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To correctly analyse data sets from current microwave detection technology, one is forced to estimate the sky signal and experimental noise simultaneously. Given a time-ordered data set we propose a formalism and method for estimating the signal and associated errors without prior knowledge of the noise power spectrum. We derive the method using a Bayesian formalism and relate it to the standard methods; in particular we show how this leads to a change in the estimate of the noise covariance matrix of the sky signal. We study the convergence and accuracy of the method on two mock observational strategies and discuss its application to a currently-favoured calibration procedure.
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In this lecture, after a synthetic review of measurements of CMB temperature anisotropies and of their cosmological implications, the theoretical background of CMB polarization is summarized and the concepts of the main experiments that are ongoing or are being planned are briefly described.
The desire for higher sensitivity has driven ground-based cosmic microwave background (CMB) experiments to employ ever larger focal planes, which in turn require larger reimaging optics. Practical limits to the maximum size of these optics motivates the development of quasi-optically-coupled (lenslet-coupled), multi-chroic detectors. These detectors can be sensitive across a broader bandwidth compared to waveguide-coupled detectors. However, the increase in bandwidth comes at a cost: the lenses (up to $sim$700 mm diameter) and lenslets ($sim$5 mm diameter, hemispherical lenses on the focal plane) used in these systems are made from high-refractive-index materials (such as silicon or amorphous aluminum oxide) that reflect nearly a third of the incident radiation. In order to maximize the faint CMB signal that reaches the detectors, the lenses and lenslets must be coated with an anti-reflective (AR) material. The AR coating must maximize radiation transmission in scientifically interesting bands and be cryogenically stable. Such a coating was developed for the third generation camera, SPT-3G, of the South Pole Telescope (SPT) experiment, but the materials and techniques used in the development are general to AR coatings for mm-wave optics. The three-layer polytetrafluoroethylene-based AR coating is broadband, inexpensive, and can be manufactured with simple tools. The coating is field tested; AR coated focal plane elements were deployed in the 2016-2017 austral summer and AR coated reimaging optics were deployed in 2017-2018.
The large size of the time ordered data of cosmic microwave background experiments presents challenges for mission planning and data analysis. These issues are particularly significant for Antarctica- and space-based experiments, which depend on satellite links to transmit data. We explore the viability of reducing the time ordered data to few bit numbers to address these challenges. Unlike lossless compression, few bit digitisation introduces additional noise into the data. We present a set of one, two, and three bit digitisation schemes and measure the increase in noise in the cosmic microwave background temperature and polarisation power spectra. The digitisation noise is independent of angular scale and is well-described as a constant percentage of the original detector noise. Three bit digitisation increases the map noise level by < 2%, while reducing the data volume by a factor of ten relative to 32-bit floats. Extreme digitisation is a promising strategy for upcoming experiments.
The observation of cosmic microwave background (CMB) anisotropies is one of the key probes of physical cosmology. The weak nature of this signal has driven the construction of increasingly complex and sensitive experiments observing the sky at multiple frequencies with thousands of polarization sensitive detectors. Given the high sensitivity of such experiments, instrumental systematic effects can become the limiting factor towards the full scientific exploitation of their data. In this paper we present s4cmb (Systematics for CMB), a Python package designed to simulate raw data streams in time domain of modern CMB experiments based on bolometric technology, and to inject in these realistic instrumental systematics effects. The aim of the package is to help assessing the contamination due to instrumental systematic effects on real data, to guide the design of future instruments, as well as to increase the realism of simulated data sets required in the development of accurate data analysis methods.
An algorithm is proposed for denoising the signal induced by cosmic strings in the cosmic microwave background (CMB). A Bayesian approach is taken, based on modeling the string signal in the wavelet domain with generalized Gaussian distributions. Good performance of the algorithm is demonstrated by simulated experiments at arcminute resolution under noise conditions including primary and secondary CMB anisotropies, as well as instrumental noise.
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