2. Benedetta Ciardi MPA

3. Reionization Nucleosynthesis ‘Dark Ages’ Big Bang Fluctuations begin to condense into first stars and protogalaxies Decoupling matter-radiation CMB fluctuations

4. In an ideal world we would have… Reliable simulations of + Radiative transfer galaxy formation calculations Large volume: ~ 50/h Mpc com. High resolution: ~ Correct treatment of SF and feedback effects Accurate Fast Couple simulations and radiative transfer, including the effect of the transfer on the galaxy formation and evolution process to avoid cosmic variance… to resolve objects that produce the bulk of ionizing photons… to correctly account for small mass objetcs

5. In the real world we have…

6. Simulations of galaxy formation Still don’t have enough resolution No complete treatment of feedback effects on formation of small-mass objects ?

7. Radiative transfer Point sources Diffuse radiation (Background radiation)

8. Accurate Poor angular resolution Dependent on number of sources slower Radiative transfer Monte Carlo – Ray tracing Local Optical Depth Approx. Optically Thin Variable Eddington Tensor Fast & independent on # of sources Shadowing is not well reproduced Problems with multiple sources Fast & independent on # of sources It fails in the ~ 1 range It is correct only “on average”

9. better! Summary of reionization simulations  Ciardi et al. N-body+ 20 100 Monte Carlo post-process SAM  Gnedin et al. hydro 4 0.1 LOD approx coupled  Razoumov et al. hydro 7 100 ray-tracing post-process  Ricotti et al. hydro 1 0.05 OTVET coupled  Sokasian et al. hydro 10 10 ray-tracing post-process Group Simul. L M Rad.Trans. Coupling N-body + SAM  hydrodynamics More flexibility of SAMs if different models are analyzed Small box/masses  Large box/masses Small: Very early stages of reionization  M~Jeans mass Study of feedback effect on formation of small-mass objs Contribution of small-mass objects to reionization Large: Global reionization process, down to z~6 Estimates for observability (e.g. 21cm line emission…) Monte Carlo/Ray tracing  LOD/OTVET Monte Carlo/Ray tracing: Solve exact radiative transfer Poor angular resolution Slower LOD/OTVET: Faster Approximations fail in certain regimes

10. Source type & emission properties Source type: Stars QSOs Decaying exotic particles … Stellar emission properties: Metal-free/enriched IMF Z Z=0 More ionizing photons ?

11. Simulations of galaxy formation  CDM N-body simulation  DM+gas distribution (Yoshida, Sheth & Diaferio 2001; Stoehr 2004) Semi-analytical model for galaxy formation  galaxy SFR... (Kauffmann et al. 1999; Springel et al. 2000) 20/h Mpc com. Salpeter IMF Metal-free stars Fesc=5% We don’t have the resolution to model the escape fraction ?

12. CRASH Follow the propagation of photon packets and solve the time-dependent ionization equation Input Cosmological RAdiative transfer Scheme for Hydrodynamic Ip. Discretized radiation field Involved processes treated statistically (BC, Ferrara, Marri & Raimondo 2001; Maselli, Ferrara & BC 2003) 128

13. (BC, Stoehr & White 2003) Redshift Evolution (Springel et al. 2000) ‘Proto-Cluster’ 15 Mpc ‘Field ’ 30 Mpc z=16.5 z=12 z=8.5 H0 number density Environment is important!

14. S5: Salpeter IMF+fesc=5% S20: Salpeter IMF+fesc=20% L20: Larson IMF+fesc=20% Early/Late Reionization We don’t need exotic assumptions!!! (BC, Ferrara & White 2003) 68% CL (Kogut et al. 2003)

15. Conclusions Thanks to: N. Gnedin, A. Razoumov, M. Ricotti, T. Abel Theory/simulations are not YET behind observations Higher resolution Better treatment of SF and feedback effects Deeper understanding of sources of reionization & escape fraction Need to compare radiative transfer codes on common tests (TSU3) Use results of small boxes with exact radiative transfer as guideline for big boxes with approximate radiative transfer Volume averaged ionization fraction CRASHCoralRazoumov