Simulations of the galaxy population constrained by observations from z = 3 to the present day: implications for galactic winds and the fate of their ejecta

By B. Henriques, Simon D. M. White, P. Thomas, R. Angulo, Qi Guo, Gerard Lemson, Volker Springel. 2012

188 citations recorded by the source corpus.

We apply Monte Carlo Markov Chain (MCMC) methods to large-scale simulations of galaxy formation in a LambdaCDM cosmology in order to explore how star formation and feedback are constrained by the observed luminosity and stellar mass functions of galaxies. We build models jointly on the Millennium and Millennium-II simulations, applying fast sampling techniques which allow observed galaxy abundances over the ranges 7<log(M*/Msun)<12 and z=0 to z=3 to be used simultaneously as constraints in the MCMC analysis. When z=0 constraints alone are imposed, we reproduce the results of previous modelling by Guo et al. (2012), but no single set of parameters can reproduce observed galaxy abundances at all redshifts simultaneously, reflecting the fact that low-mass galaxies form too early and thus are overabundant at high redshift in this model. The data require the efficiency with which galactic wind ejecta are reaccreted to vary with redshift and halo mass quite differently than previously assumed, but in a similar way as in some recent hydrodynamic simulations of galaxy formation. We propose a specific model in which reincorporation timescales vary inversely with halo mass and are independent of redshift. This produces an evolving galaxy population which fits observed abundances as a function of stellar mass, B- and K-band luminosity at all redshifts simultaneously. It also produces a significant improvement in two other areas where previous models were deficient. It leads to present day dwarf galaxy populations which are younger, bluer, more strongly star-forming and more weakly clustered on small scales than before, although the passive fraction of faint dwarfs remains too high.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/99df5dc303ba0ea774c1fc487dee33e98ccbee1e

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Citations in the corpus

The cosmic baryon cycle and galaxy mass assembly in the FIRE simulations (2016, background): “Semi-analytic models (SAMs ) built on dark matter halo merger trees also rely on baryon cycle processes (e.g. Somerville et al. 2008), recently incorporating more detailed treatments of galactic winds and recycling (Henriques et al. 2013; White et al. 2015).”
Colours and luminosities of z = 0.1 galaxies in the eagle simulation (2015, background): “…feedback from star formation and BHs together shape the GSMF is energetically plausible, and semi-analytical models (e.g. Cole et al. 2000; Henriques et al. 2013; Gonzalez-Perez et al. 2014; Porter et al. 2014) and numerical simulations (e.g. Oppenheimer et al. 2010; Puchwein & Springel…”
Simulating galaxy formation with the IllustrisTNG model (2017, result): “This choice of redshift-independent wind velocities at fixed halo mass is inspired by the results of semi-analytical models, where a similar approach was needed to reproduce observed stellar mass functions and restframe B- and K-band luminosity functions across redshift (Henriques et al. 2013).”
Galaxy formation in the Planck cosmology – I. Matching the observed evolution of star formation rates, colours and stellar masses (2014, methodology): “Indeed, if we were to carry out an MCMC analysis of the Henriques et al. (2013) or the Guo et al. (2013) model using this observational constraint, we would find a very low maximum likelihood value.”
Neutral hydrogen in galaxy haloes at the peak of the cosmic star formation history (2014, background): “…Bayesian analyses of semianalytic models (SAMs) constrained by the galaxy mass function reveal large degeneracies in best-fitting model parameters (e.g., Henriques et al. 2013; Lu et al. 2014), particularly for parameters that describe star formation and feedback processes (e.g., Lu et al. 2012).”
SEMI-ANALYTIC GALAXY EVOLUTION (SAGE): MODEL CALIBRATION AND BASIC RESULTS (2016, methodology): “It has been suggested by Henriques et al. (2013) that using a virial-mass dependence rather than virial-velocity one for the reincorporation rate could be conducive to reproducing observations across multiple epochs, in particular the galaxy stellar mass function.”
The EAGLE simulations of galaxy formation: calibration of subgrid physics and model variations (2015, methodology): “…models often adopt distribution sampling techniques to efficiently calibrate their many free parameters (Kampakoglou, Trotta & Silk 2008; Henriques et al. 2009, 2013, 2014; Bower et al. 2010; Lu et al. 2012; Mutch, Poole & Croton 2013). formation of disc galaxies similar to the Milky…”
Introducing the Illustris Project: the evolution of galaxy populations across cosmic time (2014, methodology): “Progress is being made by tuning the free parameters of the models and testing the results against observations (Henriques et al. 2013).”
EMERGE – an empirical model for the formation of galaxies since z ∼ 10 (2017, methodology): “Lately, several studies have used statistical methods such as MCMC methods to explore the parameter space of SAMs (e.g. Henriques et al. 2009; Lu et al. 2011, 2012; Henriques et al. 2013).”
A unified multiwavelength model of galaxy formation (2015, unknown): “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”
Physical Models of Galaxy Formation in a Cosmological Framework (2014, methodology): “Solid colored lines show predictions from semi-analytic models: SAGE (Croton et al. in prep, dark blue), Y. Lu SAM (Lu et al. 2013, magenta), GALFORM (Gonzalez-Perez et al. 2014, green), the Santa Cruz SAM (Porter et al. 2014, purple), and the MPA Millennium SAM (Henriques et al. 2013).”
The star formation main sequence and stellar mass assembly of galaxies in the Illustris simulation (2014, background): “1010 M (a modification of the reincorporation timescale was also studied by Henriques et al. 2013), but it cannot solve the problem for more-massive galaxies.”
Introducing the Illustris Project: simulating the coevolution of dark and visible matter in the Universe (2014, background): “We stress that this tension is shared by semi-analytic models and other state-of-the-art hydrodynamical simulations alike, pointing towards an open problem in low-mass galaxy formation (Weinmann et al. 2012; Henriques et al. 2013).”