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Through a very careful analysis Kolopanis and collaborators identified a negative power spectrum (PS) systematic. The 21 cm cosmology community has assumed that any observational systematics would add power, as negative PS are non-physical. In addition to the mystery of their origin, negative PS systematics raise the spectre of artificially lowering upper limits on the 21 cm PS. It appears that the source of the negative PS systematics is a subtle interaction between choices in how the PS estimate is calculated and baseline-dependent systematic power. In this paper, we present a statistical model of baseline dependent systematics to explore how negative PS systematics can appear and their statistical characteristics. This leads us to recommendations on when and how to consider negative PS systematics when reporting observational 21 cm cosmology upper limits.

 

We present deep upper limits from the 2014 Murchison Widefield Array Phase I observing season, with a particular emphasis on identifying the spectral fingerprints of extremely faint radio frequency interference (RFI) contamination in the 21 cm power spectra (PS). After meticulous RFI excision involving a combination of theSSINSRFI flagger and a series of PS-based jackknife tests, our lowest upper limit on the Epoch of Reionization (EoR) 21 cm PS signal is Δ²≤ 1.61 × 10⁴mK²atk= 0.258h Mpc⁻¹at a redshift of 7.1 using 14.7 hr of data. By leveraging our understanding of how even fainter RFI is likely to contaminate the EoR PS, we are able to identify ultrafaint RFI signals in the cylindrical PS. Surprisingly this signature is most obvious in PS formed with less than 1 hr of data, but is potentially subdominant to other systematics in multiple-hour integrations. Since the total RFI budget in a PS detection is quite strict, this nontrivial integration behavior suggests a need to more realistically model coherently integrated ultrafaint RFI in PS measurements so that its potential contribution to a future detection can be diagnosed.

 

We explore how chromatic radio frequency interference (RFI) flags affect 21-cm power spectrum measurements. We particularly study flags that are coarser than the analysis resolution. We find that such RFI flags produce excess power in the EoR window in much the same way as residual RFI. We use Fast Holographic Deconvolution (fhd) simulations to explain this as a result of chromatic disruptions in the interferometric sampling function of the array. We also use these simulations in conjunction with Error Propagated Power Spectrum with InterLeaved Observed Noise to show that without modifying current flagging strategies or implementing extremely accurate and complete foreground subtraction, 21-cm EoR experiments will fail to make a significant detection. As a mitigation strategy, we find that circumventing the chromatic structure altogether by flagging the entire analysis band when RFI is detected is simple to implement and highly successful. This demands a detection strategy with a low false-positive rate in order to prevent excessive data loss.

 

This paper presents the design and deployment of the Hydrogen Epoch of Reionization Array (HERA) phase II system. HERA is designed as a staged experiment targeting 21 cm emission measurements of the Epoch of Reionization. First results from the phase I array are published as of early 2022, and deployment of the phase II system is nearing completion. We describe the design of the phase II system and discuss progress on commissioning and future upgrades. As HERA is a designated Square Kilometre Array pathfinder instrument, we also show a number of “case studies” that investigate systematics seen while commissioning the phase II system, which may be of use in the design and operation of future arrays. Common pathologies are likely to manifest in similar ways across instruments, and many of these sources of contamination can be mitigated once the source is identified.

 

We present a broad-band map of polarized diffuse emission at 167–198 MHz developed from data from the Murchison Widefield Array (MWA). The map is designed to improve visibility simulation and precision calibration for 21 cm Epoch of Reionization (EoR) experiments. It covers a large swath – 11 000 sq. deg. – of the Southern hemisphere sky in all four Stokes parameters and captures emission on angular scales of 1–9°. The band-averaged diffuse structure is pre-dominantly unpolarized but has significant linearly polarized structure near RA  = 0 h. We evaluate the accuracy of the map by combining it with the GLEAM catalogue and simulating an observation from the MWA, demonstrating that the accuracy of the short baselines (6.1–50 wavelengths) now approaches the accuracy of the longer baselines typically used for EoR calibration. We discuss how to use the map for visibility simulation for a variety of interferometric arrays. The map has potential to improve calibration accuracy for experiments such as the Hydrogen Epoch of Reionization Array and the forthcoming Square Kilometre Array as well as the MWA.

 

ABSTRACT Calibration precision is currently a limiting systematic in 21 cm cosmology experiments. While there are innumerable calibration approaches, most can be categorized as either ‘sky-based,’ relying on an extremely accurate model of astronomical foreground emission, or ‘redundant,’ requiring a precisely regular array with near-identical antenna response patterns. Both of these classes of calibration are inflexible to the realities of interferometric measurement. In practice, errors in the foreground model, antenna position offsets, and beam response inhomogeneities degrade calibration performance and contaminate the cosmological signal. Here, we show that sky-based and redundant calibration can be unified into a highly general and physically motivated calibration framework based on a Bayesian statistical formalism. Our new framework includes sky-based and redundant calibration as special cases but can additionally support relaxing the rigid assumptions implicit in those approaches. We present simulation results demonstrating that, in a simple case, working in an intermediate regime between sky-based and redundant calibration improves calibration performance. Our framework is highly general and encompasses novel calibration approaches including techniques for calibrating compact non-redundant arrays, calibrating to incomplete sky models, and constraining calibration solutions across frequency. 

ABSTRACT We quantify the effect of radio frequency interference (RFI) on measurements of the 21-cm power spectrum during the Epoch of Reionization (EoR). Specifically, we investigate how the frequency structure of RFI source emission generates contamination in higher order wave modes, which is much more problematic than smooth-spectrum foreground sources. Using a relatively optimistic EoR model, we find that even a single relatively dim RFI source can overwhelm the EoR power spectrum signal of $\sim 10\, {\rm mK}^2$ for modes $0.1 \ \lt k \lt 2 \, h\, {\rm Mpc}^{-1}$. If the total apparent RFI flux density in the final power spectrum integration is kept below 1 mJy, an EoR signal resembling this optimistic model should be detectable for modes $k \lt 0.9\, h\, {\rm Mpc}^{-1}$, given no other systematic contaminants and an error tolerance as high as 10 per cent. More pessimistic models will be more restrictive. These results emphasize the need for highly effective RFI mitigation strategies for telescopes used to search for the EoR. 

To mitigate the effects of Radio Frequency Interference (RFI) on the data analysis pipelines of 21 cm interferometric instruments, numerous inpaint techniques have been developed. In this paper, we examine the qualitative and quantitative errors introduced into the visibilities and power spectrum due to inpainting. We perform our analysis on simulated data as well as real data from the Hydrogen Epoch of Reionization Array (HERA) Phase 1 upper limits. We also introduce a convolutional neural network that is capable of inpainting RFI corrupted data. We train our network on simulated data and show that our network is capable of inpainting real data without requiring to be retrained. We find that techniques that incorporate high wavenumbers in delay space in their modelling are best suited for inpainting over narrowband RFI. We show that with our fiducial parameters discrete prolate spheroidal sequences (dpss) and clean provide the best performance for intermittent RFI while Gaussian progress regression (gpr) and least squares spectral analysis (lssa) provide the best performance for larger RFI gaps. However, we caution that these qualitative conclusions are sensitive to the chosen hyperparameters of each inpainting technique. We show that all inpainting techniques reliably reproduce foreground dominated modes in the power spectrum. Since the inpainting techniques should not be capable of reproducing noise realizations, we find that the largest errors occur in the noise dominated delay modes. We show that as the noise level of the data comes down, clean and dpss are most capable of reproducing the fine frequency structure in the visibilities.