Event-chain Monte Carlo algorithms for three- and many-particle interactions
We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting...
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| Veröffentlicht in: | Europhysics letters 2017-02, Vol.117 (3), p.30001-30001 |
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| container_title | Europhysics letters |
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| creator | Harland, J. Michel, M. Kampmann, T. A. Kierfeld, J. |
| description | We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. We validate the resulting three-particle event-chain Monte Carlo algorithms on three different systems by comparison with conventional local Monte Carlo simulations: i) a test system of three particles with a three-particle interaction that depends on the enclosed triangle area; ii) a hard-needle system in two dimensions, where needle interactions constitute three-particle interactions of the needle end points; iii) a semiflexible polymer chain with a bending energy, which constitutes a three-particle interaction of neighboring chain beads. The examples demonstrate that the generalization to many-particle interactions broadens the applicability of event-chain algorithms considerably. |
| doi_str_mv | 10.1209/0295-5075/117/30001 |
| format | Article |
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A. ; Kierfeld, J.</creator><creatorcontrib>Harland, J. ; Michel, M. ; Kampmann, T. A. ; Kierfeld, J.</creatorcontrib><description>We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. We validate the resulting three-particle event-chain Monte Carlo algorithms on three different systems by comparison with conventional local Monte Carlo simulations: i) a test system of three particles with a three-particle interaction that depends on the enclosed triangle area; ii) a hard-needle system in two dimensions, where needle interactions constitute three-particle interactions of the needle end points; iii) a semiflexible polymer chain with a bending energy, which constitutes a three-particle interaction of neighboring chain beads. 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A.</creatorcontrib><creatorcontrib>Kierfeld, J.</creatorcontrib><title>Event-chain Monte Carlo algorithms for three- and many-particle interactions</title><title>Europhysics letters</title><addtitle>EPL</addtitle><addtitle>EPL</addtitle><description>We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. We validate the resulting three-particle event-chain Monte Carlo algorithms on three different systems by comparison with conventional local Monte Carlo simulations: i) a test system of three particles with a three-particle interaction that depends on the enclosed triangle area; ii) a hard-needle system in two dimensions, where needle interactions constitute three-particle interactions of the needle end points; iii) a semiflexible polymer chain with a bending energy, which constitutes a three-particle interaction of neighboring chain beads. The examples demonstrate that the generalization to many-particle interactions broadens the applicability of event-chain algorithms considerably.</description><subject>02.70.Tt</subject><subject>05.10.Ln</subject><subject>64.70.M</subject><subject>Algorithms</subject><subject>Chains (polymeric)</subject><subject>Computer simulation</subject><subject>Hoisting</subject><subject>Mathematical analysis</subject><subject>Monte Carlo methods</subject><subject>Monte Carlo simulation</subject><subject>Needles</subject><subject>Particle interactions</subject><subject>Particles</subject><subject>Physics</subject><issn>0295-5075</issn><issn>1286-4854</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kUFv1DAQhS0EEkvhF3CJxAUOYT127MTHalsoUlAPLSo3a-pMWJdsvNjeiv57vGy1SBx6Gmn0Pc_ze4y9Bf4RBDdLLoyqFW_VEqBdSs45PGMLEJ2um041z9niSLxkr1K6KwB0oBesP7-nOddujX6uvoY5U7XCOIUKpx8h-rzepGoMscrrSFRXOA_VBueHeosxezdR5Yskoss-zOk1ezHilOjN4zxh3z6dX68u6v7y85fVaV-7putysTQ4N2qQLTkDpEVDLY3QUeOIQCJoNzRCaKEUgjNoOjUQNaMwg7iFW5Qn7MPh3TVOdhv9BuODDejtxWlv9zsuORij23so7PsDu43h145SthufHE0TzhR2yYLh5ZZUxhT03X_oXdjFufzESoCSGG-MKpQ8UC6GlCKNRwfA7b4Nu8_a7rO2pQ37t42iqg8qnzL9Pkow_rS6lQXt-I3V38-u4AxubF_45SMftv9sPHXhD5uJmAg</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Harland, J.</creator><creator>Michel, M.</creator><creator>Kampmann, T. 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A.</au><au>Kierfeld, J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Event-chain Monte Carlo algorithms for three- and many-particle interactions</atitle><jtitle>Europhysics letters</jtitle><stitle>EPL</stitle><addtitle>EPL</addtitle><date>2017-02-01</date><risdate>2017</risdate><volume>117</volume><issue>3</issue><spage>30001</spage><epage>30001</epage><pages>30001-30001</pages><issn>0295-5075</issn><eissn>1286-4854</eissn><coden>EULEEJ</coden><abstract>We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. 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| subjects | 02.70.Tt 05.10.Ln 64.70.M Algorithms Chains (polymeric) Computer simulation Hoisting Mathematical analysis Monte Carlo methods Monte Carlo simulation Needles Particle interactions Particles Physics |
| title | Event-chain Monte Carlo algorithms for three- and many-particle interactions |
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