分类： 天文学 >> 天文学 提交时间： 2023-02-19
Anton V. Afanasiev
Simona Mei
Hao Fu
Francesco Shankar
Stefania Amodeo
Daniel Stern
Elizabeth A. Cooke
Anthony H. Gonzalez
Gaël Noirot
Alessandro Rettura
Dominika Wylezalek
Carlos De Breuck
Nina A. Hatch
Spencer A. Stanford
Joël Vernet
摘要： (Abridged) We study the galaxy mass-size relation in CARLA spectroscopically
confirmed clusters at $1.410.5$ are
systematically $\gtrsim 0.2-0.3~{\rm dex}$ larger than field ETGs. The passive
ETG average size evolution is slower at $1
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Hao Fu
Francesco Shankar
Mohammadreza Ayromlou
Max Dickson
Ioanna Koutsouridou
Yetli Rosas-Guevara
Christopher Marsden
Kristina Brocklebank
Mariangela Bernardi
Nikolaos Shiamtanis
Joseph Williams
Lorenzo Zanisi
Viola Allevato
Lumen Boco
Silvia Bonoli
Andrea Cattaneo
Paola Dimauro
Fangzhou Jiang
Andrea Lapi
Nicola Menci
摘要： The relative roles of mergers and star formation in regulating galaxy growth are still a matter of intense debate. We here present our DECODE, a new Discrete statistical sEmi-empiriCal mODEl specifically designed to predict rapidly and efficiently, in a full cosmological context, galaxy assembly and merger histories for any given input stellar mass-halo mass (SMHM) relation. DECODE generates object-by-object dark matter merger trees (hence discrete) from accurate subhalo mass and infall redshift probability functions (hence statistical) for all subhaloes, including those residing within other subhaloes, with virtually no resolution limits on mass or volume. Merger trees are then converted into galaxy assembly histories via an input, redshift dependent SMHM relation, which is highly sensitive to the significant systematics in the galaxy stellar mass function and on its evolution with cosmic time. DECODE can accurately reproduce the predicted mean galaxy merger rates and assembly histories of hydrodynamic simulations and semi-analytic models, when adopting in input their SMHM relations. In the present work we use DECODE to prove that only SMHM relations implied by stellar mass functions characterized by large abundances of massive galaxies and significant redshift evolution, at least at $M_\star \gtrsim 10^{11} \, M_\odot$, can simultaneously reproduce the local abundances of satellite galaxies, the galaxy (major merger) pairs since $z \sim 3$, and the growth of Brightest Cluster Galaxies. The same models can also reproduce the local fraction of elliptical galaxies, on the assumption that these are strictly formed by major mergers, but not the full bulge-to-disc ratio distributions, which require additional processes.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Duncan Farrah
Sara Petty
Kevin Croker
Gregory Tarle
Michael Zevin
Evanthia Hatziminaoglou
Francesco Shankar
Lingyu Wang
David L Clements
Andreas Efstathiou
Mark Lacy
Kurtis A. Nishimura
Jose Afonso
Chris Pearson
Lura K Pitchford
摘要： The assembly of stellar and supermassive black hole (SMBH) mass in elliptical galaxies since $z\sim1$ can help to diagnose the origins of locally-observed correlations between SMBH mass and stellar mass. We therefore construct three samples of elliptical galaxies, one at $z\sim0$ and two at $0.7\lesssim z \lesssim2.5$, and quantify their relative positions in the $M_{BH}-M_*$ plane. Using a Bayesian analysis framework, we find evidence for translational offsets in both stellar mass and SMBH mass between the local sample and both higher redshift samples. The offsets in stellar mass are small, and consistent with measurement bias, but the offsets in SMBH mass are much larger, reaching a factor of seven between $z\sim1$ and $z\sim0$. The magnitude of the SMBH offset may also depend on redshift, reaching a factor of $\sim20$ at $z\sim 2$. The result is robust against variation in the high and low redshift samples and changes in the analysis approach. The magnitude and redshift evolution of the offset are challenging to explain in terms of selection and measurement biases. We conclude that either there is a physical mechanism that preferentially grows SMBHs in elliptical galaxies at $z\lesssim 2$, or that selection and measurement biases are both underestimated, and depend on redshift.
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