Cosmic shear and the intrinsic alignment of galaxies [Elektronische Ressource] / vorgelegt von Benjamin Joachimi

Benjamin Joachimi

Sujets

• Astronomie
• Physik

Informations

• Publié par: rheinische_friedrich-wilhelms-universitat_bonn
• Publié le: 01 janvier 2010
• Nombre de lectures: 24
• Langue: English
• Poids de l'ouvrage: 5 Mo

Extrait

CosmicShear
andthe
IntrinsicAlignmentofGalaxies
Dissertation
zur
Erlangung des Doktorgrades (Dr. rer. nat.)
der
Mathematisch-Naturwissenschaftlichen Fakulta¨t
der
Rheinischen Friedrich-Wilhelms-Universita¨t Bonn
vorgelegt von
Benjamin Joachimi
aus
Rheine
Bonn, 2010ii
AngefertigtmitGenehmigungderMathematisch-NaturwissenschaftlichenFakulta¨t
der Rheinischen Friedrich-Wilhelms-Universita¨t Bonn
1. Gutachter: Prof. Dr. Peter Schneider
2. Gutachter: Prof. Dr. Andreas Eckart
Tag der Promotion: 04. November 2010
Erscheinungsjahr: 2010iii
To strive,
To seek,
To find,
And not to yield.
Lord Alfred Tennyson, Ulyssesiv
Abstract
Cosmology has recently entered an era of increasingly rich observational data sets, all being
in agreement with a cosmological standard model that features only a small number of free
parameters. One of the most powerful techniques to constrain these parameters and test the
accuracy of the concordance model is the weak gravitational lensing of distant galaxies by the
large-scale structure, or cosmic shear. This thesis investigates the optimisation of present and
futurecosmicshearsurveyswithrespecttotheextractionofcosmologicalinformationanddeals
with the characterisation and control of the intrinsic alignment of galaxies, a major systematic
in cosmic shear data.
A detailed derivation of the covariance of the weak lensing convergence bispectrum is pre-
sented, clarifying the relation between existing formalisms, providing illustration, and simpli-
fying the practical computation. The results are then applied to forecasts on cosmological
constraints by cosmic shear two- and three-point statistics with the proposed Euclid satellite.
Besides, a novel method to assess the impact of unknown systematics on cosmological parame-
ter constraints is summarised, and several aspects concerning the weak lensing analysis of the
Hubble Space Telescope COSMOS survey are highlighted.
A synopsis of the current state of knowledge about the intrinsic alignment of galaxies is
given, including its physical origin, modelling attempts, simulation results, and existing ob-
servations. Possible corrections to the prevailing model of intrinsic alignments are suggested,
before presenting new observational constraints on matter-intrinsic shear correlations using
several galaxy samples from the Sloan Digital Sky Survey. For the first time a data set with
onlyphotometricredshiftinformationisincluded, afterdevelopingtheformalismforcorrelation
function models that take photometric redshift scatter into account. The intrinsic alignment
signal of early-type galaxies is found to increase with galaxy luminosity and to be inconsistent
with the default redshift evolution of a widely used model, both with high confidence.
Moreover the nulling technique is developed, a method to remove gravitational shear-
intrinsic ellipticity correlations from cosmic shear data by solely relying on the well-known
redshift dependence of the signals, and its performance on realistically modelled cosmic shear
two-point statistics is investigated. Subsequently, the principle of intrinsic alignment boosting,
aninverseandlikewisegeometricalapproachcapableofextractingtheintrinsicalignmentsignal
fromcosmic sheardata, isderived. Bothtechniques areshown torobustlyremove orisolatethe
intrinsic alignment signal, but are subject toasignificant lossofstatistical power caused bythe
similarity between the redshift dependence of the lensing signal and shear-intrinsic correlations
in combination with strict model independence.
As an alternative ansatz, the joint analysis of various probes available from cosmic shear
surveys is considered, including cosmic shear, galaxy clustering, lensing magnification effects,
and cross-correlations between galaxy number densities and shapes. The self-calibration ca-
pabilities of intrinsic alignments and the galaxy bias in the combined data are found to be
excellent for realistic survey parameters, recovering the constraints on cosmological parameters
for a pure cosmic shear signal in presence of flexible parametrisations of intrinsic alignments
and galaxy bias with about a hundred nuisance parameters in total.CONTENTS v
Contents
1 Introduction 1
2 Principles of cosmology 4
