scholarly journals Peeling off foregrounds with the constrained moment ILC method to unveil primordial CMB B modes

2021 ◽  
Vol 503 (2) ◽  
pp. 2478-2498
Author(s):  
Mathieu Remazeilles ◽  
Aditya Rotti ◽  
Jens Chluba
Keyword(s):  
Statistical Moment ◽  
Component Separation ◽  
Line Of Sight ◽  
Microwave Background ◽  
Spectral Signatures ◽  
Moment Expansion ◽  
Trade Offs ◽  
Bias Variance ◽  
Peeling Off ◽  
Component Separation Method

ABSTRACT Galactic foregrounds are the main obstacle to observations of the cosmic microwave background (CMB) B-mode polarization. In addition to obscuring the inflationary B-mode signal by several orders of magnitude, Galactic foregrounds have non-trivial spectral signatures that are partially unknown and distorted by averaging effects along the line of sight, within the pixel/beam window, and by various analysis choices (e.g. spherical harmonic transforms and filters). Statistical moment expansion methods provide a powerful tool for modelling the effective Galactic foreground emission resulting from these averaging effects in CMB observations, while blind component separation treatments can handle unknown foregrounds. In this work, we combine these two approaches to develop a new semiblind component separation method at the intersection of parametric and blind methods, called constrained moment ILC (cMILC). This method adds several constraints to the standard ILC method to deproject the main statistical moments of the Galactic foreground emission. Applications to maps are performed in needlet space and when compared to the NILC method, this helps in significantly reducing residual foreground contamination (bias, variance, and skewness) in the reconstructed CMB B-mode map, power spectrum, and tensor-to-scalar ratio. We consider sky simulations for experimental settings similar to those of LiteBIRD and PICO, illustrating which trade-offs between residual foreground biases and degradation of the constraint on r can be expected within the new cMILC framework. We also outline several directions that require more work in preparation for the coming analysis challenges.

scholarly journals Galactic Foreground Constraints on Primordial B-mode Detection for Ground-based Experiments

2022 ◽  
Vol 924 (1) ◽  
pp. 11
Author(s):  
Carlos Hervías-Caimapo ◽  
Anna Bonaldi ◽  
Michael L. Brown ◽  
Kevin M. Huffenberger
Keyword(s):  
Fisher Information Matrix ◽  
Spectral Energy Distribution ◽  
Information Matrix ◽  
Component Separation ◽  
Spectral Energy ◽  
Noise Levels ◽  
Microwave Background ◽  
Mode Detection ◽  
Error Bar ◽  
Component Separation Method

Abstract Contamination by polarized foregrounds is one of the biggest challenges for future polarized cosmic microwave background (CMB) surveys and the potential detection of primordial B-modes. Future experiments, such as Simons Observatory (SO) and CMB-S4, will aim at very deep observations in relatively small (f sky ∼ 0.1) areas of the sky. In this work, we investigate the forecasted performance, as a function of the survey field location on the sky, for regions over the full sky, balancing between polarized foreground avoidance and foreground component separation modeling needs. To do this, we simulate observations by an SO-like experiment and measure the error bar on the detection of the tensor-to-scalar ratio, σ(r), with a pipeline that includes a parametric component separation method, the Correlated Component Analysis, and the use of the Fisher information matrix. We forecast the performance over 192 survey areas covering the full sky and also for optimized low-foreground regions. We find that modeling the spectral energy distribution of foregrounds is the most important factor, and any mismatch will result in residuals and bias in the primordial B-modes. At these noise levels, σ(r) is not especially sensitive to the level of foreground contamination, provided the survey targets the least-contaminated regions of the sky close to the Galactic poles.

scholarly journals Local Bubble contribution to the 353-GHz dust polarized emission

2019 ◽  
Vol 631 ◽  
pp. L11 ◽  
Author(s):  
R. Skalidis ◽  
V. Pelgrims
Keyword(s):  
Magnetic Field ◽  
Line Of Sight ◽  
Optical Polarization ◽  
Local Interstellar Medium ◽  
Microwave Background ◽  
Local Bubble ◽  
Submillimeter Wavelengths ◽  
Polarized Emission ◽  
The Magnetic Field ◽  
Robust Evidence

