Variance and Covariance Estimation in Stationary Monte Carlo Device Simulation
This work deals with the Monte Carlo method for stationary device simulation, known as the Single-Particle Monte Carlo method. A thorough mathematical analysis of this method clearly identifies the independent, identically distributed random variables of the simulated process. Knowledge of these random variables allows usage of straight-forward estimates of the stochastic error. The presented method of error estimation is applicable to both distributed quantities and integrated quantities such as terminal currents.
KeywordsMonte Carlo Particle Density Device Simulation Stochastic Error Free Flight
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- C. Jungemann and B. Meinerzhagen, “Efficiency and Stochastic Error of Monte Carlo Device Simulations,” in Int.Electron Devices Meeting, pp. 109–112, 2000.Google Scholar
- H. Kosina, M. Nedjalkov, and S. Selberherr, “Variance Reduction in Monte Carlo Device Simulation by Means of Event Biasing,” in Proc. Modeling and Simulation of Microsystems, MSM 2001 (M. Laudon and B. Romanowicz, eds.), pp. 11–14, Computational Publications, Mar. 2001.Google Scholar
- R. Rubinstein, Simulation and the Monte Carlo Method. John Wiley and Sons, 1981.Google Scholar