Recent progress on cluster and meron algorithms for strongly correlated systems
Recent progress on cluster and meron algorithms for strongly correlated systems
Ab initio studies of strongly interacting bosonic and fermionic systems are greatly facilitated by efficient Monte Carlo algorithms. This article emphasizes this requirement and outlines the ideas behind the construction of the cluster algorithms and illustrates them via specific examples. Numerical studies of fermionic systems at finite densities and at real-times are sometimes hindered by the infamous sign problem, which is also discussed. The construction of meron cluster algorithms, which can solve certain sign problems, is discussed. Cluster algorithms which can simulate certain pure Abelian gauge theories (realized as quantum link models) are also discussed.
1669–1680
Banerjee, Debasish
dcc5d706-d0ed-40b7-94f6-a4ddd7d41646
26 June 2021
Banerjee, Debasish
dcc5d706-d0ed-40b7-94f6-a4ddd7d41646
Banerjee, Debasish
(2021)
Recent progress on cluster and meron algorithms for strongly correlated systems.
Indian Journal of Physics, 95, .
(doi:10.1007/s12648-021-02155-5).
Abstract
Ab initio studies of strongly interacting bosonic and fermionic systems are greatly facilitated by efficient Monte Carlo algorithms. This article emphasizes this requirement and outlines the ideas behind the construction of the cluster algorithms and illustrates them via specific examples. Numerical studies of fermionic systems at finite densities and at real-times are sometimes hindered by the infamous sign problem, which is also discussed. The construction of meron cluster algorithms, which can solve certain sign problems, is discussed. Cluster algorithms which can simulate certain pure Abelian gauge theories (realized as quantum link models) are also discussed.
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Published date: 26 June 2021
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Local EPrints ID: 500412
URI: http://eprints.soton.ac.uk/id/eprint/500412
PURE UUID: a73a2a76-f23f-4a65-87b9-9d4599219857
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Date deposited: 29 Apr 2025 16:41
Last modified: 30 Apr 2025 02:13
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Author:
Debasish Banerjee
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