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Open AccessJournal ArticleDOI

Erratum: Spectral index of the Galactic foreground emission in the 50–87 MHz range

TLDR
In this paper, a subset of data from the Large-aperture Experiment to Detect the Dark Age (LEDA) in the range $50-87$~MHz and constrain the foreground spectral index in the northern sky visible from mid-latitudes.
Abstract
Total-power radiometry with individual meter-wave antennas is a potentially effective way to study the Cosmic Dawn ($z\sim20$) through measurement of sky brightness arising from the $21$~cm transition of neutral hydrogen, provided this can be disentangled from much stronger Galactic and extra-galactic foregrounds. In the process, measured spectra of integrated sky brightness temperature can be used to quantify the foreground emission properties. In this work, we analyze a subset of data from the Large-aperture Experiment to Detect the Dark Age (LEDA) in the range $50-87$~MHz and constrain the foreground spectral index $\beta$ in the northern sky visible from mid-latitudes. We focus on two zenith-directed LEDA radiometers and study how estimates of $\beta$ vary with local sidereal time (LST). We correct for the effect of gain pattern chromaticity and compare estimated absolute temperatures with simulations. We develop a reference dataset consisting of 14 days of optimal condition observations. Using this dataset we estimate, for one radiometer, that $\beta$ varies from $-2.55$ at LST~$<6$~h to a steeper $-2.58$ at LST~$\sim13$~h, consistently with sky models and previous southern sky measurements. In the LST~$=13-24$~h range, however, we find that $\beta$ fluctuates between $-2.55$ and $-2.61$ (data scatter $\sim0.01$). We observe a similar $\beta$ vs. LST trend for the second radiometer, although with slightly smaller $|\beta|$, in the $-2.46<\beta<-2.43$ range, over $24$~h of LST (data scatter $\sim0.02$). Combining all data gathered during the extended campaign between mid-2018 to mid-2019, and focusing on the LST~$=9-12.5$~h range, we infer good instrument stability and find $-2.56<\beta<-2.50$ with $0.09<\Delta\beta<0.12$.

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Bayesian evidence-driven diagnosis of instrumental systematics for sky-averaged 21-cm cosmology experiments

TL;DR: A Bayesian evidence-based model comparison is capable of determining whether or not such a systematic model is needed as the true underlying generative model of an experimental dataset is in principle unknown.
References
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Journal ArticleDOI

SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python

TL;DR: SciPy as discussed by the authors is an open source scientific computing library for the Python programming language, which includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics.
Journal ArticleDOI

Astropy: A community Python package for astronomy

TL;DR: Astropy as discussed by the authors is a Python package for astronomy-related functionality, including support for domain-specific file formats such as flexible image transport system (FITS) files, Virtual Observatory (VO) tables, common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions.
Journal ArticleDOI

SciPy 1.0: fundamental algorithms for scientific computing in Python.

TL;DR: SciPy as discussed by the authors is an open-source scientific computing library for the Python programming language, which has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year.
Journal ArticleDOI

HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere

TL;DR: This paper considers the requirements and implementation constraints on a framework that simultaneously enables an efficient discretization with associated hierarchical indexation and fast analysis/synthesis of functions defined on the sphere and demonstrates how these are explicitly satisfied by HEALPix.
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