Growth of Structure Measurement from a Large Cluster Survey using Chandra and XMM-Newton

1. Growth of Structure Measurement from a Large Cluster Survey using Chandra and XMM-Newton John R. Peterson (Purdue), J. Garrett Jernigan (SSL, Berkeley), Ravi Gupta (U Penn), Justin Bankert (Purdue), Steven M. Kahn (KIPAC, Stanford) We present a large X-ray selected seredipitous cluster survey based on a novel joint analysis of archival Chandra and XMM-Newton data. The survey provides enough depth to reach clusters of flux of ~ 1014 ergs cm-2 s-1 near z ~ 1 and simultaneously a large enough sample to find evidence for the strong evolution of clusters expected from structure formation theory. We detected a total of 723 clusters of which 462 are newly discovered clusters with greater than 6σ significance. In addition, we also detect and measure 261 previously-known clusters and groups that can be used to calibrate the survey. The survey exploits a technique which combines the exquisite Chandra imaging quality with the high throughput of the XMM-Newton telescopes using overlapping survey regions. A large fraction of the contamination from AGN point sources is mitigated by using this technique. This results in a higher sensitivity for finding clusters of galaxies with relatively few photons and a large part of our survey has a flux sensitivity between 10-14 and 10-15 ergs cm2 s-1. The survey covers 41.2 square degrees of overlapping Chandra and XMM-Newton fields and 122.2 square degrees of non-overlapping Chandra data. We measure the log N-log S distribution and fit it with a redshift-dependent model characterized by a luminosity distribution proportional to exp(-z/z0). We find that z0 to be in the range 0.7 to 1.3, indicative of rapid cluster evolution, as expected for cosmic structure formation using parameters appropriate to the concordance cosmological model. Cluster Candidates: The Survey: We searched both the XMM-Newton and Chandra data archives for observations that were greater than 15 degrees away from the galactic plane. We then selected all Chandra observations and XMM-Newton observations that overlapped with the Chandra data. Then we processed the data using the standard event processing pipelines, excluding high background periods. Finally, we sorted the photons by location and tiled the sky in 0.5 degree square pieces for further analysis. A remarkably large survey exists. There are approximately 120 sq. degrees of Chandra data and 40 sq. degrees of overlapping XMM and Chandra data. The plot above shows the full sky with Chandra exposures (blue), XMM exposures (green), and overlapping exposures (red). The average exposure time is approximately 30 ks. Since the slope of the log N-log S cluster distribution is close to -1, then the total number of clusters expected in such a survey simply scales as the overall exposure time. The varying depth of the survey does not affect the overall numbers of clusters of galaxies. The Method: Clusters+ Background Raw Data AGN Chandra XMM AGN Candidates: We invented a novel analysis technique which combines the throughput of XMM-Newton and the excellent PSF of the Chandra telescope. Since AGN outnumber clusters at a ratio of 20 to 1, efficient methods had to be developed to determine the difference between AGN and Clusters. With XMM-Newton data alone, this can be difficult because of the larger PSF. We use the Chandra PSF and the XMM throughput to separate the AGN (middle) from the clusters (right). For each AGN detected with Chandra (top middle), we subtract photons in the XMM map (bottom middle) at the same position. The result is that we have a highly efficient method of extracting cluster candidates with relatively few numbers of photons (compare the contrast in the bottom left with the bottom right). Survey Results: We plot log N-log S results to the right. We plot the clusters (black, red, and green points) as a function of flux. We draw typical log N-log S measured from previous surveys at high fluxes (blue curves), and they agree within the error of our current measurements. However, at low fluxes we show dramatic evolution of the log N-log S distribution that is expected from structure formation. The survey goes to a flux level corresponding to high enough redshift to see the deficit of number of clusters per comoving volume. No evolution Theoretical Expectation: Cumulative # of Clusters per sq. deg. Flux Future Work: We have demonstrated the capability to have an extremely large cluster survey. The survey shows strong sensitivity to the growth of structure. Therefore, we expect the cosmological constraints will be strong. After follow-up of the sources, we can determine the mass and redshift of the clusters and compare to the theoretical expectation shown to the right (Jenkins et al. 2001). The contours differ by a factor of ten, so there is a dramatic turnover at high redshift in the number of clusters. The sensitivity to particular cosmological parameters is also shown to the right, which results in a different distribution in mass and redshift. For more information about this paper, see Peterson et al. 2009, ApJ 707, 878.