The physics driving the cosmic star formation history

By Joop Schaye, Claudio Dalla Vecchia, C. Booth, R. Wiersma, Tom Theuns, M. Haas, S. Bertone, Alan R. Duffy, Ian G. McCarthy, F. V. D. Voort. 2009

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We investigate the physics driving the cosmic star formation (SF) history using the more than 50 large, cosmological, hydrodynamical simulations that together comprise the OverWhelmingly Large Simulations project. We systematically vary the parameters of the model to determine which physical processes are dominant and which aspects of the model are robust. Generically, we find that SF is limited by the build-up of dark matter haloes at high redshift, reaches a broad maximum at intermediate redshift and then decreases as it is quenched by lower cooling rates in hotter and lower density gas, gas exhaustion and self-regulated feedback from stars and black holes. The higher redshift SF is therefore mostly determined by the cosmological parameters and to a lesser extent by photoheating from reionization. The location and height of the peak in the SF history, and the steepness of the decline towards the present, depend on the physics and implementation of stellar and black hole feedback. Mass loss from intermediate-mass stars and metal-line cooling both boost the SF rate at late times. Galaxies form stars in a self-regulated fashion at a rate controlled by the balance between, on the one hand, feedback from massive stars and black holes and, on the other hand, gas cooling and accretion. Paradoxically, the SF rate is highly insensitive to the assumed SF law. This can be understood in terms of self-regulation: if the SF efficiency is changed, then galaxies adjust their gas fractions so as to achieve the same rate of production of massive stars. Self-regulated feedback from accreting black holes is required to match the steep decline in the observed SF rate below redshift 2, although more extreme feedback from SF, for example in the form of a top-heavy initial stellar mass function at high gas pressures, can help.

