Monte Carlo methods and Markov Chain algorithms have long been central to computational science, forming the backbone of numerical simulation in a variety of disciplines. These techniques employ ...

The Annals of Statistics, Vol. 39, No. 6 (December 2011), pp. 3262-3289 (28 pages) Adaptive and interacting Markov chain Monte Carlo algorithms (MCMC) have been recently introduced in the literature.

The application of Bayesian methods to large-scale phylogenetics problems is increasingly limited by computational issues, motivating the development of methods that can complement existing Markov ...

Researchers have developed a highly efficient method to investigate systems with long-range interactions that were previously puzzling to experts. These systems can be gases or even solid materials ...

COLLEGE PARK, Md.--(BUSINESS WIRE)--IonQ (NYSE: IONQ), an industry leader in quantum computing, in collaboration with the Fidelity Center for Applied Technology (FCAT), today announced an efficient ...

There are two flavors of QMC, (a) variational Monte Carlo (VMC) and (b) projector Monte Carlo (PMC). VMC starts by proposing a functional form for the wavefunction and then optimizes the parameters of ...

Marking a significant step in the roadmap for quantum advantage for financial applications, Goldman Sachs and QC Ware researchers have designed new, robust quantum algorithms that outperform ...