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Recently there have been exciting developments in Monte Carlo methods, with the development of new MCMC and sequential Monte Carlo (SMC) algorithms which are based on continuous-time, rather than discrete-time, Markov processes. This has…

Computation · Statistics 2020-09-29 Paul Fearnhead , Joris Bierkens , Murray Pollock , Gareth O Roberts

Markov chain Monte Carlo (MCMC) algorithms offer various strategies for sampling; the Hamiltonian Monte Carlo (HMC) family of samplers are MCMC algorithms which often exhibit improved mixing properties. The recently introduced magnetic HMC,…

Machine Learning · Statistics 2020-10-16 James A. Brofos , Roy R. Lederman

We use the Gutzwiller Monte Carlo approach to simulate the dissipative XYZ-model in the vicinity of a dissipative phase transition. This approach captures classical spatial correlations together with the full on-site quantum behavior, while…

Quantum Physics · Physics 2018-06-12 Wim Casteels , Ryan M. Wilson , Michiel Wouters

One bottleneck of quantum Monte Carlo (QMC) simulation of strongly correlated electron systems lies at the scaling relation of computational complexity with respect to the system sizes. For generic lattice models of interacting fermions,…

Strongly Correlated Electrons · Physics 2019-02-20 Zi Hong Liu , Xiao Yan Xu , Yang Qi , Kai Sun , Zi Yang Meng

In this paper, we discuss magnetic properties of dilute systems of localized spins interacting with itinerant carriers. More precisely, we compare recent available Monte Carlo results with our two step approach (TSA) calculations. The TSA…

Disordered Systems and Neural Networks · Physics 2015-05-13 Richard Bouzerar , Georges Bouzerar

Using a common technique for approximating distributions [generalized functions], we are able to use standard Monte Carlo methods to compute QFT quantities in Minkowski spacetime, under phase transitions, or when dealing with coalescing…

High Energy Physics - Lattice · Physics 2010-04-01 D. D. Ferrante , J. Doll , G. S. Guralnik , D. Sabo

We propose a nonequilibrium Monte Carlo (MC) approach to explore nonequilibrium dynamical ferromagnetism of interacting single molecule magnets (SMMs). Both quantum spin tunneling and thermally activated spin reversal are successfully…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Gui-Bin Liu , Bang-Gui Liu

An adaptation of the full configuration interaction quantum Monte Carlo (FCIQMC) method is presented, for correlated electron problems containing heavy elements and the presence of significant relativistic effects. The modified algorithm…

Chemical Physics · Physics 2020-10-26 Robert J. Anderson , George H. Booth

A closed system of the equations for the local Bloch vectors and spin correlation functions is obtained by decomplexification of the Liouville-von Neumann equation for three magnetic qubits with the exchange interaction, that takes place in…

Quantum Physics · Physics 2007-05-23 E. A. Ivanchenko

In the absence of a fermion sign problem, auxiliary field (or determinantal) quantum Monte Carlo (DQMC) approaches have long been the numerical method of choice for unbiased, large-scale simulations of interacting many-fermion systems. More…

Strongly Correlated Electrons · Physics 2016-12-22 Peter Broecker , Simon Trebst

We have simulated the classical Heisenberg antiferromagnet on a triangular lattice using a local Monte Carlo algorithm. The behavior of the correlation length $\xi$, the susceptibility at the ordering wavevector $\chi(\bf Q)$, and the spin…

Condensed Matter · Physics 2009-10-28 M. Wintel , H. U. Everts , W. Apel

This thesis offers novel strategies for the measurement of quantum correlations present in controllable quantum systems, as well as for a full-fledged implementation of the models of light-matter interaction through which these correlations…

Quantum Physics · Physics 2016-11-30 Julen S. Pedernales

Dynamical properties are studied numerically for a variant of the Kondo model with singlet and triplet crystalline electric field (CEF) levels where Kondo and CEF singlets compete for the ground state. Using the continuous-time quantum…

Strongly Correlated Electrons · Physics 2011-02-28 Shintaro Hoshino , Junya Otsuki , Yoshio Kuramoto

The two-dimensional Falicov-Kimball (FK) model is analyzed using Monte Carlo method. In the case of concentrations of both itinerant and localized particles equal to 0.5 we determine temperature dependence of specific heat, charge density…

Strongly Correlated Electrons · Physics 2009-11-11 Maciej M. Maska , Katarzyna Czajka

A review of the Loop Algorithm, its generalizations, and its relation to some other Monte Carlo techniques is given. The loop algorithm is a Quantum Monte Carlo procedure which employs nonlocal changes of worldline configurations,…

Strongly Correlated Electrons · Physics 2014-10-13 H. G. Evertz

In the present paper we consider the initial data, external force, viscosity coefficients, and heat conductivity coefficient as random data for the compressible Navier--Stokes--Fourier system. The Monte Carlo method, which is frequently…

Numerical Analysis · Mathematics 2023-04-04 Maria Lukacova -- Medvidova , Bangwei She , Yuhuan Yuan

Continuous-time determinantal algorithm is proposed for the quantum Monte Carlo simulation of the interacting fermions. The scheme does not invoke Hubbard-Stratonovich transformation. The fermionic action is divided into two parts. One of…

Strongly Correlated Electrons · Physics 2007-05-23 A. N. Rubtsov

The kinetics of the chiral phase transition is studied within a linear quark-meson-$\sigma$ model, using a Monte-Carlo approach to semiclassical particle-field dynamics. The meson fields are described on the mean-field level and quarks and…

High Energy Physics - Phenomenology · Physics 2015-09-30 Carsten Greiner , Christian Wesp , Hendrik van Hees , Alex Meistrenko

Adaptive and interacting Markov chain Monte Carlo algorithms (MCMC) have been recently introduced in the literature. These novel simulation algorithms are designed to increase the simulation efficiency to sample complex distributions.…

Statistics Theory · Mathematics 2012-03-15 G. Fort , E. Moulines , P. Priouret

We study time-changed Markov processes to speed up the convergence of Markov chain Monte Carlo (MCMC) algorithms. The time-changed process is defined by adjusting the speed of time of a base process via a user-chosen, state-dependent…

Computation · Statistics 2025-04-08 Andrea Bertazzi , Giorgos Vasdekis
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