XMM Cluster Survey: Cosmology Forecasts & Discoveries

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 OverviewAnd related publications • 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) • Cosmology Forecasts • Sahlen et al. (in press; 0802.4462)

4. 1.1 Project SummaryXCS 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. 1.6 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 after the addition (and detection) of a fake cluster

10. 1.7 Features (X-ray Spectroscopy) • 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)

11. 1.8 Features (Added value science) • 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

12. 1.9 Features (Added value science) • 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)

13. 1.10 Features (Added value science) • 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

14. 1.11 Features (Added value science) • 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

15. 2.1 Cosmology ForecastsXCS 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 ForecastsUnderstanding 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 ForecastsUnderstanding 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 ForecastsWe 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. SummaryXCS is producing object catalogues for a variety of science applications