Multiple Peaks in the Angular Power Spectrum of the Cosmic Microwave Background: Significance and Consequences for Cosmology
Bibliographic record
Abstract
Three peaks and two dips have been detected in the power spectrum of the cosmic microwave background by the BOOMERANG experiment, at l = (213 ), (541 ), (845 ) and l = (416 ), (750 ), respectively. Using model-independent analyses, we find that all five features are statistically significant, and we measure their location and amplitude. These are consistent with the adiabatic inflationary model. We also calculate the mean and variance of the peak and dip locations and amplitudes in a large seven-dimensional parameter space of such models, which gives good agreement with the model-independent estimates. We forecast where the next few peaks and dips should be found if the basic paradigm is correct. We test the robustness of our results by comparing Bayesian marginalization techniques on this space with likelihood maximization techniques applied to a second seven-dimensional cosmological parameter space, using an independent computational pipeline, and find excellent agreement: Ω tot = 1.02 versus 1.04 ± 0.05, Ω b h 2 = 0.022 versus 0.019 , and n s = 0.96 versus 0.90 ± 0.08. The determination of the best fit by the maximization procedure effectively ignores nonzero optical depth of reionization τ C > 0, and the difference in primordial spectral index n s between the two methods is thus a consequence of the strong correlation of n s with the τ C .
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".