MOS Scientific Applications Michael Balogh University of Durham

MOS Scientific Applications (mostly galaxy clusters) Michael Balogh University of Durham

Outline 1.Galaxy Clusters: scientific motivation 2.Canadian Network for Observational Cosmology (CNOC) 3.More clusters and groups with MOS 4.Ultra-plex spectroscopy: H  spectroscopy of 4 clusters at z~0.4 5.Future considerations

Why Clusters?

Why clusters? 1.Very rare objects, in the tail of the mass distribution. So very sensitive to cosmology 2.Largest structures just virialising today, so we can study the process of structure formation 3.Extreme environments can affect galaxy properties

University of Durham Institute for Computational Cosmology 150 Mpc/h dalla Vechia, Jenkins & Frenk

Tying star formation to structure growth Groups Clusters

Renormalised relative to M ☼ A Press-Schechter plot showing the growth of the mass structure of the universe LCDM cosmology Rapid growth of structure Groups Clusters

Steidel et al Why Does Star Formation Stop? Cluster environments inhibit star formation (Balogh et al. 1997; 1998) Can the growth in the abundance of clusters explain the global decline of star formation? Or is it related to internal galaxy properties?

Why MOS? Clusters are ideal targets for MOS because: 1. high density of galaxies 2. close in velocity space, so can use narrow wavelength range to increase multiplex 3. Learn about cluster dynamics and galaxy properties from the same set of spectra

CNOC: Cluster masses

CNOC: Goals Sample: 15 X-ray luminous clusters from EMSS, 0.2<z<0.55 Goal to obtain member redshifts per cluster, for a total of ~1500 (r~22) Observations over large fields (~0.5 degree) to sample virialised region Carlberg, Yee, Ellingson 1996 ApJS 102, 269

CNOC: Survey Strategy MOS on CFHT 1.4 band-limiting filters to sample rest-frame ~3500Å – 4300 Å, at 4 redshift slices 2.Obtain ~30 spectra per 9′ field of view; 2-3 masks per field, 1-5 fields per cluster 3.Real-time operations: Imaging, mask design, mask cutting, and spectroscopy all done at the telescope Carlberg, Yee, Ellingson 1996 ApJS 102, 269

CNOC: Survey Strategy Carlberg, Yee, Ellingson 1996 ApJS 102, 269

CNOC: Results 1.Dynamical measurement of  m 2.Mass profiles of clusters 3.Cluster galaxy properties

Dynamical measurement of  m 1.From velocity and spatial distribution, determine cluster mass M and virial radius, R 2.Calculate mass-to-light ratio M/L Carlberg et al ApJ 462, 32

Dynamical measurement of  m 1.Assume average galaxy M/L is the same in clusters and in the field 2.Use the field sample from same survey to measure (M/L) crit =  crit /j, where j is the luminosity density of the Universe 3.This calculation yields  m ~0.3; the most convincing evidence for low  m at the time. Carlberg et al ApJ 462, 32

CNOC: Average mass profiles Carlberg et al ApJ 478, 462 Carlberg et al ApJ 485, L13 Dynamically determined average mass profile of the most massive clusters In good agreement with predictions from simulations (Navarro, Frenk & White 1996)

CNOC: Galaxy populations Balogh et al. 1997, ApJ 488, L75 Measurements of [OII] emission line for galaxies in clusters and the surrounding field at z~0.3 [OII] closely related to star formation rate (SFR) Showed that average SFR within the virialised regions of clusters is much lower than in lower density regions

CNOC: Galaxy populations Balogh et al. 1998, ApJ 504, L75 Showed presence of strong radial gradient in SFR. Always lower than the field Gradient much steeper than expected from morphology-density relation Observed relation Morph-density relation Field

CNOC: Galaxy populations Balogh, Navarro & Morris 2000 Use numerical model of infall to estimate timescale for disruption of SFR Radial gradients in CNOC clusters suggest  ~2 Gyr

CNOC: Remaining Questions 1.Are X-ray luminous clusters unusual? 2.Dust-obscured starburts? Is [OII] a good enough SFR indicator? Are data complete enough to rule out a small fraction of intense, cluster-induced starbursts? 3.How far does the cluster’s influence extend? 4.Is star formation sensitive to local effects (i.e. density) or global ones (i.e. clusters vs. groups)

1. Low L x Clusters

Low L x Clusters at z~0.25 Cl0818 z=0.27  =630 Cl0819 z=0.23  =340 Cl0841 z=0.24  =390 Cl0849 z=0.23  =750 Cl1309 z=0.29  =640 Cl1444 z=0.29  =500 Cl1701 z=0.24  =590 Cl1702 z=0.22  =370 L x ~ ergs/s, ~ 10 X less massive than CNOC

