Issue |
EPL
Volume 121, Number 1, January 2018
|
|
---|---|---|
Article Number | 10008 | |
Number of page(s) | 6 | |
Section | General | |
DOI | https://doi.org/10.1209/0295-5075/121/10008 | |
Published online | 09 March 2018 |
Irreversible Markov chains in spin models: Topological excitations
1 Laboratoire de Physique Statistique, Département de physique de l'ENS, Ecole Normale Supérieure, PSL Research University, Université Paris Diderot, Sorbonne Paris Cité, Sorbonne Universités, UPMC Univ. Paris 06, CNRS 75005 Paris, France
2 Department of Physics, Graduate School of Science, The University of Tokyo - 7-3-1 Hongo, Bunkyo, Tokyo, Japan
(a) ze.lei@ens.fr
(b) werner.krauth@ens.fr
Received: 24 November 2017
Accepted: 21 February 2018
We analyze the convergence of the irreversible event-chain Monte Carlo algorithm for continuous spin models in the presence of topological excitations. In the two-dimensional XY model, we show that the local nature of the Markov-chain dynamics leads to slow decay of vortex-antivortex correlations while spin waves decorrelate very quickly. Using a Fréchet description of the maximum vortex-antivortex distance, we quantify the contributions of topological excitations to the equilibrium correlations, and show that they vary from a dynamical critical exponent at the critical temperature to in the limit of zero temperature. We confirm the event-chain algorithm's fast relaxation (corresponding to z = 0) of spin waves in the harmonic approximation to the XY model. Mixing times (describing the approach towards equilibrium from the least favorable initial state) however remain much larger than equilibrium correlation times at low temperatures. We also describe the respective influence of topological monopole-antimonopole excitations and of spin waves on the event-chain dynamics in the three-dimensional Heisenberg model.
PACS: 02.70.Tt – Justifications or modifications of Monte Carlo methods / 75.10.Hk – Classical spin models / 02.50.Ng – Distribution theory and Monte Carlo studies
© EPLA, 2018
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