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Record W4236805167 · doi:10.1093/mnras/stab1363

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

2021· article· en· W4236805167 on OpenAlexfundno aff
Marta Spinelli, G. Bernardi, Hugh Garsden, L J Greenhill, Anastasia Fialkov, Jayce Dowell, Danny C. Price

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsnot available
FundersInstituto Nazionale di Fisica NucleareInstitut sur la Nutrition et les Aliments FonctionnelsRoyal SocietyNational Science Foundation
KeywordsSkySidereal timePhysicsSky brightnessRadiometerSpectral indexAstrophysicsBrightnessZenithLatitudeBrightness temperatureAstronomySpectral lineRemote sensingOpticsGeography

Abstract

fetched live from OpenAlex

ABSTRACT Total-power radiometry with individual meter-wave antennas is a potentially effective way to study the Cosmic Dawn (z ∼ 20) through measurement of the 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 analyse a subset of data from the Large-aperture Experiment to Detect the Dark Age (LEDA) in the 50–87 MHz range and constrain the foreground spectral index β in the northern sky visible from mid-latitudes. We focus on two zenith-directed LEDA radiometers and study how estimates of β vary with local sidereal time (LST). We correct for the effect of gain pattern chromaticity and compare estimated absolute temperatures with simulations. We select a reference data set consisting of 14 d of observations in optimal conditions. Using this data set, we find, for one radiometer, that β varies from −2.55 at LST <6 h to a steeper −2.58 at LST ∼13 h, consistently with sky models and previous southern sky measurements. In the 13 − 24 h LST range, however, we find that β varies between −2.55 and −2.61 (data scatter ∼0.01). We observe a similar β versus LST trend for the second radiometer, although with slightly smaller |β| over the 24 h, in the −2.46 < β < −2.43 range (data scatter ∼ 0.02). Combining all data gathered during the extended campaign between mid-2018 and mid-2019, and focusing on the LST = 9−12.5 h range, we infer good instrument stability and find −2.56 < β < −2.50 with 0.09 < Δβ < 0.12.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.212
Teacher spread0.202 · 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 designObservational
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

Citations28
Published2021
Admission routes1
Has abstractyes

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