Deterministic theory of Monte Carlo variance
Journal Article
·
· Transactions of the American Nuclear Society
OSTI ID:426386
- 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--
- Journal Information:
- Transactions of the American Nuclear Society, Journal Name: Transactions of the American Nuclear Society Vol. 75; ISSN TANSAO; ISSN 0003-018X
- Country of Publication:
- United States
- Language:
- English
Similar Records
A kinetic theory for nonanalog Monte Carlo particle transport algorithms: Exponential transform with angular biasing in planar-geometry anisotropically scattering media
Automatic variance reduction for Monte Carlo simulations via the local importance function transform
Implementation of hybrid variance reduction methods in a multi group Monte Carlo code for deep shielding problems
Journal Article
·
Tue Sep 01 00:00:00 EDT 1998
· Journal of Computational Physics
·
OSTI ID:653492
Automatic variance reduction for Monte Carlo simulations via the local importance function transform
Technical Report
·
Wed Jan 31 23:00:00 EST 1996
·
OSTI ID:212579
Implementation of hybrid variance reduction methods in a multi group Monte Carlo code for deep shielding problems
Conference
·
Mon Jul 01 00:00:00 EDT 2013
·
OSTI ID:22212710