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Quantifying Baryonic Feedback on Warm-Hot Circumgalactic Medium in CAMELS Simulations

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arxiv 2410.16361 v2 pith:7EH7V7CE submitted 2024-10-21 astro-ph.GA

classification astro-ph.GA
keywords feedbackstellarhalosimbasimulationssubgriddifferentefficiency
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The baryonic physics shaping galaxy formation and evolution are complex, spanning a vast range of scales and making them challenging to model. Cosmological simulations rely on subgrid models that produce significantly different predictions. Understanding how models of stellar and active galactic nuclei (AGN) feedback affect baryon behavior across different halo masses and redshifts is essential. Using the SIMBA and IllustrisTNG suites from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, we explore the effect of parameters governing the subgrid implementation of stellar and AGN feedback. We find that while IllustrisTNG shows higher cumulative feedback energy across all halos, SIMBA demonstrates a greater spread of baryons, quantified by the closure radius and circumgalactic medium (CGM) gas fraction. This suggests that feedback in SIMBA couples more effectively to baryons and drives them more efficiently within the host halo. There is evidence that different feedback modes are highly interrelated in these subgrid models. Parameters controlling stellar feedback efficiency significantly impact AGN feedback, as seen in the suppression of black hole mass growth and delayed activation of AGN feedback to higher mass halos with increasing stellar feedback efficiency in both simulations. Additionally, AGN feedback efficiency parameters affect the CGM gas fraction at low halo masses in SIMBA, hinting at complex, non-linear interactions between AGN and SNe feedback modes. Overall, we demonstrate that stellar and AGN feedback are intimately interwoven, especially at low redshift, due to subgrid implementation, resulting in halo property effects that might initially seem counterintuitive.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Cosmological analysis of X-ray cluster surveys VII. Bypassing scaling relations with Lagrangian Deep Learning and Simulation-based inference

    astro-ph.CO 2025-07 conditional novelty 6.0 of 10

    A simulation-based forward model combining conditioned Lagrangian Deep Learning with simulation-based inference aims to bypass empirical scaling relations in X-ray cluster cosmology, demonstrated on CAMELS/IllustrisTN...

  2. How does feedback affect the star formation histories of galaxies?

    astro-ph.GA 2025-08 conditional novelty 5.0 of 10

    A unified empirical equation, fitted separately to three simulation suites, links galaxy star formation history shape to halo mass, baryon fraction, black hole mass, and feedback strength.

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