It has not been shown so far whether the diffuse Galactic polarized emission at frequencies relevant for cosmic microwave background (CMB) studies originates from nearby or more distant regions of our Galaxy. This questions previous attempts that have been made to constrain magnetic field models at local and large scales. The scope of this work is to investigate and quantify the contribution of the dusty and magnetized local interstellar medium to the observed emission that is polarized by thermal dust. We used stars as distance candles and probed the line-of-sight submillimeter polarization properties by comparing the emission that is polarized by thermal dust at submillimeter wavelengths and the optical polarization caused by starlight. We provide statistically robust evidence that at high Galactic latitudes (|b| ≥ 60°), the 353 GHz polarized sky as observed by Planck is dominated by a close-by magnetized structure that extends between 200 and 300 pc and coincides with the shell of the Local Bubble. Our result will assist modeling the magnetic field of the Local Bubble and characterizing the CMB Galactic foregrounds.

scholarly journals The Impact of CN Line Profile Measurements on the Cosmic Microwave Background Temperature

1990 ◽  
Vol 139 ◽  
pp. 390-391
Author(s):  
M. E. Kaiser ◽  
E. L. Wright
Keyword(s):  
Cosmic Microwave Background ◽  
Line Profile ◽  
Line Of Sight ◽  
High Signal ◽  
Microwave Background ◽  
A Value ◽  
Cosmic Microwave Background Temperature ◽  
Background Temperature ◽  
The Impact ◽  
Cmb Temperature

We present moderate to high signal-to-noise high-resolution (R ≈ 150,000–170,000) optical spectra toward ζ Oph. Gaussian fits to our data indicate a value of the line-width parameter b, of b = 1.4 ± 0.2 km s−1, along this line of sight. When CN is used as an indirect probe of the cosmic microwave background (CMB) temperature, the line profile is used to determine saturation corrections in the line. This affects column density calculations, which are reflected in the excitation temperature. Current measurements of the b-value along this line of sight range from 0.88 ± 0.02 km s−1 (Crane et al. 1986) to 1.3 ± 0.1 km s−1 (Hegyi, Traub, and Carleton 1972). The extreme range of these b-values yield saturation corrections to the CMB temperature that differ by 0.05 K, which is equal to the quoted precision of current measurements. Preliminary analysis of observations toward HD 29647 indicate that TCMB = 2.70 ± 0.14 K at 2.64 mm toward this line of sight.

scholarly journals Hierarchical Bayesian CMB component separation with the No-U-Turn Sampler

2020 ◽  
Vol 496 (4) ◽  
pp. 4383-4401
Author(s):  
R D P Grumitt ◽  
Luke R P Jew ◽  
C Dickinson
Keyword(s):  
Hierarchical Model ◽  
Mean Shift ◽  
Component Separation ◽  
Parameter Estimates ◽  
Microwave Background ◽  
Spectral Parameters ◽  
Mean Shift Algorithm ◽  
Performance Improvements ◽  
Gradient Based ◽  
Sampling Algorithms

ABSTRACT In this paper, we present a novel implementation of Bayesian cosmic microwave background (CMB) component separation. We sample from the full posterior distribution using the No-U-Turn Sampler (NUTS), a gradient-based sampling algorithm. Alongside this, we introduce new foreground modelling approaches. We use the mean shift algorithm to define regions on the sky, clustering according to naively estimated foreground spectral parameters. Over these regions we adopt a complete pooling model, where we assume constant spectral parameters, and a hierarchical model, where we model individual pixel spectral parameters as being drawn from underlying hyperdistributions. We validate the algorithm against simulations of the LiteBIRD and C-Band All-Sky Survey (C-BASS) experiments, with an input tensor-to-scalar ratio of r = 5 × 10−3. Considering multipoles 30 ≤ ℓ < 180, we are able to recover estimates for r. With LiteBIRD-only observations, and using the complete pooling model, we recover r = (12.9 ± 1.4) × 10−3. For C-BASS and LiteBIRD observations we find r = (9.0 ± 1.1) × 10−3 using the complete pooling model, and r = (5.2 ± 1.0) × 10−3 using the hierarchical model. Unlike the complete pooling model, the hierarchical model captures pixel-scale spatial variations in the foreground spectral parameters, and therefore produces cosmological parameter estimates with reduced bias, without inflating their uncertainties. Measured by the rate of effective sample generation, NUTS offers performance improvements of ∼103 over using Metropolis–Hastings to fit the complete pooling model. The efficiency of NUTS allows us to fit the more sophisticated hierarchical foreground model that would likely be intractable with non-gradient-based sampling algorithms.

