On the fly nodal searches in importance sampled fixed-node diffusion Monte Carlo using a parallel, fine-grained, genetic algorithm
Evolution of a wave function in a fixed-node diffusion Monte Carlo simulation guided by a genetic algorithm. The top panel shows an initial guess at the wave function and its nodal surface; the middle panel shows a typical individual in the population of possible solutions. The bottom panel shows a...
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| Vydáno v: | Chemical physics letters Ročník 619; s. 71 - 76 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
05.01.2015
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| ISSN: | 0009-2614, 1873-4448 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Evolution of a wave function in a fixed-node diffusion Monte Carlo simulation guided by a genetic algorithm. The top panel shows an initial guess at the wave function and its nodal surface; the middle panel shows a typical individual in the population of possible solutions. The bottom panel shows a high fitness, converged, individual from the final generation of individuals. [Display omitted]
•Genetic algorithm finds nodes in diffusion Monte Carlo calculations.•New approach allows for importance sampling.•Nodes optimized on the fly.•Application made to a non-integrable quartic oscillator.•Excellent agreement with accurate results.
A method for finding nodal surfaces on the fly in importance-sampled, fixed-node diffusion Monte Carlo calculations is described. The procedure relies on minimizing the difference between the nodal functions of the guiding wave function, ΨT, and HˆΨT, where Hˆ is the Hamiltonian. This is done by allowing the trial function to depend on a set of parameters whose values are then optimized using a parallel genetic algorithm (e.g., the Pikaia code developed in astrophysics). Application is made to the calculation of several excited states of a non-integrable two-dimensional quartic oscillator and to excited states of the He–C2H2 complex. |
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| ISSN: | 0009-2614 1873-4448 |
| DOI: | 10.1016/j.cplett.2014.11.054 |