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- W4289445758 abstract "We present a fast, hierarchical, and adaptive algorithm for Metropolis Monte Carlo simulations of systems with long-range interactions that reproduces the dynamics of a standard implementation exactly, i.e., the generated configurations and consequently all measured observables are identical, allowing in particular for nonequilibrium studies. The method is demonstrated for the power-law interacting long-range Ising model with nonconserved order parameter and a Lennard-Jones system both in two dimensions. The measured runtimes support an average complexity $O(Nlog N)$, where $N$ is the number of spins or particles. Importantly, prefactors of this scaling behavior are small, which in practice manifests in speedup factors larger than $10^4$. The method is general and will allow the treatment of large systems that were out of reach before, likely enabling a more detailed understanding of physical phenomena rooted in long-range interactions." @default.
- W4289445758 created "2022-08-02" @default.
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- W4289445758 date "2022-07-29" @default.
- W4289445758 modified "2023-09-23" @default.
- W4289445758 title "Fast, hierarchical, and adaptive algorithm for Metropolis Monte Carlo simulations of long-range interacting systems" @default.
- W4289445758 doi "https://doi.org/10.48550/arxiv.2207.14670" @default.
- W4289445758 hasPublicationYear "2022" @default.
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