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Variational Monte Carlo is a many-body numerical method that scales well with system size. It has been extended to study the Green function only recently by Charlebois and Imada (2020). Here we generalize the approach to systems with open…

Strongly Correlated Electrons · Physics 2022-12-20 P. Rosenberg , D. Sénéchal , A. -M. S. Tremblay , M. Charlebois

In this paper we propose a multiscale method for the acoustic wave equation in highly oscillatory media. We use a higher-order extension of the localized orthogonal decomposition method combined with a higher-order time stepping scheme and…

Numerical Analysis · Mathematics 2024-07-23 Felix Krumbiegel , Roland Maier

A class of Monte Carlo algorithms which incorporate absorbing Markov chains is presented. In a particular limit, the lowest-order of these algorithms reduces to the $n$-fold way algorithm. These algorithms are applied to study the escape…

Condensed Matter · Physics 2009-10-22 M. A. Novotny

The implementation and reliability of a quadratic diffusion Monte Carlo method for the study of ground-state properties of atoms are discussed. We show in the simple yet non-trivial calculation of the binding energy of the Li atom that the…

Condensed Matter · Physics 2009-11-07 A. Sarsa , J. Boronat , J. Casulleras

A technique for reducing the number of integrals in a Monte Carlo calculation is introduced. For integrations relying on classical or mean-field trajectories with local weighting functions, it is possible to integrate analytically at least…

Statistical Mechanics · Physics 2024-05-17 Jarod Tall , Steven Tomsovic

Sequential Monte Carlo techniques are useful for state estimation in non-linear, non-Gaussian dynamic models. These methods allow us to approximate the joint posterior distribution using sequential importance sampling. In this framework,…

Computation · Statistics 2012-07-09 Mike Klaas , Nando de Freitas , Arnaud Doucet

Phase reduction is a commonly used techinque for analyzing stable oscillators, particularly in studies concerning synchronization and phase lock of a network of oscillators. In a widely used numerical approach for obtaining phase reduction…

Adaptation and Self-Organizing Systems · Physics 2015-05-14 Daisuke Takeshita , Renato Feres

In this paper we consider fully Bayesian inference in general state space models. Existing particle Markov chain Monte Carlo (MCMC) algorithms use an augmented model that takes into account all the variable sampled in a sequential Monte…

Methodology · Statistics 2014-07-31 Christopher K. Carter , Eduardo F. Mendes , Robert Kohn

A revised new iterative method based on Green function defined by quadratures along a single trajectory is developed and applied to solve the ground state of the double-well potential. The result is compared to the one based on the original…

Quantum Physics · Physics 2007-05-23 Zhao Wei-Qin

Many problems of practical interest rely on Continuous-time Markov chains~(CTMCs) defined over combinatorial state spaces, rendering the computation of transition probabilities, and hence probabilistic inference, difficult or impossible…

An intrinsic measure of the quality of a variational wave function is given by its overlap with the ground state of the system. We derive a general formula to compute this overlap when quantum dynamics in imaginary time is accessible. The…

Statistical Mechanics · Physics 2007-07-26 Christophe Mora , Xavier Waintal

Microscopic models of classical degrees of freedom coupled to non-interacting fermions occur in many different contexts. Prominent examples from solid state physics are descriptions of colossal magnetoresistance manganites and diluted…

Statistical Mechanics · Physics 2009-06-16 Alexander Weiße

A real-time path integral Monte Carlo approach is developed to study the dynamics in a many-body quantum system until reaching a nonequilibrium stationary state. The approach is based on augmenting an exact reduced equation for the…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Lothar Mühlbacher , Eran Rabani

A nonperturbative method to obtain on- and off-site one-particle Green's function is introduced and applied to noninteracting Hubbard model with next nearest neighbor hopping and interacting Hubbard model in large dimensions, for example.…

Strongly Correlated Electrons · Physics 2008-02-03 Jongbae Hong

In this work, we introduce three algorithmic improvements to reduce the cost and improve the scaling of orbital space variational Monte Carlo (VMC). First, we show that by appropriately screening the one- and two-electron integrals of the…

Chemical Physics · Physics 2018-07-30 Iliya Sabzevari , Sandeep Sharma

We study the propagation of coherent states in self-interacting bosonic quantum field theories in the semi-classical (mean-field) regime. Relying on Hepp's method and a detailed analysis of the associated classical and quantum field…

Mathematical Physics · Physics 2026-03-09 Zied Ammari , Julien Malartre , Maher Zerzeri

We consider the numerical integration of non-autonomous separable parabolic equations using high order splitting methods with complex coefficients (methods with real coefficients of order greater than two necessarily have negative…

Numerical Analysis · Mathematics 2014-05-20 Muaz Seydaoğlu , Sergio Blanes

We present a numerically exact steady-state inchworm Monte Carlo method for nonequilibrium quantum impurity models. Rather than propagating an initial state to long times, the method is directly formulated in the steady-state. This…

Strongly Correlated Electrons · Physics 2023-05-17 André Erpenbeck , Emanuel Gull , Guy Cohen

Ground state properties of condensed Helium are calculated using the Path Integral Ground State (PIGS) method. A fourth-order approximation is used as short (imaginary) time propagator. We compare our results with those obtained with other…

Statistical Mechanics · Physics 2009-11-10 Javier E. Cuervo , Pierre-Nicholas Roy , Massimo Boninsegni

We explore the utilization of higher-order discretization techniques in optimizing the gate count needed for quantum computer based solutions of partial differential equations. To accomplish this, we present an efficient approach for…

Quantum Physics · Physics 2024-12-30 Boris Arseniev , Dmitry Guskov , Richik Sengupta , Igor Zacharov
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