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 ap...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.展开更多
基金supported by the CAS “Light of West China Program” (2017-QNXZ-B)Youth Innovation Promotion Association CAS+3 种基金the Heaven Lake Hundred-Talent Program of Xinjiang Uygur Autonomous Region of Chinathe 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)
文摘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.
