. Kara , P. Parotto , D. Sexty

Generative models of complex systems often require post-hoc parameter adjustments to produce useful outputs. For example, energy-based models for protein design are sampled at an artificially low ''temperature'' to generate novel,…

Quantitative Methods · Quantitative Biology 2025-12-11 Peter W Fields , Vudtiwat Ngampruetikorn , David J Schwab , Stephanie E Palmer

The problem of extrapolation and interpolation of asymptotic series is considered. Several new variants of improving the accuracy of the self-similar approximants are suggested. The methods are illustrated by examples typical of chemical…

Mathematical Physics · Physics 2010-04-08 V. I. Yukalov , E. P. Yukalova , S. Gluzman

The use of excessively long timesteps in dissipative particle dynamics simulations may produce simulation artifacts due to the generation of configurations which are not representative of the desired canonical ensemble. The configurational…

Statistical Mechanics · Physics 2007-05-23 Michael P. Allen

A new approach for the parallel forward modeling of transient electromagnetic (TEM) fields is presented. It is based on a family of uniform-in-time rational approximants to the matrix exponential that share a common denominator independent…

Numerical Analysis · Mathematics 2025-06-16 Ralph-Uwe Börner , Stefan Güttel

Accurate predictions of thermo-mechanically coupled process in metals can lead to a reduction of cost and an increase of productivity in manufacturing processes such as forming. For modeling these coupled processes with the finite element…

Materials Science · Physics 2019-05-30 Jifeng Li , Ignacio Romero , Javier Segurado

In the paradigm of thermodynamic computing, instead of behaving deterministically, hardware undergoes a stochastic process in order to sample from a distribution of interest. While it has been hypothesized that thermodynamic computers may…

Asynchronous iterations are more and more investigated for both scaling and fault-resilience purpose on high performance computing platforms. While so far, they have been exclusively applied within space domain decomposition frameworks,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-22 Frederic Magoules , Guillaume Gbikpi-Benissan
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