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 observational data and key parameters such as the median slope of virial radius, mean SFR values, and the rate of SFR change across different redshift scans. Furthermore, positive correlations emerge between deviations from observational data and parameters related to galaxy mergers. We validate these correlations using the Random Forest Regression method. Our findings underscore the invaluable insights provided by the H3 survey in unravelling the cosmic history of galaxies akin to the Milky Way, thereby advancing our understanding of galactic evolution and shedding light on the formation and evolution of Milky Way-like galaxies in cosmological simulations.

Emami, R., Hernquist, L., Smith, R., Steiner, J.F., Tremblay, G., Finkbeiner, D., et al. (2025). Unravelling the role of merger histories in the population of in situ stars: Linking IllustrisTNG cosmological simulation to H3 survey. PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF AUSTRALIA, 42, 1-18 [10.1017/pasa.2025.10032].

Unravelling the role of merger histories in the population of in situ stars: Linking IllustrisTNG cosmological simulation to H3 survey

Marinacci, Federico;Bugiani, Letizia;
2025

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 observational data and key parameters such as the median slope of virial radius, mean SFR values, and the rate of SFR change across different redshift scans. Furthermore, positive correlations emerge between deviations from observational data and parameters related to galaxy mergers. We validate these correlations using the Random Forest Regression method. Our findings underscore the invaluable insights provided by the H3 survey in unravelling the cosmic history of galaxies akin to the Milky Way, thereby advancing our understanding of galactic evolution and shedding light on the formation and evolution of Milky Way-like galaxies in cosmological simulations.
2025
Emami, R., Hernquist, L., Smith, R., Steiner, J.F., Tremblay, G., Finkbeiner, D., et al. (2025). Unravelling the role of merger histories in the population of in situ stars: Linking IllustrisTNG cosmological simulation to H3 survey. PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF AUSTRALIA, 42, 1-18 [10.1017/pasa.2025.10032].
Emami, Razieh; Hernquist, Lars; Smith, Randall; Steiner, James F.; Tremblay, Grant; Finkbeiner, Douglas; Vogelsberger, Mark; Grindlay, Josh; Marinacci...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1028952
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