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Record W4392885952 · doi:10.1093/mnras/stae665

Angular correlations of cosmic microwave background spectrum distortions from photon diffusion

2024· article· en· W4392885952 on OpenAlexafffund
Nathaniel Starkman, Glenn D. Starkman, Arthur Kosowsky

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaImperial College LondonU.S. Department of Energy
KeywordsPhysicsCosmic microwave backgroundPhotonCosmic background radiationAstrophysicsCOSMIC cancer databaseSpectrum (functional analysis)Cosmic infrared backgroundDiffusionMicrowaveAstronomyComputational physicsOpticsAnisotropyQuantum mechanics

Abstract

fetched live from OpenAlex

ABSTRACT During cosmic recombination, charged particles bind into neutral atoms and the mean free path of photons rapidly increases, resulting in the familiar diffusion damping of primordial radiation temperature variations. An additional effect is a small photon spectrum distortion, because photons arriving from a particular sky direction were originally in thermal equilibrium at various spatial locations with different temperatures; the combination of these different blackbody temperature distributions results in a spectrum with a Compton y-distortion. Using the approximation that photons had zero mean free path prior to their second-to-last scattering, we derive an expression for the resulting y-distortion, and compute the angular correlation function of the diffusion y-distortion and its cross-correlation with the square of the photon temperature fluctuation. Detection of the cross-correlation is within reach of existing arcminute-resolution microwave background experiments such as the Atacama Cosmology Telescope and the South Pole Telescope.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.216
Teacher spread0.209 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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