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Auxiliary-field quantum Monte Carlo methods enable the calculation of thermal and ground state properties of correlated quantum many-body systems in model spaces that are many orders of magnitude larger than those that can be treated by…

Nuclear Theory · Physics 2019-07-29 Y. Alhassid

A general method for computing kinetic isotope effects is described. The method uses the quantum-instanton approximation and is based on the thermodynamic integration with respect to the mass of the isotopes and on the path-integral…

Chemical Physics · Physics 2007-05-23 Jiri Vanicek , William H. Miller

We numericaly demonstrate that, in double well models, the autocorrelation time of open path integral Monte Carlo simulations can be much smaller compared to standard ones using ring polymers. We also provide an intuitive explanation based…

Computational Physics · Physics 2016-08-04 Guglielmo Mazzola , Matthias Troyer

We explore to what extent path-integral quantum Monte Carlo methods can efficiently simulate the tunneling behavior of quantum adiabatic optimization algorithms. Specifically we look at symmetric cost functions defined over n bits with a…

Quantum Physics · Physics 2016-03-09 Lucas T. Brady , Wim van Dam

We develop Monte Carlo methods for sampling random states and corresponding bit strings in qubit systems. To this end, we derive exact probability density functions that yield the Porter-Thomas distribution in the limit of large systems. We…

Quantum Physics · Physics 2025-09-05 Andreas Raab

In nuclear fusion and fission, fluctuation and dissipation arise due to the coupling of collective degrees of freedom with internal excitations. Close to the barrier, both quantum, statistical and non-Markovian effects are expected to be…

Nuclear Theory · Physics 2010-04-06 G. Hupin , D. Lacroix

Simulating samples from arbitrary probability distributions is a major research program of statistical computing. Recent work has shown promise in an old idea, that sampling from a discrete distribution can be accomplished by perturbing and…

Computation · Statistics 2016-04-13 Chris J. Maddison

We provide an overview of Monte Carlo algorithms based on Markovian stochastic dynamics of interacting and reacting many-particle systems not in thermal equilibrium. These agent-based simulations are an effective way of introducing students…

Statistical Mechanics · Physics 2025-07-24 Mohamed Swailem , Ulrich Dobramysl , Ruslan Mukhamadiarov , Uwe C. Täuber

We consider quantum-to-classical mapping for an arbitrary system of interacting spins at finite temperatures. We prove that, in the large-$S$ limit, the asymptotic form of the partition function coincides with that of a classical model for…

Statistical Mechanics · Physics 2026-02-19 A. El Mendili , M. E. Zhitomirsky

Monte Carlo methods play a central role in particle physics, where they are indispensable for simulating scattering processes, modeling detector responses, and performing multi-dimensional integrals. However, traditional Monte Carlo methods…

Quantum Physics · Physics 2025-10-14 Heechan Yi , Kayoung Ban , Myeonghun Park , Kyoungchul Kong

In this note, variational Monte Carlo method based on neural quantum states for spin systems is reviewed. Using a neural network as the wave function allows for a more generalized expression of various types of interactions, including…

Strongly Correlated Electrons · Physics 2024-06-04 Yuntai Song

We introduce a Monte Carlo method, as a modification of existing cluster algorithms, which allows simulations directly on systems of infinite size, and for quantum models also at beta=infinity. All two-point functions can be obtained,…

Statistical Mechanics · Physics 2007-05-23 H. G. Evertz , W. von der Linden

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 progress in numerical study of the short-time critical dynamics is briefly reviewed.

Statistical Mechanics · Physics 2009-10-31 B. Zheng

The stochastic series expansion quantum Monte Carlo method is used to study thin ferromagnetic films, described by a Heisenberg model including local anisotropies. The magnetization curve is calculated, and the results compared to Schwinger…

Strongly Correlated Electrons · Physics 2009-11-07 P. Henelius , P. Fröbrich , P. J. Kuntz , C. Timm , P. J. Jensen

In this work we investigate the ground state and the dissipative quantum dynamics of interacting charged particles in an external potential at finite temperature. The recently devised time-dependent quantum Monte Carlo (TDQMC) method allows…

Quantum Physics · Physics 2025-01-29 Ivan P. Christov

We present a new way to compute and interpret quantum tunneling in a 1-D double-well potential. For large transition time we show that the quantum action functional gives an analytical expression for tunneling amplitudes. This has been…

Quantum Physics · Physics 2007-05-23 F. Paradis , H. Kroger , G. Melkonyan , K. J. M. Moriarty

Describing correlated electron systems near phase transitions has been a major challenge in computational condensed-matter physics. In this paper, we apply highly accurate fixed node quantum Monte Carlo techniques, which directly work with…

Strongly Correlated Electrons · Physics 2018-01-10 Li Chen , Lucas K. Wagner

The quantum instanton approximation is a type of quantum transition state theory that calculates the chemical reaction rate using the reactive flux correlation function and its low order derivatives at time zero. Here we present several…

Chemical Physics · Physics 2009-11-11 Sandy Yang , Takeshi Yamamoto , William H. Miller

We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable…

High Energy Physics - Lattice · Physics 2013-11-19 K. Jansen , H. Leovey , A. Ammon , A. Griewank , M. Müller-Preussker
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