Monday, December 4, 2023

Understanding Molecular Clouds and Star Cluster Formation

Studying the formation of stars and star clusters is a topic of great interest in astrophysics. The giant molecular clouds (GMC) play a crucial role in the process, serving as the building blocks of stars and clusters. However, the interplay between the self-gravity of a molecular cloud and the feedback from a star cluster forming in its center is not well understood. In a recent study, researchers performed 1D radiation-hydrodynamic simulations to describe this interplay.

The model used in the study was a one-dimensional radiation-hydrodynamic model of a spherically symmetric cloud evolving under the influence of self-gravity and feedback from a star cluster forming in its center. The feedback included ionizing radiation, stellar winds, and radiation pressure acting on gas and dust. The star cluster was formed from the gas flowing into the cloud center, and the feedback parameters were determined from stellar evolution models and the cluster’s star-forming history.

The model was compared to a semi-analytic code called WARPFIELD, which implements similar physical processes and explores the scenario that the young cluster R136 in the Large Magellanic Cloud was formed due to the re-collapse of the shell formed by the previous generation star cluster. The researchers found good qualitative agreement between the model and WARPFIELD. However, the model required 3-4 times higher stellar mass to disrupt the cloud than WARPFIELD, as it took into account the self-gravity of the cloud surrounding the shell.

The researchers used the model to explore star formation in clouds with different mass, radius, and density profiles, measuring their star formation efficiency (SFE), which is the fraction of the cloud mass converted to stars. They found that SFE is a function of a single parameter, with log(SFE) proportional to -n_hm^-0.46, where n_hm is the cloud mean particle density within its half-mass radius. Furthermore, the researchers found that the feedback efficiency, i.e. the fraction of the feedback energy retained by gas, has a nearly constant value of approximately 10^-3.

The study provides new insights into the interplay between the self-gravity of a molecular cloud and the feedback from a star cluster forming in its center. By neglecting any turbulent forces or external dynamics that would support the cloud against its collapse, the researchers focused on the stellar feedback as the dominant mechanism to regulate the SFE. The study’s findings suggest that SFE is dependent on a single parameter, the cloud mean particle density within its half-mass radius. Additionally, the feedback efficiency remains constant, implying that the amount of feedback energy retained by gas is nearly the same in different clouds.

The study has important implications for our understanding of star and cluster formation in molecular clouds. The findings suggest that the self-gravity of the cloud and the feedback from a star cluster forming in its center play a crucial role in regulating the SFE. Further studies are needed to explore the interplay between these factors in more detail, including the effects of external forces such as turbulence and magnetic fields.

This highlights the importance of understanding the interplay between self-gravity and feedback in regulating star formation in molecular clouds. By using 1D radiation-hydrodynamic simulations, the researchers were able to shed light on the complex processes involved in star and cluster formation. The findings have important implications for our understanding of the formation and evolution of galaxies, as stars and clusters are the building blocks of galaxies. Further research in this area could lead to new insights into the nature of the universe and our place in it.

 

 

 

 

 

 

 

Source: Kourniotis, M., Wunsch, R., Mart'inez-Gonz'alez, S., Palouvs, J., Tenorio-
Tagle, G., & Ehlerov'a, S. (2023). Simulations of pre-supernova feedback in spherical
 clouds. https://doi.org/10.48550/arXiv.2303.08827

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