Monte Carlo advances and concentrated solar applications

Advances in Quantum Monte Carlo

Current Advances in Monte Carlo Methods

In this review paper, we outline the principles of Monte Carlo simulation of fluid mixtures, with emphasis on methods for calculation of free energies and phase equilibria. We begin with a brief introduction to common intermolecular potential models. We discuss density-dependent potentials that can accurately represent properties over a wide range of densities. A number of Monte Carlo technique...

Recent Advances in Monte Carlo Offline Rendering

The research problems in Monte Carlo rendering have changed over the years. At first, the question was one of efficiency: how can we render an image quickly? Recent research has focused on rendering more complex effects, such as soft shadows and motion blur. There has also been research into the Monte Carlo technique itself; while it is a wellknown numerical technique, many subtleties have been...

Advances in Markov chain Monte Carlo methods

Probability distributions over many variables occur frequently in Bayesian inference, statistical physics and simulation studies. Samples from distributions give insight into their typical behavior and can allow approximation of any quantity of interest, such as expectations or normalizing constants. Markov chain Monte Carlo (MCMC), introduced by Metropolis et al. (1953), allows sampling from d...

The Monte Carlo Framework and Financial Applications

In these notes we describe the general Monte-Carlo framework for estimating expectations. We also give several applications from finance and describe how to simulate correlated normal random variables using the Cholesky decomposition of the covariance matrix. The ability to generate correlated normal random variables finds applications throughout finance. These applications include simulating c...