230 citations · 1.3k across the 68 of their papers we have counts for
11 papers · 1 filter
Extending the regime of linear response with synthetic forcings
Renato Spacek, Gabriel Stoltz
Transport coefficients, such as the mobility, thermal conductivity and shear viscosity, are quantities of prime interest in statistical physics. At the macroscopic level, transport…
Unbiasing Hamiltonian Monte Carlo algorithms for a general Hamiltonian function
Tony Lelièvre, Régis Santet, Gabriel Stoltz
Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo method that allows to sample high dimensional probability measures. It relies on the integration of the Hamiltonian dyna…
Error estimates and variance reduction for nonequilibrium stochastic dynamics
Gabriel Stoltz
Equilibrium properties in statistical physics are obtained by computing averages with respect to Boltzmann-Gibbs measures, sampled in practice using ergodic dynamics such as the La…
Martingale product estimators for sensitivity analysis in computational statistical physics
Petr Plechac, Gabriel Stoltz, Ting Wang
We introduce a new class of estimators for the linear response of steady states of stochastic dynamics. We generalize the likelihood ratio approach and formulate the linear respons…
Multiple projection MCMC algorithms on submanifolds
Tony Lelièvre, Gabriel Stoltz, Wei Zhang
We propose new Markov Chain Monte Carlo algorithms to sample probability distributions on submanifolds, which generalize previous methods by allowing the use of set-valued maps in…
Convergence of the likelihood ratio method for linear response of non-equilibrium stationary states
Petr Plechac, Gabriel Stoltz, Ting Wang
We consider numerical schemes for computing the linear response of steady-state averages of stochastic dynamics with respect to a perturbation of the drift part of the stochastic d…