Constraining the 21 cm brightness temperature of the IGM at z = 6.6 around LAEs with the murchison widefield array

The locations of Ly α-emitting galaxies (LAEs) at the end of the Epoch of Reionization (EoR) are expected to correlate with regions of ionized hydrogen, traced by the redshifted 21 cm hyperfine line. Mapping the neutral hydrogen around regions with detected and localized LAEs offers an avenue to constrain the brightness temperature of the Universe within the EoR by providing an expectation for the spatial distribution of the gas, thereby providing prior information unavailable to power spectrum measurements. We use a test set of 12 h of observations from the Murchison Widefield Array (MWA) in extended array configuration, to constrain the neutral hydrogen signature of 58 LAEs, detected with the Subaru Hypersuprime Cam in the Silverrush survey, centred on z = 6.58. We assume that detectable emitters reside in the centre of ionized H II bubbles during the end of reionization, and predict the redshifted neutral hydrogen signal corresponding to the remaining neutral regions using a set of different ionized bubble radii. A pre-whitening matched filter detector is introduced to assess detectability. We demonstrate the ability to detect, or place limits upon, the amplitude of brightness temperature fluctuations, and the characteristic H II bubble size. With our limited data, we constrain the brightness temperature of neutral hydrogen to ΔTB B = 15 ± 2h-1 cMpc

A Real Time Processing system for big data in astronomy: Applications to HERA

As current- and next-generation astronomical instruments come online, they will generate an unprecedented deluge of data. Analyzing these data in real time presents unique conceptual and computational challenges, and their long-term storage and archiving is scientifically essential for generating reliable, reproducible results. We present here the real-time processing (RTP) system for the Hydrogen Epoch of Reionization Array (HERA), a radio interferometer endeavoring to provide the first detection of the highly redshifted 21 cm signal from Cosmic Dawn and the Epoch of Reionization by an interferometer. The RTP system consists of analysis routines run on raw data shortly after they are acquired, such as calibration and detection of radio-frequency interference (RFI) events. RTP works closely with the Librarian, the HERA data storage and transfer manager which automatically ingests data and transfers copies to other clusters for post-processing analysis. Both the RTP system and the Librarian are public and open source software, which allows for them to be modified for use in other scientific collaborations. When fully constructed, HERA is projected to generate over 50 terabytes (TB) of data each night, and the RTP system enables the successful scientific analysis of these data

Measuring HERA's Primary Beam in Situ: Methodology and First Results

The central challenge in 21 cm cosmology is isolating the cosmological signal from bright foregrounds. Many separation techniques rely on the accurate knowledge of the sky and the instrumental response, including the antenna primary beam. For drift-scan telescopes, such as the Hydrogen Epoch of Reionization Array (HERA), that do not move, primary beam characterization is particularly challenging because standard beam-calibration routines do not apply (Cornwell et al.) and current techniques require accurate source catalogs at the telescope resolution. We present an extension of the method from Pober et al. where they use beam symmetries to create a network of overlapping source tracks that break the degeneracy between source flux density and beam response and allow their simultaneous estimation. We fit the beam response of our instrument using early HERA observations and find that our results agree well with electromagnetic simulations down to a -20 dB level in power relative to peak gain for sources with high signal-to-noise ratio. In addition, we construct a source catalog with 90 sources down to a flux density of 1.4 Jy at 151 MHz.The central challenge in 21 cm cosmology is isolating the cosmological signal from bright foregrounds. Many separation techniques rely on the accurate knowledge of the sky and the instrumental response, including the antenna primary beam. For drift-scan telescopes, such as the Hydrogen Epoch of Reionization Array (HERA), that do not move, primary beam characterization is particularly challenging because standard beam-calibration routines do not apply (Cornwell et al.) and current techniques require accurate source catalogs at the telescope resolution. We present an extension of the method from Pober et al. where they use beam symmetries to create a network of overlapping source tracks that break the degeneracy between source flux density and beam response and allow their simultaneous estimation. We fit the beam response of our instrument using early HERA observations and find that our results agree well with electromagnetic simulations down to a -20 dB level in power relative to peak gain for sources with high signal-to-noise ratio. In addition, we construct a source catalog with 90 sources down to a flux density of 1.4 Jy at 151 MHz

