A joint analysis of BLAST 250-500 μm and LABOCA 870 μm observations in the Extended Chandra Deep Field-South
Bibliographic record
Abstract
We present a joint analysis of the overlapping Balloon-borne Large Aperture Submillimetre Telescope (BLAST) 250, 350, 500 μm, and LABOCA 870 μm observations [from the LABOCA ECDFS Submm Survey (LESS) survey] of the Extended Chandra Deep Field-South. Out to z∼ 3, the BLAST filters sample near the peak wavelength of thermal far-infrared (FIR) emission from galaxies (rest-frame wavelengths ∼60–200 μm), primarily produced by dust heated through absorption in star-forming clouds. However, identifying counterparts to individual BLAST peaks is very challenging, given the large beams [full-width at half-maximum (FWHM) 36–60 arcsec]. In contrast, the ground-based 870 μm observations have a significantly smaller 19 arcsec FWHM beam, and are sensitive to higher redshifts (z∼ 1–5, and potentially beyond) due to the more favourable negative K-correction. We use the LESS data, as well as deep Spitzer and VLA imaging, to identify 118 individual sources that produce significant emission in the BLAST bands. We characterize the temperatures and FIR luminosities for a subset of 69 sources which have well-measured submillimetre (submm) spectral energy distributions (SEDs) and redshift measurements out to z∼ 3. For flux-limited sub-samples in each BLAST band, and a dust emissivity index β= 2.0, we find a median temperature T= 30 K (all bands) as well as median redshifts: z= 1.1 (interquartile range 0.2–1.9) for S250 > 40 mJy; z= 1.3 (interquartile range 0.6–2.1) for S350 > 30 mJy; and z= 1.6 (interquartile range 1.3–2.3) for S500 > 20 mJy. Taking into account the selection effects for our survey (a bias towards detecting lower-temperature galaxies), we find no evidence for evolution in the local FIR–temperature correlation out to z∼ 2.5. Comparing with star-forming galaxy SED templates, about 8 per cent of our sample appears to exhibit significant excesses in the radio and/or mid-IR, consistent with those sources harbouring active galactic nuclei (AGN). Since our statistical approach differs from most previous studies of submm galaxies, we describe the following techniques in two appendices: our ‘matched filter’ for identifying sources in the presence of point-source confusion; and our approach for identifying counterparts using likelihood ratios. This study is a direct precursor to future joint FIR/submm surveys, for which we outline a potential identification and SED measurement strategy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".