The quenching of galaxies, bulges, and disks since cosmic noon A machine learning approach for identifying causality in astronomical data

被引:51
|
作者
Bluck, Asa F. L. [1 ,2 ,3 ]
Maiolino, Roberto [1 ,2 ]
Brownson, Simcha [1 ,2 ]
Conselice, Christopher J. [4 ]
Ellison, Sara L. [5 ]
Piotrowska, Joanna M. [1 ,2 ]
Thorp, Mallory D. [5 ]
机构
[1] Univ Cambridge, Kavli Inst Cosmol, Madingley Rd, Cambridge CB3 0HA, England
[2] Univ Cambridge, Astrophys Grp, Cavendish Lab, 19 JJ Thomson Ave, Cambridge CB3 0HE, England
[3] Florida Int Univ, Dept Phys, 11200 SW 8th St, Miami, FL 33199 USA
[4] Univ Manchester, Jodrell Bank Ctr Astrophys, Oxford Rd, Manchester, Lancs, England
[5] Univ Victoria, Dept Phys & Astron, Finnerty Rd, Victoria, BC V8P 1A1, Canada
基金
加拿大自然科学与工程研究理事会; 美国安德鲁·梅隆基金会; 英国科学技术设施理事会; 美国国家科学基金会; 美国国家航空航天局;
关键词
galaxies; formation; evolution; star formation; structure; statistics; SUPERMASSIVE BLACK-HOLES; INTEGRAL FIELD SPECTROSCOPY; ACTIVE GALACTIC NUCLEI; STAR-FORMATION HISTORY; SDSS-IV MANGA; SIMILAR-TO; MAIN-SEQUENCE; STELLAR MASS; ALMAQUEST SURVEY; MULTIWAVELENGTH MEASUREMENT;
D O I
10.1051/0004-6361/202142643
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
We present an analysis of the quenching of star formation in galaxies, bulges, and disks throughout the bulk of cosmic history, from z & x2004;=& x2004;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.
引用
收藏
页数:40
相关论文
共 1 条
  • [1] JWST/CEERS sheds light on dusty star-forming galaxies: Forming bulges, lopsidedness, and outside-in quenching at cosmic noon
    Le Bail, Aurelien
    Daddi, Emanuele
    Elbaz, David
    Dickinson, Mark
    Giavalisco, Mauro
    Magnelli, Benjamin
    Gomez-Guijarro, Carlos
    Kalita, Boris S.
    Koekemoer, Anton M.
    Holwerda, Benne W.
    Bournaud, Frederic
    de la Vega, Alexander
    Calabro, Antonello
    Dekel, Avishai
    Cheng, Yingjie
    Bisigello, Laura
    Franco, Maximilien
    Costantin, Luca
    Lucas, Ray A.
    Perez-Gonzalez, Pablo G.
    Lu, Shiying
    Wilkins, Stephen M.
    Haro, Pablo Arrabal
    Bagley, Micaela B.
    Finkelstein, Steven L.
    Kartaltepe, Jeyhan S.
    Papovich, Casey
    Pirzkal, Nor
    Yung, L. Y. Aaron
    ASTRONOMY & ASTROPHYSICS, 2024, 688