scholarly journals Combining ILC and moment expansion techniques for extracting average-sky signals and CMB anisotropies

2020 ◽  
Author(s):  
Aditya Rotti ◽  
Jens Chluba
Keyword(s):  
Data Analysis ◽  
Cosmic Microwave Background ◽  
Linear Combination ◽  
Recent Work ◽  
Mode Analysis ◽  
Full Potential ◽  
Spectral Distortion ◽  
Microwave Background ◽  
Moment Methods ◽  
Moment Expansion

Abstract The method of weighted addition of multi-frequency maps, more commonly referred to as Internal Linear Combination (ILC), has been extensively employed in the measurement of cosmic microwave background (CMB) anisotropies and its secondaries along with similar application in 21cm data analysis. Here we argue and demonstrate that ILC methods can also be applied to data from absolutely-calibrated CMB experiments to extract average-sky signals in addition to the conventional CMB anisotropies. The performance of the simple ILC method is, however, limited, but can be significantly improved by adding constraints informed by physics and existing empirical information. In recent work, a moment description has been introduced as a technique of carrying out high precision modeling of foregrounds in the presence of inevitable averaging effects. We combine these two approaches to construct a heavily constrained form of the ILC, dubbed MILC, which can be used to recover tiny monopolar spectral distortion signals in the presence of realistic foregrounds and instrumental noise. This is a first demonstration for measurements of the monopolar and anisotropic spectral distortion signals using ILC and extended moment methods. We also show that CMB anisotropy measurements can be improved, reducing foreground biases and signal uncertainties when using the MILC. While here we focus on CMB spectral distortions, the scope extends to the 21cm monopole signal and B-mode analysis. We briefly discuss augmentations that need further study to reach the full potential of the method.

Bias-Variance Trade-offs: Novel Applications

2011 ◽  
pp. 101-110 ◽  
Author(s):  
Paul Munro ◽  
Hannu Toivonen ◽  
Geoffrey I. Webb ◽  
Wray Buntine ◽  
Peter Orbanz ◽  
...  
Keyword(s):  
Trade Offs ◽  
Bias Variance ◽  
Novel Applications

Integrated Line of Sight and Model Predictive Control for Path Following and Roll Motion Control Using Rudder

2015 ◽  
Vol 59 (02) ◽  
pp. 99-112 ◽  
Author(s):  
Cheng Liu ◽  
Jing Sun ◽  
Zaojian Zou
Keyword(s):  
Model Predictive Control ◽  
Motion Control ◽  
Predictive Control ◽  
Path Following ◽  
Design Parameters ◽  
Line Of Sight ◽  
Roll Motion ◽  
Control Input ◽  
Problem Model ◽  
Trade Offs

Roll motion control and path following are two representative marine control problems that have been traditionally treated separately. However, these two problems are closely coupled, as roll motion could cause negative effects on marine surface vessels during path following in seaways and path following actions could cause undesirable roll motion. In this article, an optimal controller is proposed for the integrated path following and roll motion control problem. The rudder, whose actuation amplitude and rate are both limited, is the only control input, while the cross-track error, heading angle, roll rate, and roll angle are the outputs that collectively define the performance of the system. This leads to a classic underactuated problem. Model predictive control is the natural choice for the solution, given its capability in dealing with constraints and multi-input-multi-output system, and its design will be pursued in this article. Line of sight technique is used to extend the straight-line path following to arbitrary path following. A four degrees of freedom high-fidelity model is implemented as the simulation model, and the simulation results verify the effectiveness of the proposed controller. The influences of the control design parameters on system performance are investigated and the trade-offs between two key attributes, namely, the roll reduction and path following, are explored.

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