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A chronicle of galaxy mass assembly in the EAGLE simulation

11 Jan 2017-Monthly Notices of the Royal Astronomical Society (Oxford University Press)-Vol. 464, Iss: 2, pp 1659-1675

AbstractWe analyse the mass assembly of central galaxies in the Evolution and Assembly of Galaxies and their Environments (EAGLE) hydrodynamical simulations. We build merger trees to connect galaxies to their progenitors at different redshifts and characterize their assembly histories by focusing on the time when half of the galaxy stellar mass was assembled into the main progenitor. We show that galaxies with stellar mass M∗ < 1010.5M_ assemble most of their stellar mass through star formation in the main progenitor (‘in situ’ star formation). This can be understood as a consequence of the steep rise in star formation efficiency with halo mass for these galaxies. For more massive galaxies, however, an increasing fraction of their stellar mass is formed outside the main progenitor and subsequently accreted. Consequently, while for low-mass galaxies, the assembly time is close to the stellar formation time, the stars in high-mass galaxies typically formed long before half of the present-day stellar mass was assembled into a single object, giving rise to the observed antihierarchical downsizing trend. In a typical present-day M∗ ≥ 1011M_ galaxy, around 20 per cent of the stellar mass has an external origin. This fraction decreases with increasing redshift. Bearing in mind that mergers only make an important contribution to the stellar mass growth of massive galaxies, we find that the dominant contribution comes from mergers with galaxies of mass greater than one-tenth of the main progenitor’s mass. The galaxy merger fraction derived from our simulations agrees with recent observational estimates.

Topics: Galaxy merger (68%), Elliptical galaxy (68%), Stellar mass loss (66%), Lenticular galaxy (65%), Stellar mass (65%)

Summary (5 min read)

Introduction

  • Key words: galaxies: evolution – galaxies: formation – galaxies: high-redshift – galaxies: interactions – galaxies: stellar content.
  • To evaluate the relative importance of mergers to galaxy assembly, the authors need to know their merging histories.
  • The approach may miss physical correlations between the merging objects.
  • The authors investigate the assembly histories and merger histories of galaxies and discuss the impact of feedback on galaxy mass buildup in Section 3.

2.1 EAGLE simulation

  • The galaxy samples for this study are selected from the EAGLE simulation suite (Crain et al. 2015; Schaye et al. 2015).
  • The largest EAGLE simulation, hereafter referred to as Ref-L100N1504, employs 15043 dark matter particles and an initially equal number of gas particles in a periodic cube with side-length 100 comoving Mpc (cMpc) on each side.
  • The uncertainty in these models introduces parameters whose values must be calibrated by comparison to observational data (Vernon, Goldstein & Bower 2010).
  • The subgrid parameters calibrated by requiring that the model fits three key properties of local galaxies well: the galaxy stellar mass function, the galaxy size – mass relation and the normalization of the black hole mass – galaxy mass relation and that variations of the parameters alter the simulation outcome in predictable ways (Crain et al. 2015).
  • The authors find that it describes many aspects of the observed universe well (i.e. within the plausible observational uncertainties), including the evolution of the galaxy stellar mass function and star formation rates (Furlong et al. 2015b), evolution of galaxy colours and luminosity functions (Trayford et al. 2015).

2.2.1 Halo identification

  • Dark matter structures in the EAGLE simulations are initially identified using the ‘Friends-of-Friends’ (FoF) algorithm with a linking length of 0.2 times the mean inter-particle spacing (Davis et al. 1985).
  • The gravitationally bound substructures within the FoF groups are then identified by the SUBFIND algorithm (Springel et al. 2001; Dolag et al. 2009).
  • Briefly, the algorithm assigns a mass density at the position of every particle through a kernel interpolation over a certain number of its nearest neighbours.
  • The local minima in the gravitational potential field are the centres of subhalo candidates.
  • Particles are assigned to at most one subhalo.

2.2.2 Subhalo merger tree

  • Subhaloes survive as distinct objects for an extended period of time.
  • The authors use the D-Trees algorithm (Jiang et al. 2014) to locate the whereabouts of the Nlink = min(Nlinkmax, max(ftraceN, Nlinkmin)) most bound particles of the subhalo, where N is the total particle number in the subhalo.
  • When two subhaloes are close to each other, their volumes of influence become intertwined and the definition of the main halo may become unclear.
  • The main progenitor is then the progenitor that has the maximum branch mass among its contemporaries.
  • The subhalo merger trees derived by the method described above are publicly available through an SQL data base1 similar to that used for the Millennium simulations (see McAlpine et al. 2016, for more details).

2.3 Galaxy sample, galaxy merger tree, and merger type

  • Galaxies are identified as the stellar components of the subhaloes.
  • Previous studies based on the EAGLE simulations adopt an aperture of 30 pkpc to measure galaxy stellar mass (e.g. Furlong et al. 2015b; Schaye et al. 2015).
  • Nevertheless, subhaloes do contain a significant population of diffuse stars, particularly in more massive haloes (Furlong et al. 2015b).
  • Using the actual stellar mass complicates interpretation of the relative mass contribution from different types of merger events since it depends on the age of the stellar population that is accreted.
  • The authors therefore use the stellar mass initially formed (‘initial mass’), not the actual stellar mass, to evaluate the contributions from internal and external processes to galaxy assembly.

2.3.1 Galaxy sample

  • In order to test the robustness of their results to resolution, the authors also extract 1381 galaxies within the same mass range, as a comparison sample, from the EAGLE simulation Recal-L025N0752 (2 × 7523 dark matter and gas particles in a 25 cMpc box), which has eight times better mass resolution and the same snapshot frequency as Ref-L100N1504.
  • The authors use subgrid physical models with parameters recalibrated to the present-day observations, as this provides the best match to the observed galaxy population (see Schaye et al. 2015).

2.3.2 Galaxy merger tree

  • The authors construct galaxy merger trees by focusing on the stellar component of the subhalo merger trees.
  • The main branch of the tree is marked by the thick black line.
  • It is important to bear in mind that the identification of the main branch is always based on the branch mass; at any particular epoch, the most massive galaxy progenitor may not lie on the main branch.
  • For the reasons described in Section 2.2.2, using the branch mass yields more stable and intuitive results.
  • Galaxy merger trees appear broadly similar to subhalo merger trees, except that the latter contain more fine branches corresponding to small subhaloes within which no stars have formed.

2.3.3 Merger type

  • The effects of tidal forces and torques during a merger depend on the mass ratio of the merging systems (e.g. Barnes & Hernquist 1992).
  • It is therefore useful to classify mergers into different types according to the mass ratio between the two merging systems, μ ≡ M2/M1 (M1 > M2).
  • For galaxy mergers, μ is the ratio of stellar masses between two merging galaxies.
  • While this is straightforward in semi-analytic models (since galaxies are uniquely defined entities), in numerical simulations (and in nature as well), merging systems experience mass-loss due to tidal stripping throughout the merging process.
  • The value of Rmerge ranges from ∼20 to 200 pkpc in the stellar mass range explored in this work , and is similar to the projected separation criteria adopted in observational galaxy pair studies.

3.1 Galaxy formation and assembly time-scales

  • In contrast, the most massive galaxies formed their stars relatively early, tf ∼ 11 Gyr, and have ta < tf indicating that a fraction of their stars are formed elsewhere and subsequently assembled into the final system.
  • This trend agrees well with previous work (e.g. De Lucia et al.
  • Many previous studies have pointed out that in a CDM cosmology, halo growth is driven by a mix of mergers and accretion of matter that has not yet collapsed into identifiable haloes (e.g. Kauffmann & White 1993; Lacey & Cole 1993; Guo & White 2008; Fakhouri & Ma 2010; Genel et al.
  • This fundamental differences results in the stark contrast between Figs 3 and 4.

