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How to kill a galaxy
(A review of galaxy properties as a
function of environment)
Michael Balogh
University of Waterloo, Canada
(Look for new job postings on AAS)
Collaborators
Richard Bower , Simon Morris, Dave Wilman
No picture: Vince Eke, Cedric Lacey, Fumiaki Nakata
Durham
John Mulchaey
& Gus Oemler
OCIW
Bob Nichol, Chris
Miller & Alex Gray
Carnegie Mellon
Baugh, Cole, Frenk (Durham)
Ivan Baldry &
Karl Glazebrook
Johns Hopkins
No picture: Taddy Kodama
Ian Lewis (Oxford)
and the 2dFGRS team
Ray Carlberg
Toronto
Outline
1. Background and motivation
2. Low redshift: SDSS and 2dFGRS
3. Groups and clusters at z~0.5
4. GALFORM predictions
5. Conclusions
Outline
1. Background and motivation
2. Low redshift: SDSS and 2dFGRS
3. Groups and clusters at z~0.5
4. GALFORM predictions
5. Conclusions
Why Does Star Formation
Stop?
(Hopkins et al 2004)
A) Internal? i.e. gas consumption and “normal” aging
B) External? Hierarchical build-up of structure inhibits star formation
Galaxy clusters:
the end of star formation?
• “Dead” galaxies (i.e.
little gas or star
formation) found in rich
clusters
• Hierarchical formation
models predict number
of clusters increases
with time.
• So perhaps dense
environments are
responsible for
terminating star
formation?
Nature or Nurture?
• Nature? Elliptical galaxies only form in
protoclusters at high redshift. Rest of
population is due to infall.
• or Nurture? Galaxy evolution proceeds along
a different path within dense environments.
– If this is true in groups and clusters, then
environment could be the driving force of recent
galaxy evolution…
Early type galaxies
Tight colour-magnitude relation (Faber 1973; Visvanathan &
Sandage 1977; Terlevich et al. 2001)
Bower, Lucey & Ellis 1992
• van Dokkum & Franx 1996:
• M/L evolution consistent
with high formation redshift
Morphology-Density Relation
Field
Clusters
E
S0
Spirals
Dressler 1980
Low redshift
NS0/NE
Number of galaxies
Morphology-density: evolution
Z~0.5
Redshift
Dressler et al. 1997; Couch et al. 1994; 1998
Fasano et al. 2000
Wide field HST: Treu et al. 2003
Log surface density
HI deficiency
Mark I and II imaging of Virgo galaxies
Davies & Lewis 1973
VLA imaging of Coma spirals
Bravo-Alfaro et al. 2000
18 nearby clusters: Solanes et al. 2001
Star formation
• Fraction of emission-line galaxies depends strongly on environment, on all scales
• Trend holds in groups, field, cluster outskirts (Lewis et al. 2002; Gomez et al. 2003)
• Fraction never reaches 100%, even at lowest densities
Cluster infall
regions
A901/902 supercluster
(Gray et al. 2004)
correlation with dark
matter density
Emission line
fraction in SDSS
and 2dFGRS
(Balogh et al. 2004)
Emission line fraction
Emission lines
• Cluster galaxies of given
morphological type show less
nebular emission than field
galaxies
• suggests star formation is
suppressed in cluster galaxies
Dressler, Thompson & Shectman 1985; Also Gisler 1978
Virgo spirals
Ha distribution
• Cluster galaxies often show
peculiar distribution of Ha
emission: usually truncated,
or globally suppressed
• In some cases, star
formation
is
centrally
enhanced (Moss & Whittle
1993; 2000)
Ha for Virgo galaxy
Ha for normal galaxy
Koopmann & Kenney 2004
also: Vogt et al. 2004
Additional physics?
•
Ram-pressure stripping (Gunn & Gott 1972)
•
Collisions / harassment (Moore et al. 1995)
•
“Strangulation” (Larson et al. 1980; Balogh et al. 2000)
Additional physics?
• Ram-pressure stripping (Gunn & Gott 1972)
•
Collisions / harassment (Moore et al. 1995)
•
“Strangulation” (Larson et al. 1980; Balogh et al. 2000)
short timescale
Quilis, Moore & Bower 2000
Kenney et al. 2003
Additional physics?
•
Ram-pressure stripping (Gunn & Gott 1972)
• Collisions / harassment (Moore et al. 1995)
•
“Strangulation” (Larson et al. 1980; Balogh et al. 2000)
important in
groups?
Also tidal effects from LSS? (Gnedin 2003)
Additional physics?
•
Ram-pressure stripping (Gunn & Gott 1972)
•
Collisions / harassment (Moore et al. 1995)
• “Strangulation” (Larson et al. 1980; Balogh et al. 2000)
–
Either through tidal disruption, or shock-heating to level at which it can’t cool (e.g.
Springel & Hernquist 2001)
long timescale
Additional physics?
•
Ram-pressure stripping (Gunn & Gott 1972)
•
Collisions / harassment (Moore et al. 1995)
• “Strangulation” (Larson et al. 1980; Balogh et al. 2000)
–
Either through tidal disruption, or shock-heating to level at which it can’t cool (e.g.
