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.
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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 bluered 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 2003 Finn et et al. 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 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