MétaCan
Menu
Back to cohort
Record W2345814028 · doi:10.1093/mnras/stw1022

First limits on the 21 cm power spectrum during the Epoch of X-ray heating

2016· article· en· W2345814028 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.

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsRedshiftSpectral densityAstrophysicsIonosphereObservatoryCalibrationInterference (communication)Noise (video)GalaxyRemote sensingAstronomyTelecommunications

Abstract

fetched live from OpenAlex

We present first results from radio observations with the Murchison Widefield
\nArray seeking to constrain the power spectrum of 21 cm brightness temperature
\nfluctuations between the redshifts of 11.6 and 17.9 (113 and 75 MHz). Three
\nhours of observations were conducted over two nights with significantly
\ndifferent levels of ionospheric activity. We use these data to assess the
\nimpact of systematic errors at low frequency, including the ionosphere and
\nradio-frequency interference, on a power spectrum measurement. We find that
\nafter the 1-3 hours of integration presented here, our measurements at the
\nMurchison Radio Observatory are not limited by RFI, even within the FM band,
\nand that the ionosphere does not appear to affect the level of power in the
\nmodes that we expect to be sensitive to cosmology. Power spectrum detections,
\ninconsistent with noise, due to fine spectral structure imprinted on the
\nforegrounds by reflections in the signal-chain, occupy the spatial Fourier
\nmodes where we would otherwise be most sensitive to the cosmological signal. We
\nare able to reduce this contamination using calibration solutions derived from
\nautocorrelations so that we achieve an sensitivity of 10 mK⁴ on comoving
\nscales k ≲ 0.5 h Mpc⁻¹. This represents the first upper limits on
\nthe 21 cm power spectrum fluctuations at redshifts 12 ≲ z ≲ 18 
\nbut is still limited by calibration systematics. While calibration improvements
\nmay allow us to further remove this contamination, our results emphasize that
\nfuture experiments should consider carefully the existence of and their ability
\nto calibrate out any spectral structure within the EoR window.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.359

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 science0.0010.000
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 head0.007
GPT teacher head0.188
Teacher spread0.180 · 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