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The microscopic calculation of nuclear level densities in the presence of correlations is a difficult many-body problem. The shell model Monte Carlo method provides a powerful technique to carry out such calculations using the framework of…

Nuclear Theory · Physics 2013-05-27 Y. Alhassid , C. Özen , H. Nakada

We develop a Monte Carlo framework to analyze the statistics of quantum work in correlated electron systems. Using the Ising-Kondo model in heavy fermions as a paradigmatic platform, we thoroughly illustrate the process of determining the…

Statistical Mechanics · Physics 2025-05-23 Qian-Xi Zhao , Jian-Jun Dong , Zi-Xiang Hu

We present a multilevel Monte Carlo simulation method for analysing multi-scale physical systems via a hierarchy of coarse-grained representations, to obtain numerically-exact results, at the most detailed level. We apply the method to a…

Statistical Mechanics · Physics 2022-10-04 Paul B. Rohrbach , Hideki Kobayashi , Robert Scheichl , Nigel B. Wilding , Robert L. Jack

The microscopic description of collectivity in heavy nuclei in the framework of the configuration-interaction shell model has been a major challenge. The size of the model space required for the description of heavy nuclei prohibits the use…

Nuclear Theory · Physics 2015-06-18 C. Özen , Y. Alhassid , H. Nakada

We introduce a Diagrammatic Monte Carlo (DiagMC) approach to angular momentum properties of quantum many-particle systems possessing a macroscopic number of degrees of freedom. The treatment is based on a diagrammatic expansion that merges…

Quantum Gases · Physics 2018-10-24 G. Bighin , T. V. Tscherbul , M. Lemeshko

We present the numerical Quantum Monte Carlo results for the ground state energy of circular quantum dots in which Rashba spin-orbit iteraction is present. Diffusion Monte Carlo with spin propagation is applied in order to treat the…

Superconductivity · Physics 2015-05-18 A. Ambrosetti , F. Pederiva , E. Lipparini

We present a quantum Monte Carlo algorithm for the simulation of general quantum and classical many-body models within a single unifying framework. The algorithm builds on a power series expansion of the quantum partition function in its…

Statistical Mechanics · Physics 2020-08-05 Lalit Gupta , Tameem Albash , Itay Hen

We discuss a sampling algorithm which generates flat histogram in energy. In combination with transition matrix Monte Carlo, the density of states and derived quantities such as entropy and free energy as a function of temperature can be…

Statistical Mechanics · Physics 2009-10-31 Jian-Sheng Wang

We propose a Multi-Cell Monte Carlo algorithm, or (MC)^2, for predicting stable phases in chemically complex crystalline systems. Free atomic transfer among cells is achieved via the application of the lever rule, where an assigned molar…

Materials Science · Physics 2018-11-13 Changning Niu , You Rao , Wolfgang Windl , Maryam Ghazisaeidi

A Monte Carlo simulator is presented to reproduce data of nucleus-nucleus interactions at high energies. The program is designed in a microscopic point of view, where the cascade approach is applied. Moreover, each nucleon from both the…

High Energy Physics - Phenomenology · Physics 2007-05-23 N. M. Hassan , N. El-Harby , M. T. Hussein

We introduce an exact Monte Carlo approach to the statistics of discrete quantum systems which does not rely on the standard fragmentation of the imaginary time, or any small parameter. The method deals with discrete objects, kinks,…

Condensed Matter · Physics 2009-10-28 N. V. Prokof'ev , B. V. Svistunov , I. S. Tupitsyn

This paper proposes an efficient method for the simultaneous estimation of the state of a quantum system and the classical parameters that govern its evolution. This hybrid approach benefits from efficient numerical methods for the…

Quantum Physics · Physics 2017-11-08 Jason F Ralph , Simon Maskell , Kurt Jacobs

We introduce a general Monte Carlo method based on Nested Sampling (NS), for sampling complex probability distributions and estimating the normalising constant. The method uses one or more particles, which explore a mixture of nested…

Computation · Statistics 2012-02-27 Brendon J. Brewer , Livia B. Pártay , Gábor Csányi

These lecture notes introduce quantum spin systems and several computational methods for studying their ground-state and finite-temperature properties. Symmetry-breaking and critical phenomena are first discussed in the simpler setting of…

Strongly Correlated Electrons · Physics 2015-03-17 Anders W. Sandvik

Multi-dimensional density of states provides a useful description of complex frustrated systems. Recent advances in Monte Carlo methods enable efficient calculation of the density of states and related quantities, which renew the interest…

Disordered Systems and Neural Networks · Physics 2009-11-10 Yukito Iba , Hisanao Takahashi

We introduce a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform technique to compute the dynamical properties of self-bound quantum many-body systems in continuous Hilbert…

Nuclear Theory · Physics 2025-04-30 Elad Parnes , Nir Barnea , Giuseppe Carleo , Alessandro Lovato , Noemi Rocco , Xilin Zhang

A method is presented to tackle the sign problem in the simulations of systems having indefinite or complex-valued measures. In general, this new approach is shown to yield statistical errors smaller than the crude Monte Carlo using…

High Energy Physics - Lattice · Physics 2008-11-26 T D Kieu , C J Griffin

Detailed numerical results obtained with state-of-the-art Quantum Monte Carlo (QMC) simulations are presented for the superfluid phase of $^4$He at saturated vapor pressure. The aim of this contribution is that of providing reliable,…

Statistical Mechanics · Physics 2026-05-04 Massimo Boninsegni

We present a numerically efficient method for the characterisation of a quantum process subject to dissipation and noise. The master equation evolution of a maximally entangled state of the quantum system and a non-evolving ancilla system…

Quantum Physics · Physics 2013-12-04 Jake Gulliksen , D. D. Bhaktavatsala Rao , Klaus Mølmer

Computing systems interacting with real-world processes must safely and reliably process uncertain data. The Monte Carlo method is a popular approach for computing with such uncertain values. This article introduces a framework for…