Non-linear inverse problems in the geosciences often involve probabilistic sampling of
multimodal density functions or global optimization and sometimes both. Efficient algorithmic …

We present a case study on the utility of graphics cards to perform massively parallel
simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics …

We introduce an algorithm for systematically improving the efficiency of parallel tempering
Monte Carlo simulations by optimizing the simulated temperature set. Our approach is …

Monte Carlo simulations are methods for simulating statistical systems. The aim is to
generate a representative ensemble of configurations to access thermodynamical quantities …

We apply a recently developed adaptive algorithm that systematically improves the
efficiency of parallel tempering or replica exchange methods in the numerical simulation of …

A heuristic is developed specifying that temperatures in replica-exchange simulations
should be spaced such that about 20% of the phase-swap attempts are accepted. The result …

Parallel tempering (PT) methods are a popular class of Markov chain Monte Carlo schemes
used to sample complex high-dimensional probability distributions. They rely on a collection …

We consider optimal temperature spacings for Metropolis-coupled Markov chain Monte
Carlo (MCMCMC) and Simulated Tempering algorithms. We prove that, under certain …

We give conditions under which a Markov chain constructed via parallel or simulated
tempering is guaranteed to be rapidly mixing, which are applicable to a wide range of …

Parallel tempering (PT) is a class of Markov chain Monte Carlo algorithms that constructs a
path of distributions annealing between a tractable reference and an intractable target, and …