Springel & Hernquist 2001)
long timescale
S to S0 transformation?
Kenney et al. 2003
Vollmer et al. 2004
• Ram pressure stripping of the disk
could transform a spiral into a S0
(Gunn & Gott 1972; Solanes &
Salvador-Solé 2001)
• Strangulation may lead to anemic or
passive spiral galaxies (Shiyoa et al.
2002)
Non-SF spiral galaxies from SDSS (Goto et al. 2003)
First noted by Poggianti et al. (1999) in z~0.5 clusters
S to S0 transformation?
• But bulges of S0 galaxies larger
than those of spirals (Dressler
1980; Christlein & Zabludoff
2004)
Bulge size
Dressler 1980
• Requires S0 formation
preferentially from spirals with
large bulges (Larson, Tinsley &
Caldwell 1980) perhaps due to
extended merger history in
dense regions (Balogh et al.
2002)
Arguments against ram pressure stripping:
1. S0 galaxies found far from the cluster
core
Gill et al. 2004
Spiral fraction
Groups (Postman & Geller 1984)
Local galaxy density (3d)
– Galaxies well beyond Rvirial may have
already been through cluster core (e.g.
Balogh et al. 2000; Mamon et al. 2004;
Gill et al. 2004)
2. Morphology-density relation holds
equally well for irregular clusters,
centrally-concentrated clusters, and
groups
- but may be able to induce
bursts strong enough to consume the
gas
Observations: z~0.3
• Strangulation model:
– infall rate + assumed
decay rate of star
formation => radial
gradient in SFR
• Radial gradients in
CNOC clusters
suggest t ~2 Gyr
Balogh, Navarro & Morris (2000)
Outline
1. Background and motivation
2. Low redshift: SDSS and 2dFGRS
3. Groups and clusters at z~0.5
4. GALFORM predictions
5. Conclusions
Colour-magnitude relation
CMR for spiral galaxies
also observed (e.g.
Chester & Roberts 1964;
Visvanathan 1981; Tully,
Mould & Aaronson
1982)
SDSS allows full
distribution to be
quantified with high
precision ( Baldry et al.
2003; Hogg et al. 2003;
Blanton et al. 2003)
Sloan DSS data
Analysis of colours in
SDSS data:
Bright
• Colour distribution in 0.5 mag
bins can be fit with two
Gaussians
• Mean and dispersion of each
distribution depends strongly
on luminosity
• Dispersion includes variation in
dust, metallicity, SF history, and
photometric errors
• Bimodality exists out to z~1
(Bell et al. 2004)
Faint
(u-r)
Baldry et al. 2003
• 24346 galaxies from
SDSS
DR1.
magnitude limited
with z<0.08
• density
estimates
based on Mr<-20
Balogh et al. 2004
• Fraction of red galaxies
depends strongly on
density. This is the primary
influence of environment on the
colour distribution.
• Mean colours depend weakly on environment:
transitions between two populations must be
rapid (or rare at the present day)
• How rapid must the bluered
transition be?
Red Peak
• colour evolves rapidly if
timescale for star formation to
stop is short
• if transformations occur
uniformly in time:
• need t<0.5 Gyr
Blue Peak
• if transformations are more
common in the past, longer
timescales permitted
Ha distribution
• Ha distribution shows a
bimodality: mean/median of
whole distribution can be
misleading
Balogh et al. 2004
The star-forming population
• Amongst the starforming population,
there is no trend in Ha
distribution with
density
• Hard to explain with
simple, slow-decay
models (e.g. Balogh et al.
2000)
Isolated Galaxies
All galaxies
Bright galaxies
• Selection of isolated
galaxies:
– non-group members,
with low densities on
1 and 5.5 Mpc scales
• ~30% of isolated
galaxies show
negligible SF
– environment must not
be only driver of
evolution.
Summary: SDSS & 2dFGRS
• SFH depends on environment and galaxy
luminosity (mass) in a separable way.
• Colour and Ha distributions suggest any
transformations must have a short timescale,
or have occurred preferentially in the past
– but how do you reconcile this with large fraction
of Virgo spirals with unusual Ha distributions?
hmmm…
Outline
1. Background
2. Low redshift: SDSS and 2dFGRS
3. Groups and clusters at z~0.5
4. GALFORM predictions
5. Conclusions
Evolution in clusters and
groups
•
Results from low redshift surveys suggests
we focus on two separate effects:
1. Evolution in the fraction of active galaxies
2. Evolution in the SFR distribution of those active
galaxies
Orientation: if environment drives evolution,
expect to see weaker evolution in clusters
and groups than in isolated galaxies…
Butcher-Oemler Effect
• Concentrated clusters at high redshift may have
Blue fraction
Blue fraction
more blue galaxies than concentrated clusters at low
redshift
• But blue fraction depends strongly on luminosity
and radius so care needs to be taken to evaluate blue
fraction at same luminosity limit, and within same
(appropriate) radius.
