1. The XMM Cluster Survey: Project summary and Cosmology Forecasts Kathy Romer University of Sussex

2. XCS Collaboration Institutes: Sussex, Porto, Edinburgh, Liverpool John Moore’s, Portsmouth, etc. Students: Mark Hosmer, Nicola Mehrtens, Martin Sahlen, Ben Hoyle PostDoc’s: Ed Lloyd-Davies, John Stott, Matt Hilton (Durban) Faculty: Collins, Kay (Manchester), Liddle, Mann, Miller (CTIO), Nichol, Stanford (UC Davis), Romer, Viana, West (ESO) Funding: Institutes; STFC (UK); Chandra and XMM Guest Observing programmes (USA)

3. Talk Overview And related publications 1.Project Summary Romer et al. 2001 (9910217) Stanford et al. 2006 (0606075) Hilton et al. 2007 (0708.3258) Collins et al. 2008 (submitted to Nature) 2.Cosmology Forecasts Sahlen et al. (in press; 0802.4462)

4. 1.1 Project Summary XCS is an X-ray cluster survey based on all XMM data in the public archive Goals –Cosmological parameters –Scaling Relations Distinguishing Features –Area –Selection function –X-ray spectroscopy –Added value science

5. 1.2 Justification for Goals Parameters: –Clusters probe a different part of the parameter space to CMB and SNe Scaling relations: –we need to know these relations to do cosmology –they tell us about structure formation –(see next talk)

6. 1.3 Features (Area) Distinguishing Features –Area 170 square degrees already [conservative] prediction of 500 sq.deg by the end of XMM These values account for overlaps and exclude regions unsuitable for cluster finding; in Galactic plane, near low-z clusters etc. –Selection function –X-ray spectroscopy –Added value science Public (or soon to be public) XMM observations

7. 1.4 Features (Selection Function) Distinguishing Features –Area –Selection function XCS is run using pipelines we add fake clusters to test to the XCS sensitivity and build up selection functions For Sahlen et al. 2008, we used simple analytical models, but recently we switched over to hydro-simulations –X-ray spectroscopy –Added value science Just one of the many XCS pipelines that convert data into the archive into catalogues of point sources and cluster candidates

8. 1.5 Features (Selection Function) Distinguishing Features –Area –Selection function XCS is run using pipelines we add fake clusters to test to the XCS sensitivity and build up selection functions For Sahlen et al. 2008, we used simple analytical models, but recently we switched over to hydro-simulations –X-ray spectroscopy –Added value science An XCS image before the addition of a fake cluster

9. Distinguishing Features –Area –Selection function XCS is run using pipelines we add fake clusters to test to the XCS sensitivity and build up selection functions For Sahlen et al. 2008, we used simple analytical models, but recently we switched over to hydro-simulations –X-ray spectroscopy –Added value science An XCS image after the addition (and detection) of a fake cluster 1.6 Features (Selection Function)

10. Distinguishing Features –Area –Selection function –X-ray spectroscopy ~300 XCS candidates were detected with 500 or more counts 124 XCS500 clusters have redshifts already (see next talk) –Added value science The XCS L-T relation (see next talk) 1.7 Features (X-ray Spectroscopy)

11. Distinguishing Features –Area –Selection function –X-ray spectroscopy –Added value science Rare object discovery: –Fossil Groups –High redshift clusters Mass calibration for future cluster surveys: –Dark Energy Survey –Planck Galaxy Evolution Quasar properties An XCS discovery of a Fossil Group 1.8 Features (Added value science)

12. Distinguishing Features –Area –Selection function –X-ray spectroscopy –Added value science Rare object discovery: –Fossil Groups –High redshift clusters Mass calibration for future cluster surveys: –Dark Energy Survey –Planck Galaxy Evolution Quasar properties Combined J & K MOIRCS image of XMM XCSJ2215 (z=1.45) 1.9 Features (Added value science)

13. Distinguishing Features –Area –Selection function –X-ray spectroscopy –Added value science Rare object discovery: –Fossil Groups –High redshift clusters Mass calibration for future cluster surveys: –Dark Energy Survey –Planck Galaxy Evolution Quasar properties Comparison of optical and X-ray properties for XCS (and 400 sq.deg) clusters in the SDSS region 1.10 Features (Added value science)

14. Distinguishing Features –Area –Selection function –X-ray spectroscopy –Added value science Rare object discovery: –Fossil Groups –High redshift clusters Mass calibration for future cluster surveys: –Dark Energy Survey –Planck Galaxy Evolution Quasar properties An XCS Quasar: we have 100 with both optical and X-ray spectroscopy 1.11 Features (Added value science)

15. 2.1 Cosmology Forecasts XCS will deliver Omega-M to 10% and Sigma-8 to 6% These predictions: –Are based on a XCS500 sample drawn from a 500 sq. deg survey –Assume a flat Universe –Use beta-model clusters for the selection function –Allow for errors in X-ray temperatures and photo-z’s –Include self-calibration of the luminosity-temperature relation –See 0802.4462 for full details

16. 2.2 Cosmology Forecasts Understanding scaling relations is essential We have made fake XCS catalogues using a variety of assumptions about scaling relations and find the catalogue properties vary significantly Making the wrong assumptions when fitting for parameters distorts the results

17. 2.3 Cosmology Forecasts Understanding scaling relations is essential We have made fake XCS catalogues using a variety of assumptions about scaling relations and find the catalogue properties vary significantly Making the wrong assumptions when fitting for parameters distorts the results Assume the wrong scaling relation and the correct parameter values can lie outside the 90% confidence region!

18. 2.4 Cosmology Forecasts We are extending and improving the forecasts Selection functions were based on simple beta models and flat geometry –Now we use hydro “clusters” –And non-flat cosmologies We are forecasting for other surveys: contiguous XMM surveys; XEUS follow-up of XCS etc. We need independent mass estimates (e.g. from lensing) –XSC parameter constraints require an external M-Tx calibration The inner black contours represent the improvement in parameters if all XCS clusters have measured temperatures (e.g. from XMM follow-up or XEUS)

19. Summary XCS is producing object catalogues for a variety of science applications