3.2 The redshift evolution of galaxy formation and assembly times

  • In previous section, the authors have shown that the delay between formation time and assembly time can provide some useful hints on how a galaxy assembles its mass.
  • The authors show results for Ref-L100N1504 (solid lines), as well as for the higher resolution (but smaller volume) simulation Recal-L025N0752 (dashed lines) in order to demonstrate the convergence of the results.
  • The shaded region represents the 25th–75th percentiles of the δt distribution.
  • While low-mass galaxies have median δt < 0.1 at all redshifts, high-mass galaxies have median δt decreasing with increasing redshift, showing that stellar accretion loses ground to in situ star formation.
  • The same redshift dependence is also found in semi-analytic studies (e.g. Guo & White 2008).

3.3 The contribution of star formation in external galaxies

  • Time-scale studies shed light on the manner in which galaxies with different masses at different redshifts aggregate their stars.
  • But they do not explore quantitatively the roles of internal and external processes therein.
  • The authors sum up the mass that a galaxy has acquired from mergers and accretion, and derive the fractional contribution of external processes, fext, by comparing this mass to the final galaxy mass.
  • Lines show the median values, while the shaded regions represent the 25th–75th percentiles of the distribution.
  • Both results of the reference Ref-L100N1504 (solid lines) and the higher resolution Recal-L025N0752 (dashed lines) simulations are shown in order to demonstrate the convergence of the results.

3.4 Galaxy merging history

  • In preceding sections, the authors explored the relative roles that in situ and external star formation play in galaxy mass build-up.
  • The authors continue their investigation by exploring the separate contributions of the different external processes in galaxy assembly.

3.4.1 Redshift of last major merger

  • Almost all of their present-day galaxies, irrespective of their stellar mass, have experienced at least one major merger event in their lives.
  • The authors use the merger trees to determine the redshift, zlast, when they experienced their last major merger.
  • The most massive galaxies have a very active merging history, with 68 per cent of the population having been involved in a major merger event since z = 1.5 (a lookback time of 10 Gyr).
  • For comparison, Fig. 7 also shows the cumulative distributions of zlast for the parent subhaloes of those galaxies (dashed lines).
  • In sharp contrast to the active merging histories of high-mass galaxies, only 20 per cent of their host subhaloes have undergone a major merger event in the last 10 Gyr. Intermediate- and low-mass galaxies share more similarity with their parent subhaloes.

3.4.2 The contributions of major mergers, minor mergers, and accretion

  • The authors continue their investigation of fractional mass contribution in Section 3.3 further to explore the respective contributions from major merger, minor merger and accretion and their dependence on galaxy mass and redshift.
  • The panels from left to right in Fig. 8 show the cumulative fraction of galaxies at redshift z = 0 (solid lines), 1 (dashed lines), and 2 (dotted lines) as a function of the minimum fractional mass contribution from major mergers, minor mergers and accretion, respectively.
  • Low-mass galaxies at redshift z = 0 mainly acquire their external masses through accretion, while major mergers are the main contributor for their high-mass counterparts.
  • Around ∼61 per cent of the most massive population acquired more than half of their external mass through major merger events.
  • Parry et al. (2009) arrived at the same conclusion from their analysis of semi-analytic models in the Millennium simulation (see fig. 8 in their work).

3.4.3 Evolution of the galaxy merger fraction

  • Observationally, the frequencies of galaxy pairs and morphologically distorted galaxies at different redshifts are commonly used to put constraints on the role of galaxy mergers, especially major mergers, in driving galaxy formation.
  • The galaxy merger fraction increases monotonically towards high redshifts before levelling off at z 1–3, depending on mass.
  • Note that this comparison is qualitative since a detailed comparison would require careful reconstruction of the observational criteria.
  • The merger diagnostics are also sensitive to merger mass ratios, the authors also consider the impact on their results of extending the merger mass ratio to a smaller value (μ ≥ 1/10).

3.5 The impact of feedback on galaxy mass assembly

  • A very interesting question is whether this is due to the feedback from star formation and black hole growth.
  • These runs differ in simulation volume but have the same resolution.
  • In the strong feedback case, the analysis consistently suggests a slight decrease of fext as more of the star-forming gas within small galaxies is lost in outflows, reducing their contribution to the stellar mass.
  • In the middle panel, fext is lower than the reference simulation (and is more similar to the curve in the left-hand panel).
  • In the absence of effective stellar feedback, AGN feedback has a similar impact in high- and low-mass haloes (Bower et al. 2016) and the authors expect the differences between the panels to be smaller, as seen.

4 C O M PA R I S O N S TO OTH E R WO R K

  • This is a topic that has been extensively studied using N-body simulations and semi-analytic galaxy formation models.
  • Assuming a uniform galaxy formation efficiency to derive galaxy merging histories from halo merging histories inevitably underestimates the importance of major galaxy mergers, and overstates the role of minor mergers.
  • In the high-mass galaxies, the assembly and formation times become increasingly similar with increasing redshift and the fraction of externally formed stellar mass declines (Figs 5 and 6). (iv) As in Guo & White (2008), the authors compare the stellar mass contributions from in situ star formation and external processes to galaxies of various stellar masses and redshifts.
  • The authors find both agreements and discrepancies between their results and those of other recent simulations.

A P P E N D I X C : EF F E C T O F T H E A P E RTU R E

  • The galaxy mass is defined as the actual (or initial) stellar mass enclosed by a spherical aperture with a galactocentric radius of 100 pkpc (proper kpc).
  • By using an aperture mass, the authors may underestimate the total stellar mass of a massive galaxy, and thus overestimate the fractional mass contributions of external processes, fext.
  • Galaxies are split into three stellar mass bins as indicated by colours and legends.
  • Lines represent the medians of the distributions while the shaded regions (dotted lines) mark the 25th and the 75th percentiles.
  • This paper has been typeset from a TEX/LATEX file prepared by the author.

