Galaxy formation in the Planck cosmology – I. Matching the observed evolution of star formation rates, colours and stellar masses

By B. Henriques, Simon D. M. White, P. Thomas, R. Angulo, Qi Guo, Gerard Lemson, Volker Springel, R. Overzier. 2014

471 citations recorded by the source corpus.

We have updated the Munich galaxy formation model to the Planck first-year cosmology, while modifying the treatment of baryonic processes to reproduce recent data on the abundance and passive fractions of galaxies from z = 3 down to z = 0. Matching these more extensive and more precise observational results requires us to delay the reincorporation of wind ejecta, to lower the threshold for turning cold gas into stars, to eliminate ram-pressure stripping in halos less massive than 10 14 M⊙, and to modify our model for radio-mode feedback. These changes cure the most obvious failings of our previous models, namely the overly early formation of low-mass galaxies and the overly large fraction of them that are passive at late times. The new model reproduces the observed evolution both of the stellar mass function and of the distribution of star-formation rate at each stellar mass. Massive galaxies assemble most of their mass before z = 1 and are predominantly old and passive at z = 0, while lower mass galaxies assemble later and are predominantly blue and star-forming at z = 0. This phenomenological but physically based model allows the observations to be interpreted in terms of the eciency of the various processes t hat control the formation and evolution of galaxies as a function of their stellar mass, gas content, environment and time.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/078ddac2049a3c4f7f91174ff324b2417b8d3ae6

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In Astronomy and Astrophysics

1. P. Hopkins
2. L. Hernquist
3. Volker Springel
4. R. Dav'e
5. R. Somerville
6. Simon D. M. White
7. T. Naab
8. C. Conroy

In Instrumentation

1. P. Hopkins
2. L. Hernquist
3. Volker Springel
4. R. Dav'e
5. R. Somerville
6. Simon D. M. White
7. C. Conroy
8. T. Naab

Citations in the corpus

• Theoretical Challenges in Galaxy Formation (2016, background): “…input what are thought to be the most important physical processes in a simple fashion (e.g. Bower et al. 2006; Croton et al. 2006; Guo et al. 2011; Henriques et al. 2015; Kauffmann, White & Guiderdoni 1993; Somerville & Primack 1999) aim at finding that set which best produces realistic mock…”
• First results from the IllustrisTNG simulations: the galaxy colour bimodality (2017, background): “The co-evolution of a central blackhole and its host galaxy is an important ingredient (Bower et al. 2006; Somerville et al. 2008; Benson 2012), and more recent efforts continue to explore galaxy color as a fundamental observational constraint (e.g. Henriques et al. 2015; Zu & Mandelbaum 2017).”
• Constraining the galaxy–halo connection over the last 13.3 Gyr: star formation histories, galaxy mergers and structural properties (2017, background): “Additionally, in such massive galaxies the gas can be kept from cooling by the feedback from active galactic nuclei (Croton et al. 2006; Cattaneo et al. 2008; Henriques et al. 2015; Somerville & Davé 2015, and references therein).”
• THE EVOLUTION OF GALAXY NUMBER DENSITY AT z < 8 AND ITS IMPLICATIONS (2016, background): “Furthermore these theoretical models show that there are indeed galaxies down to these low masses, both through dark matter halos and through simulated galaxies (e.g., Jenkins et al. 2001; Gonzalez-Perez et al. 2014; Henriques et al. 2015).”
• (Star)bursts of FIRE: observational signatures of bursty star formation in galaxies (2015, methodology): “In many simple analytical models, all galaxies with a given stellar mass are assumed to have the same SFR (Mitra et al. 2015), whereas in semianalytical models, scatter in the SFR at fixed M∗ is ensured by accounting for the merger and accretion histories of different halos (Henriques et al. 2015).”
• Galaxy Protoclusters as Drivers of Cosmic Star Formation History in the First 2 Gyr (2017, methodology): “Our preferred SAM is that of Henriques et al. (2015) (hereafter H15), whose free parameters were constrained using the observed galaxy stellar mass functions and mass-dependent quiescent fractions at z = 0-3 (see the 5 We use “(proto)clusters” as a shorthand for “clusters and protoclusters” in…”
• First results from the IllustrisTNG simulations: matter and galaxy clustering (2017, background): “…matching a large variety of observational data, both at the present epoch and at high redshift (e.g. Kauffmann, White & Guiderdoni 1993; De Lucia et al. 2006; Somerville et al. 2008; Benson 2012; Clay et al. 2015; Henriques et al. 2015; Croton et al. 2016; Lacey et al. 2016; Cattaneo et al. 2017).”
• A unified multiwavelength model of galaxy formation (2015, methodology): “Important progress has already been made in applying statisticalmethods such as emulation (Bower et al. 2010), Monte Carlo Markov Chain (MCMC) (Henriques et al. 2009, 2013, 2015; Lu et al. 2011, 2014; Mutch et al. 2013; Benson 2014) or Particle Swarm Optimization (Ruiz et al. 2015) to parameter esti”
• Simulating galaxy formation with the IllustrisTNG model (2017, background): “…Vogelsberger & Angulo 2012; Kim et al. 2014; Skillman et al. 2014) and coupled with ever-more comprehensive semi-analytical models for galaxy formation (from Kauffmann, White & Guiderdoni 1993; Springel et al. 2001 to Benson 2012; Henriques et al. 2015; Lacey et al. 2016; Croton et al. 2016).”
• THE EVOLUTION OF THE GALAXY STELLAR MASS FUNCTION AT z = 4–8: A STEEPENING LOW-MASS-END SLOPE WITH INCREASING REDSHIFT (2015, methodology): “In its latest version of the model (Henriques et al. 2015), they tuned their model parameters to reproduce the observed evolution of the GSMFs and passive fractions of galaxies at z ≤ 3.”
• The z = 9-10 galaxy population in the Hubble Frontier Fields and CLASH surveys: the z = 9 luminosity function and further evidence for a smooth decline in ultraviolet luminosity density at z≥ 8 (2016, methodology): “Although the Khochfar et al. simulation produces more starformation rate density at higher redshift than either the Illustris or c© 0000 RAS, MNRAS 000, 000–000 Munich models, the best predictions are produced by the fairly simple analytic models of Dayal et al. (2015), Cai et al. (2014) and Mason e”
• Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe (2016, background): “Hydrodynamical simulations (e.g., Genel et al. 2014; Torrey et al. 2014; Furlong et al. 2015), semi-analytical models (e.g., Mitchell et al. 2014; Henriques et al. 2015), and pure analytic models (e.g., Lilly et al. 2013; Dekel & Burkert 2014) are all systematically offset from observations of…”
• Modelling and interpreting spectral energy distributions of galaxies with BEAGLE (2016, background): “…ingredients required to describe the evolution of the galaxy population (e.g. Gonzalez-Perez et al. 2014; Lu et al. 2014; Vogelsberger et al. 2014; Henriques et al. 2015; Schaye et al. 2015): collapse and hierarchical growth of dark E-mail: jchevall@cosmos.esa.int †ESA Research Fellow. matter…”
• MUFASA: Galaxy Formation Simulations With Meshless Hydrodynamics (2016, result): “It is also opposite to the discrepancy versus the recent models such as Illustris, EAGLE, and the SAM of Henriques et al. (2015), which tend to underpredict the SFRD at low-z while still generally agreeing with GSMF evolution.”