20-22 May 2015
Asia/Bangkok timezone
The Centennial Celebration of General Relativity Theory and 80 Years of Thai Physics Graduate

Modified kinetic Monte-Carlo algorithm based on fluctuation theorem

20 May 2015, 14:15
15m
Phokeethra 2 ()

Phokeethra 2

Oral presentation Statistical and Theoretical Physics Statistical and Theoretical Physics

Speaker

Mr Takol Tangphati (Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand)

Description

Kinetic Monte Carlo (KMC) is an algorithm which finds transitions between states during an evolution of a system out of equilibrium according to the prescribed transition rate probabilities. One Major caveat with the original KMC is no attention that is given to how the system interacts with the environment. In particular, it is not known how the transition rate probability matrix plays a role in determining the heat exchange with the environment. To improve upon KMC, a fluctuation theorem is applied to KMC that connects the ratio of transition rate probability and its time conjugate to the entropy change of the environment. Our Modified Kinetic Monte Carlo (MKMC) algorithm chooses the next state in such a way as to obey the second law of thermodynamics. We apply the algorithm to solve the problem of Brownian heat engine operating between two heat baths. The result of the simulation is consistent with the analytic solution and the second law of thermodynamics.

Primary author

Mr Takol Tangphati (Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand)

Co-author

Dr Surachate Limkumnerd ((1) Department of Physics, Faculty of Science, Chulalongkorn University, Phayathai Road, Patumwan, Bangkok 10330, Thailand and (2) Research Center in Thin Film Physics, Thailand Center of Excellence in Physics, CHE, 328 Si Ayutthaya Road, Bangkok 10400, Thailand)

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