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Abstract The circumgalactic medium (CGM) around massive galaxies plays a crucial role in regulating star formation and feedback. Using the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) suite, we develop emulators for the X-ray surface brightness profile and the X-ray luminosity–stellar mass scaling relation, to investigate how stellar and active galactic nucleus (AGN) feedback shape the X-ray properties of the hot CGM. Our analysis shows that at CGM scales (1012≲Mhalo/M⊙≲ 1013, 10 ≲rkpc−1≲ 400), stellar feedback more significantly impacts the X-ray properties than AGN feedback within the parameters studied. Comparing the emulators to recent eROSITA All Sky Survey (eRASS) observations, it is found that stronger feedback than is currently implemented in the IllustrisTNG, SIMBA, and Astrid simulations is required to match the observed CGM properties. However, adopting these enhanced feedback parameters causes deviations in the stellar mass–halo mass relations from observational constraints below the group-mass scale. This tension suggests possible unaccounted-for systematics in X-ray CGM observations or inadequacies in the feedback models of cosmological simulations.
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Calibrating Cosmological Simulations with Implicit Likelihood Inference Using Galaxy Growth Observables
Abstract In a novel approach employing implicit likelihood inference (ILI), also known as likelihood-free inference, we calibrate the parameters of cosmological hydrodynamic simulations against observations, which has previously been unfeasible due to the high computational cost of these simulations. For computational efficiency, we train neural networks as emulators on ∼1000 cosmological simulations from the CAMELS project to estimate simulated observables, taking as input the cosmological and astrophysical parameters, and use these emulators as surrogates for the cosmological simulations. Using the cosmic star formation rate density (SFRD) and, separately, the stellar mass functions (SMFs) at different redshifts, we perform ILI on selected cosmological and astrophysical parameters (Ωm,σ8, stellar wind feedback, and kinetic black hole feedback) and obtain full six-dimensional posterior distributions. In the performance test, the ILI from the emulated SFRD (SMFs) can recover the target observables with a relative error of 0.17% (0.4%). We find that degeneracies exist between the parameters inferred from the emulated SFRD, confirmed with new full cosmological simulations. We also find that the SMFs can break the degeneracy in the SFRD, which indicates that the SMFs provide complementary constraints for the parameters. Further, we find that a parameter combination inferred from an observationally inferred SFRD reproduces the target observed SFRD very well, whereas, in the case of the SMFs, the inferred and observed SMFs show significant discrepancies that indicate potential limitations of the current galaxy formation modeling and calibration framework, and/or systematic differences and inconsistencies between observations of the SMFs.
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- PAR ID:
- 10396828
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 944
- Issue:
- 1
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 67
- Size(s):
- Article No. 67
- Sponsoring Org:
- National Science Foundation
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