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MNRAS 464, 1659–1675 (2017) doi:10.1093/mnras/stw2437
Advance Access publication 2016 September 27
A chronicle of galaxy mass assembly in the EAGLE simulation
Yan Qu,
1
John C. Helly,
2
Richard G. Bower,
2
Tom Theuns,
2
Robert A. Crain,
3
Carlos S. Frenk,
2
Michelle Furlong,
2
Stuart McAlpine,
2
Matthieu Schaller,
2
Joop Schaye
4
and Simon D. M. White
5
1
National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang, Beijing 10012, China
2
Institute of Computational Cosmology, Durham University, South Road, Durham DH1 3LE, UK
3
Astrophysics Research Institute, Liverpool John Moores University, 146 Brownlow Hill, Liverpool L3 5RF, UK
4
Leiden Observatory, Leiden University, Postbus 9513, NL-2300 RA Leiden, the Netherlands
5
Max-Planck-Institut f
¨
ur Astrophysik, Karl-Schwarzschild-Strae 1, D-85741 Garching, Germany
Accepted 2016 September 26. Received 2016 August 29; in original form 2016 March 28
ABSTRACT
We analyse the mass assembly of central galaxies in the Evolution and Assembly of Galaxies
and their Environments (EAGLE) hydrodynamical simulations. We build merger trees to
connect galaxies to their progenitors at different redshifts and characterize their assembly
histories by focusing on the time when half of the galaxy stellar mass was assembled into the
main progenitor. We show that galaxies with stellar mass M
< 10
10.5
M
assemble most of
their stellar mass through star formation in the main progenitor (‘in situ star formation). This
can be understood as a consequence of the steep rise in star formation efficiency with halo
mass for these galaxies. For more massive galaxies, however, an increasing fraction of their
stellar mass is formed outside the main progenitor and subsequently accreted. Consequently,
while for low-mass galaxies, the assembly time is close to the stellar formation time, the stars
in high-mass galaxies typically formed long before half of the present-day stellar mass was
assembled into a single object, giving rise to the observed antihierarchical downsizing trend.
In a typical present-day M
10
11
M
galaxy, around 20 per cent of the stellar mass has an
external origin. This fraction decreases with increasing redshift. Bearing in mind that mergers
only make an important contribution to the stellar mass growth of massive galaxies, we find
that the dominant contribution comes from mergers with galaxies of mass greater than one-
tenth of the main progenitor’s mass. The galaxy merger fraction derived from our simulations
agrees with recent observational estimates.
Key words: galaxies: evolution galaxies: formation galaxies: high-redshift galaxies:
interactions galaxies: stellar content.
1 INTRODUCTION
In the cold dark matter (CDM) cosmological model, the growth
of dark matter haloes is largely self-similar, with larger haloes be-
ing formed more recently than their low-mass counterparts. The
formation and assembly of galaxies are, however, much more com-
plex. Feedback from massive stars and the formation of black holes
generates a strongly non-linear relationship between the masses of
dark matter haloes and those of the galaxies they host. For low-mass
haloes (with mass 10
11.5
M
), the stellar mass increases rapidly,
with a slope of 2, but in higher mass haloes, the stellar mass of
the main (or ‘central’) galaxy increases much more slowly than the
E-mail:
quyan@nao.cas.cn
halo mass, with a slope of 0.5 (e.g. Benson et al. 2003; Behroozi,
Wechsler & Conroy
2013; Moster, Naab & White 2013). The mass
assembly of galaxies will therefore be quite different from those of
their parent haloes. Establishing how galaxies assemble their stars
over cosmic time is then central to understanding galaxy formation
and evolution.
One question we need to answer is the relative importance of the
growth of galaxies via internal ongoing star formation (‘in situ’),
in comparison to the mass contributions of external processes (e.g.
Guo & White
2008; Zolotov et al. 2009;Oseretal.2010; Font et al.
2011; McCarthy et al. 2012; Pillepich, Madau & Mayer 2015).
These external processes can be further divided to distinguish be-
tween the mass growth due to mergers with galaxies of comparable
mass (‘major mergers’), and the mass gained from much smaller
galaxies (‘minor mergers’) or barely resolved systems and diffuse
C
2016 The Authors
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1660 Y. Qu et al.
mass (‘accretion’). While major mergers can rapidly increase a
galaxy’s stellar mass, minor mergers are much more common (e.g.
Hopkins et al.
2008; Parry, Eke & Frenk 2009).
To evaluate the relative importance of mergers to galaxy assem-
bly, we need to know their merging histories. From an observational
perspective, counts of close galaxy pairs (e.g. Williams, Quadri &
Franx
2011;Man,Zirm&Toft2014), or galaxies with disturbed
morphologies (e.g. Lotz et al.
2008; Conselice, Yang & Bluck 2009;
L
´
opez-Sanjuan et al.
2011; Stott et al. 2013), provide a census of
galaxy mergers. These values can be further converted into galaxy
merger rates t hrough the use of a merger time-scale (e.g. Kitzbichler
& White
2008). Unfortunately, those methods have their own lim-
itations: galaxies in close-pairs may not be physically related, and
may be chance line-of-sight superpositions; morphological distur-
bances are not unique to galaxy mergers. For example, clumpy star
formation driven by gravitational instability can also foster the for-
mation of galaxies with irregular morphologies (Lotz et al.
2008).
In addition, these methods are sensitive to the merger stage and
the mass ratio of the merging galaxies. Due to these limitations, the
scatter between merger rate measurements is large, and it is difficult
to make a reliable assessment of the complementary contribution
of mergers to galaxy growth. Recently, deep surveys have begun
to shed more light on the galaxy merger rate at high redshifts (e.g.
Man et al.
2014). Even so, the evolution of the merger rate remains
controversial. An alternative approach is to extract the merger rates
of galaxies from a model that reproduces the observed abundance
of galaxies (and their distribution in mass), and its evolution with
redshift, in a full cosmological context.
In the hierarchical structure formation scenario, the assembly of
galaxies is believed to be closely related to the formation histories
of their parent haloes. The practice of using halo merger histories
to understand the build-up of galaxies can be traced back to Bower
(
1991), Cole (1991), and Kauffmann, White & Guiderdoni (1993).
In these pioneering works, the growth of haloes is described by
analytical methods. Numerical techniques like N-body numerical
simulations can deal more accurately with the gravitational pro-
cesses underlying the evolution of cosmic structure. The clustering
of haloes is tracked, snapshot by snapshot, and stored in a tree
form (‘merger tree’). Halo merger trees therefore record, in a direct
way, when and how haloes assemble by accreting other building
blocks, and are widely used to rebuild galaxy assembly histories
(e.g. Kauffmann et al.
1993, 1999; Roukema et al. 1997; Springel
et al.
2001).
To compute galaxy merger rates, one possibility is to combine
the halo merger trees with a redshift-dependent abundance match-
ing model that statistically assigns galaxies to dark matter haloes
(Fakhouri & Ma
2008;Behroozietal.2013; Moster et al. 2013).
In this fashion, the observed abundance of galaxies can be inverted
to estimate the galaxy merger rate as a function of halo mass and
redshift. This provides a great deal of insight, but relies on the
accuracy of the statistical model. Although appealing because of
its close relation to the real data, the approach may miss physical
correlations between the merging objects. A preferable approach is
therefore to form galaxies within dark matter haloes using a physical
galaxy formation model. It is important to note, however, that reli-
able conclusions can only be obtained if the overall galaxy stellar
mass function accurately reproduces observational measurements
(Benson et al.
2003; Schaye et al. 2015).
One approach is to use ‘semi-analytic’ models of galaxy forma-
tion. By introducing phenomenological descriptions for feedback
from star formation and active galactic nuclei (AGN), such mod-
els are able to reproduce the observed galaxy stellar mass function
(e.g. Bower et al.
2006; Croton et al. 2006
, for a recent review, see
Knebe et al.
2015). De Lucia et al. (2006) study the assembly of
elliptical galaxies in a semi-analytic model based on the model of
Croton et al. (
2006). They find that stars in massive galaxies (with
stellar mass M
10
11
M
) are formed earlier (z 2.5) but are as-
sembled later (by z 0.8). De Lucia & Blaizot (
2007) show further
