Deterministic theory of Monte Carlo variance
- Univ. of Michigan, Ann Arbor, MI (United States)
The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validate this theory.
- OSTI ID:
- 426386
- Report Number(s):
- CONF-961103-; ISSN 0003-018X; TRN: 96:006307-0107
- Journal Information:
- Transactions of the American Nuclear Society, Vol. 75; Conference: Winter meeting of the American Nuclear Society (ANS) and the European Nuclear Society (ENS), Washington, DC (United States), 10-14 Nov 1996; Other Information: PBD: 1996
- Country of Publication:
- United States
- Language:
- English
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