The quenching of galaxies, bulges, and disks since cosmic noon

Abstract

We present an analysis of the quenching of star formation in galaxies, bulges, and disks throughout the bulk of cosmic history, from z = 2 − 0. We utilise observations from the Sloan Digital Sky Survey and the Mapping Nearby Galaxies at Apache Point Observatory survey at low redshifts. We complement these data with observations from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey at high redshifts. Additionally, we compare the observations to detailed predictions from the LGalaxies semi-analytic model. To analyse the data, we developed a machine learning approach utilising a Random Forest classifier. We first demonstrate that this technique is extremely effective at extracting causal insight from highly complex and inter-correlated model data, before applying it to various observational surveys. Our primary observational results are as follows: at all redshifts studied in this work, we find bulge mass to be the most predictive parameter of quenching, out of the photometric parameter set (incorporating bulge mass, disk mass, total stellar mass, and B/T structure). Moreover, we also find bulge mass to be the most predictive parameter of quenching in both bulge and disk structures, treated separately. Hence, intrinsic galaxy quenching must be due to a stable mechanism operating over cosmic time, and the same quenching mechanism must be effective in both bulge and disk regions. Despite the success of bulge mass in predicting quenching, we find that central velocity dispersion is even more predictive (when available in spectroscopic data sets). In comparison to the LGalaxies model, we find that all of these observational results may be consistently explained through quenching via preventative ‘radio-mode’ active galactic nucleus feedback. Furthermore, many alternative quenching mechanisms (including virial shocks, supernova feedback, and morphological stabilisation) are found to be inconsistent with our observational results and those from the literature.

The Effect of Environment on Galaxy Spiral Arms, Bars, Concentration, and Quenching

“…In their argument, they assume that the time-averaged feedback from an AGN scales with black hole mass. Supporting the idea of AGN quenching or morphological quenching, spatially resolved stellar population synthesis shows that the disks of spirals tend to have younger stellar ages at larger radii, implying inside-out quenching and/or inside-out disk growth (Pérez et al 2013;González Delgado et al 2016Ellison et al 2018;Méndez-Abreu et al 2021;Bluck et al 2022b).…”

“…Bait et al (2017) find that morphology correlates most strongly with sSFR, independent of environment, and conclude that the same physical process is responsible for both the morphology change and the decrease in sSFR. Bluck et al (2014Bluck et al ( , 2022a conclude that quenching is most closely correlated with the growth of the bulge and/or the central stellar velocity dispersion. Schawinski et al (2014) suggest that there are two different evolutionary paths for star-forming disk galaxies: some become spheroidal quickly via mergers and quench rapidly, while others retain their disk-like structure as their sSFRs slowly decrease, becoming red spirals.…”

“…What About Quenching Due to AGN Feedback? Bluck et al (2022a) argue that radio-mode AGN feedback is the dominant quenching mechanism in galaxies. In radio-mode AGN feedback (also known as kinetic AGN feedback), jets Figure 19.…”

“…Hot gas removal also involves ram pressure stripping, as well as processes such as viscous stripping and thermal evaporation (Cowie & Songaila 1977;Nulsen 1982;Cortese et al 2021); starvation is often distinguished from ram pressure stripping of the cold gas because it quenches much more slowly (timescale of a few Gyr) by preventing later infall and fueling of star formation (Cortese et al 2021). (3) tidal stripping of gas from the disks of spirals by interactions (Kilborn et al 2009), (4) disk gas being driven into the center of a galaxy by a bar or an interaction, depleting the outer disk of gas while triggering central star formation and building up the stellar bulge (Moss & Whittle 2000;Smith et al 2007;Li et al 2008), and (5) heating of the interstellar gas by feedback from active galactic nuclei (AGNs; Bluck et al 2014Bluck et al , 2016Bluck et al , 2020Bluck et al , 2022a. (6) Increasing the central spheroidal component of a galaxy could potentially stabilize a gaseous disk, slowing star formation, a process known as morphological quenching (Martig et al 2009(Martig et al , 2013Gensior et al 2020).…”

Revealing the Galaxy-Halo Connection Through Machine Learning

“…Machado Poletti Valle et al (2021) used an XG-Boost model to predict gas shapes in dark matter halos in the IllustrisTNG simulations. Bluck et al (2022) used Random Forest classifiers to study quenching mechanisms in observations, semianalytical models, and cosmological simulations. Piotrowska et al (2022) also used Random Forest classifiers to examine how supermassive black hole feedback quenches central galaxies in the EAGLE, Illustris, and IllustrisTNG simulations.…”