1. The 1 st galaxies and the cosmic web: the clustering of galaxy hosts from dark matter simulations Darren Reed Los Alamos National Laboratory arxiv:0804.0004 Katrin Heitmann (LANL) Salman Habib (LANL) Zarija Lukic (Illinois) Richard Bower (ICC-Durham) Carlos Frenk (ICC-Durham) Adrian Jenkins (ICC-Durham) Tom Theuns (ICC-Durham) (see astro-ph/0607150) soccorro, 2008

2. Overview High redshift dark matter simulations – capture entire luminous mass range mini-halos “1 st stars” (T vir > ~2000K) “galaxy halos” (T vir > 10 4 K) We found how many halos (universal mass function)……… now need to know where are the halos? Clustering background and its importance Halo clustering results Conclusions

3. The dark ages……. L. Hernquist ionized, z > 1100 (CMB) reionized, z 6 neutral --> 21cm Spitzer Subaru LOFAR,SKA...

4. star formation in metal free gas T vir >10 4 K: Atomic cooling Efficient T vir >~ 2000K: H 2 line cooling Inefficient Mhalo ≥ ~10 8 Msun Mhalo ≥ ~10 5.5 Msun H+e -  H - +hυ H - +H  H 2 +e- mini-halo ~10-1000 M sun ? cools lots of stars? 1 st galaxies?

5. high z (reionizing era) halo clustering -JWST (or sooner) to measure z >~ 6 clustering --galaxies form within halos -galaxy clustering at high redshift --sensitive to cosmology (e.g. σ 8, D.M. type) --sensitive to galaxy formation physics (e.g. SNe)  probe cosmology and galaxy form. physics

6. Simulation Techniques Cosmological parameters: (  =0.25,  =0.75,  8 =0.9, H 0 =73, n s =1)  8 : amplitude of power spectrum, (rms mass fluctuation of 8 Mpc/h spheres) + Hi-z SNe, 2df, etc. NASA/WMAP High-z (linear) gaussian random realization Evolve particles (gravity) L-GADGET2 (PM-tree code V. Springel)

7. z=10 12 Mpc/h

8. z=10

9. What is a halo? friends-of-friends ~iso-density link length ~ 0.2 lmean -->~“universal” halo mass function, f( σ mass (m)) Lukic et al. 2008 z=0

10. Is f(σ) redshift invariant? “almost” f sim /f(σ) f sim /f(σ,n eff ) (z dependent) n eff ≡slope of P(k) at scale of halo P(k) α k neff Reed et al. 2007

11. highly clustered, “biased” weakly clustered bias(r)=(ξ halos (r)/ξ mass (r)) 1/2 ξ (r) = N pair /N pair_random -1

12. halo bias auto-correlation function of “galaxy” halos mass b =(ξ halos /ξ mass ) 1/2 halos mass

13. Scale-dependence of halo bias z=10 Sheth, Mo & Tormen large scale prediction (b SMT ) Small scales strongly biased “non-universal” vs lo-z sims M vir >10 1 0 our fit lo-z sim fit by Diaferio et al. (2003)

14. Scale-dependence of halo bias z=10 Sheth, Mo & Tormen large scale prediction (b SMT ) Small scales strongly biased “non-universal” vs lo-z sims b(r) =f( σ mass (r)) M vir >10 1 0 our fit lo-z sim fit by Diaferio et al. (2003)

15. z=10 12 Mpc/h

16. z=3

17. z=1

18. z=0

19. z=10

20. z=3

21. z=1

22. z=0

23. z=0 galaxiesz=10 galaxies Why is the scale dependence of halo bias so steep during the dark ages?

24. Universality of large-scale bias “universal” mass variable,, MW=predictions of Mo & White (1996) SMT=Sheth, Mo & Tormen (2001) Millennium run data from Gao et al. (2005).

25. mass halos Finite-box effects on velocities. Pairwise velocity dispersion along the line of separation

26. Conclusions Clustering measured in dark matter simulations  halos of 1 st “galaxies” and 1 st stars Spatial clustering  steep scale dependence, “non-universal”  Large-scale “universal” & consistent with analytic predictions Impending Observational uses:  cosmological probe on small scales, e.g. σ 8, DM type  physics of galaxy formation, local feedback effects, how galaxies populate halos