| Issue |
2014
SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo
|
|
|---|---|---|
| Article Number | 03407 | |
| Number of page(s) | 5 | |
| Section | 3. Monte Carlo Methods for Simulation: d. Uncertainty and Bias in Monte Carlo | |
| DOI | https://doi.org/10.1051/snamc/201403407 | |
| Published online | 06 June 2014 | |
Stochastic Perturbation Algorithms for Kinetic Monte Carlo Simulations
Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Korea
* Corresponding Author, E-mail: shimhj@snu.ac.kr
The accuracy of the kinetic Monte Carlo (KMC) simulations depends on the reliability of transition data used in the calculations. The sensitivity analyses may be useful to quantify the uncertainty of the KMC output and enhance the accuracy by ordering the transition data by importance. I derive a formulation of the differential operator sampling method for the KMC perturbation analysis from the Neumann series solution to the KMC master equation. The effectiveness of the KMC perturbation method is demonstrated in a simplified radioactive decay problem and the Langmuirian adsorption dynamics problem.
Key words: Kinetic Monte Carlo / Perturbation / Differential Operator Sampling
© Owned by the authors, published by EDP Sciences, 2014