NEW PROBES OF COSMIC MICROWAVE BACKGROUND LARGE-SCALE ANOMALIES by Simone Aiola B. Sc., University of Rome La Sapienza, 2010 M. Sc., University of Rome La Sapienza, 2012 M. Sc., University of Pittsburgh, 2014 Submitted to the Graduate Faculty of the Kenneth P. Dietrich School of Arts and Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH KENNETH P. DIETRICH SCHOOL OF ARTS AND SCIENCES PHYSICS AND ASTRONOMY DEPARTMENT This dissertation was presented by Simone Aiola It was defended on April 28th 2016 and approved by Arthur Kosowsky, Dept. of Physics and Astronomy, University of Pittsburgh Ayres Freitas, Dept. of Physics and Astronomy, University of Pittsburgh Je↵rey Newman, Dept. of Physics and Astronomy, University of Pittsburgh Glenn Starkman, Dept. of Physics, Case Western Reserve University Andrew Zentner, Dept. of Physics and Astronomy, University of Pittsburgh Dissertation Director: Arthur Kosowsky, Dept. of Physics and Astronomy, University of Pittsburgh ii Copyright © by Simone Aiola 2016 iii NEW PROBES OF COSMIC MICROWAVE BACKGROUND LARGE-SCALE ANOMALIES Simone Aiola, PhD University of Pittsburgh, 2016 Fifty years of Cosmic Microwave Background (CMB) data played a crucial role in constrain- ing the parameters of the ⇤CDM model, where Dark Energy, Dark Matter, and Inflation are the three most important pillars not yet understood. Inflation prescribes an isotropic universe on large scales, and it generates spatially-correlated density fluctuations over the whole Hubble volume. CMB temperature fluctuations on scales bigger than a degree in the sky, a↵ected by modes on super-horizon scale at the time of recombination, are a clean snap- shot of the universe after inflation. In addition, the accelerated expansion of the universe, driven by Dark Energy, leaves a hardly detectable imprint in the large-scale temperature sky at late times. Such fundamental predictions have been tested with current CMB data and found to be in tension with what we expect from our simple ⇤CDM model. Is this tension just a random fluke or a fundamental issue with the present model? In this thesis, we present a new framework to probe the lack of large-scale correlations in the temperature sky using CMB polarization data. Our analysis shows that if a suppression in the CMB polarization correlations is detected, it will provide compelling evidence for new physics on super-horizon scale. To further analyze the statistical properties of the CMB temperature sky, we constrain the degree of statistical anisotropy of the CMB in the context of the observed large-scale dipole power asymmetry. We find evidence for a scale-dependent dipolar modulation at 2.5σ.Toisolatelate-timesignalsfromtheprimordialones,wetestthe anomalously high Integrated Sachs-Wolfe e↵ect signal generated by superstructures in the universe. We find that the detected signal is in tension with the expectations from ⇤CDM iv at the 2.5σ level, which is somewhat smaller than what has been previously argued. To conclude, we describe the current status of CMB observations on small scales, highlighting the tensions between Planck, WMAP, and SPT temperature data and how the upcoming data release of the ACTpol experiment will contribute to this matter. We provide a description of the current status of the data-analysis pipeline and discuss its ability to recover large-scale modes. Keywords: Cosmology, Cosmic Microwave Background, Temperature Anisotropies. v TABLE OF CONTENTS PREFACE ......................................... xiii I. MOTIVATION AND THESIS SYNOPSIS ................ 1 II. INTRODUCTION ................................ 3 A. The Standard Model of Cosmology ...................... 3 1. Cosmic Dynamics: H0,⌦M ,⌦⇤,⌦K .................... 4 2. Inflation: As, At, ns, nt, r ......................... 6 3. Dark Energy: ⌦DE, w ............................ 8 B. The Cosmic Microwave Background Radiation ................ 9 1. Temperature power spectrum ....................... 12 2. Polarization power spectrum ........................ 16 III. MICROWAVE BACKGROUND POLARIZATION AS A PROBE OF LARGE-ANGLE CORRELATIONS .................. 21 A. Introduction ................................... 21 B. Background ................................... 23 1. Temperature Correlation Function and Statistics ............. 23 2. Stokes Q and U Correlation Functions and Statistics .......... 24 3. E- and B-mode Correlation Functions and Statistics ........... 25 C. Error limits on measuring a suppressed C(✓)forfutureCMBpolarization experiments ................................... 28 D. Local Bˆ(ˆn )andEˆ(ˆn )CorrelationFunctions ................. 30 E. Q and U Correlations ............................. 32 F. Discussion .................................... 