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Context.Feedback from stars in the form of radiation, stellar winds, and supernovae is crucial to regulating the star formation activity of galaxies. Dwarf galaxies are especially susceptible to these processes, making them an ideal test bed for studying the effects of stellar feedback in detail. Recent numerical models have aimed to resolve the interstellar medium (ISM) in dwarf galaxies with a very high resolution of several solar masses. However, when it comes to modeling the radiative feedback from stars, many models opt for simplified approaches instead of explicitly solving radiative transfer (RT) because of the computational complexity involved. Aims.We introduce the Realistic ISM modeling in Galaxy Evolution and Lifecycles (RIGEL) model, a novel framework to self-consistently model the effects of stellar feedback in the multiphase ISM of dwarf galaxies with explicit RT on a star-by-star basis. Methods.The RIGEL model integrates detailed implementations of feedback from individual massive stars into the state-of-the-art radiation-hydrodynamics code,AREPO-RT. It forms individual massive stars from the resolved multiphase ISM by sampling the initial mass function and tracks their evolution individually. The lifetimes, photon production rates, mass-loss rates, and wind velocities of these stars are determined by their initial masses and metallicities based on a library that incorporates a variety of stellar models. The RT equations are solved explicitly in seven spectral bins accounting for the infrared to He IIionizing bands, using a moment-base scheme with the M1 closure relation. The thermochemistry model tracks the nonequilibrium H, He chemistry as well as the equilibrium abundance of C I, C II, O I, O II, and CO in the irradiated ISM to capture the thermodynamics of all ISM phases, from cold molecular gas to hot ionized gas. Results.We evaluated the performance of the RIGEL model using 1 M⊙resolution simulations of isolated dwarf galaxies. We found that the star formation rate (SFR) and interstellar radiation field (ISRF) show strong positive correlations with the metallicity of the galaxy. Photoionization and photoheating can reduce the SFR by an order of magnitude by removing the available cold, dense gas fuel for star formation. The presence of ISRF also significantly changes the thermal structure of the ISM. Radiative feedback occurs immediately after the birth of massive stars and rapidly disperses the molecular clouds within 1 Myr. As a consequence, radiative feedback reduces the age spread of star clusters to less than 2 Myr, prohibits the formation of massive star clusters, and shapes the cluster initial mass function to a steep power-law form with a slope of ∼ − 2. The mass-loading factor (measured atz = 1 kpc) of the fiducial galaxy has a median ofηM ∼ 50, while turning off radiative feedback reduces this factor by an order of magnitude. Conclusions.We demonstrate that RIGEL effectively captures the nonlinear coupling of early radiative feedback and supernova feedback in the multiphase ISM of dwarf galaxies. This novel framework enables the utilization of a comprehensive stellar feedback and ISM model in cosmological simulations of dwarf galaxies and various galactic environments spanning a wide dynamic range in both space and time.
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This content will become publicly available on July 1, 2026
ASURA-FDPS-ML: Star-by-star Galaxy Simulations Accelerated by Surrogate Modeling for Supernova Feedback
Abstract We introduce new high-resolution galaxy simulations accelerated by a surrogate model that reduces the computation cost by approximately 75%. Massive stars with a zero-age main-sequence mass of more than about 10M⊙explode as core-collapse supernovae (CCSNe), which play a critical role in galaxy formation. The energy released by CCSNe is essential for regulating star formation and driving feedback processes in the interstellar medium (ISM). However, the short integration time steps required for SN feedback have presented significant bottlenecks in astrophysical simulations across various scales. Overcoming this challenge is crucial for enabling star-by-star galaxy simulations, which aim to capture the dynamics of individual stars and the inhomogeneous shell’s expansion within the turbulent ISM. To address this, our new framework combines direct numerical simulations and surrogate modeling, including machine learning and Gibbs sampling. The star formation history and the time evolution of outflow rates in the galaxy match those obtained from resolved direct numerical simulations. Our new approach achieves high-resolution fidelity while reducing computational costs, effectively bridging the physical scale gap and enabling multiscale simulations.
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- PAR ID:
- 10648139
- Publisher / Repository:
- AAS
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 987
- Issue:
- 1
- ISSN:
- 0004-637X
- Page Range / eLocation ID:
- 86
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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