Berlin 2018 – scientific programme
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CPP: Fachverband Chemische Physik und Polymerphysik
CPP 28: Condensed Matter Simulations augmented by Advanced Statistical Methodologies I (joint session DY/CPP)
CPP 28.3: Talk
Tuesday, March 13, 2018, 11:30–11:45, BH-N 334
Adaptive 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. We equip this method with self-adaptive schemes for choosing the algorithmic parameters, including the temperature and sweep protocols as well as the population size. The resulting method is significantly more efficient for simulations of systems with complex free-energy landscapes than some more traditional approaches, and it is particularly well suited for massively parallel computing environments such as (clusters of) GPUs.