The first talks of the day at this ICMS workshop [“at the interface between mathematical statistics and molecular simulation”] were actually lectures introducing molecular simulation to statisticians by Michael Allen from Warwick and computational statistics to physicists by Omiros Papaspiliopoulos. Allen’s lecture was quite pedagogical, even though I had to quiz wikipedia for physics terms and notions. Like a force being the gradient of a potential function. He gave a physical meaning to Langevin’ equation. As well as references from the Journal of Chemical Physics that were more recent than 1953. He mentioned alternatives to Langevin’s equation too and I idly wondered at the possibility of using those alternatives as other tools for improved MCMC simulation. Although introducing friction may not be the most promising way to speed up the thing… He later introduced what statisticians call Langevin’ algorithm (MALA) as smart Monte Carlo (Rossky et al., …1978!!!). Recovering Hamiltonian and hybrid Monte Carlo algorithms as a fusion of molecular dynamics, Verlet algorithm, and Metropolis acceptance step! As well as reminding us of the physics roots of umbrella sampling and the Wang-Landau algorithm.
Omiros Papaspiliopoulos also gave a very pedagogical entry to the convergence of MCMC samplers which focussed on the L² approach to convergence. This reminded me of the very first papers published on the convergence of the Gibbs sampler, like the 1990 1992 JCGS paper by Schervish and Carlin. Or the 1991 1996 Annals of Statistics by Amit. (Funny that I located both papers much earlier than when they actually appeared!) One surprising fact was that the convergence of all reversible ergodic kernels is necessarily geometric. There is no classification of kernels in this topology, the only ranking being through the respective spectral gaps. A good refresher for most of the audience, statisticians included.
The following talks of Day 1 were by Christophe Andrieu, who kept with the spirit of a highly pedagogical entry, covering particle filters, SMC, particle Gibbs and pseudo-marginals, and who hit the right tone I think given the heterogeneous audience. And by Ben Leimkuhler about particle simulation for very large molecular structures. Closing the day by focussing on Langevin dynamics. What I understood from the talk was an improved entry into the resolution of some SPDEs. Gaining two orders when compared with Euler-Marayama. But missed the meaning of the friction coefficient γ converging to infinity in the title…
Taking advantage of cheap [early] Sunday morning flights to 
