Cross-correlating Planck tSZ with RCSLenS weak lensing: implications for cosmology and AGN feedback

We present measurements of the spatial mapping between (hot) baryons and the total matter in the Universe, via the cross-correlation between the thermal Sunyaev–Zeldovich (tSZ)map from Planck and the weak gravitational lensing maps from theRed Cluster Sequence Lensing Survey (RCSLenS). The cross-correlations are performed on the map level where all the sources (including diffuse intergalactic gas) contribute to the signal. We consider two configurationspace correlation function estimators, ξ y–κ and ξ y–γt , and a Fourier-space estimator, Cy–κ , in our analysis. We detect a significant correlation out to 3◦ of angular separation on the sky. Based on statistical noise only, we can report 13σ and 17σ detections of the cross-correlation using the configuration-space y–κ and y–γ t estimators, respectively. Including a heuristic estimate of the sampling variance yields a detection significance of 7σ and 8σ, respectively. A similar level of detection is obtained from the Fourier-space estimator, Cy–κ . As each estimator probes different dynamical ranges, their combination improves the significance of the detection. We compare our measurements with predictions from the cosmo-OverWhelmingly Large Simulations suite of cosmological hydrodynamical simulations, where different galactic feedback models are implemented. We find that a model with considerable active galactic nuclei (AGN) feedback that removes large quantities of hot gas from galaxy groups and Wilkinson Microwave Anisotropy Probe 7-yr best-fitting cosmological parameters provides the bestmatch to the measurements. All baryonic models in the context of a Planck cosmology overpredict the observed signal. Similar cosmological conclusions are drawn when we employ a halo model with the observed ‘universal’ pressure profile.

[1]  T. Kitching,et al.  RCSLenS: The Red Cluster Sequence Lensing Survey , 2016, 1603.07722.

[2]  T. Kitching,et al.  CFHTLenS and RCSLenS Cross-Correlation with Planck Lensing Detected in Fourier and Configuration Space , 2016, 1603.07723.

[3]  A. Heavens,et al.  Parameter inference with estimated covariance matrices , 2015, 1511.05969.

[4]  C. B. D'Andrea,et al.  Cosmology from cosmic shear with Dark Energy Survey science verification data , 2015, 1507.05552.

[5]  R. B. Barreiro,et al.  Planck 2015 results - XXII. A map of the thermal Sunyaev-Zeldovich effect , 2015, 1502.01596.

[6]  B. Garilli,et al.  The galaxy-halo connection from a joint lensing, clustering and abundance analysis in the CFHTLenS/VIPERS field , 2015, 1502.02867.

[7]  J. Melin,et al.  Testing Sunyaev-Zel'dovich measurements of the hot gas content of dark matter haloes using synthetic skies , 2015, 1501.05666.

[8]  C. Heymans,et al.  Baryons, neutrinos, feedback and weak gravitational lensing , 2014, 1407.4301.

[9]  G. Hinshaw,et al.  Probing the diffuse baryon distribution with the lensing-tSZ cross-correlation , 2014, 1404.4808.

[10]  G. Hinshaw,et al.  Dissecting the thermal Sunyaev-Zeldovich-gravitational lensing cross-correlation with hydrodynamical simulations , 2014, 1412.6051.

[11]  N. Battaglia,et al.  DECONSTRUCTING THERMAL SUNYAEV–ZEL’DOVICH—GRAVITATIONAL LENSING CROSS-CORRELATIONS: IMPLICATIONS FOR THE INTRACLUSTER MEDIUM , 2014, 1412.5593.

[12]  L. Waerbeke,et al.  Weak lensing corrections to tSZ-lensing cross correlation , 2014, 1408.6284.

[13]  J. Schaye,et al.  Towards a realistic population of simulated galaxy groups and clusters , 2013, 1312.5462.

[14]  J. Schaye,et al.  The thermal Sunyaev–Zel'dovich effect power spectrum in light of Planck , 2013, 1312.5341.

[15]  David N. Spergel,et al.  Detection of thermal SZ-CMB lensing cross-correlation in Planck nominal mission data , 2013, 1312.4525.

[16]  G. Hinshaw,et al.  Detection of warm and diffuse baryons in large scale structure from the cross-correlation of gravitational lensing and the thermal Sunyaev-Zeldovich effect , 2013, 1310.5721.