that massive members in galaxy clusters assemble through mergers
late in the history of the Universe, with half of their present-day
mass being in place in their main progenitor by z 0.5. In contrast,
less massive galaxies undergo relatively few mergers, acquiring
only 20 per cent of their final stellar mass from external objects.
Parry et al. (
2009) study the assembly and morphology of galaxies
in the semi-analytic model of Bower et al. (
2006). They found many
similarities, but also important disagreements, stemming primarily
from the differing importance of disc instabilities in the two mod-
els. Parry et al. (
2009) find that major mergers are not the primary
mass contributors to most spheroids except the brightest ellipticals.
This, instead, is brought in by minor mergers and disc instabilities.
In their model, the majority of ellipticals, and the overwhelming
majority of spirals, never experience a major merger.
Semi-analytic studies such as those above give important insights
but suffer from the limitations inherent to the approach, for example,
the neglect of tidal stripping of infalling satellites and the absence of
information about the spatial distribution of stars, as well as being
limited by the overall accuracy of the model. Numerical simulations
have fewer limitations, and have thus become an alternative useful
tool for these studies. Hopkins et al. (
2010) compare the galaxy
merger rates derived from a variety of analytical models and hydro-
dynamical simulations. They find that the predicted galaxy merger
rates depend strongly on the prescriptions for baryonic physical pro-
cesses, especially those in satellite galaxies. For example, the lack
of strong feedback can result in a difference in predicted merger
rates by as much as a factor of 5. Mass ratios used in merger clas-
sification also have an impact on merger rate prediction. Using the
stellar mass ratio, rather than the halo mass ratio, can result in an
order of magnitude change in the derived merger rate.
With rapidly increasing computational power and much pro-
gresses in modelling physical processes on subgrid scales, cosmo-
logical N-body hydrodynamical simulations are increasingly capa-
ble of capturing the physics of galaxy formation (e.g. Hopkins et al.
2013; Vogelsberger et al. 2014). The Evolution and Assembly of
Galaxies and their Environments (EAGLE) simulation project ac-
curately reproduces the observed properties of galaxies, including
their stellar mass, sizes, and formation histories, within a large and
representative cosmological volume (Schaye et al.
2015; Furlong
et al.
2015a,b). This degree of fidelity makes the EAGLE simu-
lations a powerful tool for understanding and interpreting a wide
range of observational measurements. Previous papers have focused
on the evolution of the mass function and the size distribution of
galaxies (Furlong et al.
2015a,b), the luminosity function and colour
diagram (Trayford et al.
2015) and galaxy rotation curves (Schaller
et al.
2015a), as well as many aspects of the H
I and H
2
distribution
of galaxies (Lagos et al.
2015;Bah
´
eetal.2016; Crain et al. 2016)
in the EAGLE Universe. But none has tracked the assembly of in-
dividual galaxies and decipher the underlying mechanisms as yet.
As an attempt to shed some light on the issue, in this work, we
connect galaxies seen at different redshifts, creating a merger
tree that enables us to establish which high-redshift fragments col-
lapse to form which present-day galaxies (and vice versa). In this
way, we can quantify the importance of in situ star formation rel-
ative to the mass gain from galaxy mergers and diffuse accretion.
Throughout the paper, we will focus on the main, or ‘central’,
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Galaxy mass assembly in the EAGLE simulation 1661
galaxies, avoiding the complications of environmental processes
such as ram pressure stripping and strangulation that suppress star
formation and strip stellar mass from satellites. Unless otherwise
stated, stellar masses refer to the stellar mass of a galaxy at the
redshift of observation, not to the initial mass of stars formed.
The outline of this paper is as follows. In Section 2, we provide
a brief overview of the numerical techniques and subgrid physi-
cal models employed by the EAGLE simulations, and describe the
methodology used to construct merger trees from simulation out-
puts. We investigate the assembly histories and merger histories of
galaxies and discuss the impact of feedback on galaxy mass build-
up in Section 3. We compare our results with some previous works
in Section 4, and finally summarize in Section 5. The appendices
present the detailed criteria we use to define galaxy mergers and
show the impacts of our choices of galaxy mass on our results. The
cosmological parameters used in this work is from the Planck mis-
sion (Planck Collaboration XVI
2014),
= 0.693,
m
= 0.307,
h = 0.677, n
s
= 0.96, and σ
8
= 0.829.
2 EAGLE SIMULATION AND MERGER TREE
2.1 EAGLE simulation
The galaxy samples for this study are selected from the EAGLE
simulation suite (Crain et al.
2015; Schaye et al. 2015). The
EAGLE simulations follow the evolution (and, where appropri-
ate, the formation) of dark matter, gas, stars, and black holes from
redshift z = 127 to the present day at z = 0. They were carried
out with a modified version of the
GADGET 3 code (Springel 2005)
using a pressure–entropy-based formulation of smoothed particle
hydrodynamics method (Hopkins
2013), coupled to several other
improvements to the hydrodynamic calculation (Dalla Vecchia., in
preparation; Schaye et al.
2015; Schaller et al. 2015b). The simula-
tions include subgrid descriptions for radiative cooling (Wiersma,
Schaye & Smith
2009), star formation (Schaye & Dalla Vecchia
2008), multi-element metal enrichment (Wiersma et al. 2009), black
hole formation (Rosas-Guevara et al.
2015; Springel, Di Matteo &
Hernquist
2005), as well as feedback from massive stars (Dalla
Vecchia & Schaye
2012) and AGN (for a complete description, see
Schaye et al.
2015). The subgrid models are calibrated using a well-
defined set of local observational constraints on the present-day
galaxy stellar mass function and galaxy sizes (Crain et al.
2015).
Each simulation outputs 29 snapshots to store particle properties
over the redshift range of 0 z 20. The corresponding time inter-
val between snapshot outputs ranges from 0.3 to 1.35 Gyr. The
largest EAGLE simulation, hereafter referred to as Ref-L100N1504,
employs 1504
3
dark matter particles and an initially equal number
of gas particles in a periodic cube with side-length 100 comoving
Mpc (cMpc) on each side. This setup results in a particle mass of
9.7 × 10
6
M
and 1.81 × 10
6
M
(initial mass) for dark matter and
gas particles, respectively. The gravitational force between particles
is calculated using a Plummer potential with a softening length set
to the smaller of 2.66 comoving kpc (ckpc) and 0.7 physical kpc
(pkpc).
The formation of galaxies involves physical processes operating
on a huge range of scales, from the gravitational forces that drive the
formation of large-scale structure on 10–100 Mpc scales, to the pro-
cesses that lead to the formation of individual stars and black holes
on 0.1 pc and smaller scales. Such a dynamic range, 10
9
in length
and perhaps 10
27
in mass, cannot be computed efficiently without
the use of subgrid models. Such models are inevitably approximate
and uncertain. In EAGLE, we require that the subgrid models are
physically plausible, numerically stable, and as simple as possible.
The uncertainty in these models introduces parameters whose val-
ues must be calibrated by comparison to observational data (Vernon,
Goldstein & Bower
2010). We explicitly recognize that these mod-
els are approximate and adopt the clear methodology for selecting
parameters and validating the model that is described in detail in
Schaye et al. (
2015) and Crain et al. (2015). The subgrid parame-
ters calibrated by requiring that the model fits three key properties
of local galaxies well: the galaxy stellar mass function, the galaxy
size mass relation and the normalization of the black hole mass
galaxy mass relation and that variations of the parameters alter the
simulation outcome in predictable ways (Crain et al.
2015). We find
that these data sets can be described well with physically plausible
values for the subgrid parameters. We then compare the s imulation
with further observational data to validate the simulation. We find
that it describes many aspects of the observed universe well (i.e.
within the plausible observational uncertainties), including the evo-
lution of the galaxy stellar mass function and star formation rates
(Furlong et al.
2015b), evolution of galaxy colours and luminosity
