SCUBA-2: iterative map-making with the Sub-Millimetre User Reduction Facility
Bibliographic record
Abstract
The Submillimetre Common User Bolometer Array 2 (SCUBA-2) is an instrument operating on the 15-m James Clerk Maxwell Telescope, nominally consisting of 5120 bolometers in each of two simultaneous imaging bands centred over 450 and 850 μm. The camera is operated by scanning across the sky and recording data at a rate of 200 Hz. As the largest of a new generation of multiplexed kilopixel bolometer cameras operating in the (sub)millimetre, SCUBA-2 data analysis represents a significant challenge. We describe the production of maps using smurf (Sub-Millimetre User Reduction Facility) in which we have adopted a fast, iterative approach to map-making that enables data reduction on single, modern, high-end desktop computers, with execution times that are typically shorter than the observing times. smurf is used in an automated setting, both at the telescope for real-time feedback to observers and for the production of science products for the JCMT Science Archive at the Canadian Astronomy Data Centre. Three detailed case studies are used to: (i) explore convergence properties of the map-maker using simple prior constraints (Uranus – a point source); (ii) achieve the white-noise limit for faint point-source studies (extragalactic blank-field survey of the Lockman Hole); and (iii) demonstrate that our strategy is capable of recovering angular scales comparable to the size of the array footprint (approximately 5 arcmin) for bright extended sources (star-forming region M17).
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".