Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/83349
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHu, Haoen
dc.contributor.authorChen, Xiaosongen
dc.contributor.authorDeng, Youjinen
dc.date.accessioned2017-05-31T07:27:20Zen
dc.date.accessioned2019-12-06T15:20:31Z-
dc.date.available2017-05-31T07:27:20Zen
dc.date.available2019-12-06T15:20:31Z-
dc.date.issued2017en
dc.identifier.citationHu, H., Chen, X., & Deng, Y. (2016). Irreversible Markov chain Monte Carlo algorithm for self-avoiding walk. Frontiers of Physics, 12, 120503-.en
dc.identifier.issn2095-0470en
dc.identifier.urihttps://hdl.handle.net/10356/83349-
dc.description.abstractWe formulate an irreversible Markov chain Monte Carlo algorithm for the self-avoiding walk (SAW), which violates the detailed balance condition and satisfies the balance condition. Its performance improves significantly compared to that of the Berretti–Sokal algorithm, which is a variant of the Metropolis–Hastings method. The gained efficiency increases with spatial dimension (D), from approximately 10 times in 2D to approximately 40 times in 5D. We simulate the SAW on a 5D hypercubic lattice with periodic boundary conditions, for a linear system with a size up to L = 128, and confirm that as for the 5D Ising model, the finite-size scaling of the SAW is governed by renormalized exponents, v* = 2/d and γ/v* = d/2. The critical point is determined, which is approximately 8 times more precise than the best available estimate.en
dc.format.extent7 p.en
dc.language.isoenen
dc.relation.ispartofseriesFrontiers of Physicsen
dc.rights© 2017 Higher Education Press and Springer-Verlag Berlin Heidelberg. This is the author created version of a work that has been peer reviewed and accepted for publication by Frontiers of Physics, Higher Education Press and Springer-Verlag Berlin Heidelberg. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1007/s11467-016-0646-6].en
dc.subjectMonte Carlo algorithmsen
dc.subjectSelf-avoiding walken
dc.titleIrreversible Markov chain Monte Carlo algorithm for self-avoiding walken
dc.typeJournal Articleen
dc.contributor.schoolSchool of Chemical and Biomedical Engineeringen
dc.identifier.doi10.1007/s11467-016-0646-6en
dc.description.versionAccepted versionen
item.grantfulltextopen-
item.fulltextWith Fulltext-
Appears in Collections:SCBE Journal Articles
Files in This Item:
File Description SizeFormat 
Irreversible Markov chain Monte Carlo algorithm for self-avoiding walk.pdf362.64 kBAdobe PDFThumbnail
View/Open

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.