37 vi IV. MICROWAVE BACKGROUND CORRELATIONS FROM DIPOLE ANISOTROPY MODULATION ....................... 39 A. Introduction ................................... 39 B. Dipole-Modulation-Induced Correlations and Estimators .......... 41 C. Simulations and Analysis Pipeline ....................... 45 1. Characterization of the Mask ....................... 45 2. Simulated Skies ............................... 46 3. Bias Estimates ............................... 47 D. Microwave Sky Data .............................. 48 E. Results ..................................... 49 1. Geometrical Test .............................. 49 2. Model Fitting ................................ 51 F. Discussion .................................... 52 V. GAUSSIAN APPROXIMATION OF PEAK VALUES IN THE IN- TEGRATED SACHS-WOLFE EFFECT .................. 59 A. Introduction ................................... 59 B. Correlated Components of the Temperature Sky ............... 63 C. Methodology and Analysis ........................... 66 1. Harmonic-Space Filtering .......................... 66 2. Simulation Pipeline ............................. 66 3. Results and Comparison with Previous Work ............... 69 D. The Stacked ISW Signal Using Planck Sky Maps .............. 71 E. Discussion .................................... 73 VI. MAXIMUM LIKELIHOOD MAP MAKING FOR THE ATACAMA COSMOLOGY TELESCOPE ......................... 78 A. Current picture in experimental CMB cosmology .............. 78 B. The Atacama Cosmology Telescope ...................... 80 1. Observations ................................. 80 C. Ninkasi: a Maximum-likelihood Map-making pipeline ............ 81 1. Noise Model ................................. 84 vii 2. Data Filtering and the Transfer Function on Large Scales ........ 86 D. Conclusions ................................... 88 VII. CONCLUSIONS ................................. 92 1. Future Prospects .............................. 94 BIBLIOGRAPHY .................................... 95 viii LIST OF TABLES 1PolarizationsensitivitiesthatreflecttheactualPlancksensitivityinCMB channels, and the design sensitivity for two satellite proposals. ........ 28 2 Expected values of S1/2 statistic from a toy-model map with pixel noise using sensitivites from Table 1 and assuming complete suppression of the true cor- relation function for Q, U, Eˆ, Bˆ.Theseestimatesaccountforsensitivitiesfor future CMB polarization satellites. ........................ 30 3 Best-fit values of the amplitude A,spectralindexn and direction angles (`, b) for the dipole vector, as a function of the maximum multipole lmax. ...... 58 4 Results from Gaussian random skies, stacked on peaks of the ISW–in signal (the ISW generated for structure in the redshift range 0.4 <z<0.75). .... 69 5 Mean temperature deviations for GNS08 cluster and void locations, for four temperature maps with di↵erent foreground cleaning procedures. We estimate the mean and standard deviation σFG from the four di↵erent maps. ...... 74 ix LIST OF FIGURES 1FractionoffreeelectronsintheuniverseXe as function of redshift. ...... 11 2SpectralenergydensityoftheCMBmeasuredfromtheCOBEsatellite.... 12 3Totaltemperaturepowerspectrumandeachcontributingcomponentindepen- dently plotted. ................................... 19 4TemperatureandpolarizationpowerspectracomputedassumingPlanckbest- fit ⇤CDM model. ................................. 20 5 Angular correlation function of local B-modes r =0.1withσbeam =2.7◦ smoothing. ..................................... 31 6 Angular correlation function of constrained local E-modes r =0.1withσbeam = 2.7◦ smoothing. .................................. 32 7 S1/2 statistic distribution for the angular correlation function of E-modes r = 0.1withσbeam =2.7◦ radian smoothing. ..................... 33 8 S1/2 statistic distribution for the angular correlation function of B-modes r = 0.1withσbeam =2.7◦ radian smoothing. ..................... 33 9 Angular correlation function of Q and U polarizations with r =0.1. The shaded regions correspond to the 68% C.L. errors. ............... 35 QQ 10 S1/2 distribution for C (✓)withr =0.1. The blue dashed line shows the ⇤CDM prediction for the ensemble average. ................... 36 UU 11 S1/2 distribution for C (✓)withr =0.1. The blue dashed line shows the ⇤CDM prediction for the ensemble average. ................... 36 x 12 Correlation matrices for the Cartesian components of the dipole vector. These matrices are estimated using 2000 random simulated skies masked with the apodized Planck U73 mask. The ordering of the components follows the con- vention defined for the dipole vector. ....................... 47 13 Measured Cartesian components of the dipole vector from the SMICA Planck map as a function of the central