Early phases of galaxy

evolution

Gianfranco De Zotti (INAF-OAPd)

Andrea Lapi, Alessandro Bressan, Luigi

Danese, Mattia Negrello

What is the main driver of

galaxy formation?

• The spectacular success of hierarchical-CDM at explaining

the large-scale structure (> 1Mpc) has led to the widespread

opinion that the formation of visible galaxies parallels that

of dark matter halos: small objects form first and merge

together to make larger ones

• Most of the star-formation, and of the black hole accretion,

in the early universe is triggered by galaxy interactions and

mergers, and therefore occurs in bursts

Mg bFe5015

Mg2Mg1

Fe5270

Fe5335

Fe5406

Hb

Narrow Band Indices Lick-IDS System

A5V 0.5- 1 Gyr

G0V 4.5 Gyr

K0III red giant

M0III RGB

M.S. Clemens, A. Bressan,

B. Nikolic, Rampazzo 09

∑

Age, Z

[a/Fe]Model

s

14000 ETGs 0.01 < z < 0.1

Lick Indices: Hb Hdf

Mg1 Mg2 Mgb

Fe4383 Fe4531 Fe5270 Fe5335

• Galaxies with higher mass

are older, more metal rich and

a-enhanced.

The star formation was

rapid (< 1Gyr) in ETGs with

high mass

The star formation was

slow (several Gyr) at low

masses

• Environment affects only the

mean age of ETGs, at a given s:

ETGs in high density form first

• Environment has no effect on

metallicity and a-nhancement.

After collapse, formation

and evolution are driven by the

potential well

Galaxy Formation

all

r5 is the distance to the fifth-nearest

neighbour. 1/r5 < 0.5: low-density

environment; 1/r5 > 1.5: high-density

environment;

Galaxy Formation

all

Evolution of

DM Halos:

smaller halos

form first

Feedback reverses

formation

timescales:

in smaller galaxies

star formation

proceeds slowly

lower [a/Fe]

indicates

longer duration

Problems with merger-driven galaxy evolution - 1

• Correlations tight enough to allow little room for random

processes and for sensitivity to environment have been

known for a long time (colour-luminosity; fundamental

plane relations; dynamical mass - luminosity) and have been

recently confirmed with very large samples. More recently:

luminosity–size (Nair et al. 2010), SFR-mass at z~2

(Maraston et al. 2010; Pannella et al. 2009)

• Insensitivity to environment

• Tight contraints on increase of stellar mass of massive

ETGs since z=1.5-2 (Pérez-González et al. 2008;

Marchesini et al. 2009; Mancone et al. 2010; Fan et al.

2010).

Problems with merger-driven galaxy evolution - 2

• Integral-field near-IR spectroscopy has shown that many of

these galaxies have ordered, rotating velocity fields with no

kinematic evidence for ongoing merging (Genzel et al.

2006; Förster-Schreiber et al. 2009; Carilli et al. 2010). A

complex morphology is not necessarily a symptom of

merging .

• At z ∼ 2.3, massive quiescent galaxies are typically 5 times

more compact, and two orders of magnitude more dense

than local ellipticals of the same mass (Cimatti et al. 2008;

van Dokkum et al. 2008). The size evolution by mergers is

tightly constrained by limits on mass increase (Fan et al.

2010).

Problems with merger-driven galaxy evolution - 3

• Large (~50-60%, Driver et al. 2008) stellar mass fraction in

fragile disks. The remarkably thin disc of the Milky Way

formed ≈ 8.8±1.7 Gyr ago (del Peloso et al. 2005),

corresponding to a formation redshift of ≈1.3(+0.9,-0.45)

and exhibits a quiescent history. The kinematic observations

(Shen et al. 2010) show no sign of a significant merger-

made bulge. Another example is the giant edge-on galaxy

NGC 4565 (Kormendy & Barentine 2010). Giant, pure disk

galaxies seem to be common in environments far from rich

clusters of galaxies (Kormendy et al. 2010). How did these

galaxies grow so large with no observational sign that they

suffered a major merger in the last 9 – 10 Gyr?

Problems with merger-driven galaxy evolution - 4

• The distribution of galaxy luminosities is very different from

the distribution of DM halo masses: many fewer faint

galaxies relative to bright galaxies than low mass to high

mass DM halos and exponential decline at the high end of

the luminosity function: the efficiency of galaxy formation

must depend strongly upon halo mass (see e.g. Shankar et al.

