New Probes of Cosmic Microwave Background Large-scale Anomalies

119 Pages·2016·9.03 MB·English

by  Simone Aiola

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
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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 2.5�. To isolate late-time signals from the primordial ones, we test the
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
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at the 2.5� 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
thetensionsbetweenPlanck,WMAP,andSPTtemperaturedataandhowtheupcomingdata
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.
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TABLE OF CONTENTS
PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
I. MOTIVATION AND THESIS SYNOPSIS . . . . . . . . . . . . . . . . 1
II. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
A. The Standard Model of Cosmology . . . . . . . . . . . . . . . . . . . . . . 3
1. Cosmic Dynamics: H ,⌦ ,⌦ ,⌦ . . . . . . . . . . . . . . . . . . . . 4
0 M ⇤ K
2. Inflation: A , A , n , n , r . . . . . . . . . . . . . . . . . . . . . . . . . 6
s t s t
3. Dark Energy: ⌦ , w . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
DE
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(✓) for future CMB polarization
experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
ˆ ˆ
D. Local B(nˆ) and E(nˆ) Correlation Functions . . . . . . . . . . . . . . . . . 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
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2. Data Filtering and the Transfer Function on Large Scales . . . . . . . . 86
D. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
VII. CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
1. Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
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LIST OF TABLES
1 Polarization sensitivities that reflect the actual Planck sensitivity in CMB
channels, and the design sensitivity for two satellite proposals. . . . . . . . . 28
2 Expected values of S statistic from a toy-model map with pixel noise using
1/2
sensitivites from Table 1 and assuming complete suppression of the true cor-
ˆ ˆ
relation function for Q, U, E, B. These estimates account for sensitivities for
future CMB polarization satellites. . . . . . . . . . . . . . . . . . . . . . . . . 30
3 Best-fit values of the amplitude A, spectral index n and direction angles (`,b)
for the dipole vector, as a function of the maximum multipole l . . . . . . . 58
max
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 � from the four di↵erent maps. . . . . . . 74
FG
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LIST OF FIGURES
1 Fraction of free electrons in the universe X as function of redshift. . . . . . . 11
e
2 Spectral energy density of the CMB measured from the COBE satellite. . . . 12
3 Total temperature power spectrum and each contributing component indepen-
dently plotted. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4 Temperature and polarization power spectra computed assuming Planck best-
fit ⇤CDM model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
5 Angular correlation function of local B-modes r = 0.1 with � = 2.7
beam �
smoothing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
6 AngularcorrelationfunctionofconstrainedlocalE-modesr = 0.1with� =
beam
2.7 smoothing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
�
7 S statistic distribution for the angular correlation function of E-modes r =
1/2
0.1 with � = 2.7 radian smoothing. . . . . . . . . . . . . . . . . . . . . . 33
beam �
8 S statistic distribution for the angular correlation function of B-modes r =
1/2
0.1 with � = 2.7 radian smoothing. . . . . . . . . . . . . . . . . . . . . . 33
beam �
9 Angular correlation function of Q and U polarizations with r = 0.1. The
shaded regions correspond to the 68% C.L. errors. . . . . . . . . . . . . . . . 35
10 S distribution for CQQ(✓) with r = 0.1. The blue dashed line shows the
1/2
⇤CDM prediction for the ensemble average. . . . . . . . . . . . . . . . . . . . 36
11 S distribution for CUU(✓) with r = 0.1. The blue dashed line shows the
1/2
⇤CDM prediction for the ensemble average. . . . . . . . . . . . . . . . . . . . 36
x