Exhaustive state-to-state cross sections for reactive molecular collisions from importance sampling simulation and a neural network representation | Zendy

Debasish Koner | Zendy; Oliver T. Unke | Zendy; Kyle Boe | Zendy; Raymond J. Bemish | Zendy; Markus Meuwly | Zendy

Open Access

Exhaustive state-to-state cross sections for reactive molecular collisions from importance sampling simulation and a neural network representation

Author(s) -

Debasish Koner,

Oliver T. Unke,

Kyle Boe,

Raymond J. Bemish,

Markus Meuwly

Publication year - 2019

Publication title -

the journal of chemical physics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.071

H-Index - 357

eISSN - 1089-7690

pISSN - 0021-9606

DOI - 10.1063/1.5097385

Subject(s) - statistical physics , non equilibrium thermodynamics , representation (politics) , monte carlo method , state (computer science) , population , computer science , artificial neural network , trajectory , function (biology) , flow (mathematics) , algorithm , physics , artificial intelligence , mathematics , mechanics , statistics , thermodynamics , political science , law , demography , evolutionary biology , sociology , politics , biology , astronomy

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