Starts 16 Feb 2016 11:00
Ends 16 Feb 2016 16:00
Central European Time
SISSA, room 128
Abstract:
I show how the lifting principle and a new pairwise decomposition of the Metropolis filter allows one to design a class of powerful rejection-free Markov-chain Monte Carlo algorithms that break detailed balance yet satisfy detailed balance. These algorithms generalize our recent hard-sphere event-chain Monte Carlo method. The new approach breaks with all the three paradigms of common Markov-chain methods: 1) Moves are infinitesimal rather than finite; 2) Detailed balance is broken yet global balance is satisfied; 3) Rejections are replaced by liftings, and moves are persistent.

As an application, I demonstrate considerable speed-up of the event-chain algorithm for particle systems and for spin models and sketch extensions to the simulation of quantum systems and the treatment of long-range systems without cutoffs or Ewald summations.

To illustrate the results that were obtained with these algorithms, I will discuss our new understanding of two-dimensional melting.

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