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Journal ArticleDOI

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

TL;DR: 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 $0.09<\Delta\beta<0.12$.
Citations
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Journal ArticleDOI
TL;DR: The Radio Experiment for the Analysis of Cosmic Hydrogen (REACH) is a sky-averaged 21 cm experiment aiming at improving the current observations by tackling the issues faced by current instruments related to residual systematic signals in the data as mentioned in this paper .
Abstract: Observations of the 21-cm line from primordial hydrogen promise to be one of the best tools to study the early epochs of the Universe: the dark ages, the cosmic dawn and the subsequent epoch of reionization. In 2018, the Experiment to Detect the Global Epoch of Reionization Signature (EDGES) caught the attention of the cosmology community with a potential detection of an absorption feature in the sky-averaged radio spectrum centred at 78 MHz. The feature is deeper than expected, and, if confirmed, would call for new physics. However, different groups have re-analysed the EDGES data and questioned the reliability of the signal. The Radio Experiment for the Analysis of Cosmic Hydrogen (REACH) is a sky-averaged 21-cm experiment aiming at improving the current observations by tackling the issues faced by current instruments related to residual systematic signals in the data. The novel experimental approach focuses on detecting and jointly explaining these systematics together with the foregrounds and the cosmological signal using Bayesian statistics. To achieve this, REACH features simultaneous observations with two different antennas, an ultra-wideband system (redshift range about 7.5 to 28) and a receiver calibrator based on in-field measurements. Simulated observations forecast percent-level constraints on astrophysical parameters, potentially opening up a new window to the infant Universe. The Radio Experiment for the Analysis of Cosmic Hydrogen (REACH) aims to detect the sky-averaged 21-cm neutral hydrogen line from the early Universe by jointly analysing the cosmological signal, foreground emission and systematic effects.

18 citations

Journal ArticleDOI
TL;DR: In this paper, a 2D cylindrical spatial power spectrum for data at 43.1-53.5 MHz incoherently integrated for 4 hours was presented, and an analysis of the array sensitivity was performed.
Abstract: The Large-aperture Experiment to detect the Dark Age (LEDA) was designed to measure the 21-cm signal from neutral hydrogen at Cosmic Dawn, $z \approx $15-30. Using observations made with the $\approx $ 200 m diameter core of the Owens Valley Long Wavelength Array (OVRO-LWA), we present a 2-D cylindrical spatial power spectrum for data at 43.1-53.5 MHz ($z_{\rm median}\approx 28$) incoherently integrated for 4 hours, and an analysis of the array sensitivity. Power from foregrounds is localized to a "wedge" within $k_\perp, k_\parallel$ space. After calibration of visibilities using 5 bright compact sources including VirA, we measure $\Delta^2(k) \approx 2 \times 10^{12}\ \mathrm{mK}^2$ outside the foreground wedge, where an uncontaminated cosmological signal would lie, in principle. The measured $\Delta^2(k)$ is an upper limit that reflects a combination of thermal instrumental and sky noise, and unmodelled systematics that scatter power from the wedge, as will be discussed. By differencing calibrated visibilities for close pairs of frequency channels, we suppress foreground sky structure and systematics, extract thermal noise, and use a mix of coherent and incoherent integration to simulate a noise-dominated power spectrum for a 3000 h observation and $z = $16-37. For suitable calibration quality, the resulting noise level, $\Delta^2(k) \approx 100$ mK$^2$ (k = 0.3 Mpc$^{-1}$), would be sufficient to detect peaks in the 21-cm spatial power spectrum due to early Ly-$\alpha$ and X-ray sources, as predicted for a range of theoretical model parameters.

17 citations

Journal ArticleDOI
TL;DR: The Bustling Universe Radio Survey Telescope in Taiwan (BURSTT) is optimized to discover and localize a large sample of rare, high-fluence, and nearby fast radio bursts as mentioned in this paper .
Abstract: Fast Radio Bursts (FRBs) are bright millisecond-duration radio transients that appear about 1000 times per day, all-sky, for a fluence threshold 5 Jy ms at 600 MHz. The FRB radio-emission physics and the compact objects involved in these events are subjects of intense and active debate. To better constrain source models, the Bustling Universe Radio Survey Telescope in Taiwan (BURSTT) is optimized to discover and localize a large sample of rare, high-fluence, and nearby FRBs. This population is the most amenable to multi-messenger and multi-wavelength follow-up, which allows a deeper understanding of source mechanisms. BURSTT will provide horizon-to-horizon sky coverage with a half power field-of-view (FoV) of ∼104 deg2, a 400 MHz effective bandwidth between 300 and 800 MHz, and subarcsecond localization, which is made possible using outrigger stations that are hundreds to thousands of km from the main array. Initially, BURSTT will employ 256 antennas. After tests of various antenna designs and optimizing the system’s performance, we plan to expand to 2048 antennas. We estimate that BURSTT-256 will detect and localize ∼100 bright (≥100 Jy ms) FRBs per year. Another advantage of BURSTT’s large FoV and continuous operation will be its greatly enhanced monitoring of FRBs for repetition. The current lack of sensitive all-sky observations likely means that many repeating FRBs are currently cataloged as single-event FRBs.

