Gaussianity of Degree‐Scale Cosmic Microwave Background Anisotropy Observations
Bibliographic record
Abstract
We present results from a first test of the Gaussianity of degree-scale cosmic microwave background (CMB) anisotropy. We investigate Gaussianity of the CMB anisotropy by studying the topology of CMB anisotropy maps from the QMAP and Saskatoon experiments. We also study the QMASK map, a combination map of the QMAP and Saskatoon data. We measure the genus from noise-suppressed Wiener-filtered maps at an angular scale of about 1 5. To test the Gaussianity of the observed anisotropy, we compare these results to those derived from a collection of simulated maps for each experiment in a Gaussian spatially flat, cosmological constant dominated, cold dark matter model. The genus-threshold level relations of the QMAP and Saskatoon maps are consistent with Gaussianity. While the combination QMASK map has a mildly non-Gaussian genus curve that is not a consequence of known foreground contamination, this result is not statistically significant at the 2 σ level. These results extend previous upper limits on the non-Gaussianity of the large angular scale (>10°) CMB anisotropy (measured by the COBE Differential Microwave Radiometer experiment) down to degree angular scales.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".