Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 160

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Non-Gaussianity of the Derived Maps from the First-Year Wilkinson Microwave Anisotropy Probe Data

Open access
Chiang, Lung-Yih, Naselsky, Pavel D., Verkhodanov, Oleg V., Way, Michael J.·2003·The Astrophysical Journal

Abstract

We present non-Gaussianity testing on derived maps from the recently released first-year Wilkinson Microwave Anisotropy Probe data by Tegmark, de Oliveria-Costa, & Hamilton. Our test is based on a phase-mapping technique that has the advantage of testing non-Gaussianity at separate multipole bands. We show that their foreground-cleaned map is against the random-phase hypothesis at all four multipole bands centered around ℓ = 150, 290, 400, and 500. Their Wiener-filtered map, on the other hand, is Gaussian for ℓ < 250 and marginally Gaussian for 224 < ℓ < 350. However, we see the evidence of non-Gaussianity for ℓ > 350 as we detect certain degrees of phase coupling, hence against the random-phase hypothesis. Our phase-mapping technique is particularly useful for testing the accuracy of component separation methods.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1086/376822

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 160

Metadata

Authors
Chiang, L.-Y., Naselsky, P. D., Verkhodanov, O. V., & Way, M. J.
Venue
The Astrophysical Journal
Published
2003-05-27
Volume
590
Issue
2
Pages
L65-L68
ISSN
  • 0004-637X (ISSN-L)
  • 1538-4357
OpenAlex
W2949346063
Cited by
160
References
1
FWCI
14.69
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Non-Gaussianity of the Derived Maps from the First-Year Wilkinson Microwave Anisotropy Probe Data. https://app.cochat.ai/papers/10.1086/376822
The paper
Chiang, L.-Y., Naselsky, P. D., Verkhodanov, O. V., & Way, M. J. (2003). Non-Gaussianity of the Derived Maps from the First-Year Wilkinson Microwave Anisotropy Probe Data. The Astrophysical Journal. https://doi.org/10.1086/376822

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.