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| Auteurs principaux: | , |
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| Format: | Preprint |
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2024
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| Accès en ligne: | https://arxiv.org/abs/2402.18985 |
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| _version_ | 1866913552072179712 |
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| author | Mozolenko, Vyacheslav Shchur, Lev |
| author_facet | Mozolenko, Vyacheslav Shchur, Lev |
| contents | We present a modification of the Rose-Machta algorithm (Phys. Rev. E 100 (2019) 063304) and estimate the density of states for a two-dimensional Blume-Capel model, simulating $10^5$ replicas in parallel for each set of parameters. We perform a finite-size analysis of the specific heat and Binder cumulant, determine the critical temperature along the critical line, and evaluate the critical exponents. The results obtained are in good agreement with those obtained previously using various methods -- Markov Chain Monte Carlo simulation, Wang-Landau simulation, transfer matrix, and series expansion. The simulation results clearly illustrate the typical behavior of specific heat along the critical lines and through the tricritical point. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_18985 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Blume-Capel model analysis with microcanonical population annealing method Mozolenko, Vyacheslav Shchur, Lev Statistical Mechanics Artificial Intelligence We present a modification of the Rose-Machta algorithm (Phys. Rev. E 100 (2019) 063304) and estimate the density of states for a two-dimensional Blume-Capel model, simulating $10^5$ replicas in parallel for each set of parameters. We perform a finite-size analysis of the specific heat and Binder cumulant, determine the critical temperature along the critical line, and evaluate the critical exponents. The results obtained are in good agreement with those obtained previously using various methods -- Markov Chain Monte Carlo simulation, Wang-Landau simulation, transfer matrix, and series expansion. The simulation results clearly illustrate the typical behavior of specific heat along the critical lines and through the tricritical point. |
| title | Blume-Capel model analysis with microcanonical population annealing method |
| topic | Statistical Mechanics Artificial Intelligence |
| url | https://arxiv.org/abs/2402.18985 |