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Sequential Monte Carlo Samplers are a class of stochastic algorithms for Monte Carlo integral estimation w.r.t. probability distributions, which combine elements of Markov chain Monte Carlo methods and importance sampling/resampling…

Probability · Mathematics 2007-05-23 Andreas Eberle , Carlo Marinelli

Antiferromagnetic Heisenberg spin chains with various spin values ($S=1/2,1,3/2,2,5/2$) are studied numerically with the quantum Monte Carlo method. Effective spin $S$ chains are realized by ferromagnetically coupling $n=2S$…

Strongly Correlated Electrons · Physics 2009-10-30 Y. J. Kim , M. Greven , U. -J. Wiese , R. J. Birgeneau

We describe an embarrassingly parallel, anytime Monte Carlo method for likelihood-free models. The algorithm starts with the view that the stochasticity of the pseudo-samples generated by the simulator can be controlled externally by a…

Machine Learning · Computer Science 2015-12-03 Edward Meeds , Max Welling

Understanding the real time dynamics of quantum systems without quasiparticles constitutes an important yet challenging problem. We study the superfluid-insulator quantum-critical point of bosons on a two-dimensional lattice, a system whose…

Strongly Correlated Electrons · Physics 2014-05-06 William Witczak-Krempa , Erik Sorensen , Subir Sachdev

We calculate the spatial correlation function and momentum distribution of a phase-fluctuating, elongated three-dimensional condensate, in a trap and in free expansion. We take the inhomogeneous density profile into account {\it{via}} a…

Condensed Matter · Physics 2009-11-07 F. Gerbier , J. H. Thywissen , S. Richard , M. Hugbart , P. Bouyer , A. Aspect

In recent years efficient algorithms have been developed for the numerical computation of relativistic single-particle path integrals in quantum field theory. Here, we adapt this "worldline Monte Carlo" approach to the standard problem of…

A novel method for extracting physical parameters from experimental and simulation data is presented. The method is based on statistical concepts and it relies on Monte Carlo simulation techniques. It identifies and determines with maximal…

High Energy Physics - Phenomenology · Physics 2012-05-31 C. N. Papanicolas , E. Stiliaris

In two-dimensional lattice fermion model a determinant representation for the two-point correlation function of the twist field in the disorder phase is obtained. This field is defined by twisted boundary conditions for lattice fermion…

High Energy Physics - Theory · Physics 2007-05-23 Anatolij I. Bugrij , Vitalij N. Shadura

Two-dimensional $CP^{N-1}$ models are investigated by Monte Carlo methods on the lattice, for values of $N$ ranging from 2 to 21. Scaling and rotation invariance are studied by comparing different definitions of correlation length $\xi$.…

High Energy Physics - Lattice · Physics 2009-10-22 Massimo Campostrini , Paolo Rossi , Ettore Vicari

On the base of a Feynman-Kac--type formula involving Poisson stochastic processes, recently a Monte Carlo algorithm has been introduced, which describes exactly the real- or imaginary-time evolution of many-body lattice quantum systems. We…

Other Condensed Matter · Physics 2011-07-19 Massimo Ostilli , Carlo Presilla

The QCD-coupling is a necessary input in the computation of many observables, and the parametric error on input parameters can be a dominant source of uncertainty. The coupling can be extracted by comparing high order perturbative…

High Energy Physics - Lattice · Physics 2022-03-16 Leonardo Chimirri , Rainer Sommer

Binary mixtures of hard-spheres with different diameters and square-well attraction between different particles are studied by theory and Monte Carlo simulations. In our mesoscopic theory, local fluctuations of the volume fraction of the…

Soft Condensed Matter · Physics 2021-10-04 O. Patsahan , A. Meyra , A. Ciach

Angular distribution and correlation measurements are an essential part in nuclear structure experiments, especially when spectroscopic information of a specific nucleus is unknown. In most cases, the experimental determination of the…

Nuclear Theory · Physics 2022-03-09 A. Chalil , T. Materna , O. Litaize , A. Chebboubi , F. Gunsing

We study dynamical properties of the one- and two-dimensional Falicov-Kimball model using lattice Monte Carlo simulations. In particular, we calculate the spreading of charge correlations in the equilibrium model and after an interaction…

Strongly Correlated Electrons · Physics 2018-04-11 Andreas J. Herrmann , Andrey E. Antipov , Philipp Werner

Computing observables from conditioned dynamics is typically computationally hard, because, although obtaining independent samples efficiently from the unconditioned dynamics is usually feasible, generally most of the samples must be…

Data Analysis, Statistics and Probability · Physics 2026-01-08 Alfredo Braunstein , Giovanni Catania , Luca Dall'Asta , Matteo Mariani , Anna Paola Muntoni

We consider the problem of adaptive stratified sampling for Monte Carlo integration of a differentiable function given a finite number of evaluations to the function. We construct a sampling scheme that samples more often in regions where…

Machine Learning · Statistics 2012-10-22 Alexandra Carpentier , Rémi Munos

We establish stochastic functional integral representations for incompressible fluid flows occupying wall-bounded domains using the conditional law duality for a class of diffusion processes. These representations are used to derive a…

Fluid Dynamics · Physics 2023-04-19 Vladislav Cherepanov , Zhongmin Qian

We study canonical and affine versions of the quantized covariant Euclidean free real scalar field-theory on four dimensional lattices through the Monte Carlo method. We calculate the two-point function at small values of the bare coupling…

High Energy Physics - Lattice · Physics 2021-10-28 Riccardo Fantoni , John R. Klauder

We extend to quenched disordered systems the variational scheme for real space renormalization group calculations that we recently introduced for homogeneous spin Hamiltonians. When disorder is present our approach gives access to the flow…

Statistical Mechanics · Physics 2020-11-11 Yantao Wu , Roberto Car

We calculate the efficiency of a rejection-free dynamic Monte Carlo method for $d$-dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential $r^{-p}$. Theoretically we find the algorithmic efficiency…

Statistical Mechanics · Physics 2009-11-13 Marta L. Guerra , M. A. Novotny , Hiroshi Watanabe , Nobuyasu Ito