1. FIRST LIGHT IN THE UNIVERSE Richard Ellis, Caltech 1.Role of Observations in Cosmology & Galaxy Formation 2.Galaxies & the Hubble Sequence 3.Cosmic Star Formation Histories 4.Stellar Mass Assembly 5.Witnessing the End of Cosmic Reionization 6.Into the Dark Ages: Lyman Drop-outs 7.Gravitational Lensing & Lyman Alpha Emitters 8.Cosmic Infrared Background 9.Future Observational Prospects Saas-Fee, April 2006

2. “..describes a true order among the galaxies, not one imposed by the classifier” (Sandage et al 1994) Distinguishes dynamically distinct structures: spirals & S0s – rotating stellar disks spheroids – ellipsoidal/triaxial systems with anisotropic dispersions There exist physical variables that govern the sequence: * gas content/integrated color  ratio of current to past average star formation rate * inner structures  bulge/disk ratio Hubble’s Morphological Sequence

3. Changing Paradigms of Galaxy Formation Classical (1963-1985): galaxies evolve in isolation present-day properties governed by SF history ellipticals: prompt conversion of gas  stars spirals: gradual consumption of gas, continuous SF Dark matter-based (1985-): g. instability governs merging of DM halos low mass halos collapse first (bottom up formation) mergers transform morphologies (ellipticals form late) dense environments evolve faster (clusters older than field) Importance of feedback (1995-) evolution of morphology-density relation  environment assembly history as a function of mass  downsizing

4. Colors & Star Formation Histories: Classical View Ellipticals and bulges – old stellar systems following an initial burst of formation; modest ‘monolithic’ collapse Spiral disks – significant dissipation during collapse, continuous star formation and younger mean stellar age E Sbc Scd Irr U-V V-K Tinsley & Danly Ap J 242, 435 1980

5. Hierarchical Assembly DM fractionates prior to recombination (halos) which grow whilst baryons locked to radiation After recombination gas cools into halos which continue to merge hierarchically `Morphology’ is directly linked to mergers: disks form first and those that merge form ellipticals Baugh et al MNRAS 283, 1361 (1996)

6. Morphological Evolution: HST z = 0z > 1

7. Numerical simulations suggest product of equal mass encounter may resemble spheroidal Toomre, A 1977 Yale Conference `Evolution of Galaxies’ ed. Tinsley & Larson Barnes & Hernquist 1996 Ap J 471, 115  Mass ratio used as the basis of defining morphological transformations in semi- analytic models Mergers are a key feature

8. Tell-tale Signs of Mergers in Local Ellipticals Orbital shells SAURON lenslet array Davies et al 2001 Ap J Lett 548,33 (2001)

9. The Development of DM Structure The ability to follow the distribution of dark matter in simulations is fairly well advanced. The same cannot be said of our understanding of how galaxies that we can detect are “painted on” to the large scale matter distribution. 100 Mpc

10. Galaxy Formation in Cold Dark Matter Models Semi-analytical models: Numerical recipe for introducing baryons into DM n-body simulations and predicting observations using prescriptive methods for star formation & morphological assembly Classic papers: Kauffmann et al 1993 MNRAS 264, 201 Somerville & Primack 1999 MNRAS 310, 1087 Cole et al 2000 MNRAS 319, 168

11. Semi-analytic prescription for galaxy formation in CDM models Key issues: rate of cooling of baryons into DM halos, feedback from hot stars, supernovae and AGN

12. Semi-analytic models (VIRGO) Galaxies are color-coded according to the epoch of their collapse: red = oldest blue = youngest Galaxies in the most strongly clustered regions formed first.

13. Implications of Hierarchical Growth  galaxy formation and evolution is accelerated in dense regions

14. Morphological Transformations: Nature vs Nurture Dressler Ap J 236, 351 (1980) Proportion of spheroidals is a strong function of projected galaxian density Either: spheroidals formed naturally in high density systems at early times, Or: spheroidals are the results of environmentally- induced activity These hypotheses can be distinguished using high redshift data

15. Coma z  0 AC118 z=0.31 Evolution in Cluster Galaxy Morphologies The `Morphs’: Dressler, Ellis, Smail, Oemler et al

16. Environmental density  plays key role in governing morphological mix: - Morphology-density relation was already in place at z~1 - Continued growth of E/S0s in high  environs since then - Hypothesis: conversion of spirals to S0s with only Es at z > 1? Smith et al Ap J 620, 78 (2005) f E/S0 Evolution of Morphology Density Relation

17. Galaxy Luminosity Function The field galaxy luminosity function is defined:  (L) h -3 Mpc -3 Schechter’s function (differential form):  (L) dL/L* =  * (L/L*) -  exp (-L/L*) dL/L* where  * is the normalisation,  is a faint end slope and L* is a characteristic luminosity Total galaxy density N TOT =   (L) dL =  * Γ(α +1) Luminosity density ρ L =   (L) L dL =  * L* Γ(α +2) ( N TOT diverges if α < -1 whereas ρ L diverges only if α <-2) log  (L) Mpc -3 log L  exponential decline power law faint end  L* **

18.  2 fit to 1/Vmax LF 2dF Galaxy Luminosity Function - Practicalities STY Schechter fit gives  -1.2 (due to clustering? non- Schechter form?) (mean K- corrections) Observed numbers  Luminosity Derived LF

19. Is the Schechter function universal? Paul Schechter

20. Final 2dF Luminosity Function: NGP vs SGP Schechter function is a good, but not perfect, fit

21. LF comparisons 2dF versus SDSS - good agreement

22. Semi-Analytic Models to the Test -  - !! Bower et al astro-ph/0511338 2dFGRS Too many bright blue galaxies Too many faint red galaxies Millenium Simulation: SF is too active in massive local systems CDM  B-V log stellar mass Bimodal color distribution coded by halo mass Field Galaxy Luminosity Function