Optimizing sparse RFI prediction using deep learning

Radio frequency interference (RFI) is an ever-present limiting factor among radio telescopes even in the most remote observing locations. When looking to retain the maximum amount of sensitivity and reduce contamination for Epoch of Reionization studies, the identification and removal of RFI is especially important. In addition to improved RFI identification, we must also take into account computational efficiency of the RFI-Identification algorithm as radio interferometer arrays such as the Hydrogen Epoch of Reionization Array (HERA) grow larger in number of receivers. To address this, we present a deep fully convolutional neural network (DFCN) that is comprehensive in its use of interferometric data, where both amplitude and phase information are used jointly for identifying RFI. We train the network using simulated HERA visibilities containing mock RFI, yielding a known \u2018ground truth\u2019 data set for evaluating the accuracy of various RFI algorithms. Evaluation of the DFCN model is performed on observations from the 67 dish build-out, HERA-67, and achieves a data throughput of 1.6 7 105 HERA time-ordered 1024 channelled visibilities per hour per GPU. We determine that relative to an amplitude only network including visibility phase adds important adjacent time\u2013frequency context which increases discrimination between RFI and non-RFI. The inclusion of phase when predicting achieves a recall of 0.81, precision of 0.58, and F2 score of 0.75 as applied to our HERA-67 observations

Detection of cosmic structures using the bispectrum phase. II. First results from application to cosmic reionization using the Hydrogen Epoch of Reionization Array

Characterizing the epoch of reionization (EoR) at $z\gtrsim 6$ via the redshifted 21 cm line of neutral Hydrogen (HI) is critical to modern astrophysics and cosmology, and thus a key science goal of many current and planned low-frequency radio telescopes. The primary challenge to detecting this signal is the overwhelmingly bright foreground emission at these frequencies, placing stringent requirements on the knowledge of the instruments and inaccuracies in analyses. Results from these experiments have largely been limited not by thermal sensitivity but by systematics, particularly caused by the inability to calibrate the instrument to high accuracy. The interferometric bispectrum phase is immune to antenna-based calibration and errors therein, and presents an independent alternative to detect the EoR HI fluctuations while largely avoiding calibration systematics. Here, we provide a demonstration of this technique on a subset of data from the Hydrogen Epoch of Reionization Array (HERA) to place approximate constraints on the IGM brightness temperature. From this limited data, at $z=7.7$ we infer "$1\sigma$" upper limits on the IGM brightness temperature to be $\le 316$ "pseudo" mK at $\kappa_\parallel=0.33\,\textrm{"pseudo"}\,h$ Mpc$^{-1}$ (data-limited) and $\le 1000$ "pseudo" mK at $\kappa_\parallel=0.875\,\textrm{"pseudo"}\,h$ Mpc$^{-1}$ (noise-limited). The "pseudo" units denote only an approximate and not an exact correspondence to the actual distance scales and brightness temperatures. By propagating models in parallel to the data analysis, we confirm that the dynamic range required to separate the cosmic HI signal from the foregrounds is similar to that in standard approaches, and the power spectrum of the bispectrum phase is still data-limited (at $\gtrsim 10^6$ dynamic range) indicating scope for further improvement in sensitivity as the array build-out continues

Detection of cosmic structures using the bispectrum phase. II. First results from application to cosmic reionization using the Hydrogen Epoch of Reionization Array