2006; Behroozi et al. 2010).

It is now generally agreed that baryonic processes must come

into play to suppress the formation of stars in lowest and

highest mass dark matter halos (probably energy/momentum

input from supernovae explosions at low masses, AGN

feedback at high masses). But is the role of baryon processes

even more important?

Are baryon processes the main driver?

The above difficulties have been addressed and overcome,

under some conditions, by models in the framework of the

merging scenario. In some cases, however, the solutions

rely on assumptions not very clearly justified and are

somewhat contrived.

Difficulties are more easily overcome if baryon processes,

rather than merging, are the main drivers of galaxy

evolution (Granato et al. 2001, 2004; Lapi et al. 2006), still

in the general framework of hierachical clustering in a

ΛCDM universe.

Key ingredients - 1

• In the build-up of a galactic halo we can schematically

identify two phases (Zhao et al. 2003):

– a fast accretion phase (timescale « H(z)-1) in which the potential

well is created by major mergers, and that can define the formation

epoch of the galaxy

– a slow accretion (minor merger) phase in which mass is added in

the outskirts of the halo, affecting only weakly the central region

where the stellar component resides.

In general this second phase affects only marginally the

stellar component, although occasionally major mergers

also occur, but they involve a minority of large galaxies.

Halo mass vs velocity evolution

(Zhao et al. 2003)

Halos form, gas is shock heated to virial T

Gas cools, collapse and forms stars directly, in small

halos SNae quench SF, in big ones nothing prevents a

huge burst of SF (~1000 Msun/yr over 0.5 Gyr), SMGs

phase

(almost) passive evolution of stellar population follows.

ERO phase with dormant SMBH

SF promotes the growth of a SMBH, powering high z

QSO. QSO activity expels the ISM, terminating SF and

its own growth. QSO phase

Co-evolution scheme by Granato et al. (2004)

HOT GAS

COLD GAS

RESERVOIR

(low J)

STARS IGM

SMBH-QSO

SNae feedback

QSO feedback

Radiative

cooling

Radiation

drag

(SFR)

Viscous

accretion

Collapse

Physical processes

Stellar

evolution

Arrows correspond to a set of differential

equations describing the various processes,

solved numerically. Approximate analytical

solutions given by Mao et al. (2007).

Baryon-driven evolution:

implications and predictions - 1

• Mbh – σ correlation (Silk & Rees 1998)

• Downsizing: SN explosions quench star-formation (and

may unbind the gas) in low-mass halos, but may enhance it

(through shocks) in massive halos (Granato et al 2001;

2004)

• Critical mass (Mhalo ~ 3×1011 Msun corresponding to M* ~

1.2×1010 Msun ) above which the AGN feedback overcomes

Snae as the main agent controlling the SFR (Granato et al.

2004; Shankar et al. 2006). A “halo mass floor” Mmin ≈

1011 Msun was introduced on essentially empirical grounds,

by Bouché et al. (2010)

• M* - Mhalo relationship (Shankar et al. 2006)

Baryon-driven evolution:

implications and predictions - 2

• Ωstar « Ωb : the total mass density in stars is

Ωstar=0.0027±0.0005 (Fukugita & Peebles 2004), i.e.

5.8%±1.1% of the total baryonic mass density of the

Universe Ωb = 0.0456 ± 0.0016 (Komatsu et al. 2010); the

ISM adds little.Therefore, only a small fraction of all

baryons are kept in galaxies.

• Very high (thousands Msun/yr) SFRs for very massive high-

z galaxies, without invoking non-standard (top-heavy)

IMFs. SCUBA counts and redshift distributions easily

accounted for.

• SPT & Herschel counts, including strongly lensed sources

(Negrello et al. 2007).

1.4 mm cumulative SPT counts (Vieira et al. 2010)

Models: short dashed Lagache et

al. (2004) ; long dashed line,

Negrello et al. (2007); dot-dashed

line, Pearson & Khan (2009)

Top panel: all dust-dominated

sources included.

Bottom panel: counts calculated

excluding sources that have IRAS-

FSC counterparts (within 1') and

models calculated excluding

populations that should be

detectable in the IRAS 60 μm band

above the typical FSC limit of 0.2 Jy.

