Simulating the SZ Sky Predictions for Upcoming Sunyaev-Zel’dovich Effect Galaxy Cluster Surveys Eric J. Hallman CASA, University of Colorado 16 February, 2007 Clusters of Galaxies as Cosmological Probes Conference Aspen, CO

Collaborators Brian O’Shea (LANL) Jack Burns (University of Colorado) Mike Norman (UCSD) Rick Wagner (UCSD) Robert Harkness (SDSC)

SZ Surveys of Galaxy Clusters Survey yield depends on cosmology AND gas physics AND details of dynamical states of clusters How does observable scale with mass? What is the selection function in mass for cluster surveys? Also depends on instrument properties, survey strategy, confusion, etc.

ΛCDM  m =0.3,   =0.7,  8 =0.9 AMR gives high resolution (8 h -1 kpc) in dense regions 512 h -1 Mpc on a side, use 7 levels of refinement root grid, 7 levels everywhere DM mass = 7.3x10 10 M solar, baryon mass = 1.1x10 10 Initial run is adiabatic physics only Adaptive Mesh Refinement (AMR) Light Cone Simulations (N-body + Hydro) Enzo (O’Shea et al. 2005,

How do we make simulated surveys? Surveys sample the universe at all observable epochs, so…. Stack simulations at different evolutionary states in discrete redshift intervals to approximate Each  z uses physical extent of box in line of sight which matches that redshift interval Modify angular scale of image to fixed angular size for all redshifts, flux diminishes (but not in SZE!) Random shifting, rotating, some tiling Model telescope response, background, foreground contamination, point sources, etc etc (Future work)

Sky Surveys X-ray and SZE synthetic surveys Clusters above 1x10 14 M solar in field out to z=3 2048x2048, 10x10 degrees, 17.6” / pixel

Why do we have N-body + hydro? In real universe, clusters are neither isothermal nor in equilibrium generally (e.g. M. Voit’s talk) Variations in cluster physics make a difference (Evrard’s and Rudd’s talks) In order to characterize scatter, survey selection (in mass) from simulations, must include baryons!

Cold FrontsFilamentsBullet Subcluster 1E Abell 1795 Abell 2256 (Sun et al 2002)(Fabian et al 2001)(Markevitch et al 2002) Clusters are NOT generally in equilibrium (dynamical, hydrostatic or otherwise)

Merger Boosting See also C. Sarazin’s talk

Identification of Sources

Hallman et al Identification with SExtractor Upcoming Surveys: SPT: 1.0’, ~4000deg^2, 10  K APEX-SZ: 1.0’, ?deg^2, 10  K ACT: 1.7’, deg^2,2  K Planck, 5.0’, all-sky, 2.2  K 90% limits for 200 stacking realizations of the survey APEX: ACT: Planck:

What else should be included? What we get: full array of dynamical states large volume gaussian background What we’re missing (so far) ref. N. Sehgal atmosphere point sources additional physics other instrumental effects We are working on all of these!

Halos in the Simulation Identify via HOP algorithm clusters at z=0 in simulation box above M = 5x10 13 M solar Identify their locations in the 2d projection of the simulated survey Match to locations of halos provided by SExtractor

Hallman et al. 2007

Recall L. Verde’s talk

Stacking Caveats Stacking with a single simulation has problems Constant physical resolution (as f(z)) on the grid does not equal constant angular resolution on the sky Large scale correlations can be generated How can we solve that? Use multiple simulations!

The Big One(s) We are generating a complete, unique numerical simulation for each  z Each simulation has a physical size specified by it’s angular extent at that redshift (ITC 10 degrees square). Allows lower computational effort for the most nearby volumes, since their physical resolution must be highest. Eliminates stacking issues (almost). 2 cubic Gpc of total simulated volume

Plans for Huge LCs From smaller set of simulations, refine baryonic physics (cooling, star formation, SN feedback, AGN feedback, conduction, etc.) Vary cosmology (e.g., w,  8 ), determine precision necessary to distinguish Synthetic Observations (X-ray/SZE primarily) including both instrumental effects, backgrounds/foregrounds, etc.

Summary Survey yields depend on luminosity function, which depends on cosmology AND detailed baryonic physics AND dynamical states AND confusion, etc. If you want high precision, non-trivial problems in counting clusters Numerical N-body + hydro (!) simulations coupled with realistic synthetic observations allow us to understand systematics, get the “right” answer!

Sample Stacking Solution

Synthetic Observations

Constraints from Clusters, Dark Energy Equation of State Haiman et al 2001

Results from Adiabatic Physics Model (Projected Emission-Weighted Temperature) 5 Mpc