functions (Trayford et al.
2015). It also provides a good match to
observed O
VI column densities (Rahmati et al. 2016) and molecu-
lar content of galaxies (Lagos et al.
2015), as well as a reasonable
description of the X-ray luminosities of AGN (Rosas-Guevara et al.
2015). The good agreement with these diverse data sets, especially
those distantly related to the calibration data, provides good rea-
son to believe that the simulation provides a good description of
the evolution of galaxies in the observed Universe. It can therefore
be used to explore galaxy assembly histories in ways that are not
accessible to observational studies.
2.2 Halo identification and subhalo merger tree
Building subhalo merger trees from cosmological simulations in-
volves two steps: first, we identify haloes and subhaloes as gravi-
tationally self-bound structures; secondly, we identify the descen-
dants of each subhalo across snapshot outputs and establish the
descendant–progenitor relationship over time.
2.2.1 Halo identification
Dark matter structures in the EAGLE simulations are initially iden-
tified using the ‘Friends-of-Friends’ (FoF) algorithm with a linking
length of 0.2 times the mean inter-particle spacing (Davis et al.
1985). Other particles (gas, stars and black holes) are assigned to
the same FoF group as their nearest linked dark matter neighbours.
The gravitationally bound substructures within the FoF groups are
then identified by the SUBFIND algorithm (Springel et al.
2001;
Dolag et al.
2009). Unlike the FoF group finder, SUBFIND consid-
ers all species of particle and identifies self-bound subunits within
a bound structure which we refer to as ‘subhaloes’. Briefly, the
algorithm assigns a mass density at the position of every particle
through a kernel interpolation over a certain number of its nearest
neighbours. The local minima in the gravitational potential field
are the centres of subhalo candidates. The particle membership of
the subhaloes is determined by the iso-density contours defined
by the density saddle points. Particles are assigned to at most one
subhalo. The subhalo with a minimum value of the gravitational
potential within an FoF group is defined as the main subhalo of the
group. Any particle bound to the group but not assigned to any other
subhaloes within the group are assigned to the main subhalo.
MNRAS 464, 1659–1675 (2017)
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1662 Y. Qu et al.
2.2.2 Subhalo merger tree
Although they orbit within an FoF group, subhaloes survive as
distinct objects for an extended period of time. We therefore use
subhaloes as the base units of our merger trees: FoF group merger
trees can be rebuilt from subhalo merger trees if required. The first
and main step in building the merger tree is to link subhaloes across
snapshots. As in Springel et al. (
2005), we search the descendant
of a subhalo by tracing the most bound particles of the subhalo. We
use the D-Trees algorithm (Jiang et al.
2014) to locate the where-
abouts of the N
link
= min(N
linkmax
,max(f
trace
N, N
linkmin
)) most bound
particles of the subhalo, where N is the total particle number in the
subhalo. We use parameters N
linkmin
= 10, N
linkmax
= 100, f
trace
= 0.1
in the descendant search. The advantages of focusing on the N
link
most bound particles are two-fold. On the one hand, D-Trees can
identify a descendant even if most particles are stripped away leav-
ing only a dense core. On the other hand, the criterion minimises
misprediction of mergers during flyby encounters (Fakhouri & Ma
2008; Genel et al. 2009).
The descendant identification proceeds as follows. For a subhalo
A at a given snapshot, any subhalo at the subsequent snapshot that
receives at least one particle from A is labelled as a descendant
candidate. From those candidates, we pick the one that receives the
largest fraction of A’s N
link
most bound particles (denoted as B)as
the descendant of A. A is the progenitor of B.IfB receives a larger
fraction of its own N
link
most bound particles from A than from any
other subhalo at previous snapshot, A is the principal progenitor
of B. A descendant can have more than one progenitor, but only
one principal progenitor. The principal progenitor can be thought
of as ‘surviving’ the merger while the other progenitors lose their
individual identity.
Subhaloes sometimes exhibit unstable behaviour during merg-
ers, complicating the descendant/progenitor search. When a sub-
halo passes through the dense core of another subhalo, it may not
be identifiable as a separate object at the next snapshot, but will
then reappear in a later snapshot. From a single snapshot, there
is no way to know whether the subhalo has merged with another
subhalo, or has just disappeared temporarily, and we need to search
a few snapshots ahead in order to know which case it falls into.
In practice, we search up to N
step
= 5 consecutive snapshots ahead
for the missing descendants. This gives us between one and N
step
descendant candidates. If the subhalo is the principal progenitor of
one or more candidates, the earliest candidate that does not have a
principal progenitor is chosen to be the descendant. If there is no
such candidate, then the earliest one will be chosen. If the subhalo is
not the principal progenitor of any candidates, it will be considered
to have merged with another subhalo and no longer appears as an
identifiable object.
Occasionally, two subhaloes enter into a competition for bound
particles. This occurs as the participants orbit each other prior to
merging. In SUBFIND, the influence of a subhalo is based on its
gravitational potential well. When two subhaloes are close to each
other, their volumes of influence become intertwined and the def-
inition of the main halo may become unclear. For example, when
a satellite subhalo orbits closely to its primary host, the satellite
can be tidally compressed at some stage and become denser than
the host. At this point, the satellite may be classified as the central
object of the halo so that most of the halo particles are assigned
to it. At a later time, the original central, however, can surpass the
satellite in density and reclaim the halo particles. This contest can
last for several successive snapshots, accompanied by a see-saw
exchange of their physical properties during the merging. Fig.
1
Figure 1. A section of a subhalo merger tree illustrating how subhaloes
following branches A and B exchange particles before merging. The colour
of the solid symbol reflects the halo mass, while the size of the circle
represents the ‘branch mass’, which is the sum of the total mass of all the
progenitors sitting on the same branch. A see-saw behaviour is clearly seen
in the evolution of the halo mass, which may confuse identification of the
most important branch. Instead, we use branch mass to locate the main
branch of the tree. In this plot, branch A has the largest branch mass and
is therefore chosen as the main branch, even though its progenitors are not
always the most massive ones.
shows an example in which merging haloes take turns to be classi-
fied as the central host during the merging process. Overall, fewer
than 5 per cent of subhalo mergers in the EAGLE simulations ex-
hibit this behaviour, compatible with the statistics found by Wetzel,
Cohn & White (
2009). The fact that a fierce contest between sub-
haloes is sometimes seen during the merging process highlights the
inherent difficulties in appropriately describing subhalo properties
at that stage.
The property exchanges during such periods are not physical,
but rather stem from the requirement that particles be assigned to
a unique subhalo on the basis of the spatial coordinates and the
local density field in a single snapshot. The history of an object
is, however, conveniently simplified by modifying the definition
of the most massive progenitor to account for its mass in earlier
snapshots. We refer to this progenitor as the ‘main progenitor’, and
the branch they stay on in the object’s merger tree as the ‘main
branch’. Because of the mass exchange discussed above, we track
the main branch using the ‘branch mass’, the sum of the mass over all
particle species of all progenitors on the same branch ( De Lucia &
Blaizot
2007). The main progenitor is then the progenitor that has
the maximum branch mass among its contemporaries. This can
avoid the misidentification of main progenitors due to the property
exchanges occurring for merging subhaloes as we see in Fig.
1.
It is worth noting that according to this definition, a lower mass
progenitor which has existed for a long time can sometimes be
preferred over a more massive progenitor which has formed quickly,
when locating main progenitors.
The subhalo merger trees derived by the method described above
