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Zero- and two-dimensional crystal defects form in open statistical ensembles, such as the grand canonical, that are usually inaccessible with conventional simulation techniques. This longstanding challenge is overcome with a new Hamiltonian…

Materials Science · Physics 2026-01-16 Flynn Walsh , Babak Sadigh , Joseph T. McKeown , Timofey Frolov

We apply the diagrammatic Monte Carlo approach to three-dimensional Fermi-polaron systems with mass-imbalance, where an impurity interacts resonantly with a noninteracting Fermi sea whose atoms have a different mass. This method allows to…

Quantum Gases · Physics 2015-04-23 Peter Kroiss , Lode Pollet

Two different Reverse Monte Carlo strategies, 'RMC++' and 'RMCPOW', have been compared for determining the microscopic structure of some liquid and amorphous solid systems on the basis of neutron diffraction measurements. The first, '$g(r)$…

Soft Condensed Matter · Physics 2015-01-27 V. Sánchez-Gil , E. G. Noya , L. Temleitner , L. Pusztai

A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in…

Strongly Correlated Electrons · Physics 2016-06-10 Kensaku Takai , Kota Ido , Takahiro Misawa , Youhei Yamaji , Masatoshi Imada

Monte Carlo simulations using entropic sampling to estimate the number of configurations of a given energy are a valuable alternative to traditional methods. We introduce {\it tomographic} entropic sampling, a scheme which uses multiple…

Statistical Mechanics · Physics 2015-05-28 Ronald Dickman , A. G. Cunha-Netto

Many fields of physics use quantum Monte Carlo techniques, but struggle to estimate dynamic spectra via the analytic continuation of imaginary-time quantum Monte Carlo data. One of the most ubiquitous approaches to analytic continuation is…

Computational Physics · Physics 2025-10-10 Thomas Chuna , Nicholas Barnfield , Tobias Dornheim , Michael P. Friedlander , Tim Hoheisel

Residual entropy, which reflects the degrees of freedom in a system at absolute zero temperature, is crucial for understanding quantum and classical ground states. Despite its key role in explaining low-temperature phenomena and ground…

Statistical Mechanics · Physics 2025-02-20 Zenan Dai , Xiao Yan Xu

A Monte Carlo method based on a density-of-states sampling is proposed for study of arbitrary statistical mechanical ensembles in a continuum. A random walk in the two-dimensional space of particle number and energy is used to estimate the…

Soft Condensed Matter · Physics 2009-11-07 Qiliang Yan , Roland Faller , Juan J. de Pablo

We develop generalization of the fixed-phase diffusion Monte Carlo method for Hamiltonians which explicitly depend on particle spins such as for spin-orbit interactions. The method is formulated in zero variance manner and is similar to…

Strongly Correlated Electrons · Physics 2016-04-13 Cody A. Melton , Minyi Zhu , Shi Guo , Alberto Ambrosetti , Francesco Pederiva , Lubos Mitas

To calculate the entropy of a subalgebra or of a channel with respect to a state, one has to solve an intriguing optimalization problem. The latter is also the key part in the entanglement of formation concept, in which case the subalgebra…

Quantum Physics · Physics 2008-02-03 Armin Uhlmann

Information theoretic measures (entropies, entropy rates, mutual information) are nowadays commonly used in statistical signal processing for real-world data analysis. The present work proposes the use of Auto Mutual Information (Mutual…

Data Analysis, Statistics and Probability · Physics 2019-07-24 C Granero-Belinchón , S. Roux , P. Abry , N. Garnier

The inverse problem for a disordered system involves determining the interparticle interaction parameters consistent with a given set of experimental data. Recently, Rutledge has shown (Phys. Rev. E63, 021111 (2001)) that such problems can…

Statistical Mechanics · Physics 2009-11-10 N. B. Wilding

Maximum entropy modeling is a flexible and popular framework for formulating statistical models given partial knowledge. In this paper, rather than the traditional method of optimizing over the continuous density directly, we learn a smooth…

Methodology · Statistics 2017-05-01 Gabriel Loaiza-Ganem , Yuanjun Gao , John P. Cunningham

We propose a Multilevel Monte-Carlo (MLMC) method for computing entropy measure valued solutions of hyperbolic conservation laws. Sharp bounds for the narrow convergence of MLMC for the entropy measure valued solutions are proposed. An…

Numerical Analysis · Mathematics 2016-11-24 Kjetil Olsen Lye

Given a sample of independent and identically distributed random variables, a novel nonparametric maximum entropy method is presented to estimate the underlying continuous univariate probability density function (pdf). Estimates are found…

Probability · Mathematics 2016-06-30 Jenny Farmer , Donald J. Jacobs

We present a fast, hierarchical, and adaptive algorithm for Metropolis Monte Carlo simulations of systems with long-range interactions that reproduces the dynamics of a standard implementation exactly, i.e., the generated configurations and…

Computational Physics · Physics 2023-07-27 Fabio Müller , Henrik Christiansen , Stefan Schnabel , Wolfhard Janke

We present a novel quantum Monte Carlo method based on a path integral in Fock space, which allows to compute finite-temperature properties of a many-body nuclear system with a monopole pairing interaction in the canonical ensemble. It…

Nuclear Theory · Physics 2009-01-23 N. J. Cerf

In an attempt to test the possibility of solving the inverse problem for liquid metals i.e. obtaining the effective pair potential from the experimental structure factor, we solve the modified Hypernetted-Chain Integral equation for liquid…

Statistical Mechanics · Physics 2020-06-01 Moustafa Sayem El-Daher

We present a methodology for accelerating the estimation of the free energy from path integral Monte Carlo simulations by considering an intermediate artificial reference system where interactions are inexpensive to evaluate numerically.…

Owing to their favorable scaling with dimensionality, Monte Carlo (MC) methods have become the tool of choice for numerical integration across the quantitative sciences. Almost invariably, efficient MC integration schemes are strictly…

Statistical Mechanics · Physics 2010-01-29 Artur B. Adib
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