Results 1 to 10 of about 1,455,452 (353)

Off-diagonal Wave Function Monte Carlo Studies of Hubbard Model I [PDF]

J. Phys. Soc. Jpn. 67, 3867 (1998), 2002
We propose a Monte Carlo method, which is a hybrid method of the quantum Monte Carlo method and variational Monte Carlo theory, to study the Hubbard model. The theory is based on the off-diagonal and the Gutzwiller type correlation factors which are taken into account by a Monte Carlo algorithm.
Anderson P. W., Blankenbecler R., Ceperley D., Furukawa N., Giamarchi T., Gros C., Hirsch J. E., Hirsch J. E., Imada M., Kobayashi K., Kuroki K., Kuroki K., Mott N. F., Nakanishi T., Ohtsuka H., Parola A., Umrigar C. J., White S. R., Yamaji K., Yanagisawa T., Yanagisawa T., Yanagisawa T., Yokoyama H., Yokoyama H., Zhang S.   +24 more
arxiv   +3 more sources

Metropolis Methods for Quantum Monte Carlo Simulations [PDF]

pgs. 85-98 in The Monte Carlo Method in the Physical Sciences, ed. J. E. Gubernatis, AIP Conference Proceedings, Vol 690, 2003., 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. This paper will consider some of the generalizations of the Metropolis algorithm employed in quantum Monte Carlo: Variational Monte Carlo, dynamical methods for projector ...
Ceperley, D. M.
arxiv   +5 more sources

Error in Monte Carlo, quasi-error in Quasi-Monte Carlo [PDF]

Comput.Phys.Commun. 175 (2006) 93-115, 2005
While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error. The standard Monte Carlo error estimator relies on the assumption that the points are generated independently of ...
Achilleas Lazopoulos, Adams, Bratley, Halton, Hoogland, Hoogland, James, James, Luescher, Niederreiter, Owen, Ronald Kleiss, Schlier, Weyl   +13 more
arxiv   +5 more sources

Transition matrix Monte Carlo method for quantum systems [PDF]

J. Phys. Soc. Jpn. 73, 7 (2004)., 2003
We propose an efficient method for Monte Carlo simulation of quantum lattice models. Unlike most other quantum Monte Carlo methods, a single run of the proposed method yields the free energy and the entropy with high precision for the whole range of temperature.
Berg B. A., de Oliveira P. M. C., Evertz H. G., Janke W., Kandel D., Kawashima N., Kawashima N., Lee J., Metropolis N., Sandvik A. W., Sandvik A. W., Swendsen R., Syljuåsen O. F., Troyer M., Wang F., Wang J.-S., Yamaguchi C., Yamaguchi C.   +17 more
arxiv   +3 more sources

Optimized Monte Carlo Method for glasses [PDF]

Philosophical Magazine, 2006
A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm is shown to thermalize well below the Mode Coupling temperature and to outperform other optimized Monte ...
Fernandez, L. A., Martin-Mayor, V., Verrocchio, P.   +2 more
core   +11 more sources

Balancing the maintenance strategies to making decisions using Monte Carlo method [PDF]

MethodsX
This study aims to develop comprehensive maintenance strategies tailored to enhance the dependability, performance, and lifespan of critical assets within industrial and organizational settings.
Khamiss Cheikh, E. L. Mostapha Boudi, Rabi Rabi, Hamza Mokhliss   +3 more
doaj   +2 more sources

Multilevel Monte Carlo methods [PDF]

arXiv, 2013
The author's presentation of multilevel Monte Carlo path simulation at the MCQMC 2006 conference stimulated a lot of research into multilevel Monte Carlo methods. This paper reviews the progress since then, emphasising the simplicity, flexibility and generality of the multilevel Monte Carlo approach.
arxiv   +6 more sources

Monte Carlo methods [PDF]

Applications of Mathematics, 1962
Václav Dupač
openalex   +2 more sources

Monte Carlo methods [PDF]

EPJ Web of Conferences, 2013
Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling ...
Mrinal K. Sen, Paul L. Stoffa
  +9 more sources

GENERALIZED SENSITIVITY ANALYSIS CAPABILITY WITH THE DIFFERENTIAL OPERATOR METHOD IN RMC CODE [PDF]

EPJ Web of Conferences, 2021
Sensitivity analysis is an important way for us to know how the input parameters will affect the output of a system. Therefore, recently, there is an increased interest in developing sensitivity analysis methods in continuous-energy Monte Carlo Code due ...
Shi Guanlin, Jia Conglong, Wang Kan, Cheng Quan   +3 more
doaj   +1 more source