1. Improving stability of stochastic algorithms being applied to spin Hamiltonians.
- Author
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Maibakh, E. A., Kashin, I. V., Volkovich, Vladimir A, Kashin, Ilya V, Smirnov, Andrey A, and Narkhov, Evgeniy D
- Subjects
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QUANTUM spin models , *ALGORITHMS , *QUANTUM states , *GENETIC algorithms , *PROCESS optimization - Abstract
In this paper, we propose an original approach to provide numerical stability and sustainability of stochastic schemes designed for solving multiparticle quantum spin models. It is presented as a combination of two essential improvements. The first one is refreshed view of stochastic energy estimation for an arbitrary quantum state, related to Heisenberg Hamiltonian. The second one appears as a modification of the genetic optimization algorithm to ensure stable convergence in actual computer calculation. The approach was tested on sample system, demonstrating efficiency and perspectives for further investigations in the field of microscopic magnetism. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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