A new data structure for accelerating kinetic Monte Carlo method  

作　　者：Xu-Li Zheng Dong-Hui Quan Hai-Long Zhang Xiao-Hu Li Qiang Chang Olli Sipila 

机构地区：[1]Xinjiang Astronomical Observatory,Chinese Academy of Sciences,Urumqi 830011,China [2]Department of Chemistry,Eastern Kentucky University,Richmond,KY,USA [3]Max-Planck-Institute for Extraterrestrial Physics(MPE),Giessenbachstr.1,85748 Garching,Germany [4]School of Astronomy and Space Science,University of Chinese Academy of Sciances,Beijing 100049,China

出　　处：《Research in Astronomy and Astrophysics》2019年第12期235-244,共10页天文和天体物理学研究（英文版）

基　　金：supported by the CAS “Light of West China Program” (2017-QNXZ-B);Youth Innovation Promotion Association CAS;the Heaven Lake Hundred-Talent Program of Xinjiang Uygur Autonomous Region of China;the National Natural Science Foundation of China (Nos. 11673054 11873082, U1531125, 11803080, 11503075, 11543002, 11673054 and 11703075);the National Key Basic Research Program of China (973 Program 2015CB857100);the National Key Basic Research and Development Program (2018YFA0404704)

摘　　要：The kinetic Monte Carlo simulation is a rigorous numerical approach to study the chemistry on dust grains in cold dense interstellar clouds. By tracking every single reaction in chemical networks step by step, this approach produces more precise results than other approaches but takes too much computing time. Here we present a method of a new data structure, which is applicable to any physical conditions and chemical networks, to save computing time for the Monte Carlo algorithm. Using the improved structure,the calculating time is reduced by 80 percent compared with the linear structure when applied to the osu-2008 chemical network at 10K. We investigate the effect of the encounter desorption in cold cores using the kinetic Monte Carlo model with an accelerating data structure. We found that the encounter desorption remarkably decreases the abundance of grain-surface H2 but slightly influences the abundances of other species on the grain.The kinetic Monte Carlo simulation is a rigorous numerical approach to study the chemistry on dust grains in cold dense interstellar clouds. By tracking every single reaction in chemical networks step by step, this approach produces more precise results than other approaches but takes too much computing time. Here we present a method of a new data structure, which is applicable to any physical conditions and chemical networks, to save computing time for the Monte Carlo algorithm. Using the improved structure,the calculating time is reduced by 80 percent compared with the linear structure when applied to the osu-2008 chemical network at 10K. We investigate the effect of the encounter desorption in cold cores using the kinetic Monte Carlo model with an accelerating data structure. We found that the encounter desorption remarkably decreases the abundance of grain-surface H2 but slightly influences the abundances of other species on the grain.

关 键 词：ASTROCHEMISTRY molecular processes methods:numerical ISM:molecules ISM:abundances 

分 类 号：O242.2[理学—计算数学] P148[理学—数学]