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Increased Burstiness at High Redshift in Multi-Physics Models Combining Supernova Feedback, Radiative Transfer and Cosmic Rays

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arxiv 2410.00113 v1 pith:KMVPPSVM submitted 2024-09-30 astro-ph.GA

Increased Burstiness at High Redshift in Multi-Physics Models Combining Supernova Feedback, Radiative Transfer and Cosmic Rays

classification astro-ph.GA
keywords formationstarcosmicmodelsrtnscrimhdburstinessgalaxiesgalaxy
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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abstract

We study star formation variability, or burstiness, as a method to constrain and compare different galaxy formation models at high redshift using the Azahar simulation suite. The models range from magneto-hydrodynamics with a magneto-thermo-turbulent prescription for star formation (iMHD) to more sophisticated setups incorporating radiative transfer (RTiMHD) and cosmic ray physics (RTnsCRiMHD). Analysing a sample of galaxies at redshifts $z=4-10$, we find that the RTnsCRiMHD model exhibits more regular star formation periodicity compared to iMHD and RTiMHD, as revealed by the Lomb-Scargle periodogram. While the RTiMHD model captures a notable degree of stochasticity in star formation without cosmic rays, RTnsCRiMHD galaxies display even greater scatter in the burst intensity and in the scatter around the star-forming main sequence. To evaluate the burstiness in RTnsCRiMHD against observations, we generate a mock spectrum during a mini-quenching event at $z=7.5$. This spectrum aligns well with the low-mass quiescent galaxy JADES-GS-z7-01-QU observed at $z=7.3$, though some discrepancies attributed to stellar metallicity hint at a composite spectrum. Our findings highlight the importance of including complex physical processes like cosmic rays and radiative transfer in simulations to accurately capture the bursty nature of star formation in high-redshift galaxies. Future JWST observations, particularly regarding the scatter around the star-forming main sequence, have the potential to refine and guide the next generation of galaxy formation models.

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