Modeling Of Astrochemistry During Star Formation

Interstellar matter is not inert, but is constantly evolving. On the one hand, its physical characteristics such as its density and its temperature, and on the other hand, its chemical characteristics such as the abundances of the species and their distribution, can change drastically. The phases of this evolution spread over different timescales, and this matter evolves to create very different objects such as molecular clouds ($\rm T \sim 10~K$, $\rm n \sim 10^4~cm^{-3}$, $\rm t \sim 10^6~years$), collACSing prestellar cores (inner core : $\rm T \sim 1000~K$, $\rm n \sim 10^{16}~cm^{-3}$, $\rm t \sim 10^4~years$), protostellar cores (inner core : $\rm T \sim 10^5~K$, $\rm n \sim 10^{24}~cm^{-3}$, $\rm t \sim 10^6~years$), or protoplanetary disks ($\rm T \sim 10-1000~K$, $\rm n \sim 10^{9}-10^{12}~cm^{-3}$, $\rm t \sim 10^7~years$). These objects are the stages of the star formation process. Starting from the diffuse cloud, matter evolves to form molecular clouds. Then, matter can condense to form prestellar cores, which can collACSe to form a protostar surrounded by a protoplanetary disk. The protostar can evolve in a star, and planets and comets can be formed in the disk. Thus, modeling of astrochemistry during star formation should consider chemical and physical evolution in parallel. We present a new gas-grain chemical network involving deuterated species, which takes into account ortho, para, and meta states of H$_2$, D$_2$, H$_3^+$, H$_2$D$^+$, D$_2$H$^+$, and D$_3^+$. It includes high temperature gas phase reactions, and some ternary reactions for high density, so that it should be able to simulate media with temperature equal to [$10;800$]~K and density equal to [$\sim10^4;\sim10^{12}$]~cm$^{-3}$. We apply this network to the modeling of low-mass and high-mass star formation, using a gas-grain chemical code coupled to a time dependent physical structure. Comparisons with observational constraints, such as the HDO/H$_2$O ratio in high mass star forming region, give good agreement which is promising. Besides, high density conditions have highlighted some limitations of our grain surface modeling. We present a numerical technique to model in a more realistic way H$_2$ diffusion and desorption in high density conditions