CORRELATIONS IN THE (SUB)MILLIMETER BACKGROUND FROM ACT × BLAST
Bibliographic record
Abstract
We present measurements of the auto-and cross-frequency correlation power spectra of the cosmic (sub)millimeter background at 250, 350, and 500 μm (1200, 860, and 600 GHz) from observations made with the Balloonborne Large Aperture Submillimeter Telescope (BLAST); and at 1380 and 2030 μm (218 and 148 GHz) from observations made with the Atacama Cosmology Telescope (ACT).The overlapping observations cover 8.6 deg 2 in an area relatively free of Galactic dust near the south ecliptic pole.The ACT bands are sensitive to radiation from the cosmic microwave background, to the Sunyaev-Zel'dovich effect from galaxy clusters, and to emission by radio and dusty star-forming galaxies (DSFGs), while the dominant contribution to the BLAST bands is from DSFGs.We confirm and extend the BLAST analysis of clustering with an independent pipeline and also detect correlations between the ACT and BLAST maps at over 25σ significance, which we interpret as a detection of the DSFGs in the ACT maps.In addition to a Poisson component in the cross-frequency power spectra, we detect a clustered signal at 4σ , and using a model for the DSFG evolution and number counts, we successfully fit all of our spectra with a linear clustering model and a bias that depends only on redshift and not on scale.Finally, the data are compared to, and generally agree with, phenomenological models for the DSFG population.This study demonstrates the constraining power of the cross-frequency correlation technique to constrain models for the DSFGs.Similar analyses with more data will impose tight constraints on future models.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".