77 research outputs found
A Monte Carlo comparison between template-based and Wiener-filter CMB dipole estimators
We review and compare two different CMB dipole estimators discussed in the
literature, and assess their performances through Monte Carlo simulations. The
first method amounts to simple template regression with partial sky data, while
the second method is an optimal Wiener filter (or Gibbs sampling)
implementation. The main difference between the two methods is that the latter
approach takes into account correlations with higher-order CMB temperature
fluctuations that arise from non-orthogonal spherical harmonics on an
incomplete sky, which for recent CMB data sets (such as Planck) is the dominant
source of uncertainty. For an accepted sky fraction of 81% and an angular CMB
power spectrum corresponding to the best-fit Planck 2018 CDM model, we
find that the uncertainty on the recovered dipole amplitude is about six times
smaller for the Wiener filter approach than for the template approach,
corresponding to 0.5 and 3K, respectively. Similar relative differences
are found for the corresponding directional parameters and other sky fractions.
We note that the Wiener filter algorithm is generally applicable to any dipole
estimation problem on an incomplete sky, as long as a statistical and
computationally tractable model is available for the unmasked higher-order
fluctuations. The methodology described in this paper forms the numerical basis
for the most recent determination of the CMB solar dipole from Planck, as
summarized by arXiv:2007.04997.Comment: 8 pages, 10 figures, submitted to A&
Constraints on the spectral index of polarized synchrotron emission from WMAP and Faraday-corrected S-PASS data
We constrain the spectral index of polarized synchrotron emission, ,
by correlating the recently released 2.3 GHz S-Band Polarization All Sky Survey
(S-PASS) data with the 23 GHz 9-year Wilkinson Microwave Anisotropy Probe
(WMAP) sky maps. We sub-divide the S-PASS field, which covers the Southern
Ecliptic hemisphere, into regions, and estimate
the spectral index of polarized synchrotron emission within each region using a
simple but robust T-T plot technique. Three different versions of the S-PASS
data are considered, corresponding to either no correction for Faraday
rotation; Faraday correction based on the rotation measure model presented by
the S-PASS team; or Faraday correction based on a rotation measure model
presented by Hutschenreuter and En{\ss}lin. We find that the correlation
between S-PASS and WMAP is strongest when applying the S-PASS model. Adopting
this correction model, we find that the mean spectral index of polarized
synchrotron emission gradually steepens from at low
Galactic latitudes to at high Galactic latitudes, in good
agreement with previously published results. Finally, we consider two special
cases defined by the BICEP2 and SPIDER fields, and obtain mean estimates of
and , respectively.
Adopting the WMAP 23 GHz sky map bandpass filtered to including angular scales
only between and as a spatial template, we constrain
the root-mean-square synchrotron polarization amplitude to be less than
() at 90 GHz (150 GHz) for the BICEP2 field,
corresponding roughly to a tensor-to-scalar ratio of
(), respectively. Very similar constraints are obtained for the
SPIDER field.Comment: 14 pages, 13 Figures, to be submitted to A&
BeyondPlanck XIV. Polarized foreground emission between 30 and 70GHz
We constrain polarized foreground emission between 30 and 70GHz with the
Planck Low Frequency Instrument (LFI) and WMAP data within the framework of
BeyondPlanck global Bayesian analysis. We combine for the first time
full-resolution Planck LFI time-ordered data with low-resolution WMAP sky maps
at 33, 40 and 61GHz. Spectral parameters are fit with a likelihood defined at
the native resolution of each frequency channel. This analysis represents the
first implementation of true multi-resolution component separation applied to
CMB observations for both amplitude and spectral energy distribution (SED)
parameters. For synchrotron emission, we approximate the SED as a power-law in
frequency and find that the low signal-to-noise ratio of the data set strongly