are publicly available through an
SQL data base
1
similar to that used
for the Millennium simulations (see McAlpine et al.
2016, for more
details).
1
http://www.eaglesim.org
MNRAS 464, 1659–1675 (2017)
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Galaxy mass assembly in the EAGLE simulation 1663
2.3 Galaxy sample, galaxy merger tree, and merger type
In this work, galaxies are identified as the stellar components of
the subhaloes. The main subhalo of a FoF halo hosts the ‘central’
galaxy, while other subhaloes within the group host satellite galax-
ies. We will focus on the central galaxies in our study, avoiding
the complications of environmental processes such as ram pressure
stripping and strangulation that suppress star formation and strip
stellar mass from satellite galaxies (e.g. Wetzel et al.
2013; McGee,
Bower & Balogh
2014;Barberetal.2016).
The stellar mass of a galaxy is measured using a spherical aper-
ture. This gives similar results to the commonly used 2D Petrosian
aperture used in observational work, but provides an orientation-
independent mass measurement for each galaxy. Previous studies
based on the EAGLE simulations adopt an aperture of 30 pkpc to
measure galaxy stellar mass (e.g. Furlong et al.
2015b; Schaye et al.
2015). Nevertheless, subhaloes do contain a significant population
of diffuse stars, particularly in more massive haloes (Furlong et al.
2015b). Such stars are probably deposited by interactions and tidal
stripping, and sometimes observed as low-surface brightness intr-
acluster/intragroup light (Theuns & Warren
1997; Zibetti & White
2004; McGee & Balogh 2010). Since the formation of massive
galaxies is a particular focus of this paper, we use a larger aperture,
with a radius of 100 pkpc, to calculate galaxy mass. Note that this
mass does not include the stellar mass of satellites lying within the
100 pkpc aperture. As we will show in Appendix C, this aperture
choice has little impact on galaxy properties for galaxies with stellar
mass M
< 10
11
M
(see also Schaye et al. 2015).
Unless otherwise stated, the galaxy stellar mass in this work refers
to the actual mass of stars in the galaxy at the epoch of ‘observa-
tion’. Using actual mass replicates what an ideal observer would
measure and directly addresses the question of when the current
stellar population of the galaxy was formed/assembled. Neverthe-
less, we should note that the mass budget of the current stellar
population is a combination of two processes: stellar mass gain
via star formation, accretion and merging, and mass-loss through
stellar evolution processes. However, using the actual stellar mass
complicates interpretation of the relative mass contribution from
different types of merger events since it depends on the age of the
stellar population that is accreted. We therefore use the stellar mass
initially formed (‘initial mass’), not the actual stellar mass, to evalu-
ate the contributions from internal and external processes to galaxy
assembly. In practice, this distinction has little effect on the results
and we show the effect of using initial stellar mass throughout in
Appendix B.
2.3.1 Galaxy sample
Our study is based on the formation histories of 62 543 galax-
ies in the largest EAGLE simulation R ef-L100N1504, spanning
a stellar mass range of 10
9.5
–10
12
M
over redshift z = 0–3. In
order to test the robustness of our results to resolution, we also
extract 1381 galaxies within the same mass range, as a com-
parison sample, from the EAGLE simulation Recal-L025N0752
(2 × 752
3
dark matter and gas particles in a 25 cMpc box),
which has eight times better mass resolution and the same snap-
shot frequency as Ref-L100N1504. We use subgrid physical mod-
els with parameters recalibrated to the present-day observations,
as this provides the best match to the observed galaxy popula-
tion (see Schaye et al.
2015). In order to study the mass de-
pendence of galaxy assembly, we split our samples into three
stellar mass bins: a low-mass bin (10
9.5
M
< 10
10.5
M
), an
intermediate-mass bin (10
10.5
M
< 10
11
M
), and a high-mass
bin (10
11
M
< 10
12
M
).
2.3.2 Galaxy merger tree
We construct galaxy merger trees by focusing on the stellar com-
ponent of the subhalo merger trees. Fig.
2 shows such a tree for a
galaxy with M
= 1.7 × 10
11
M
at z = 0, together with images of
its star distribution highlighting its morphological evolution since
z = 1. The main branch of the tree is marked by the thick black
line. It is important to bear in mind that the identification of the
main branch is always based on t he branch mass; at any particular
epoch, the most massive galaxy progenitor may not lie on the main
branch. However, for the reasons described in Section 2.2.2, using
the branch mass yields more stable and intuitive results.
Galaxy merger trees appear broadly similar to subhalo merger
trees, except that the latter contain more fine branches corresponding
to small subhaloes within which no stars have formed. Galaxy trees
are also less affected by the mass exchange issue than subhalo trees,
as star particles are more spatially concentrated.
2.3.3 Merger type
The effects of tidal forces and torques during a merger depend on
the mass r atio of the merging systems (e.g. Barnes & Hernquist
1992). A merger between a low-mass satellite and a more massive
host is generally less violent than a merger between systems of
comparable mass, and has a less dramatic impact on the dynamics
and morphology of the host. It is therefore useful to classify mergers
into different t ypes according to the mass ratio between the two
merging systems, μ M
2
/M
1
(M
1
> M
2
). For galaxy mergers, μ
is the ratio of stellar masses between two merging galaxies. While
for halo mergers, it is the halo mass ratio.
While this is straightforward in semi-analytic models (since
galaxies are uniquely defined entities), in numerical simulations
(and in nature as well), merging systems experience mass-loss due
to tidal stripping throughout the merging process. Our strategy is
therefore to choose a separation criterion, R
merge
, and determine
the merger type when the merging systems are separated, for the
first time, by that distance or less. For galaxy mergers, we adopt
R
merge
= 5 × R
1/2
,whereR
1/2
is the half-stellar mass radius of the
primary galaxy (note that R
merge
is not a projected but a 3D separa-
tion). The value of R
merge
ranges from 20 to 200 pkpc in the stellar
mass range explored in this work (see Appendix A), and is s imilar
to the projected separation criteria adopted in observational galaxy
pair studies. For subhalo mergers, R
merge
= r
200
,wherer
200
is the
radius of a region around the FoF group of the subhaloes within
which the density is 200 times the cosmological critical density. In
the rare event that an object is located within the R
merge
of more than
one other object, i t is considered to be the merging companion of
the nearest one.
More often than not, the secondary object may have suffered
tidal stripping of mass when the merger type is determined due to
the finite time sampling of our snapshot outputs. To alleviate the
resulting misestimate of the mass ratio, we compare the mass of
the merging systems at the start of the merging event with that at
the previous snapshot, and use the maximum to calculate the mass
ratio μ. In our study, merging events are classified as major mergers
if μ 1/4; as minor mergers if 1/4 1/10; and as diffuse
accretion, when μ<1/10. Our major merger definition is different
from that of C ole et al. (
2000) or De L ucia & Blaizot (2007)who
adopt a larger mass ratio 1/3, but is similar to more recent studies
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Figures (12)
Citations
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Journal ArticleDOI
Abstract: Numerical simulations have become a major tool for understanding galaxy formation and evolution. Over the decades the field has made significant progress. It is now possible to simulate the formation of individual galaxies and galaxy populations from well-defined initial conditions with realistic abundances and global properties. An essential component of the calculation is to correctly estimate the inflow to and outflow from forming galaxies because observations indicating low formation efficiency and strong circumgalactic presence of gas are persuasive. Energetic “feedback” from massive stars and accreting supermassive black holes—generally unresolved in cosmological simulations—plays a major role in driving galactic outflows, which have been shown to regulate many aspects of galaxy evolution. A surprisingly large variety of plausible subresolution models succeeds in this exercise. They capture the essential characteristics of the problem, i.e., outflows regulating galactic gas flows, but their predicti...

