Large Deviation Methods for the Analysis and Design of Monte Carlo Schemes in Physics and Chemistry. Final Technical Report
- Brown Univ., Providence, RI (United States)
This proposal is concerned with applications of Monte Carlo to problems in physics and chemistry where rare events degrade the performance of standard Monte Carlo. One class of problems is concerned with computation of various aspects of the equilibrium behavior of some Markov process via time averages. The problem to be overcome is that rare events interfere with the efficient sampling of all relevant parts of phase space. A second class concerns sampling transitions between two or more stable attractors. Here, rare events do not interfere with the sampling of all relevant parts of phase space, but make Monte Carlo inefficient because of the very large number of samples required to obtain variance comparable to the quantity estimated. The project uses large deviation methods for the mathematical analyses of various Monte Carlo techniques, and in particular for algorithmic analysis and design. This is done in the context of relevant application areas, mainly from chemistry and biology.
- Research Organization:
- Brown Univ., Providence, RI (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- SC0002413
- OSTI ID:
- 1123314
- Report Number(s):
- DOE-BROWN-2413
- Country of Publication:
- United States
- Language:
- English
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