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Record W2051085854 · doi:10.1086/513698

Three‐Year<i>Wilkinson Microwave Anisotropy Probe</i>(<i>WMAP</i>) Observations: Temperature Analysis

2007· article· en· W2051085854 on OpenAlexaff
G. Hinshaw, Michael R. Nolta, C. L. Bennett, Rachel Bean, Olivier Doré, M. R. Greason, M. Halpern, Robert Hill, N. Jarosik, A. Kogut, Eiichiro Komatsu, M. Limon, N. Odegard, S. S. Meyer, Lyman A. Page, Hiranya V. Peiris, David N. Spergel, Gregory S. Tucker, Licia Verde, J. L. Weiland, Edward J. Wollack, E. L. Wright

Bibliographic record

VenueThe Astrophysical Journal Supplement Series · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsUniversity of British ColumbiaCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsCMB cold spotCosmic microwave backgroundSkyPhysicsResidualAstrophysicsSpectral densityAnisotropyPoint sourceRemote sensingOpticsAlgorithmComputer scienceGeologyTelecommunications

Abstract

fetched live from OpenAlex

We present new full-sky temperature maps in five frequency bands from 23 to 94 GHz, based on data from the first 3 years of the WMAP sky survey. The new maps are consistent with the first-year maps and are more sensitive. The 3 year maps incorporate several improvements in data processing made possible by the additional years of data and by a more complete analysis of the polarization signal. These include several new consistency tests as well as refinements in the gain calibration and beam response models. We employ two forms of multifrequency analysis to separate astrophysical foreground signals from the CMB, each of which improves on our first-year analyses. First, we form an improved "Internal Linear Combination" (ILC) map, based solely on WMAP data, by adding a bias-correction step and by quantifying residual uncertainties in the resulting map. Second, we fit and subtract new spatial templates that trace Galactic emission; in particular, we now use low-frequency WMAP data to trace synchrotron emission instead of the 408 MHz sky survey. The WMAP point source catalog is updated to include 115 new sources whose detection is made possible by the improved sky map sensitivity. We derive the angular power spectrum of the temperature anisotropy using a hybrid approach that combines a maximum likelihood estimate at low l (large angular scales) with a quadratic cross-power estimate for l > 30. The resulting multifrequency spectra are analyzed for residual point source contamination. At 94 GHz the unmasked sources contribute 128 ± 27 μK 2 to l ( l + 1) C l /2π at l = 1000. After subtracting this contribution, our best estimate of the CMB power spectrum is derived by averaging cross-power spectra from 153 statistically independent channel pairs. The combined spectrum is cosmic variance limited to l = 400, and the signal-to-noise ratio per l -mode exceeds unity up to l = 850. For bins of width Δ l / l = 3%, the signal-to-noise ratio exceeds unity up to l = 1000. The first two acoustic peaks are seen at l = 220.8 ± 0.7 and l = 530.9 ± 3.8, respectively, while the first two troughs are seen at l = 412.4 ± 1.9 and l = 675.2 ± 11.1. The rise to the third peak is unambiguous; when the WMAP data are combined with higher resolution CMB measurements, the existence of a third acoustic peak is well established. Spergel et al. use the 3 year temperature and polarization data to constrain cosmological model parameters. A simple six-parameter ΛCDM model continues to fit CMB data and other measures of large-scale structure remarkably well. The new polarization data produce a better measurement of the optical depth to reionization, τ = 0.089 ± 0.03. This new and tighter constraint on τ helps break a degeneracy with the scalar spectral index, which is now found to be n s = 0.960 ± 0.016. If additional cosmological data sets are included in the analysis, the spectral index is found to be n s = 0.947 ± 0.015.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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 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

Citations972
Published2007
Admission routes1
Has abstractyes

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