317 citations


Journal ArticleDOI
Abstract: We use cosmological simulations from the FIRE (Feedback In Realistic Environments) project to study the baryon cycle and galaxy mass assembly for central galaxies in the halo mass range Mhalo ∼ 10^(10)–10^(13) M_⊙. By tracing cosmic inflows, galactic outflows, gas recycling and merger histories, we quantify the contribution of physically distinct sources of material to galaxy growth. We show that in situ star formation fuelled by fresh accretion dominates the early growth of galaxies of all masses, while the re-accretion of gas previously ejected in galactic winds often dominates the gas supply for a large portion of every galaxy’s evolution. Externally processed material contributes increasingly to the growth of central galaxies at lower redshifts. This includes stars formed ex situ and gas delivered by mergers, as well as smooth intergalactic transfer of gas from other galaxies, an important but previously underappreciated growth mode. By z = 0, wind transfer, i.e. the exchange of gas between galaxies via winds, can dominate gas accretion on to ∼L* galaxies over fresh accretion and standard wind recycling. Galaxies of all masses re-accrete ≳50 per cent of the gas ejected in winds and recurrent recycling is common. The total mass deposited in the intergalactic medium per unit stellar mass formed increases in lower mass galaxies. Re-accretion of wind ejecta occurs over a broad range of time-scales, with median recycling times (∼100–350 Myr) shorter than previously found. Wind recycling typically occurs at the scale radius of the halo, independent of halo mass and redshift, suggesting a characteristic recycling zone around galaxies that scales with the size of the inner halo and the galaxy’s stellar component.

240 citations


01 Jan 2016
Abstract: We use the Illustris simulation to study the relative contributions of in situ star formation and stellar accretion to the build-up of galaxies over an unprecedentedly wide range of masses (M_* = 10^9-10^(12) M_⊙), galaxy types, environments, and assembly histories. We find that the ‘two-phase’ picture of galaxy formation predicted by some models is a good approximation only for the most massive galaxies in our simulation – namely, the stellar mass growth of galaxies below a few times 10^(11) M_⊙ is dominated by in situ star formation at all redshifts. The fraction of the total stellar mass of galaxies at z = 0 contributed by accreted stars shows a strong dependence on galaxy stellar mass, ranging from about 10 per cent for Milky Way-sized galaxies to over 80 per cent for M_* ≈ 10^(12) M_⊙ objects, yet with a large galaxy-to-galaxy variation. At a fixed stellar mass, elliptical galaxies and those formed at the centres of younger haloes exhibit larger fractions of ex situ stars than disc-like galaxies and those formed in older haloes. On average, ∼50 per cent of the ex situ stellar mass comes from major mergers (stellar mass ratio μ > 1/4), ∼20 per cent from minor mergers (1/10 < μ < 1/4), ∼20 per cent from very minor mergers (μ < 1/10), and ∼10 per cent from stars that were stripped from surviving galaxies (e.g. flybys or ongoing mergers). These components are spatially segregated, with in situ stars dominating the innermost regions of galaxies, and ex situ stars being deposited at larger galactocentric distances in order of decreasing merger mass ratio.

168 citations


Journal ArticleDOI
Abstract: We present the evolution of galaxy sizes, from redshift 2 to 0, for actively star forming and passive galaxies in the cosmological hydrodynamical 1003 cMpc3 simulation of the EAGLE project. We find that the sizes increase with stellar mass, but that the relation weakens with increasing redshift. Separating galaxies by their star formation activity, we find that passive galaxies are typically smaller than active galaxies at a fixed stellar mass. These trends are consistent with those found in observations and the level of agreement between the predicted and observed size–mass relations is of the order of 0.1 dex for z < 1 and 0.2–0.3 dex from redshift 1 to 2. We use the simulation to compare the evolution of individual galaxies with that of the population as a whole. While the evolution of the size–stellar mass relation for active galaxies provides a good proxy for the evolution of individual galaxies, the evolution of individual passive galaxies is not well represented by the observed size–mass relation due to the evolving number density of passive galaxies. Observations of z ∼ 2 galaxies have revealed an abundance of massive red compact galaxies, which depletes below z ∼ 1. We find that a similar population forms naturally in the simulation. Comparing these galaxies with their z = 0 descendants, we find that all compact galaxies grow in size due to the high-redshift stars migrating outwards. Approximately 60 per cent of the compact galaxies increase in size further due to renewed star formation and/or mergers.

166 citations


Cites background or result from "A chronicle of galaxy mass assembly..."

  • ...As will be shown by Qu et al. (2017), the number of major and minor mergers experienced by galaxies in the EAGLE simulation is a strong function of stellar mass, consistent with findings inferred from observations of close projected pairs....

    [...]

  • ...This definition ensures that any mass lost due to stripping, before the secondary branch coalesces with the main branch, is accounted for in the accreted mass (Qu et al. 2017)....

    [...]

  • ...A full description of the trees is presented by Qu et al. (2017), with their public release1 discussed by McAlpine et al. (2016)....

    [...]


Journal ArticleDOI
Abstract: Numerical simulations have become a major tool for understanding galaxy formation and evolution. Over the decades the field has made significant progress. It is now possible to simulate the formation of individual galaxies and galaxy populations from well defined initial conditions with realistic abundances and global properties. An essential component of the calculation is to correctly estimate the inflow to and outflow from forming galaxies since observations indicating low formation efficiency and strong circum-glactic presence of gas are persuasive. Energetic 'feedback' from massive stars and accreting super-massive black holes - generally unresolved in cosmological simulations - plays a major role for driving galactic outflows, which have been shown to regulate many aspects of galaxy evolution. A surprisingly large variety of plausible sub-resolution models succeeds in this exercise. They capture the essential characteristics of the problem, i.e. outflows regulating galactic gas flows, but their predictive power is limited. In this review we focus on one major challenge for galaxy formation theory: to understand the underlying physical processes that regulate the structure of the interstellar medium, star formation and the driving of galactic outflows. This requires accurate physical models and numerical simulations, which can precisely describe the multi-phase structure of the interstellar medium on the currently unresolved few hundred parsecs scales of large scale cosmological simulations. Such models ultimately require the full accounting for the dominant cooling and heating processes, the radiation and winds from massive stars and accreting black holes, an accurate treatment of supernova explosions as well as the non-thermal components of the interstellar medium like magnetic fields and cosmic rays.

162 citations


Cites background or methods from "A chronicle of galaxy mass assembly..."

  • ...The general trend is similar to simulations (e.g. Gabor & Davé 2012, Lackner et al. 2012, Oser et al. 2010, Qu et al. 2017, Rodriguez-Gomez et al. 2016)....

    [...]

  • ...For intermediate mass galaxies (e.g. Milky Way) and low mass systems stars are primarily formed from streams of gas that accumulate centrally or in disks (e.g. Qu et al. 2017, Rodriguez-Gomez et al. 2016)....

    [...]

  • ...…high-density environments - primarily affected by feedback from accreting super-massive black holes - and their late assembly involves merging with other galaxies, which might also be of an early type (e.g. 26 Theoretical Challenges in Galaxy Formation Qu et al. 2017, Rodriguez-Gomez et al. 2016)....

    [...]