Negrello et al. is the only physical

(forward) model. While predicted

counts are similar, redshift

distributions are radically different:

Negrello et al. predicts 2 peaks, at

z~0.02 and at z~3 (see below).

Herschel/SPIRE 500µm counts

Negrello et al. (2010); counts

by Clements et al. (2010)

The model curves are

from Negrello et al.

(2007). The model

predicted 0.4 deg-2

strongly lensed sources

and 0.55 deg-2 low-z

star-forming galaxies,

i.e. 5.8 and 6.6,

respectively, in the 14.4

deg2 H-ATLAS SDP

field. The predicted

surface density of

strongly lensed gal-

axies is sensitive to the

redshift distribution.

Herschel/SPIRE 500µm redshift distributions

.

The H-ATLAS SDP catalog contains 10 sources (plus an Galactic dust

cloud) with 500 μm flux density above 100mJy: 4 galaxies with

spectroscopic redshifts in the range 0.01− 0.05, 1 blazar and 5 strongly

lensed galaxies in the redshift range 1.6 − 3.1. The figures show the

corresponding predictions by Negrello et al. (2007).

500µm

Normal late-type

Starburst

Lapi et al. 06

Merger-driven QSO activity (Hopkins et al. 2008)

Light curve with multiple peaks and SFR well correlated with LQSO

Star-formation vs AGN activity

Star forming luminosity vs. AGN luminosity for the GOODS-N AGN

and a local reference sample of extremely hard X-ray selected BAT

AGN. The dashed line is the relation implied by Netzer et al. (2009).

Shao et al. (2010)

Baryon-driven evolution:

implications and predictions - 3

We expect a correlation

between SFR and AGN

luminosity at high z

because both are correlated

with the halo mass, but not

linear (because the AGN

accretion rate is mostly

Eddington limited) and

with a large dispersion.

Bonfield et al. (2010) find

LFIR ~ LQSO0.32 (with some

uncertain dependence on

z) .

Hatziminaoglou et al. (2010) find LFIR ~ LQSO0.35 for objects at z > 2,

with a large dispersion (see figure)

Hatziminaoglou et al. (2010)

Baryon-driven evolution:

implications and predictions - 4

• During most of the active star-formation phase, the AGN

mass is well below the final value. The median X-ray

luminosity of FIR/SM bright galaxies is therefore predicted

to be relatively low. For the z~2 ULIRGS with 24 μm fluxes

of 0.14–0.5 mJy, studied by Fadda et al. (2010), the model

yields a median accretion rate of ~0.01 Msun/yr (Granato et

al. 2006) corresponding to a bolometric luminosity of ~ 6 ×

1043 erg/s and to a 2 ̶ 10 keV X-ray luminosity of ~ 3 ×

1042 erg/s, in very good agreement with the estimate (1± 6)×

1042 erg/s) by Fadda et al.

Evolution of the luminosity function - 1

Two main factors come into play:

• The UV luminosity is proportional to the SFR which

increases with increasing z since it is controlled by

tcond=max[tcool,tdyn], which is shorter at high z, when

densities are higher. For the mass range of interest: SFR

MH0.8(1+z)1.5 (Mao et al. 2007).

• The higher dust extinction for more massive objects damps

down the contribution to the LF of the most massive halos,

whose density is decreasing fast with increasing z. In the

mass range which dominates the contribution to the LF, the

increase of the SFR with redshift compensates for the

decrease of the comoving density at fixed mass.

A very low evolution of the LF is predicted.

Extinction evolution with galactic age at

z=6

MH = 1010

Msun

1011 Msun

1012 Msun

1013 Msun

SFR vs mass and z

Pannella et al. (2009)Z=2.1

Z=1.6

Dunne et al. (2009)

Rodighiero et al. (2010)

Rodighiero et al. (2010)Mao et al. (2007):

SFR ~ M0.8 (1+z)1.5 for z >1.5

and Mh > 3 × 1011 Msun

Evolution of the cumulative LAE LF

Lines:

model by

Mao et al.

(2007)

“Why the Lyα luminosity function should conspire to be unchanging over 3< z <6 when

there is such a significant change in the LBG population is particularly intriguing” (Ellis,

2008).

Evolving LBG luminosity function

Model by Mao et al. (2007) compared with recent data