The "lifted" TASEP and non-reversible Monte Carlo sampling
The "lifted" TASEP and non-reversible Monte Carlo sampling
- Event time: 3:00pm until 4:00pm
- Event date: 28th October 2025
- Speaker: Professor Werner Krauth (École Normale Supérieure, Paris)
- Location: Online - see email.
Event details
I discuss non-reversible Markov-chain Monte Carlo algorithms that, for particle systems, rigorously sample the positional Boltzmann distribution and have faster than physical dynamics. These algorithms all feature a non-thermal velocity distribution. They are exemplified by the "lifted" TASEP, which appears as a one-dimensional lattice reduction of event-chain Monte Carlo. It features exceptionally fast out-of-equilibrium mixing and equilibrium relaxation time scales, that are faster than for the (unlifted) TASEP. I finally analyze the lifted TASEP in terms of "true" self-avoiding random walks.
F. H. L. Essler, W. Krauth PRX 14, 041035 (2024)
B. Massoulié, C. Erignoux, C. Toninelli, W. Krauth PRL 135, 127102 (2025)
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