Quantum Boltzmann equation solved by Monte Carlo method for nano-scale semiconductor devices simulation

2006 ◽  
Vol 15 (1) ◽  
pp. 177-181 ◽  
Author(s):  
Du Gang ◽  
Liu Xiao-Yan ◽  
Han Ru-Qi
Keyword(s):  
Monte Carlo ◽  
Boltzmann Equation ◽  
Monte Carlo Method ◽  
Semiconductor Devices ◽  
Quantum Boltzmann Equation ◽  
Nano Scale

Investigation of gate current in nano-scale MOSFETs by Monte Carlo solution of quantum Boltzmann equation

2007 ◽  
Vol 16 (2) ◽  
pp. 537-541 ◽  
Author(s):  
Xia Zhi-Liang ◽  
Du Gang ◽  
Liu Xiao-Yan ◽  
Kang Jin-Feng ◽  
Han Ru-Qi
Keyword(s):  
Monte Carlo ◽  
Boltzmann Equation ◽  
Gate Current ◽  
Quantum Boltzmann Equation ◽  
Nano Scale

Geometry entrapment in Walk-on-Subdomains

2019 ◽  
Vol 25 (4) ◽  
pp. 329-340 ◽  
Author(s):  
Preston Hamlin ◽  
W. John Thrasher ◽  
Walid Keyrouz ◽  
Michael Mascagni
Keyword(s):  
Monte Carlo ◽  
Boltzmann Equation ◽  
Monte Carlo Method ◽  
Electrostatic Energy ◽  
Potential Solution ◽  
Long Time ◽  
Poisson Boltzmann ◽  
Poisson Boltzmann Equation ◽  
Monte Carlo Implementation

Abstract One method of computing the electrostatic energy of a biomolecule in a solution uses a continuum representation of the solution via the Poisson–Boltzmann equation. This can be solved in many ways, and we consider a Monte Carlo method of our design that combines the Walk-on-Spheres and Walk-on-Subdomains algorithms. In the course of examining the Monte Carlo implementation of this method, an issue was discovered in the Walk-on-Subdomains portion of the algorithm which caused the algorithm to sometimes take an abnormally long time to complete. As the problem occurs when a walker repeatedly oscillates between two subdomains, it is something that could cause a large increase in runtime for any method that used a similar algorithm. This issue is described in detail and a potential solution is examined.

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