Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations

Núñez, M.; Vlachos, D. G.

doi:10.1063/1.4905957

Title: Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations

Journal Article · Mon Jan 26 00:00:00 EST 2015 · Journal of Chemical Physics

DOI:https://doi.org/10.1063/1.4905957· OSTI ID:1420478

Núñez, M.; Vlachos, D. G.

Kinetic Monte Carlo simulation is an integral tool in the study of complex physical phenomena present in applications ranging from heterogeneous catalysis to biological systems to crystal growth and atmospheric sciences. Sensitivity analysis is useful for identifying important parameters and rate-determining steps, but the finite-difference application of sensitivity analysis is computationally demanding. Techniques based on the likelihood ratio method reduce the computational cost of sensitivity analysis by obtaining all gradient information in a single run. However, we show that disparity in time scales of microscopic events, which is ubiquitous in real systems, introduces drastic statistical noise into derivative estimates for parameters affecting the fast events. In this work, the steady-state likelihood ratio sensitivity analysis is extended to singularly perturbed systems by invoking partial equilibration for fast reactions, that is, by working on the fast and slow manifolds of the chemistry. Derivatives on each time scale are computed independently and combined to the desired sensitivity coefficients to considerably reduce the noise in derivative estimates for stiff systems. The approach is demonstrated in an analytically solvable linear system.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0010549

OSTI ID:: 1420478

Journal Information:: Journal of Chemical Physics, Journal Name: Journal of Chemical Physics Vol. 142 Journal Issue: 4; ISSN 0021-9606

Publisher:: American Institute of PhysicsCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 12 works

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