Dresden 2017 – wissenschaftliches Programm
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DY: Fachverband Dynamik und Statistische Physik
DY 11: Critical phenomena
DY 11.7: Vortrag
Montag, 20. März 2017, 17:15–17:30, HÜL 186
Understanding population Monte Carlo simulations — •Martin Weigel1, Lev Yu. Barash2,3, Lev N. Shchur2,3,4, and Wolfhard Janke5 — 1Applied Mathematics Research Centre, Coventry University, Coventry, CV1 5FB, England — 2Landau Institute for Theoretical Physics, 142432 Chernogolovka, Russia — 3Science Center in Chenogolovka,142432 Chernogolovka, Russia — 4National Research University Higher School of Economics, 101000 Moscow, Russia — 5Institut für Theoretische Physik, Universität Leipzig, Postfach 100920 04009, Leipzig, Germany
Population annealing is a sequential Monte Carlo scheme that is potentially able to make use of highly parallel computational resources. Additionally, it promises to allow for the accelerated simulation of systems with complex free-energy landscapes, much alike to the much more well known replica-exchange or parallel tempering approach. The relative performance with respect to such more traditional techniques, the appropriate choice of population sizes temperature protocols and other parameters, the estimation of statistical and systematic errors and many other features, however, are essentially uncharted territory. Here, we use a systematic comparison of population annealing to Metropolis as well as parallel tempering simulations for the Ising model to gauge the potential of this new approach, and we suggest a range of heuristics for its application in more general circumstances.