Margoniner et al. 2001
Andreon, Lobo & Iovino 2004
Redshift
• “Butcher-Oemler
effect” also seen in
the general field
Red galaxy fraction
Evolution of the red
sequence
High density
All galaxies
MV < -20
Low density
Redshift
(Bell et al 2004)
Cluster SFR evolution
Field
Nakata et al., MNRAS, submitted
Postman, Lubin & Oke 2001
van Dokkum et al. 2000
2dF
Clusters
Fisher et al. 1998
Czoske et al. 2001
• Based on sparsely-sampled [OII]
spectroscopy
• Suggests fraction of starforming galaxies evolves only
weakly in clusters
• Different from colour evolution?
Cluster SFR evolution
z~0.3
z~0.5
Field
Field
Tresse et al. 2002
Couch et al. 2001
Balogh et al. 2002
Fujita et al. 2003
Complete Ha studies:
Even at z=0.5, total SFR in clusters lower than in surrounding field
Kodama et al. 2004
Cluster SFR evolution
Finn
Finn et
et al.
al. 2003
2003
• Complete Ha based SFR
estimates
• Evolution in total SFR per
cluster not well constrained
• considerable scatter of
unknown origin
• systematic uncertainties in mass
estimates make scaling
uncertain
Kodama et al. 2004
Cluster SFR evolution
Finn et al. 2003
• Complete Ha based SFR
estimates
• Evolution in total SFR per
cluster not well constrained
• considerable scatter of
unknown origin
• systematic uncertainties in mass
estimates make scaling
uncertain
Kodama et al. 2004
Finn et al. in prep
Evolution in groups
z~0.05: 2dFGRS (Eke et al. 2004)
– Based on friends-of-friends linking algorithm
– calibrated with simulations. Reproduces mean
characteristics (e.g. velocity dispersion) of parent
dark matter haloes
z~0.45: CNOC2 (Carlberg et al. 2001)
– selected from redshift survey, 0.3<z<0.55
– Cycle 12 HST imaging + deeper spectroscopy
with LDSS2-Magellan
Fraction of non-SF galaxies
Group comparison
• Use [OII] equivalent width to
find fraction of galaxies
without significant star
formation
• most galaxies in groups at
z~0.4 have significant star
formation – in contrast with
local groups
Wilman et al. in 2004
Group SFR evolution
Groups
Fraction of non-SF galaxies
• Fraction of non-SF galaxies
increases with redshift
• for both groups and field
Fraction of non-SF galaxies
Field
Wilman et al. 2004
Group SFR evolution
• shape of [OII]
distribution evolves with
redshift but does not
depend on environment
• Result sensitive to
aperture effects
Wilman et al. 2004
Outline
1. Background
2. Low redshift: SDSS and 2dFGRS
3. Groups and clusters at z~0.5
4. GALFORM predictions
5. Conclusions
WIP: GALFORM model
• GALFORM is Durham model of galaxy formation (Cole et
al. 2000)
– parameters fixed to reproduce global properties of galaxies at z=0
(e.g. luminosity function) and abundance of SCUBA galaxies at high
redshift
• Use mock catalogues of 2dFGRS which include all selection
biasses
• Predict Ha from Lyman continuum photons, choose dust
model to match observed Ha distribution. This is the
weak point at the moment.
• Assume hot gas is stripped from galaxies when they merge
with larger halo (i.e. groups and clusters) which leads to
strangulation of SFR (gradual decline)
GALFORM predictions
•
•
•
Fraction of SF galaxies declines with
increasing density as in data
Similar results found by Diaferio et al.
(2001; z=0.3 CNOC clusters) and
Okamoto et al. (2003; morphologydensity relation)
Normalisation depends on SFR-Ha
transformation, but trend is robust
GALFORM predictions
• Over most of the density range,
correlation between stellar mass
and SFR fraction is invariant
 Therefore
SFR-density
correlation is due to massdensity correlation
• At highest densities, models
predict fewer SF galaxies at
fixed mass due to strangulation
• Trend with mass driven by
selection effects which make
analysis difficult
GALFORM predictions
1.
2.
Fraction of SF galaxies declines with increasing density as in data
At low densities, Ha distribution independent of environment
GALFORM predictions
1.
2.
Fraction of SF galaxies declines with increasing density as in data
At low densities, Ha distribution independent of environment
GALFORM predictions
1.
2.
3.
Fraction of SF galaxies declines with increasing density as in data
At low densities, Ha distribution independent of environment
In densest environments, Ha distribution skewed toward low values
* This is sensitive to SFR-Ha transformation however
Conclusions
• On average, galaxies in groups have less star formation than
field galaxies
• Presence of non-star forming galaxies in the lowest densities
means environment cannot be the only driver of galaxy
evolution
• Galaxy interactions and mergers:
–
–
–
–
Build larger bulges in dense environments
Consume available gas in rapid starburst
Present in all environments, but more so at higher densities
Establish red sequence in clusters at early times
• Strangulation, ram-pressure add additional suppression in
dense regions at late times