INFRARED-BRIGHT GALAXIES IN THE MILLENNIUM SIMULATION AND CMB CONTAMINATION DANIEL CHRIS OPOLOT DR. CATHERINE CRESS UWC

Aims and objectives To use supercomputer simulations to model the distribution of infrared (IR) emitting galaxies using the correlation between star-formation rate and IR luminosity Apply the result to high resolution surveys (Atacama Cosmology Telescope) to correct for contamination by IR sources on CMB observations:  SZ cluster surveys

Infrared-bright galaxies Contain a lot of dust Star forming galaxies Optical photons from young stars are absorbed by dust, reradiated at longer wavelength (IR) IR wavelength is btn μm, far-IR btn μm Up to 90% of radiation from star forming galaxies is far-IR Optical, 24 micrometers, and a multi- wavelength, 24 (blue), 70 (green), and 160 (red) microns images of Andromeda galaxy (M31).

Cosmic microwave background (CMB) & science from clusters The CMB has been travelling toward us for over 10 billion years. Looking out in the sky, we are looking back in time; observing the CMB the way it was at the time of last scattering. The growth of high-mass clusters from initial Gaussian fluctuations depends strongly on the cosmological Parameters. Bahcall and Fan, 1998, PNAS, 95

ACT SZ cluster survey Map 300 square degrees of the microwave sky 3 frequency bands (145 GHz, 220 GHz, 265 GHz) Arcminute angular resolution Cosmological signal to be detected;  Primary Microwave Background Fluctuations  Gravitational Lensing  Thermal & kinetic Sunyaev- Zel’dovich Effect Inverse Compton Scattering; Hot cluster electrons boost energy of CMB photons Thermal SZ effect Steen H. Hansen, Zuric April 2005

SZ cluster survey Thermal SZ Effect redshift independent,  proportional to n e T (cluster mass), probes cluster pressure We observe signals from clusters of a given mass & redshift bin Where And Number of clusters for a commoving volume element dV/(dzdΩ) for a solid angle dΩ on sky Number density of objects between M and M+dM at z. This is what we compute for in the simulation box (millennium simulation).

SZ cluster survey The main foreground contaminants at these frequencies are the infrared (far-infrared; dusty) point sources. Galaxies in rich clusters have low sfr – low IR fluxes/Lum We compute the total contribution to IR of dusty galaxies within the clusters, and the potential of the whole cluster being a contaminant. The flux limits are typically, At about 220 GHz At 350 GHz

SZ contaminants The aim here is to model clusters with mass, M>M cut (min. mass of a cluster that can be detected by the survey)=2x10 14 Msun, within the survey redshift range, that are capable of contributing to the SZ signal. Methodology;  Total the sfr  Compute the bolometric IR Lum  Compute the monochromatic (350 GHz in this case) Lum using the SED templates  Compute the corresponding fluxes (redshift is known-luminosity dist.)  Use the flux cuts to sort out the contaminants  Construct the number density of the contaminants  Model with redshift and subtract their effect/contribution

Preliminary result From the flux-cut profile, Which can be applied to compute the contribution of the contaminants to the angular power spectrum of the CMB We can compute Hence the total number density of the cluster- contaminant.

Preliminary result The total number density of clusters with flux cut of S(350GHz)≥0.25mJy Peaks at around z=1.0 If kSZ effect is considered – many clusters will be 100% contaminated Thermal SZ will have contamination mostly at high z.

Conclusion Though the main contribution to infrared fluxes from clusters is the galaxy components, which are known to have suppressed star formation (low IR Lum), their total contribution in the cluster cannot be neglected. The number density of the contaminants increases with z and drops off after z~1. This is because there are few clusters at high z that satisfy the mass limit even if the sfr in clusters increases with z. Thermal SZ cluster surveys are more affected by cluster contaminants, as redshift increases. Most significant at z >0.8