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Record W3006601662 · doi:10.3847/1538-4365/ab77b1

Imaging and Modeling Data from the Hydrogen Epoch of Reionization Array

2020· preprint· en· W3006601662 on OpenAlexaff
C. L. Carilli, Nithyanandan Thyagarajan, James Kent, Bojan Nikolic, Kingsley Gale‐Sides, Nicholas S. Kern, G. Bernardi, A. Mesinger, Siyanda Matika, Socorro, Orcid, Richard F. Bradley

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2020
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsMcGill University
FundersNational Radio Astronomy Observatory
KeywordsReionizationHERAPhysicsAstrophysicsSkyZenithAstronomyGalaxyOpticsRedshift

Abstract

fetched live from OpenAlex

Abstract We analyze data from the Hydrogen Epoch of Reionization Array (HERA). This is the third in a series of papers on the closure phase delay spectrum technique designed to detect the H i 21 cm emission from cosmic reionization. We present the details of the data and models employed in the power spectral analysis and discuss limitations to the process. We compare images and visibility spectra made with HERA data to parallel quantities generated from sky models based on the Galactic and Extra-Galactic All-Sky MWA (GLEAM) survey, incorporating the HERA telescope model. We find reasonable agreement between images made from HERA data with those generated from the models, down to the confusion level. For the visibility spectra, there is broad agreement between model and data across the full band of ∼80 MHz. However, models with only GLEAM sources do not reproduce a roughly sinusoidal spectral structure at the tens of percent level seen in the observed visibility spectra on scales of ∼10 MHz on 29 m baselines. We find that this structure is likely due to diffuse Galactic emission, predominantly the Galactic plane, filling the far sidelobes of the antenna primary beam. We show that our current knowledge of the frequency dependence of the diffuse sky radio emission, and the primary beam at large zenith angles, is inadequate to provide an accurate reproduction of the diffuse structure in the models. We discuss some implications arising due to this missing structure in the models, in terms of calibration, and in the search for the H i 21 cm signal, as well as possible mitigation techniques.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.656
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.267
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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