Results 31 to 40 of about 852,908 (291)

Metropolis Methods for Quantum Monte Carlo Simulations [PDF]

, 2003
Since its first description fifty years ago, the Metropolis Monte Carlo method has been used in a variety of different ways for the simulation of continuum quantum many-body systems.
Ceperley, D. M.
core   +3 more sources

Monte Carlo and Quasi Monte Carlo Approach to Ulam's Method for Position Dependent Random Maps

Communications in Advanced Mathematical Sciences, 2020
We consider position random maps $T=\{\tau_1(x),\tau_2(x),\ldots, \tau_K(x); p_1(x),p_2(x),\ldots,p_K(x)\}$ on $I=[0, 1],$ where $\tau_k, k=1, 2, \dots, K$ is non-singular map on $[0,1]$ into $[0, 1]$ and $\{p_1(x),p_2(x),\ldots,p_K(x)\}$ is a set of
Md Shafiqul Islam
doaj   +1 more source

Coupled Electron Ion Monte Carlo Calculations of Atomic Hydrogen [PDF]

, 2004
We present a new Monte Carlo method which couples Path Integral for finite temperature protons with Quantum Monte Carlo for ground state electrons, and we apply it to metallic hydrogen for pressures beyond molecular dissociation.
Ceperley, David M., Holzmann, Markus, Pierleoni, Carlo   +2 more
core   +1 more source

Semistochastic Projector Monte Carlo Method

Physical Review Letters, 2012
We introduce a semistochastic implementation of the power method to compute, for very large matrices, the dominant eigenvalue and expectation values involving the corresponding eigenvector. The method is semistochastic in that the matrix multiplication is partially implemented numerically exactly and partially with respect to expectation values only ...
Petruzielo, F. R., Holmes, A. A., Changlani, Hitesh J., Nightingale, M. P., Umrigar, C. J.   +4 more
openaire   +5 more sources

Efficient Monte Carlo Calculations of the One-Body Density [PDF]

, 2006
An alternative Monte Carlo estimator for the one-body density rho(r) is presented. This estimator has a simple form and can be readily used in any type of Monte Carlo simulation.
Assaraf, Roland, Caffarel, Michel, Scemama, Anthony   +2 more
core   +7 more sources

Uma abordagem simplificada do método Monte Carlo Quântico: da solução de integrais ao problema da distribuição eletrônica A simplified approach to the Quantum Monte Carlo method: from the solution of integrals to the electronic distribution problem

Química Nova, 2008
The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some fundamental algorithms, concepts and applicability. In order to introduce the quantum Monte Carlo method, preliminary concepts associated with Monte Carlo ...
Wagner Fernando Delfino Angelotti, André Luiz da Fonseca, Guilherme Barreto Torres, Rogério Custodio   +3 more
doaj   +1 more source

Divergence of the multilevel Monte Carlo Euler method for nonlinear stochastic differential equations

, 2013
The Euler-Maruyama scheme is known to diverge strongly and numerically weakly when applied to nonlinear stochastic differential equations (SDEs) with superlinearly growing and globally one-sided Lipschitz continuous drift coefficients.
Hutzenthaler, Martin, Jentzen, Arnulf, Kloeden, Peter E.   +2 more
core   +1 more source

Self-Learning Monte Carlo Method: Continuous-Time Algorithm

, 2017
The recently-introduced self-learning Monte Carlo method is a general-purpose numerical method that speeds up Monte Carlo simulations by training an effective model to propose uncorrelated configurations in the Markov chain.
Fu, Liang, Liu, Junwei, Nagai, Yuki, Qi, Yang, Shen, Huitao   +4 more
core   +1 more source

Optimization of ground and excited state wavefunctions and van der Waals clusters [PDF]

, 2000
A quantum Monte Carlo method is introduced to optimize excited state trial wavefunctions. The method is applied in a correlation function Monte Carlo calculation to compute ground and excited state energies of bosonic van der Waals clusters of upto seven
Andrei Mushinski, B. Bernu, C. J. Umrigar, C. J. Umrigar, C. J. Umrigar, D. Blume, D. Blume, D. H. Zhang, D. M. Ceperley, D. M. Leitner, G. H. Golub, J. de Boer, J. H. Hetherington, J. K. L. MacDonald, M. Caffarel, M. Caffarel, M. Foulkes, M. Meierovich, M. P. Nightingale, M. P. Nightingale, M. P. Nightingale, V. Melik-Alaverdian, Vilen Melik-Alaverdian, W. H. Press, W. R. Brown   +24 more
core   +3 more sources

Comparation of nonuniform and uniform Monte - Carlo Searching

MATEC Web of Conferences, 2018
Nonuniform Monte-Carlo method is often used for optimization and solution of function mapping. This method has some disadvantages. New genetic algorithm, based on uniform Monte-Carlo is proposed by authors reduce disadvantage of nonuniform Monte- Carlo ...
Handrik Marián, Handriková Jana, Vaško Milan, Dorčiak Filip   +3 more
doaj   +1 more source