Efficient gradient estimation using finite differencing and likelihood ratios for kinetic Monte Carlo simulations

Journal of Computational Physics

Volumn 231, Issue 21, 2012, Pages 7170-7186

  McGill, Jacob A ^a   Ogunnaike, Babatunde A ^a   Vlachos, Dionisios G ^a  

^a University of Delaware   (United States)

Author keywords

Finite difference; Gradient estimation; Kinetic Monte Carlo; Likelihood ratio; Sensitivity analysis; Stochastic

Indexed keywords

INTELLIGENT SYSTEMS; KINETICS; MONTE CARLO METHODS; NUMERICAL METHODS; POPULATION STATISTICS; RANDOM PROCESSES; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

FINITE DIFFERENCE; FINITE DIFFERENCING; GRADIENT ESTIMATION; GRADIENT INFORMATIONS; KINETIC MONTE CARLO; KINETIC MONTE CARLO SIMULATION; LIKELIHOOD RATIOS; OPTIMIZATION METHOD; POPULATION SIZES; STOCHASTICS;

SENSITIVITY ANALYSIS;

EID: 84865361693     PISSN: 00219991     EISSN: 10902716     Source Type: Journal    
DOI: 10.1016/j.jcp.2012.06.037     Document Type: Article

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