Low L x Clusters at z~0.25 Multiobject spectroscopy with MOSCA (Calar Alto) and LDSS2 (WHT) No band-limiting filter, to allow measurement of H  in some cases

Star Formation in Low-Lx Clusters Balogh et al Spectroscopy for 172 cluster members M r < -19 (h=1) SFR from [OII] emission line Identical to more massive clusters Balogh, et al. 2002, MNRAS 337, 256

2. Dust-obscured starbursts?

 Dec  RA AC114 (z=0.31) Butcher-Oemler effect? Does star formation take place in clusters at z>0 ? Couch et al. 2001, ApJ 549, 820

Nod & Shuffle: LDSS++ (AAT) Band-limiting filter + microslit = ~800 galaxies per 7’ field

Nod & Shuffle: LDSS++ (AAT) Advantages: 1. Perfect sky subtraction. Allows observation of H  at z=0.31 (8600 Å) 2. Short slits = maximum multiplex 3. Trivial data reduction Disadvantages: 1. Lose 2/3 of detector, unless you use an oversized CCD 2. Need √2 more exposure time, unless you nod along the slit

H  in Rich Clusters at z~0.3 Couch et al ApJ 549, 820 Balogh et al MNRAS, 335, 110 LDSS++ with nod and shuffle sky subtraction, on AAT No evidence for enhanced star formation (Field)

3. Cluster sphere of influence

Cluster sphere of influence Fibre based wide field surveys: 1.2dF galaxy redshift survey H  in galaxies within 20 Mpc of 17 clusters, down to M B =-19 (Lewis et al. 2002, MNRAS 334, 673) 2.Sloan digital sky survey Volume-limited sample of 8600 galaxies from the EDR, M R <-20.5 (Gomez et al. 2003, ApJ 584, 210)

SFR-Environment Relation in the 2dFGRS Lewis et al MNRAS 334, 673

4. Galaxy Groups

The CNOC2 Field survey 1.Similar strategy to cluster survey, using MOS on CFHT to study field galaxies out to z~0.6 Yee et al. (2000) ApJS 129, Main goal to measure evolution of correlation function and star formation rates Carlberg et al. (2000) ApJ 542, 57 Lin et al. (1999) ApJ 518, 533

CNOC2 Groups 1.Identified a sample of groups from original survey (Carlberg et al ApJ 552, 427) 2.Properties of these groups can be directly compared with low redshift counterparts from 2dFgrs and SDSS 3.Durham involvement: follow-up observations with Magellan to gain higher completeness confirming complete samples of group members using LDSS-2

CNOC2 Groups at z~0.45 LDSS2 on Magellan

CNOC2 Groups at z~0.45 Combined with CNOC2 multicolour photometry and spectroscopy, we can determine group structure, dynamics, stellar mass, and star formation history

CNOC2 Groups at z~0.45 Deep spectroscopy with LDSS-2 on Magellan 1 Infrared (Ks) images from INGRID Combined with CNOC2 multicolour photometry and spectroscopy, we can determine group structure, dynamics, stellar mass, and star formation history.

CNOC2 Groups at z=0.45 [OII]

CNOC2 Groups at z~0.45 [OII]

CNOC2 Groups at z~0.45 Preliminary results based on only 12 CNOC2 groups Have observed >30 groups to date Balogh et al. 1997

The Future: Clusters at z>1

Groups at z > 1 1.Deep multicolour (VRi′z′JK s ) images of Lynx and Q (z=1.2). 2.Proposals to observe high redshift radio galaxies and radio-loud quasars: known to reside in dense environments IRIS2 narrow band H  and [OIII] at z=2.3 GMOS/FORS2 narrow band filter + grism H  and [OII] spectroscopy at z=1.4, 1.47, 2.3

Lynx clusters: z=1.2 Subaru VRi’z’ INGRID JK s Identified 7 groups around the clusters from photometric redshifts. GMOS spectroscopy pending X (arcmin) Y (arcmin) Nakata et al. (2002)

Overdensities around HizRG Best et al z=1.59z=1.44

Conclusions 1. Clusters and groups have a large impact on galaxy star formation rates at the present day 2. Need to understand how cluster populations evolve to disentangle internal and external effects 3. MOS at high redshift essential. Nod-and-shuffle required to work at red wavelengths, but need full field of view.