limits the number of free parameters that may be robustly constrained. We
partition the sky into four large disjoint regions (High Latitude; Galactic
Spur; Galactic Plane; and Galactic Center), each associated with its own
power-law index. We find that the High Latitude region is prior-dominated,
while the Galactic Center region is contaminated by residual instrumental
systematics. The two remaining regions appear to be both signal-dominated and
clean of systematics, and for these we derive spectral indices of
and . This agrees qualitatively with the WMAP-only
polarization constraints presented by Dunkley et al. (2009), but contrasts with
several temperature-based analyses. For thermal dust emission we assume a
modified blackbody model and we fit the power-law index across the full sky. We
find , which is slightly steeper than that
previously reported from Planck HFI data, but still statistically consistent at
a 2 confidence level.Comment: 17 pages, 14 figures. All BeyondPlanck products and software will be
released publicly at http://beyondplanck.science during the online release
conference (November 18-20, 2020). Connection details will be made available
at the same website. Registration is mandatory for the online tutorial, but
optional for the conferenc
BeyondPlanck IV. On end-to-end simulations in CMB analysis -- Bayesian versus frequentist statistics
End-to-end simulations play a key role in the analysis of any
high-sensitivity CMB experiment, providing high-fidelity systematic error
propagation capabilities unmatched by any other means. In this paper, we
address an important issue regarding such simulations, namely how to define the
inputs in terms of sky model and instrument parameters. These may either be
taken as a constrained realization derived from the data, or as a random
realization independent from the data. We refer to these as Bayesian and
frequentist simulations, respectively. We show that the two options lead to
significantly different correlation structures, as frequentist simulations,
contrary to Bayesian simulations, effectively include cosmic variance, but
exclude realization-specific correlations from non-linear degeneracies.
Consequently, they quantify fundamentally different types of uncertainties, and
we argue that they therefore also have different and complementary scientific
uses, even if this dichotomy is not absolute. Before BeyondPlanck, most
pipelines have used a mix of constrained and random inputs, and used the same
hybrid simulations for all applications, even though the statistical
justification for this is not always evident. BeyondPlanck represents the first
end-to-end CMB simulation framework that is able to generate both types of
simulations, and these new capabilities have brought this topic to the
forefront. The Bayesian BeyondPlanck simulations and their uses are described
extensively in a suite of companion papers. In this paper we consider one
important applications of the corresponding frequentist simulations, namely
code validation. That is, we generate a set of 1-year LFI 30 GHz frequentist
simulations with known inputs, and use these to validate the core low-level
BeyondPlanck algorithms; gain estimation, correlated noise estimation, and
mapmaking
BeyondPlanck II. CMB map-making through Gibbs sampling
We present a Gibbs sampling solution to the map-making problem for CMB
measurements, building on existing destriping methodology. Gibbs sampling
breaks the computationally heavy destriping problem into two separate steps;
noise filtering and map binning. Considered as two separate steps, both are
computationally much cheaper than solving the combined problem. This provides a
huge performance benefit as compared to traditional methods, and allows us for
the first time to bring the destriping baseline length to a single sample. We
apply the Gibbs procedure to simulated Planck 30 GHz data. We find that gaps in
the time-ordered data are handled efficiently by filling them with simulated
noise as part of the Gibbs process. The Gibbs procedure yields a chain of map
samples, from which we may compute the posterior mean as a best-estimate map.