23. Feedback and Galaxy Formation The failure of simple semi-analytical models to reproduce the color and luminosity distribution of galaxies has led to consideration of `feedback’ - several proposed processes that could regulate star formation and mass assembly: reionization feedback: radiative heating increases the Jeans mass (which governs collapse) inhibiting early formation of low mass systems supernova feedback: can reheat the interstellar medium, heat the halo gas yet to form stars, or even eject gas from low mass systems AGN feedback: various modes postulated which transport energy from active nucleus into halo gas (heating or ejecting it) First implementation of these feedback modes discussed by: Benson et al (2003) Ap J 599, 38 Croton et al (2006) MNRAS 365, 11 De Lucia et al (2006) MNRAS 366, 499

24. BlueInfrared

28. Importance of High z Data Our understanding of the local population of galaxies is largely confined to its spatial distribution and (perhaps) some environmental trends in the broadest sense Standard model needs major `additional ingredients’ to reconcile local color and luminosity distributions: such effects have major implications for assembly and SF histories Now introduce three key 1 < z < 4 galaxy populations whose studies are relevant to addressing these issues I: Lyman break galaxies: color-selected luminous star forming galaxies z > 2 II: Sub-mm galaxies located via redshifted dust emission III: Various categories of passively-evolving sources whose selection has been enabled via deep IR data

29. Finding star-forming galaxies at high z The Lyman continuum discontinuity is particularly powerful for isolating star- forming high redshift galaxies. From the ground, we have access to the redshift range z=2.5-6 in the 0.3-1 micron range. Steidel et al 1999 Ap J 462, L17 Steidel et al 1999 Ap J 519, 1 Steidel et al 2003 Ap J 592 728

30. Photometric Cuts: Prediction and Practice Expectations Real Data (10’ field) Spectral energy distributions allow us to predict where distant SF galaxies lie in color-color diagrams such as (U-G vs G-R) (Steidel et al 1996)

31. Spectroscopic Confirmation at Keck

32. HST images of spectroscopically -confirmed “Lyman break” galaxies with z>2 in Hubble Deep Field North revealing small physical scale- lengths and irregular morphologies Giavalisco et al 1996 Ap J 470, 189

33. Extending the Technique 1 < z < 4 Lyman break Balmer break

34. Sub-mm Star Forming Sources SCUBA array15m JCMT SCUBA: 850  m array detects dusty star forming sources: - behind lensing clusters (Smail et al Ap J 490, L5, 1997) - in blind surveys (Hughes et al Nature 394, 211, 1998) Source density implies 3 dex excess over no evolution model based on density of local IRAS sources: Key question is what is the typical redshift, luminosity and SF rate? Sub-mm astronomers

35. Negative k-correction for sub-mm sources Blain et al (2002) Phys. Rept, 369,111 K-correction is the dimming due to the (1+z) shifting of the wavelength band (and its width) for a filter with response S( ) In the Rayleigh-Jeans tail of the dust blackbody spectrum, galaxies get brighter as they are redshifted to greater distance!

36. Radio Identification of Sub-mm Sources SCUBA sources often have no clear optical counterpart, so search with VLA & OVRO L ~ 10 13 L  if z~2 Could be as important as the UV Lyman break population Frayer et al (2000) AJ 120, 1668

37. Redshifts for radio-selected SCUBA sources VLA positions for 70% of f(850  m) > 5 mJy (20% b/g) Slits placed on radio positions (22 < I < 26.5) with Keck 10-fold increase in number of SCUBA redshifts (LRIS-B) Chapman et al (2003) Nature 422, 695 Chapman et al (2005) Ap J 622, 722

38. 50% completeness with LRIS-B and radio selection limits Radio-selected sub-mm sources  20% of background Most sub-mm sources have z < 4 Peak z = 2.4 – comparable to that for AGN Although  (LBG)  10  (SCUBA), luminosity/SF densities comparable Sub-mm and Lyman break galaxies coeval 2003 2005

39. Passively-Evolving Sources for z ~ 1-2: select on I-H colour for z > 2: select on J-K colour Such objects would not be seen in the Lyman break samples LBGs and sub-mm are both star forming sources Arrival of panoramic IR cameras opens possibility of locating non-SF (or dusty) galaxies at high z Termed variously: Extremely Red Objects Distant Red Galaxies depending on selection criterion.

40. FIRES – VLT+ISAAC 176 hours J,H,K imaging MS1054-03 N. Forster-Schreiber et al. 5.4’ x 5.4’, seeing 0’’45 HDF South I. Labbe et al. 2.4’ x 2.4’, seeing 0’’45

41. Objects with J-K > 2.3 Surprisingly high surface density: –~0.8/arcmin to K=21 (two fields) –~2/arcmin to K=22 (HDF-S) –~3/arcmin to K=23 (HDF-S) 2 2 van Dokkum,Franx, Rix et al

42. Z=2.43 Z=2.71 Z=3.52 Keck I: Spectroscopy (van Dokkum et al)

43. Summary of Lecture #2 Galaxy formation is a complex process involving gravitational instability, star formation, dynamical interactions/mergers, environmental processes and various forms of feedback Good progress is being made in semi-analytic modeling associated with numerical (DM-only) simulations. However, observations will always be needed to `tune’ the various theoretical ingredients - ab initio modeling is not practical. High redshift data is of unique value in testing the overall picture as it gives us the direct history of galaxy star formation and mass assembly (Lectures 3 & 4) Excellent observational progress has been made in locating diverse galaxy populations to z~3 and beyond; building the overall `jigsaw’ of galaxy evolution from each of these different populations is the challenge (Lecture 3)