Topic
Dynamic Monte Carlo method
About: Dynamic Monte Carlo method is a research topic. Over the lifetime, 13294 publications have been published within this topic receiving 371256 citations.
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TL;DR: In this article, the potential energy surface of the LiH molecule was calculated using the Green's function Monte Carlo method and the calculated correlation energy is 0.078±0.001 hartree and the binding energy is 2.56 eV.
Abstract: The potential energy surface of the LiH molecule is calculated using the Green’s function Monte Carlo method. The calculated correlation energy is 0.078±0.001 hartree and the binding energy is 2.56 eV. These results are within 6% and 2% of the experimental values, respectively. The Green’s function Monte Carlo method is discussed in some detail with particular emphasis on problems of chemical interest.
165 citations
TL;DR: In this article, Monte Carlo calculation of path integrals of non-relativistic quantum systems is applied to the N-body problem and the importance sampling of permutation and coordinates is used to avoid the negative sign problem.
Abstract: Thermodynamic properties of non-relativistic quantum systems are treated by the Monte Carlo calculation of path integrals. This method can be applied to the N-body problem. For boson systems the importance sampling of permutation and coordinates is efficient. For fermion systems direct calculation of determinant of propagators is efficient to avoid the negative sign problem.
165 citations
TL;DR: In this article, the equation of state of three-dimensional hard spheres has been obtained by the Monte Carlo method and qualitative results for a system of two-dimensional molecules with Lennard-Jones interaction are also given.
Abstract: The equation of state of three‐dimensional hard spheres has been obtained by the Monte Carlo method Some qualitative results for a system of two‐dimensional molecules with Lennard‐Jones interaction are also given, as well as a general discussion of the usefulness and limitations of the Monte Carlo method
165 citations
TL;DR: The Monte Carlo method of error propagation as mentioned in this paper consists of repeated calculation of a quantity, each time varying the input data randomly within their stated limits of precision, and the distribution of the calculated quantity then shows the effects of the imprecision of the data.
164 citations
TL;DR: A simple recursive iteration of the leapfrog discretization of Newton's equations leads to a removal of the finite-step-size error to any desired order in a manner that preserves phase-space areas and reversibility.
Abstract: We present a simple recursive iteration of the leapfrog discretization of Newton's equations which leads to a removal of the finite-step-size error to any desired order. This is done in a manner that preserves phase-space areas and reversibility, as required for use in the hybrid Monte Carlo method for simulating fermionic fields. The resulting asymptotic volume dependence is exp((ln/ital V/)/sup 1/2/). We test the scheme on the (2+1)-dimensional Hubbard model.
164 citations