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Record W4392703586 · doi:10.3847/1538-4357/ad2209

Probing the Global 21 cm Background by Velocity-induced Dipole and Quadrupole Anisotropies

2024· article· en· W4392703586 on OpenAlexaff
Selim C. Hotinli, Kyungjin Ahn

Bibliographic record

VenueThe Astrophysical Journal · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsPerimeter Institute
FundersNational Research Foundation of KoreaJohns Hopkins University
KeywordsPhysicsQuadrupoleDipoleAnisotropyAstrophysicsBackground radiationAstronomyAtomic physicsNuclear physicsOpticsQuantum mechanicsRadiation

Abstract

fetched live from OpenAlex

Abstract The motion of an observer in the rest frame of the cosmic 21 cm background induces an anisotropy in the observed background, even when the background is isotropic. The induced anisotropy includes a dipole and a quadrupole, in the order decreasing in amplitude. If observed, these multipole anisotropies can be used as additional probes of the spectral shape of the global 21 cm background for mitigating the ambiguity in the monopole spectrum probed by single-element radio telescopes such as EDGES and SARAS. This could also help with understanding the astrophysical and cosmological processes that occurred during the cosmic dawn and the epoch of reionization, and even improve the estimation of the solar velocity and the foreground spectra. Here, we study the feasibility of such observations and present science drivers for the measurement of the 21 cm dipole and quadrupole. We find that future 21 cm experiments can in principle detect the 21 cm dipole to high significance, potentially improving measurement accuracy of Earth velocity with respect to the Milky Way, galactic, and extragalactic foreground monopole spectra by an order of magnitude, as well as improving 21 cm astrophysical parameters by 2%–5%.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.248
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2024
Admission routes1
Has abstractyes

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