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Statistical Analysis of the X-Ray Morphology of Galaxy Clusters

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Statistical Analysis of the X-Ray Morphology of Galaxy Clusters Statistical analysis of the X-ray morphology of galaxy clusters Alexandra Weißmann München 2013 Statistical analysis of the X-ray morphology of galaxy clusters Alexandra Weißmann Dissertation an der Fakultät für Physik der Ludwig–Maximilians–Universität München vorgelegt von Alexandra Weißmann aus Wien, Österreich München, den 11.10.2013 Erstgutachter: Prof. Dr. Hans Böhringer Zweitgutachter: Prof. Dr. Ortwin Gerhard Tag der mündlichen Prüfung: 9.12.2013 Contents Zusammenfassung xiii Summary xv Preamble 1 1 Galaxy clusters 3 1.1 Intraclustermedium. .. .. .. .. .. .. .. .. 5 1.1.1 X-rayemission ............................. 5 1.1.2 Coolcoreclusters............................ 8 1.2 Massestimates ................................. 9 1.2.1 Hydrostaticmassestimates. 10 1.2.2 X-rayscalingrelations . 11 1.2.3 Othermassestimationmethods . 14 1.3 Clustersascosmologicalprobes . .... 16 1.3.1 Structureformationtheory . 16 1.3.2 Clustermassfunction. 18 1.3.3 Othercosmologicaltests . 19 2 Cluster substructure and morphology 21 2.1 Substructure on differentscales......................... 22 2.2 Morphologicalanalysis . .. 26 2.3 Impact of merging on the dynamics and morphology of galaxyclusters. 31 3 X-ray observatories and data analysis 37 3.1 XMM-Newton .................................. 37 3.2 Chandra ..................................... 40 3.3 X-raydatareduction .............................. 41 4 Studying the properties of galaxy cluster morphology estimators 45 4.1 Introduction................................... 46 4.2 Substructureparameters. ... 47 4.3 Sampleofsimulatedclusters . ... 49 4.4 Study of thesystematicsof substructuremeasures . .......... 50 4.4.1 Studyofshotnoisebiasanduncertainties . ..... 50 vi Contents 4.4.2 Significancethreshold . 54 4.4.3 Biascorrectionmethod. 56 4.4.4 Testingofthemethod.. .. .. .. .. .. .. 58 4.4.5 EffectoftheX-raybackground. 58 4.5 Morphology................................... 61 4.6 Clustersample ................................. 63 4.7 Dataanalysis .................................. 65 4.7.1 XMM-Newton datareduction...................... 65 4.7.2 Structureparameters .. .. .. .. .. .. .. 65 4.8 Morphologicalanalysisof80observedclusters . ......... 66 4.8.1 Improvedstructureestimator . .. 66 4.9 Discussion.................................... 68 4.9.1 Substructureestimationandbiascorrection . ....... 68 4.9.2 Morphologicalanalysisofclustersample . ..... 71 4.10Conclusions................................... 74 4.11Appendix .................................... 76 4.11.1 Tables.................................. 76 4.11.2 Gallery ................................. 79 5 Probing the evolution of the substructure frequency in galaxy clusters up to z ∼ 1 83 5.1 Introduction................................... 84 5.2 Observationsanddatareduction . .... 85 5.2.1 Low-z clustersample.......................... 85 5.2.2 High-z clustersamples ......................... 86 5.2.3 Datareduction ............................. 88 5.3 Morphologicalanalysis . .. 90 5.4 Dataquality................................... 91 5.4.1 Degrading of high-quality low-z observations . 92 5.5 Results...................................... 93 5.5.1 P3/P0 − z relation ........................... 94 5.5.2 w − z relation.............................. 96 5.6 Discussion.................................... 97 5.6.1 Comparisonwithpreviousstudies . .. 99 5.6.2 Effectofcoolcores........................... 100 5.7 Conclusions................................... 101 6 Morphological analysis of galaxy clusters using the asymmetry parameter 107 6.1 Introduction................................... 108 6.2 Simulations ................................... 109 6.3 Asymmetryparameter ............................. 110 6.3.1 Morphologicalboundary . 110 6.3.2 Dependenceonthepixelsize. 111 6.4 Studyofshotnoisebias. .. .. .. .. .. .. .. 113 6.4.1 Noisecorrection ............................ 114 Contents vii 6.4.2 Influenceofbinning . .. .. .. .. .. .. .. 117 6.5 Observationsanddatareduction . .... 118 6.5.1 Clustersamples............................. 118 6.5.2 Datareduction ............................. 119 6.5.3 Dataquality............................... 120 6.6 Evolutionofthesubstructurefrequency . ....... 121 6.7 Combinationwithothermorphologyestimators . ........ 122 6.8 Discussion.................................... 124 6.9 Conclusions................................... 126 7 Conclusions 129 A Chandra data reduction pipeline 133 Bibliography 139 Acknowledgements 151 viii Contents List of Figures 1.1 CompositeimageoftheBulletCluster . ..... 4 1.2 Galaxy cluster X-ray spectra for differentplasmatemperatures . 6 1.3 Coolingrateasafunctionoftemperature. ....... 