The SZ flux-mass ($Y$-$M$) relation at low halo masses: improvements with symbolic regression and strong constraints on baryonic feedback

Abstract

Feedback from active galactic nuclei (AGN) and supernovae can affect measurements of integrated SZ flux of halos ($Y_{\mathrm{SZ}}$) from CMB surveys, and cause its relation with the halo mass ($Y_{\mathrm{SZ}}-M$) to deviate from the self-similar power-law prediction of the virial theorem. We perform a comprehensive study of such deviations using CAMELS, a suite of hydrodynamic simulations with extensive variations in feedback prescriptions. We use a combination of two machine learning tools (random forest and symbolic regression) to search for analogues of the $Y-M$ relation which are more robust to feedback processes for low masses ($M\lesssim 10^{14}{h}^{-1}{M}_{\odot }$); we find that simply replacing $Y\to Y(1+M_{\ast }/M_{\mathrm{gas}})$ in the relation makes it remarkably self-similar. This could serve as a robust multiwavelength mass proxy for low-mass clusters and galaxy groups. Our methodology can also be generally useful to improve the domain of validity of other astrophysical scaling relations. We also forecast that measurements of the $Y-M$ relation could provide percent-level constraints on certain combinations of feedback parameters and/or rule out a major part of the parameter space of supernova and AGN feedback models used in current state-of-the-art hydrodynamic simulations. Our results can be useful for using upcoming SZ surveys (e.g., SO, CMB-S4) and galaxy surveys (e.g., DESI and Rubin) to constrain the nature of baryonic feedback. Finally, we find that the an alternative relation, $Y-M_{\ast }$, provides complementary information on feedback than $Y-M$

Version appearing in MNRAS. Minor change to Fig.6 and added Fig. A5 compared to the previous version. 7+5 pages. The code and data associated with this paper are available at https://github.com/JayWadekar/ScalingRelations_ML

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