[17]  C. A. Oxborrow,et al.  Planck 2013 results. XVI. Cosmological parameters , 2013, 1303.5076.

[18]  H. Hoekstra,et al.  CFHTLenS: mapping the large-scale structure with gravitational lensing , 2013, 1303.1806.

[19]  H. Hoekstra,et al.  Bayesian galaxy shape measurement for weak lensing surveys – III. Application to the Canada–France–Hawaii Telescope Lensing Survey , 2012, 1210.8201.

[20]  Edwin A. Valentijn,et al.  The Kilo-Degree Survey , 2012, Experimental Astronomy.

[21]  Craig Loomis,et al.  Hyper Suprime-Cam , 2012, Other Conferences.

[22]  L. Miller,et al.  CFHTLenS: the Canada–France–Hawaii Telescope Lensing Survey – imaging data and catalogue products , 2012, 1210.0032.

[23]  G. W. Pratt,et al.  Planck intermediate results: V. Pressure profiles of galaxy clusters from the Sunyaev-Zeldovich effect , 2012, 1207.4061.

[24]  J. R. Bond,et al.  ON THE CLUSTER PHYSICS OF SUNYAEV–ZEL'DOVICH AND X-RAY SURVEYS. II. DECONSTRUCTING THE THERMAL SZ POWER SPECTRUM , 2011, 1109.3711.

[25]  H. Hoekstra,et al.  CFHTLenS: Improving the quality of photometric redshifts with precision photometry , 2011, 1111.4434.

[26]  H. Hoekstra,et al.  Quantifying the effect of baryon physics on weak lensing tomography , 2011, 1105.1075.

[27]  Joop Schaye,et al.  The effects of galaxy formation on the matter power spectrum: a challenge for precision cosmology , 2011, 1104.1174.

[28]  B. Hsieh,et al.  THE RED-SEQUENCE CLUSTER SURVEY-2 (RCS-2): SURVEY DETAILS AND PHOTOMETRIC CATALOG CONSTRUCTION , 2010, 1012.3470.

[29]  G. W. Pratt,et al.  The universal galaxy cluster pressure profile from a representative sample of nearby systems (REXCESS) and the Y-SZ-M-500 relation , 2009, 0910.1234.

[30]  J. Schaye,et al.  The physics driving the cosmic star formation history , 2009, 0909.5196.

[31]  Eiichiro Komatsu,et al.  Galaxy-CMB and galaxy-galaxy lensing on large scales: Sensitivity to primordial non-Gaussianity , 2009, 0910.1361.

[32]  J. Schaye,et al.  Cosmological simulations of the growth of supermassive black holes and feedback from active galactic nuclei: method and tests , 2009, 0904.2572.

[33]  J. Schaye,et al.  Chemical enrichment in cosmological, smoothed particle hydrodynamics simulations , 2009, 0902.1535.

[34]  J. Schaye,et al.  The effect of photoionization on the cooling rates of enriched, astrophysical plasmas , 2008, 0807.3748.

[35]  Edward J. Wollack,et al.  FIVE-YEAR WILKINSON MICROWAVE ANISOTROPY PROBE OBSERVATIONS: COSMOLOGICAL INTERPRETATION , 2008, 0803.0547.

[36]  J. Schaye,et al.  Simulating galactic outflows with kinetic supernova feedback , 2008, 0801.2770.

[37]  J. Schaye,et al.  On the relation between the Schmidt and Kennicutt-Schmidt star formation laws and its implications for numerical simulations , 2007, 0709.0292.

[38]  D. Nagai,et al.  Effects of Galaxy Formation on Thermodynamics of the Intracluster Medium , 2007, astro-ph/0703661.

[39]  P. Schneider,et al.  Why your model parameter confidences might be too optimistic - unbiased estimation of the inverse covariance matrix , 2006, astro-ph/0608064.

[40]  David S. Williams Weighing the odds : a course in probability and statistics , 2001 .

[41]  N. Benı́tez Bayesian Photometric Redshift Estimation , 1998, astro-ph/9811189.

[42]  P. Schneider,et al.  A NEW MEASURE FOR COSMIC SHEAR , 1997, astro-ph/9708143.