Wide-field ultra-narrow-bandpass imaging with the Dragonfly Telephoto Array
Bibliographic record
Abstract
We describe plans for adding a wide-field narrow-band imaging capability to the Dragonfly Telephoto Array. Our plans focus on the development of the `Dragonfly Filter-Tilter', a device which places ultra-narrow bandpass interference filters ($Δλ\approx 1$ nm) in front of each of the lenses that make up the array. The filters are at the entrance pupil of the optical system, rather than in a converging beam, so their performance is not degraded by a converging light cone. This allows Dragonfly to image with a spectral bandpass that is an order of magnitude narrower than that of telescopes using conventional narrow-band filters, resulting in a large increase in the contrast and detectability of extended low surface brightness line emission. By tilting the filters, the central wavelength of the transmission curve can be tuned over a range of 7 nm, corresponding to a physical distance range of about 20 Mpc of extragalactic targets. A further benefit of our approach is that it allows off-band observations to be obtained at the same time as on-band observations, so systematic errors introduced by rapid sky variability can be removed with high precision. Taken together, these characteristics should give our imaging system the ability to detect extremely faint low-surface brightness line emission. Future versions of the Dragonfly Telephoto Array may have the sensitivity needed to directly image the circumgalactic medium of local galaxies. In this paper, we provide a detailed description of the concept, and present laboratory measurements that are used to verify the key ideas behind the instrument.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".