8 citations

Journal ArticleDOI
TL;DR: In this article, the impact of an X-ray background, such as high-energy photons from early quasars, on the temperature and ionization of the intergalactic medium prior to reionization, before the fully ionized bubbles associated with individual sources have overlapped.
Abstract: Observational studies indicate that the intergalactic medium (IGM) is highly ionized up to redshifts just over 6. A number of models have been developed to describe the process of reionization and the effects of the ionizing photons from the first luminous objects. In this paper, we study the impact of an X-ray background, such as high-energy photons from early quasars, on the temperature and ionization of the IGM prior to reionization, before the fully ionized bubbles associated with individual sources have overlapped. X-rays, which have large mean free paths relative to EUV photons, and their photoelectrons can have significant effects on the thermal and ionization balance. We find that hydrogen ionization is dominated by the X-ray photoionization of neutral helium and the resulting secondary electrons. Thus, the IGM may have been warm and weakly ionized prior to full reionization. We examine several related consequences, including the filtering of the baryonic Jeans mass scale, signatures in the cosmic microwave background, and the H$^{-}$-catalyzed production of molecular hydrogen.

7 citations

Peer Review
15 Mar 2022
TL;DR: The 21 cm line refers to a forbidden transition in neutral hydrogen associated with alignment of spins of the proton and electron and is a very low energy transition that is emitted whenever there is neutral hydrogen in the Universe as discussed by the authors .
Abstract: The 21 cm line refers to a forbidden transition in neutral hydrogen associated with alignment of spins of the proton and electron. It is a very low energy transition that is emitted whenever there is neutral hydrogen in the Universe. Since baryons are mostly ( ∼ 75%) hydrogen, one can in principle detect this emission throughout much of the history of the Universe. The dominant emission mechanism is different across cosmic ages. Before the photons decouple from matter, hydrogen is in an ionized state and does not emit in 21 cm. After recombination and during the Dark Ages, at z ∼ 30 − 1000 , the 21 cm emission is associated with density fluctuations in the neutral hydrogen medium. After the first stars turn on and galaxies begin to form, the 21 cm emission traces bubbles of ionized hydrogen in the sea of the neutral medium. This epoch, spanning z ∼ 6 − 30 , is often referred to as cosmic dawn and the Epoch of Reionization (EoR). At redshifts below z < 6 , the intergalactic medium is largely ionized, but pockets of self-shielded neutral gas form in dense galactic environments and 21 cm emission traces the distribution of galaxies. The vastly different emission mechanisms allow us to probe very different physics at different redshifts, corresponding to different observational frequencies. The instrumental challenges, namely building very sensitive and exquisitely calibrated radio telescopes, however, share many commonalities across frequency bands. The potential of the 21 cm probe has been recognized by the Decadal Survey of Astronomy & Astrophysics, whose Panel on Cosmology identified

6 citations

References
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Journal ArticleDOI
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.
Abstract: SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library 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. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments.

12,774 citations

Journal ArticleDOI
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.
Abstract: We present the first public version (v02) of the open-source and community-developed Python package, Astropy This package provides core astronomy-related functionality to the community, including support for domain-specific file formats such as flexible image transport system (FITS) files, Virtual Observatory (VO) tables, and 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 Significant functionality is under activedevelopment, such as a model fitting framework, VO client and server tools, and aperture and point spread function (PSF) photometry tools The core development team is actively making additions and enhancements to the current code base, and we encourage anyone interested to participate in the development of future Astropy versions

9,720 citations

Journal ArticleDOI
16 Sep 2020-Nature
TL;DR: In this paper, the authors review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data, and their evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.
Abstract: Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.

7,624 citations

Journal ArticleDOI
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.
Abstract: SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy 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. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

6,244 citations

Journal ArticleDOI
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.
Abstract: HEALPix the Hierarchical Equal Area isoLatitude Pixelization is a versatile structure for the pixelization of data on the sphere. An associated library of computational algorithms and visualization software supports fast scientific applications executable directly on discretized spherical maps generated from very large volumes of astronomical data. Originally developed to address the data processing and analysis needs of the present generation of cosmic microwave background experiments (e.g., BOOMERANG, WMAP), HEALPix can be expanded to meet many of the profound challenges that will arise in confrontation with the observational output of future missions and experiments, including, e.g., Planck, Herschel, SAFIR, and the Beyond Einstein inflation probe. In this paper we consider 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. We demonstrate how these are explicitly satisfied by HEALPix.

5,518 citations

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