The variation in the chain provides information on the correlated residual
noise, without need to construct a full noise covariance matrix. However, if
only a single maximum-likelihood frequency map estimate is required, we find
that traditional conjugate gradient solvers converge much faster than a Gibbs
sampler in terms of total number of iterations. The conceptual advantages of
the Gibbs sampling approach lies in statistically well-defined error
propagation and systematic error correction, and this methodology forms the
conceptual basis for the map-making algorithm employed in the BeyondPlanck
framework, which implements the first end-to-end Bayesian analysis pipeline for
CMB observations.Comment: 11 pages, 10 figures. All BeyondPlanck products and software will be
released publicly at http://beyondplanck.science during the online release
conference (November 18-20, 2020). Connection details will be made available
at the same website. Registration is mandatory for the online tutorial, but
optional for the conferenc
BeyondPlanck VII. Bayesian estimation of gain and absolute calibration for CMB experiments
We present a Bayesian calibration algorithm for CMB observations as
implemented within the global end-to-end BeyondPlanck (BP) framework, and apply
this to the Planck Low Frequency Instrument (LFI) data. Following the most
recent Planck analysis, we decompose the full time-dependent gain into a sum of
three orthogonal components: One absolute calibration term, common to all
detectors; one time-independent term that can vary between detectors; and one
time-dependent component that is allowed to vary between one-hour pointing
periods. Each term is then sampled conditionally on all other parameters in the
global signal model through Gibbs sampling. The absolute calibration is sampled
using only the orbital dipole as a reference source, while the two relative
gain components are sampled using the full sky signal, including the orbital
and Solar CMB dipoles, CMB fluctuations, and foreground contributions. We
discuss various aspects of the data that influence gain estimation, including
the dipole/polarization quadrupole degeneracy and anomalous jumps in the
instrumental gain. Comparing our solution to previous pipelines, we find good
agreement in general, with relative deviations of -0.84% (-0.67%) for 30 GHz,
-0.14% (0.02%) for 44 GHz and -0.69% (-0.08%) for 70 GHz, compared to Planck
2018 (NPIPE). The deviations we find are within expected error bounds, and we
attribute them to differences in data usage and general approach between the
pipelines. In particular, the BP calibration is performed globally, resulting
in better inter-frequency consistency. Additionally, WMAP observations are used
actively in the BP analysis, which breaks degeneracies in the Planck data set
and results in better agreement with WMAP. Although our presentation and
algorithm are currently oriented toward LFI processing, the procedure is fully
generalizable to other experiments.Comment: 18 pages, 15 figures. All BeyondPlanck products and software will be
released publicly at http://beyondplanck.science during the online release
conference (November 18-20, 2020). Connection details will be made available
at the same website. Registration is mandatory for the online tutorial, but
optional for the conferenc
BeyondPlanck XII. Cosmological parameter constraints with end-to-end error propagation
We present cosmological parameter constraints as estimated using the Bayesian
BeyondPlanck (BP) analysis framework. This method supports seamless end-to-end
error propagation from raw time-ordered data to final cosmological parameters.
As a first demonstration of the method, we analyze time-ordered Planck LFI
observations, combined with selected external data (WMAP 33-61GHz, Planck HFI
DR4 353 and 857GHz, and Haslam 408MHz) in the form of pixelized maps which are
used to break critical astrophysical degeneracies. Overall, all results are
generally in good agreement with previously reported values from Planck 2018
and WMAP, with the largest relative difference for any parameter of about 1
sigma when considering only temperature multipoles between 29<l<601. In cases
where there are differences, we note that the BP results are generally slightly
closer to the high-l HFI-dominated Planck 2018 results than previous analyses,
suggesting slightly less tension between low and high multipoles. Using low-l
polarization information from LFI and WMAP, we find a best-fit value of
tau=0.066 +/- 0.013, which is higher than the low value of tau=0.051 +/- 0.006
derived from Planck 2018 and slightly lower than the value of 0.069 +/- 0.011
derived from joint analysis of official LFI and WMAP products. Most
importantly, however, we find that the uncertainty derived in the BP processing
is about 30% larger than when analyzing the official products, after taking
into account the different sky coverage. We argue that this is due to
marginalizing over a more complete model of instrumental and astrophysical
parameters, and this results in both more reliable and more rigorously defined
uncertainties. We find that about 2000 Monte Carlo samples are required to
achieve robust convergence for low-resolution CMB covariance matrix with 225
independent modes.Comment: 13 pages, 10 figure
BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation
We present Planck LFI frequency sky maps derived within the BeyondPlanck
framework. This framework draws samples from a global posterior distribution
that includes instrumental, astrophysical and cosmological parameters, and the
main product is an entire ensemble of frequency sky map samples. This ensemble
allows for computationally convenient end-to-end propagation of low-level
instrumental uncertainties into higher-level science products. We show that the
two dominant sources of LFI instrumental systematic uncertainties are
correlated noise and gain fluctuations, and the products presented here support
- for the first time - full Bayesian error propagation for these effects at
full angular resolution. We compare our posterior mean maps with traditional
frequency maps delivered by the Planck collaboration, and find generally good
agreement. The most important quality improvement is due to significantly lower
calibration uncertainties in the new processing, as we find a fractional
absolute calibration uncertainty at 70 GHz of , which is nominally 40 times smaller than that reported by Planck
2018. However, the original Planck 2018 estimate has a non-trivial statistical
interpretation, and this further illustrates the advantage of the new framework
in terms of producing self-consistent and well-defined error estimates of all
involved quantities without the need of ad hoc uncertainty contributions. We
describe how low-resolution data products, including dense pixel-pixel
covariance matrices, may be produced directly from the posterior samples
without the need for computationally expensive analytic calculations or
simulations. We conclude that posterior-based frequency map sampling provides
unique capabilities in terms of low-level systematics modelling and error
propagation, and may play an important role for future CMB B-mode experiments.