2.1 Homogeneous world models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Matter components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3 The early Universe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.4 Structure formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.5 The concordance model and beyond . . . . . . . . . . . . . . . . . . . . . . . . . 19
3 Weak gravitational lensing 24
3.1 Gravitational lens theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.2 Shear measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3 Foundations of cosmic shear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.4 Measures of cosmic shear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.5 The status quo of cosmic shear . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4 Optimisation of cosmic shear surveys 43
4.1 Bispectrum covariance in the flat-sky limit . . . . . . . . . . . . . . . . . . . . . 43
4.1.1 Bispectrum estimator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.1.2 Averaging over triangles . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.1.3 Bispectrum covariance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.1.4 Equivalence to spherical harmonics approach . . . . . . . . . . . . . . . . 53
4.1.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.2 Forecasting the performance of cosmological surveys . . . . . . . . . . . . . . . . 62
4.2.1 Constraints from the Euclid imaging survey . . . . . . . . . . . . . . . . 62
4.2.2 Functional form filling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4.3 Cosmic shear analysis of the HST COSMOS Survey . . . . . . . . . . . . . . . . 74
4.3.1 Cosmic shear tomography with COSMOS . . . . . . . . . . . . . . . . . 74
4.3.2 Modelling the effect of dark energy on structure evolution . . . . . . . . 76
4.3.3 Analytic predictions for the COSMOS analysis . . . . . . . . . . . . . . . 78
5 The intrinsic alignment of galaxies 82
5.1 Introduction to intrinsic alignments . . . . . . . . . . . . . . . . . . . . . . . . . 83
5.1.1 The origin of intrinsic correlations . . . . . . . . . . . . . . . . . . . . . . 83
5.1.2 Models of intrinsic alignments . . . . . . . . . . . . . . . . . . . . . . . . 85
5.1.3 Evidence for intrinsic alignments . . . . . . . . . . . . . . . . . . . . . . 89
5.1.4 Control of intrinsic alignment contamination . . . . . . . . . . . . . . . . 93
5.2 The MegaZ LRG and spectroscopic SDSS samples . . . . . . . . . . . . . . . . . 95
5.3 Modelling galaxy number density-shape correlations . . . . . . . . . . . . . . . . 98
5.3.1 Three-dimensional correlation functions . . . . . . . . . . . . . . . . . . . 98vi CONTENTS
5.3.2 Contribution by other signals . . . . . . . . . . . . . . . . . . . . . . . . 104
5.3.3 Projected correlation functions . . . . . . . . . . . . . . . . . . . . . . . 108
5.4 Measurement details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.4.1 Photometric redshifts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
5.4.2 Galaxy shape and correlation function measurement . . . . . . . . . . . . 111
5.4.3 Fitting routine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
5.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
5.5.1 Scaling with line-of-sight truncation . . . . . . . . . . . . . . . . . . . . . 114
5.5.2 Galaxy bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
5.5.3 Intrinsic alignment fits . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
5.6 Implications for cosmology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
5.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
6 The nulling technique 129
6.1 Principle of nulling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
6.2 Determination of nulling weight functions . . . . . . . . . . . . . . . . . . . . . . 134
6.2.1 Piecewise linear approach . . . . . . . . . . . . . . . . . . . . . . . . . . 135
6.2.2 Chebyshev series approach . . . . . . . . . . . . . . . . . . . . . . . . . . 136
6.2.3 Simplified analytical approach . . . . . . . . . . . . . . . . . . . . . . . . 137
6.2.4 Resulting nulling weights . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
6.2.5 Higher order weights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
6.3 Information loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
6.4 Towards an efficient nulling transformation . . . . . . . . . . . . . . . . . . . . . 152
6.5 Modelling cosmic shear data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
6.5.1 Redshift distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
6.5.2 Lensing power spectra . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
6.5.3 Intri