Kavli Affiliate: David N. Spergel
| First 5 Authors: Digvijay Wadekar, Leander Thiele, J. Colin Hill, Shivam Pandey, Francisco Villaescusa-Navarro
| Summary:
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 ($Mlesssim 10^{14}, h^{-1} , M_odot$);
we find that simply replacing $Yrightarrow Y(1+M_*/M_mathrm{gas})$ 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, $Y-M_*$, provides
complementary information on feedback than $Y-M$
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