Improved Measurements of the CMB Power Spectrum with ACBAR
Bibliographic record
Abstract
We report improved measurements of temperature anisotropies in the cosmic microwave background (CMB) radiation made with the Arcminute Cosmology Bolometer Array Receiver (ACBAR). In this paper, we use a new analysis technique and include 30% more data from the 2001 and 2002 observing seasons than the first release to derive a new set of band-power measurements with significantly smaller uncertainties. The planet-based calibration used previously has been replaced by comparing the flux of RCW 38 as measured by ACBAR and BOOMERANG to transfer the WMAP -based BOOMERANG calibration to ACBAR. The resulting power spectrum is consistent with the theoretical predictions for a spatially flat, dark energy-dominated ΛCDM cosmology, including the effects of gravitational lensing. Despite the exponential damping on small angular scales, the primary CMB fluctuations are detected with a signal-to-noise ratio of greater than 4, up to multipoles of ℓ = 2000. This increase in the precision of the fine-scale CMB power spectrum leads to only a modest decrease in the uncertainties on the parameters of the standard cosmological model. At high angular resolution, secondary anisotropies are predicted to be a significant contribution to the measured anisotropy. A joint analysis of the ACBAR results at 150 GHz and the CBI results at 30 GHz in the multipole range 2000 < ℓ < 3000 shows that the power, reported by CBI in excess of the predicted primary anisotropy, has a frequency spectrum consistent with the thermal Sunyaev-Zel'dovich effect and inconsistent with primary CMB. The results reported here are derived from a subset of the total ACBAR data set; the final ACBAR power spectrum at 150 GHz will include 3.7 times more effective integration time and 6.5 times more sky coverage than is used here.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".