Application of variance reduction techniques in EGSnrc based Monte-Carlo method

Variance Reduction Techniques in Monte Carlo Methods

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the introduction of computers. This increased computer power has stimulated simulation analysts to develo...

Monte Carlo calculation of specific absorbed fractions: variance reduction techniques.

The purpose of the present work is to calculate specific absorbed fractions using variance reduction techniques and assess the effectiveness of these techniques in improving the efficiency (i.e. reducing the statistical uncertainties) of simulation results in cases where the distance between the source and the target organs is large and/or the target organ is small. The variance reduction techn...

Variance Reduction in Monte-Carlo Tree Search

Monte-Carlo Tree Search (MCTS) has proven to be a powerful, generic planning technique for decision-making in single-agent and adversarial environments. The stochastic nature of the Monte-Carlo simulations introduces errors in the value estimates, both in terms of bias and variance. Whilst reducing bias (typically through the addition of domain knowledge) has been studied in the MCTS literature...

Static Inductance Extraction by Means of the Monte Carlo Method and Variance Reduction Techniques for Acceleration

With increasing signal frequencies inductive effects of metallic interconnections in all kinds of packages become more and more important for the electrical performance of a circuit. During the design process it is therefore of interest to have a stable, fast and accurate simulation tool which is capable of extracting the inductance of large and complicated geometries. This work presents a new ...

Monte Carlo Integration and Variance Reduction