(Abridged.)Comment: 32 pages, 23 figures, data available from
https://www.cosmoglobe.uio.no
BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation
We present posterior sample-based cosmic microwave background (CMB)
constraints from Planck LFI and WMAP observations derived through global
end-to-end Bayesian processing. We use these samples to study correlations
between CMB, foreground, and instrumental parameters, and we identify a
particularly strong degeneracy between CMB temperature fluctuations and
free-free emission on intermediate angular scales, which is mitigated through
model reduction, masking, and resampling. We compare our posterior-based CMB
results with previous Planck products, and find generally good agreement, but
with higher noise due to exclusion of HFI data. We find a best-fit CMB dipole
amplitude of , in excellent agreement with previous Planck
results. The quoted uncertainty is derived directly from the sampled posterior
distribution, and does not involve any ad hoc contribution for systematic
effects. Similarly, we find a temperature quadrupole amplitude of
, in good agreement with previous results in
terms of the amplitude, but the uncertainty is an order of magnitude larger
than the diagonal Fisher uncertainty. Relatedly, we find lower evidence for a
possible alignment between and than previously reported
due to a much larger scatter in the individual quadrupole coefficients, caused
both by marginalizing over a more complete set of systematic effects, and by
our more conservative analysis mask. For higher multipoles, we find that the
angular temperature power spectrum is generally in good agreement with both
Planck and WMAP. This is the first time the sample-based asymptotically exact
Blackwell-Rao estimator has been successfully established for multipoles up to
, and it now accounts for the majority of the cosmologically
important information. Cosmological parameter constraints are presented in a
companion paper. (Abriged)Comment: 26 pages, 24 figures. Submitted to A&A. Part of the BeyondPlanck
paper suit
BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data
We describe the BeyondPlanck project in terms of motivation, methodology and
main products, and provide a guide to a set of companion papers that describe
each result in fuller detail. Building directly on experience from ESA's Planck
mission, we implement a complete end-to-end Bayesian analysis framework for the
Planck Low Frequency Instrument (LFI) observations. The primary product is a
joint posterior distribution P(omega|d), where omega represents the set of all
free instrumental (gain, correlated noise, bandpass etc.), astrophysical
(synchrotron, free-free, thermal dust emission etc.), and cosmological (CMB
map, power spectrum etc.) parameters. Some notable advantages of this approach
are seamless end-to-end propagation of uncertainties; accurate modeling of both
astrophysical and instrumental effects in the most natural basis for each
uncertain quantity; optimized computational costs with little or no need for
intermediate human interaction between various analysis steps; and a complete
overview of the entire analysis process within one single framework. As a
practical demonstration of this framework, we focus in particular on low-l CMB
polarization reconstruction, paying special attention to the LFI 44 GHz
channel. We find evidence of significant residual systematic effects that are
still not accounted for in the current processing, but must be addressed in
future work. These include a break-down of the 1/f correlated noise model at 30
and 44 GHz, and scan-aligned stripes in the Southern Galactic hemisphere at 44
GHz. On the Northern hemisphere, however, we find that all results are
consistent with the LCDM model, and we constrain the reionization optical depth
to tau = 0.067 +/- 0.016, with a low-resolution chi-squared
probability-to-exceed of 16%. The marginal CMB dipole amplitude is 3359.5 +/-
1.9 uK. (Abridged.)Comment: 77 pages, 46 figures. All BeyondPlanck products and software will be
released publicly at http://beyondplanck.science during the online release
conference (November 18-20, 2020). Connection details will be made available
at the same website. Registration is mandatory for the online tutorial, but
optional for the conferenc
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