The influence of the cloud virial parameter on the initial mass function
ABSTRACT Crucial for star formation is the interplay between gravity and turbulence. The observed cloud virial parameter, $\alpha _{\mathrm{vir}}$, which is the ratio of twice the turbulent kinetic energy to the gravitational energy, is found to vary significantly in different environments, where the scatter among individual star-forming clouds can exceed an order of magnitude. Therefore, a strong dependence of the initial mass function (IMF) on $\alpha _{\mathrm{vir}}$ may challenge the notion of a universal IMF. To determine the role of $\alpha _{\mathrm{vir}}$ on the IMF, we compare the star-particle mass functions obtained in high-resolution magnetohydrodynamical simulations including jet and heating feedback, with $\alpha _{\mathrm{vir}}=0.0625$, 0.125, and 0.5. We find that varying $\alpha _{\mathrm{vir}}$ from $\alpha _{\mathrm{vir}}\sim 0.5$ to $\alpha _{\mathrm{vir}}< 0.1$ shifts the peak of the IMF to lower masses by a factor of $\sim 2$ and increases the star formation rate by a similar factor. The dependence of the IMF and star formation rate on $\alpha _{\mathrm{vir}}$ is non-linear, with the dependence subsiding at $\alpha _{\mathrm{vir}}< 0.1$. Our study shows a systematic dependence of the IMF on $\alpha _{\mathrm{vir}}$. Yet, it may not be measurable easily in observations, considering the uncertainties, and the relatively weak dependence found in this study.
Authors
- Christoph Federrath (ORCID: https://orcid.org/0000-0002-0706-2306)
- Sajay Sunny Mathew (ORCID: https://orcid.org/0000-0002-8381-8195)
- Amit Seta (ORCID: https://orcid.org/0000-0001-9708-0286)
Institutions
- Australian National University (AU)
- Australian Research Council (AU)
- ASTRO-3D (AU)
Publication Details
- Journal
- Monthly Notices of the Royal Astronomical Society
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1093/mnras/stae2692
- Citations
- 5
- Primary Topic
- Astrophysics and Star Formation Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.66
Funders
- U.S. Department of Energy
- University of Chicago
- University of Rochester
- National Computational Infrastructure
- Deutscher Akademischer Austauschdienst
- Gujarat Cancer Society
- Gauss Centre for Supercomputing
- Universities Australia
- Australian Research Council
- Leibniz-Gemeinschaft