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 ...
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 ...
Inference for a complex system with a rough energy landscape is a central topic in Monte Carlo computation. Motivated by the successes of the Wang—Landau algorithm in discrete systems, we generalize ...
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 ...
A North Carolina State University physicist and his German colleagues have created a new, more precise algorithm for simulating particle interactions when a single impurity is introduced into a Fermi ...
The Monte Carlo method is an alternate way to model drug sales estimates. Using my earlier method, I came up with an annual revenue estimate of $100 million for BAY 43-9006 in the treatment of renal ...
CAMBRIDGE, United Kingdom, May 27, 2021 /CNW/ -- Cambridge Quantum Computing (CQC) today announced the discovery of a new algorithm that accelerates quantum Monte Carlo integration - shortening the ...
We consider the pricing of a special kind of option, the so-called autocallable, which may terminate prior to maturity due to a barrier condition on one or several underlyings. Standard Monte Carlo ...
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