  • ...For high halo masses, the evolution of the galaxies shows a clear two-phase characteristic (Feldmann et al. 2010; Johansson, Naab & Ostriker 2012; Naab et al. 2007; NavarroGonzález et al. 2013; Oser et al. 2010; Qu et al. 2017; Rodriguez-Gomez et al. 2016)....

    [...]

  • ...Stars added in major and minor mergers can make up as much as 50 % of the largely outer envelopes (in case of minor mergers) of these systems (Naab, Johansson & Ostriker 2009; Qu et al. 2017; Rodriguez-Gomez et al. 2016)....

    [...]


References
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Peter A. R. Ade1, Nabila Aghanim2, C. Armitage-Caplan3, Monique Arnaud4  +324 moreInstitutions (70)
Abstract: This paper presents the first cosmological results based on Planck measurements of the cosmic microwave background (CMB) temperature and lensing-potential power spectra. We find that the Planck spectra at high multipoles (l ≳ 40) are extremely well described by the standard spatially-flat six-parameter ΛCDM cosmology with a power-law spectrum of adiabatic scalar perturbations. Within the context of this cosmology, the Planck data determine the cosmological parameters to high precision: the angular size of the sound horizon at recombination, the physical densities of baryons and cold dark matter, and the scalar spectral index are estimated to be θ∗ = (1.04147 ± 0.00062) × 10-2, Ωbh2 = 0.02205 ± 0.00028, Ωch2 = 0.1199 ± 0.0027, and ns = 0.9603 ± 0.0073, respectively(note that in this abstract we quote 68% errors on measured parameters and 95% upper limits on other parameters). For this cosmology, we find a low value of the Hubble constant, H0 = (67.3 ± 1.2) km s-1 Mpc-1, and a high value of the matter density parameter, Ωm = 0.315 ± 0.017. These values are in tension with recent direct measurements of H0 and the magnitude-redshift relation for Type Ia supernovae, but are in excellent agreement with geometrical constraints from baryon acoustic oscillation (BAO) surveys. Including curvature, we find that the Universe is consistent with spatial flatness to percent level precision using Planck CMB data alone. We use high-resolution CMB data together with Planck to provide greater control on extragalactic foreground components in an investigation of extensions to the six-parameter ΛCDM model. We present selected results from a large grid of cosmological models, using a range of additional astrophysical data sets in addition to Planck and high-resolution CMB data. None of these models are favoured over the standard six-parameter ΛCDM cosmology. The deviation of the scalar spectral index from unity isinsensitive to the addition of tensor modes and to changes in the matter content of the Universe. We find an upper limit of r0.002< 0.11 on the tensor-to-scalar ratio. There is no evidence for additional neutrino-like relativistic particles beyond the three families of neutrinos in the standard model. Using BAO and CMB data, we find Neff = 3.30 ± 0.27 for the effective number of relativistic degrees of freedom, and an upper limit of 0.23 eV for the sum of neutrino masses. Our results are in excellent agreement with big bang nucleosynthesis and the standard value of Neff = 3.046. We find no evidence for dynamical dark energy; using BAO and CMB data, the dark energy equation of state parameter is constrained to be w = -1.13-0.10+0.13. We also use the Planck data to set limits on a possible variation of the fine-structure constant, dark matter annihilation and primordial magnetic fields. Despite the success of the six-parameter ΛCDM model in describing the Planck data at high multipoles, we note that this cosmology does not provide a good fit to the temperature power spectrum at low multipoles. The unusual shape of the spectrum in the multipole range 20 ≲ l ≲ 40 was seen previously in the WMAP data and is a real feature of the primordial CMB anisotropies. The poor fit to the spectrum at low multipoles is not of decisive significance, but is an “anomaly” in an otherwise self-consistent analysis of the Planck temperature data.

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"A chronicle of galaxy mass assembly..." refers methods in this paper

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    [...]


Journal ArticleDOI
Abstract: We present the first results based on Planck measurements of the CMB temperature and lensing-potential power spectra. The Planck spectra at high multipoles are extremely well described by the standard spatially-flat six-parameter LCDM cosmology. In this model Planck data determine the cosmological parameters to high precision. We find a low value of the Hubble constant, H0=67.3+/-1.2 km/s/Mpc and a high value of the matter density parameter, Omega_m=0.315+/-0.017 (+/-1 sigma errors) in excellent agreement with constraints from baryon acoustic oscillation (BAO) surveys. Including curvature, we find that the Universe is consistent with spatial flatness to percent-level precision using Planck CMB data alone. We present results from an analysis of extensions to the standard cosmology, using astrophysical data sets in addition to Planck and high-resolution CMB data. None of these models are favoured significantly over standard LCDM. The deviation of the scalar spectral index from unity is insensitive to the addition of tensor modes and to changes in the matter content of the Universe. We find a 95% upper limit of r<0.11 on the tensor-to-scalar ratio. There is no evidence for additional neutrino-like relativistic particles. Using BAO and CMB data, we find N_eff=3.30+/-0.27 for the effective number of relativistic degrees of freedom, and an upper limit of 0.23 eV for the summed neutrino mass. Our results are in excellent agreement with big bang nucleosynthesis and the standard value of N_eff=3.046. We find no evidence for dynamical dark energy. Despite the success of the standard LCDM model, this cosmology does not provide a good fit to the CMB power spectrum at low multipoles, as noted previously by the WMAP team. While not of decisive significance, this is an anomaly in an otherwise self-consistent analysis of the Planck temperature data.

5,946 citations


Journal ArticleDOI
02 Jun 2005-Nature
TL;DR: It is shown that baryon-induced features in the initial conditions of the Universe are reflected in distorted form in the low-redshift galaxy distribution, an effect that can be used to constrain the nature of dark energy with future generations of observational surveys of galaxies.
Abstract: The cold dark matter model has become the leading theoretical picture for the formation of structure in the Universe. This model, together with the theory of cosmic inflation, makes a clear prediction for the initial conditions for structure formation and predicts that structures grow hierarchically through gravitational instability. Testing this model requires that the precise measurements delivered by galaxy surveys can be compared to robust and equally precise theoretical calculations. Here we present a simulation of the growth of dark matter structure using 2,1603 particles, following them from redshift z = 127 to the present in a cube-shaped region 2.230 billion lightyears on a side. In postprocessing, we also follow the formation and evolution of the galaxies and quasars. We show that baryon-induced features in the initial conditions of the Universe are reflected in distorted form in the low-redshift galaxy distribution, an effect that can be used to constrain the nature of dark energy with future generations of observational surveys of galaxies.

4,572 citations


"A chronicle of galaxy mass assembly..." refers background in this paper

  • ...As in Springel et al. (2005), we search the descendant of a subhalo by tracing the most bound particles of the subhalo....

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Journal ArticleDOI
Abstract: A set of new mathematical results on the theory of Gaussian random fields is presented, and the application of such calculations in cosmology to treat questions of structure formation from small-amplitude initial density fluctuations is addressed. The point process equation is discussed, giving the general formula for the average number density of peaks. The problem of the proper conditional probability constraints appropriate to maxima are examined using a one-dimensional illustration. The average density of maxima of a general three-dimensional Gaussian field is calculated as a function of heights of the maxima, and the average density of 'upcrossing' points on density contour surfaces is computed. The number density of peaks subject to the constraint that the large-scale density field be fixed is determined and used to discuss the segregation of high peaks from the underlying mass distribution. The machinery to calculate n-point peak-peak correlation functions is determined, as are the shapes of the profiles about maxima.

2,965 citations


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