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Record W1966633224 · doi:10.1093/mnrasl/slt074

Determination of <i>z</i> ∼ 0.8 neutral hydrogen fluctuations using the 21 cm intensity mapping autocorrelation

2013· article· en· W1966633224 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsMcGill UniversityCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersNational Astronomical Observatories, Chinese Academy of SciencesNatural Sciences and Engineering Research Council of CanadaAssociated UniversitiesCanadian Institute for Advanced ResearchJohn Templeton FoundationNational Natural Science Foundation of ChinaNational Radio Astronomy ObservatoryNational Science Foundation
KeywordsPhysicsRedshiftIntensity mappingAstrophysicsSpectral densityUpper and lower boundsGalaxyRadio telescopeIntensity (physics)Computational physicsStatisticsOpticsMathematics

Abstract

fetched live from OpenAlex

Abstract The large-scale distribution of neutral hydrogen in the Universe will be luminous through its 21 cm emission. Here, for the first time, we use the auto-power spectrum of 21 cm intensity fluctuations to constrain neutral hydrogen fluctuations at z ∼ 0.8. Our data were acquired with the Green Bank Telescope and span the redshift range 0.6 &amp;lt; z &amp;lt; 1 over two fields totalling ≈41 deg2 and 190 h of radio integration time. The dominant synchrotron foregrounds exceed the signal by ∼103, but have fewer degrees of freedom and can be removed efficiently. Even in the presence of residual foregrounds, the auto-power can still be interpreted as an upper bound on the 21 cm signal. Our previous measurements of the cross-correlation of 21 cm intensity and the WiggleZ galaxy survey provide a lower bound. Through a Bayesian treatment of signal and foregrounds, we can combine both fields in auto- and cross-power into a measurement of ΩHI bHI= [0.62+0.23−0.15] × 10−3 at 68 per cent confidence with 9 per cent systematic calibration uncertainty, where ΩHI is the neutral hydrogen (H i) fraction and bHI is the H i bias parameter. We describe observational challenges with the present data set and plans to overcome them.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.448

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 science0.0000.000
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 head0.011
GPT teacher head0.200
Teacher spread0.189 · 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