Unravelling the role of merger histories in the population of In situ stars: linking IllustrisTNG cosmological simulation to H3 survey
Razieh Emami, Lars Hernquist, Randall Smith, James F. Steiner, Grant Tremblay, Douglas Finkbeiner, Mark Vogelsberger, Josh Grindlay, Federico Marinacci, Kung-Yi Su, Cecilia Garraffo, Yuan-Sen Ting, Phillip A. Cargile, Rebecca L. Davies, Chlo\"e E. Benton, Yijia Li

TL;DR
This study compares the distribution of in-situ stars in Milky Way-like galaxies from TNG50 simulations with H3 survey data, revealing key correlations with merger history and internal galaxy parameters that influence their alignment.
Contribution
It links cosmological simulation data with observational survey results to identify factors affecting in-situ star distributions in Milky Way-like galaxies.
Findings
28% of galaxies match H3 data reasonably well
Significant correlations between deviations and merger parameters
Validation of correlations using Random Forest Regression
Abstract
We undertake a comprehensive investigation into the distribution of in~situ stars within Milky Way-like galaxies, leveraging TNG50 simulations and comparing their predictions with data from the H3 survey. Our analysis reveals that 28% of galaxies demonstrate reasonable agreement with H3, while only 12% exhibit excellent alignment in their profiles, regardless of the specific spatial cut employed to define in~situ stars. To uncover the underlying factors contributing to deviations between TNG50 and H3 distributions, we scrutinise correlation coefficients among internal drivers(e.g., virial radius, star formation rate [SFR]) and merger-related parameters (such as the effective mass-ratio, mean distance, average redshift, total number of mergers, average spin-ratio and maximum spin alignment between merging galaxies). Notably, we identify significant correlations between deviations from…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Stellar, planetary, and galactic studies · Astronomical Observations and Instrumentation
