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 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 ...

The Wang-Landau algorithm (Wang and Landau (2001)) is a recent Monte Carlo method that has generated much interest in the Physics literature due to some spectacular simulation performances. The ...

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 ...

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 ...

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 ...

A quantum version of a computer algorithm widely used in finance, engineering and scientific modelling shows promising signs of operating much faster than existing methods. Experts say there are many ...

The proposed technique is expected to enable quantum sampling algorithms to scale to high precision, paving the way for quantum advantage on practical problems “The Fidelity Center for Applied ...