A 3D physico-chemical model of a pre-stellar core

II. Dynamic chemical evolution in a pre-stellar core model using tracer particles

¹ Max-Planck-Institut für extraterrestrische Physik, Giessenbachstrasse 1, 85748 Garching, Germany
² Niels Bohr Institute, University of Copenhagen, Jagtvej 155A, 2200 Copenhagen, Denmark

^★ Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 19 January 2026
Accepted: 11 March 2026

Abstract

Context. Pre-stellar cores mark the earliest phase of star formation. By characterizing their physical and chemical structure, we can establish the initial conditions for star and planet formation and assess how closely the chemical composition of these cores is connected to later evolutionary stages.

Aims. We explore the differences between static and dynamically evolving physico-chemical models of pre-stellar cores. The results are compared with observations of the pre-stellar core L1544 to estimate how well 3D physico-chemical models can reproduce the chemistry at this evolutionary stage.

Methods. A 3D magnetohydrodynamic model of a pre-stellar core embedded in a dynamic star-forming cloud was post-processed using sequentially dust radiative transfer, a gas-grain chemical model, and a nonlocal thermodynamic equilibrium line-radiative transfer model. The chemical evolution was modeled along ~20 000 tracer particle trajectories to capture the effect of a realistic dynamical evolution as the core formed. The emission morphology of CH₃OH and c-C₃H₂ and the intensities of CH₃OH, c-C₃H₂, CS, SO, HCN, HCO⁺, and N₂H⁺ were compared with observations of L1544. We compared initial elemental abundances with and without depletion of heavier elements.

Results. Our results show a distinct difference in chemical morphology between the dynamical and static models. The dynamical model reproduces the observed spatial distribution of CH₃OH and c-C₃H₂ toward L1544, whereas the static model fails to reproduce this morphology. In contrast, when we compared modeled and observed intensities across a broad range of molecules, the static model agreed well with observations for L1544. The dynamical model systematically predicts lower abundances and modeled intensities for six of the seven species presented here. For sulfur-bearing species, the intensities agree better with observations when the initial abundances are not depleted in heavier elements.

Conclusions. We reveal distinct differences between dynamical and static physico-chemical models. The static model predicts higher abundances and intensities for the majority of the molecules we studied than the dynamical model. This discrepancy may stem from the specific choices of initial conditions, which might limit the ability of the dynamical models to fully capture the physical and chemical history. The intensities predicted by the static model are comparable to those observed toward L1544.