7 1.4 Emission measure and X-ray surface brightness profiles for cool core and non- coolcoreclusters ................................ 8 1.5 Comparison of weak lensing (MWL) and hydrostatic mass estimates (MX) .. 11 1.6 L − T relations ................................. 13 1.7 Comparison of the observed cluster mass function with predictions from cos- mologicalmodels ................................ 19 1.8 Constraints on ΩM and σ8 in a flat ΛCDMcosmology. 20 2.1 Examplesofsubstructuresinclustercores . ........ 23 2.2 Substructuresonlargescales . .... 25 2.3 X-raycontoursforfourmorphologicaltypes . ........ 27 2.4 Power ratios computed in differentapertures. 29 2.5 Evolution of the hydrostatic disequilibrium and the cluster mass during the mergingprocess................................. 32 2.6 Evolution of the merging system in X-ray scaling relations .......... 35 3.1 XMM-Newton telescopeconfiguration . 38 3.2 Lightpath inthe XMM-Newton telescopes for the EPIC MOS and pn cameras 39 3.3 ComparisonoftheCCDarraysofEPICMOSandpn . ... 39 3.4 Illustration of the Chandra X-rayobservatory . 41 3.5 SchematicviewoftheACISCCDarrays. ... 42 4.1 Comparison of 80 clusters observed with XMM-Newton and 121 simulated X-ray cluster images in the P3/P0 − w plane ................. 50 4.2 A relaxed and a disturbed simulated cluster X-ray image with different noise levels ...................................... 51 4.3 P3/P0 distribution (reflecting the bias) for different structured clusters and counts...................................... 52 4.4 Dependence of the bias as a function of P3/P0ideal and wideal ......... 55 4.5 Significance S of the P3/P0 and w measurements for differentcounts . 56 4.6 Illustrationoftheprobabilityofanegativebias . ........... 59 4.7 Background and bias corrected P3/P0 as a function of P3/P0ideal ....... 61 x List of Figures 4.8 Background and noise corrected center shifts as a function of wideal ...... 61 4.9 Example gallery of clusters visually classified as essentially relaxed and dis- turbed ...................................... 62 4.10 Motivation for the simple and morphological boundaries for P3/P0 and w .. 63 4.11 Center shift histogram of all simulated clusters defining the w boundary . 64 4.12 Example of cluster images classified using the w boundary .......... 64 4.13 P3/P0 − w planeforall80observedclusters. 67 4.14 Comparison of the P3/P0profileofA115,theBulletClusterandA2204 . 68 4.15 Relation between the significant peak (S > 0) of the P3/P0 profile and the center shift parameter for differentmorphologies . 69 4.16 Histogram for all four morphological types showing the position of P3/P0max 73 4.17 Galleryofclustersclassifiedasregular . ......... 79 4.18 Gallery ofclustersclassified as intermediate . ........... 80 4.19 Galleryofclustersclassifiedascomplex . ........ 81 4.20 Galleryofclustersclassifiedasdouble . ........ 81 5.1 Redshift distribution of the low-z and high-z samples ............. 86 5.2 Examples of the background-included, point-source-corrected smoothed X-ray images of the low-z sample........................... 87 5.3 Examples of the background-included, point-source-corrected smoothed X-ray images of the high-z samples.......................... 88 5.4 Overview of the net photon counts distribution within r500 of the low-z and high-z samples ................................. 92 5.5 Undegraded P3/P0 − z relation......................... 95 5.6 Degraded P3/P0 − z relation .......................... 96 5.7 Undegraded w − z relation ........................... 98 5.8 Comparisonwithpreviousstudies . .... 100 6.1 Distribution of the asymmetry parameter A for simulated ideal cluster images 111 6.2 Dependence of A onthebinfactorforideal simulatedclusterimages . 112 6.3 Dependence of A onthephotonstatistics. 113 6.4 A as a function of the smoothing kernel in units of r500 for ideal cluster images 115 6.5 Performance of the A parameter after smoothing with a kernel of 0.05 r500 for the mean photon statistics of the high-z 400SD and low-z sample . 116 6.6 Performance of the A parameter after binning for the mean photon statistics of the high-z 400SD and low-z sample ..................... 117 6.7 A−z relation using smoothed poissonized degraded low-z and smoothed high-z observations................................... 122 6.8 Comparison of P3/P0, w and A for the low-z sample ............. 125 A.1 Chandra datareductionpipelineflowchart . 134 List of Tables 1.1 Characteristical properties of galaxy clusters . ............ 5 3.1 Characteristics of the Chandra ACIS-I and XMM-Newton MOS and pn detectors relevantforimaging............................... 38 4.1 Statistical results on P3/P0 and w for poissonized simulated cluster images . 53 4.2 Dependence of the significance of the signal on total number counts (net counts within r500) for P3/P0c and wc ..................... 57 4.3 Overview of the boundaries for P3/P0
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