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  1. Free, publicly-accessible full text available April 1, 2023
  2. Abstract

    We report the most sensitive upper limits to date on the 21 cm epoch of reionization power spectrum using 94 nights of observing with Phase I of the Hydrogen Epoch of Reionization Array (HERA). Using similar analysis techniques as in previously reported limits, we find at 95% confidence that Δ2(k= 0.34hMpc−1) ≤ 457 mK2atz= 7.9 and that Δ2(k= 0.36hMpc−1) ≤ 3496 mK2atz= 10.4, an improvement by a factor of 2.1 and 2.6, respectively. These limits are mostly consistent with thermal noise over a wide range ofkafter our data quality cuts, despite performing a relatively conservative analysis designed to minimize signal loss. Our results are validated with both statistical tests on the data and end-to-end pipeline simulations. We also report updated constraints on the astrophysics of reionization and the cosmic dawn. Using multiple independent modeling and inference techniques previously employed by HERA Collaboration, we find that the intergalactic medium must have been heated above the adiabatic cooling limit at least as early asz= 10.4, ruling out a broad set of so-called “cold reionization” scenarios. If this heating is due to high-mass X-ray binaries during the cosmic dawn, as is generally believed, our result’s 99% credible interval excludes the local relationshipmore »between soft X-ray luminosity and star formation and thus requires heating driven by evolved low-metallicity stars.

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  3. Abstract

    Recent extreme fire seasons in California have prompted utilities such as Pacific Gas and Electric to pre-emptively de-energize portions of the electrical grid during periods of extreme fire weather to reduce the risk of powerline-related fire ignitions. The policy was deployed in 2019, resulting in 12 million person-days of power outages and widespread societal disruption. Retrospective weather and vegetation moisture data highlight hotspots of historical risk across northern California. We estimate an average of 1.6 million person-days of de-energization per year, based on recent historical climate conditions and assuming publicly stated utility de-energization thresholds. We further estimate an additional 70% increase in the population affected by de-energization when vegetation remains abnormally dry later into autumn—suggesting that climate change will likely increase population vulnerable to de-energization. Adaptation efforts to curtail fire risk can be beneficial, but efforts to prepare affected populations, modernize the grid, and refine decision-making surrounding such policies have high potential to reduce the magnitude of negative externalities experienced during the 2019 de-energization events.

  4. Abstract

    Motivated by the desire for wide-field images with well-defined statistical properties for 21 cm cosmology, we implement an optimal mapping pipeline that computes a maximum likelihood estimator for the sky using the interferometric measurement equation. We demonstrate this “direct optimal mapping” with data from the Hydrogen Epoch of Reionization (HERA) Phase I observations. After validating the pipeline with simulated data, we develop a maximum likelihood figure-of-merit for comparing four sky models at 166 MHz with a bandwidth of 100 kHz. The HERA data agree with the GLEAM catalogs to < 10%. After subtracting the GLEAM point sources, the HERA data discriminate between the different continuum sky models, providing most support for the model of Byrne et al. We report the computation cost for mapping the HERA Phase I data and project the computation for the HERA 320-antenna data; both are feasible with a modern server. The algorithm is broadly applicable to other interferometers and is valid for wide-field and noncoplanar arrays.

  5. Abstract We report upper limits on the Epoch of Reionization 21 cm power spectrum at redshifts 7.9 and 10.4 with 18 nights of data (∼36 hr of integration) from Phase I of the Hydrogen Epoch of Reionization Array (HERA). The Phase I data show evidence for systematics that can be largely suppressed with systematic models down to a dynamic range of ∼10 9 with respect to the peak foreground power. This yields a 95% confidence upper limit on the 21 cm power spectrum of Δ 21 2 ≤ ( 30.76 ) 2 mK 2 at k = 0.192 h Mpc −1 at z = 7.9, and also Δ 21 2 ≤ ( 95.74 ) 2 mK 2 at k = 0.256 h Mpc −1 at z = 10.4. At z = 7.9, these limits are the most sensitive to date by over an order of magnitude. While we find evidence for residual systematics at low line-of-sight Fourier k ∥ modes, at high k ∥ modes we find our data to be largely consistent with thermal noise, an indicator that the system could benefit from deeper integrations. The observed systematics could be due to radio frequency interference, cable subreflections, or residualmore »instrumental cross-coupling, and warrant further study. This analysis emphasizes algorithms that have minimal inherent signal loss, although we do perform a careful accounting in a companion paper of the small forms of loss or bias associated with the pipeline. Overall, these results are a promising first step in the development of a tuned, instrument-specific analysis pipeline for HERA, particularly as Phase II construction is completed en route to reaching the full sensitivity of the experiment.« less
  6. Abstract 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 2 σ level) for k > 0.2 h 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 ∼25 σ —with foregrounds dominating on larger scales and thermal noise dominating at smaller scales. Our pipeline is able to detect this amplifiedmore »input signal after suppressing foregrounds with a dynamic range (foreground to noise ratio) of ≳10 7 . 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.« less