Subfields: Astronomy and Astrophysics, Instrumentation

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Citations in the corpus

KiDS-450: The tomographic weak lensing power spectrum and constraints on cosmological parameters (2017, methodology): “In this work, we make use of the results obtained from the OverWhelmingly Large Simulations (Schaye et al. 2010; MNRAS 471, 4412–4435 (2017) Downloaded from https://academic.oup.com/mnras/article-abstract/471/4/4412/3979479 by Walaeus Library LUMC user on 10 January 2018 van Daalen et al. 2011) by i”
The dark nemesis of galaxy formation : why hot haloes trigger black hole growth and bring star formation to an end (2016, background): “…as equilibrium systems in which the star formation rate must balance the gas inflow rate, either by converting the inflowing gas into stars or, more importantly, by driving an outflow (eg., White & Frenk 1991; Finlator & Davé 2008; Schaye et al. 2010; Bouché et al. 2010; Davé et al. 2012).”
Galactic star formation and accretion histories from matching galaxies to dark matter haloes (2012, methodology): “…of the baryonic component based either on a hydrodynamical (Katz et al. 1996; Springel & Hernquist 2003; Kereš et al. 2005; Crain et al. 2009; Schaye et al. 2010; Oppenheimer et al. 2010) or on a semi-analytic method (Kauffmann et al. 1999; Springel et al. 2001; Hatton et al. 2003; Springel…”
Simulating galactic outflows with thermal supernova feedback (2012, background): “This freedom associated with the implementation of feedback from star formation is currently the limiting factor for the predictive power of cosmological simulations (e.g. Schaye et al. 2010; Scannapieco et al. 2011).”
A case study of hurdle and generalized additive models in astronomy: the escape of ionizing radiation (2018, methodology): “The FiBY simulation suite used a customized version of the smoothed-particle hydrodynamics code GADGET (Springel 2005) tailored for the Overwhelmingly Large Simulations project (Schaye et al. 2010).”
The accretion history of dark matter haloes - III. A physical model for the concentration-mass relation (2015, methodology): “…Mo H. J., Jing Y. P., Börner G., 2003, MNRAS, 339, 12 Zhao D. H., Jing Y. P., Mo H. J., Börner G., 2009, ApJ, 707, 354 A P P E N D I X A : SI M U L AT I O N S A N D C O S M O L O G Y In this work, we use the set of cosmological DMONLYDMONLY simulations from the OWLS project (Schaye et al. 2010).”
The APOSTLE simulations: solutions to the Local Group's cosmic puzzles (2015, methodology): “EAGLE is an evolution of the models used in the GIMIC (Crain et al. 2009) and OWLS (Schaye et al. 2010) projects and has been calibrated to reproduce the z = 0.1 stellar mass function and galaxy sizes from 108 to 1011 M in a cosmological volume of 1003 Mpc3.”
Galaxy evolution in cosmological simulations with outflows ― I. Stellar masses and star formation rates (2011, methodology): “We note that this model is similar to the “REFERENCE” outflow model of the OverWhelmingly Large Simulations (OWLS Schaye et al. 2010), except that we include hydrodynamic decoupling while they do not; in fact, they have also considered models likw nw and vzw (below) except without decoupling.”
A model for cosmological simulations of galaxy formation physics: multi-epoch validation (2013, background): “Over the last several years, a large body of results based on hydrodynamical simulations of galaxy formation have been obtained (e.g., Ocvirk et al. 2008; Crain et al. 2009; Schaye et al. 2010; Davé et al. 2011; McCarthy et al. 2012; Puchwein & Springel 2013; Kannan et al. 2013).”
The enrichment of the intergalactic medium with adiabatic feedback – I. Metal cooling and metal diffusion (2009, methodology): “However, Schaye et al. (2010) used the cooling model from Wiersma et al. (2009a) which also includes the suppression of metal cooling by UV background, yet still found a larger enhancement of SFR comparable to Choi & Nagamine (2009).”
The baryonic assembly of dark matter haloes (2011, background): “…2000; Murray, Quataert & Thompson 2005; Murray, Ménard & Thompson 2011), and inferred from comparison of the measured star formation history and stellar mass density with cosmological simulations (Springel & Hernquist 2003b; Kereš et al. 2009b; Oppenheimer et al. 2010; Schaye et al. 2010).”
The BAHAMAS project: Calibrated hydrodynamical simulations for large-scale structure cosmology (2016, background): “This results in simulations that neglected AGN feedback approximately reproducing the peak of the observed cosmic star formation history at z ∼ 1− 3 (Schaye et al. 2010).”
Impact of baryon physics on dark matter structures: a detailed simulation study of halo density profiles (2010, methodology): “Table 1 lists the runs with baryonic physics, along with their original OWLS names (Schaye et al. 2010), and highlights their key differences.”
An accurate halo model for fitting non-linear cosmological power spectra and baryonic feedback models (2015, methodology): “…& Knox 2004) and recent work using hydrodynamical simulations together with prescriptions for feedback (e.g.,Jing et al. 2006; Rudd et al. 2008; Schaye et al. 2010; Martizzi et al. 2014) have shown that the redistribution of matter caused bynon-linear processes such as gas cooling,…”
Evolution of galaxy stellar masses and star formation rates in the eagle simulations (2014, methodology): “The star formation threshold is metallicity dependent and given by n∗H(Z) = 0.1 cm−3 ( Z 0.002 )−0.64 , (2) where Z is the metallicity (from Schaye 2004, equations 19 and 24, also used in SFTHRESHZ model of the OWLS project).”
Galaxy Evolution in Cosmological Simulations with Outflows II: Metallicities and Gas Fractions (2011, background): “…perturbations are typi- 1 http://www-hpcc.astro.washington.edu/tools/skid.html cally so frequent that gas is rapidly driven inwards until it forms stars, and thus raising (lowering) the threshold would only introduce a small delay (advancement) in processing gas into stars (Schaye et al. 2010).”
The EAGLE project: Simulating the evolution and assembly of galaxies and their environments (2014, methodology): “By computing 4 Note that OWLS used tables based on version 05.07. c© 0000 RAS, MNRAS 000, 000–000 the rates element-by-element, we account not only for variations in the metallicity, but also for variations in the relative abundances of the elements.”
Molecular hydrogen abundances of galaxies in the EAGLE simulations (2015, methodology): “The OWLS simulation suite described in Schaye et al. (2010), a forerunner of EAGLE, explored lower resolution and smaller cosmological volumes than EAGLE.”