Characterizing the epoch of reionization (EoR) at $z\gtrsim 6$ via the redshifted 21 cm line of neutral Hydrogen (HI) is critical to modern astrophysics and cosmology, and thus a key science goal of many current and planned low-frequency radio telescopes. The primary challenge to detecting this signal is the overwhelmingly bright foreground emission at these frequencies, placing stringent requirements on the knowledge of the instruments and inaccuracies in analyses. Results from these experiments have largely been limited not by thermal sensitivity but by systematics, particularly caused by the inability to calibrate the instrument to high accuracy. The interferometric bispectrum phase is immune to antenna-based calibration and errors therein, and presents an independent alternative to detect the EoR HI fluctuations while largely avoiding calibration systematics. Here, we provide a demonstration of this technique on a subset of data from the Hydrogen Epoch of Reionization Array (HERA) to place approximate constraints on the IGM brightness temperature. From this limited data, at $z=7.7$ we infer "$1\sigma$" upper limits on the IGM brightness temperature to be $\le 316$ "pseudo" mK at $\kappa_\parallel=0.33\,\textrm{"pseudo"}\,h$ Mpc$^{-1}$ (data-limited) and $\le 1000$ "pseudo" mK at $\kappa_\parallel=0.875\,\textrm{"pseudo"}\,h$ Mpc$^{-1}$ (noise-limited). The "pseudo" units denote only an approximate and not an exact correspondence to the actual distance scales and brightness temperatures. By propagating models in parallel to the data analysis, we confirm that the dynamic range required to separate the cosmic HI signal from the foregrounds is similar to that in standard approaches, and the power spectrum of the bispectrum phase is still data-limited (at $\gtrsim 10^6$ dynamic range) indicating scope for further improvement in sensitivity as the array build-out continues

Automated Detection of Antenna Malfunctions in Large-N Interferometers: A case study With the Hydrogen Epoch of Reionization Array

We present a framework for identifying and flagging malfunctioning antennas in large radio interferometers. We outline two distinct categories of metrics designed to detect outliers along known failure modes of large arrays: cross-correlation metrics, based on all antenna pairs, and auto-correlation metrics, based solely on individual antennas. We define and motivate the statistical framework for all metrics used, and present tailored visualizations that aid us in clearly identifying new and existing systematics. We implement these techniques using data from 105 antennas in the Hydrogen Epoch of Reionization Array (HERA) as a case study. Finally, we provide a detailed algorithm for implementing these metrics as flagging tools on real data sets

Validation of the HERA Phase i Epoch of Reionization 21 cm Power Spectrum Software Pipeline

We describe the validation of the HERA Phase I software pipeline by a series of modular tests, building up to an end-to-end simulation. The philosophy of this approach is to validate the software and algorithms used in the Phase I upper-limit analysis on wholly synthetic data satisfying the assumptions of that analysis, not addressing whether the actual data meet these assumptions. We discuss the organization of this validation approach, the specific modular tests performed, and the construction of the end-to-end simulations. We explicitly discuss the limitations in scope of the current simulation effort. With mock visibility data generated from a known analytic power spectrum and a wide range of realistic instrumental effects and foregrounds, we demonstrate that the current pipeline produces power spectrum estimates that are consistent with known analytic inputs to within thermal noise levels (at the 2σ level) for k > 0.2h Mpc-1 for both bands and fields considered. Our input spectrum is intentionally amplified to enable a strong "detection"at k ∼ 0.2 h Mpc-1 - at the level of ∼25σ - with foregrounds dominating on larger scales and thermal noise dominating at smaller scales. Our pipeline is able to detect this amplified input signal after suppressing foregrounds with a dynamic range (foreground to noise ratio) of ⪆107. Our validation test suite uncovered several sources of scale-independent signal loss throughout the pipeline, whose amplitude is well-characterized and accounted for in the final estimates. We conclude with a discussion of the steps required for the next round of data analysis

Foreground modelling via Gaussian process regression: An application to HERA data

The key challenge in the observation of the redshifted 21-cm signal from cosmic reionization is its separation from the much brighter foreground emission. Such separation relies on the different spectral properties of the two components, although, in real life, the foreground intrinsic spectrum is often corrupted by the instrumental response, inducing systematic effects that can further jeopardize the measurement of the 21-cm signal. In this paper, we use Gaussian Process Regression to model both foreground emission and instrumental systematics in $\sim 2$ hours of data from the Hydrogen Epoch of Reionization Array. We find that a simple co-variance model with three components matches the data well, giving a residual power spectrum with white noise properties. These consist of an "intrinsic" and instrumentally corrupted component with a coherence-scale of 20 MHz and 2.4 MHz respectively (dominating the line of sight power spectrum over scales $k_{\parallel} \le 0.2$ h cMpc$^{-1}$) and a baseline dependent periodic signal with a period of $\sim 1$ MHz (dominating over $k_{\parallel} \sim 0.4 - 0.8$h cMpc$^{-1}$) which should be distinguishable from the 21-cm EoR signal whose typical coherence-scales is $\sim 0.8$ MHz