Constraints on galaxy formation from the cosmic-far-infrared-background – optical-imaging cross-correlation using Herschel and UNIONS
Bibliographic record
Abstract
Using $\it{Herschel}$-SPIRE imaging and the Canada-France Imaging Survey (CFIS) Low Surface Brightness data products from the Ultraviolet Near-Infrared Optical Northern Survey (UNIONS), we present a cross-correlation between the cosmic infrared background and cosmic optical background fluctuations. With a combined sky area of $91\,{\rm deg}^2$ and a minimum resolved scale of $18\,$arcsec, the cross-spectrum is measured for two cases: all galaxies are kept in the images; or all individually-detected galaxies are masked to produce `background' maps. We report the detection of the cross-correlation signal at $\gtrsim 22\,\sigma$ ($\gtrsim 18\,\sigma$ for the background map). The part of the optical brightness variations that are correlated with the submm emission translates to an rms brightness of $\simeq 32.5\,{\rm mag}\,{\rm arcsec}^{-2}$ in the $r$ band, a level normally unreachable for individual sources. A critical issue is determining what fraction of the cross-power spectrum might be caused by emission from Galactic cirrus. For one of the fields, the Galactic contamination is approximately a factor of 10 higher than the extragalactic signal, with the contamination being estimated using a linear regression from several external survey maps; however, for the other fields, the contamination is typically around 20 per cent. An additional discriminant is that the cross-power spectrum is of the approximate form $P(k)\propto 1/k$, much shallower than that of Galactic cirrus. We interpret the results in a halo-model framework, which shows good agreement with independent measurements for the scalings of star-formation rates in galaxies. The approach presented in this study holds great promise for future surveys such as FYST/CCAT-prime combined with ${\it Euclid}$ or the Vera Rubin Observatory (LSST), which will enable a detailed exploration of the evolution of star formation in galaxies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".