A Multi-Wavelength Technique for Estimating Galaxy Cluster Mass Accretion Rates

Autor:	Soltis, John, Ntampaka, Michelle, Diemer, Benedikt, ZuHone, John, Bose, Sownak, Delgado, Ana Maria, Hadzhiyska, Boryana, Hernandez-Aguayo, Cesar, Nagai, Daisuke, Trac, Hy
Rok vydání:	2024
Předmět:	Astrophysics - Cosmology and Nongalactic Astrophysics
Druh dokumentu:	Working Paper
Popis:	The mass accretion rate of galaxy clusters is a key factor in determining their structure, but a reliable observational tracer has yet to be established. We present a state-of-the-art machine learning model for constraining the mass accretion rate of galaxy clusters from only X-ray and thermal Sunyaev-Zeldovich observations. Using idealized mock observations of galaxy clusters from the MillenniumTNG simulation, we train a machine learning model to estimate the mass accretion rate. The model constrains 68% of the mass accretion rates of the clusters in our dataset to within 33% of the true value without significant bias, a ~58% reduction in the scatter over existing constraints. We demonstrate that the model uses information from both radial surface brightness density profiles and asymmetries. Comment: 13 pages, 9 figures, 1 table
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2412.05370 Zobrazit plný text záznamu View this record from Arxiv