First Light with the 120-lens Dragonfly Spectral Line Mapper
Bibliographic record
Abstract
Abstract The Dragonfly Spectral Line Mapper (DSLM) is a 120-lens distributed aperture narrowband imaging telescope that is operating as a pathfinder for an upcoming 1140-lens instrument being built to directly image the circumgalactic medium of nearby galaxies. DSLM has been on sky since 2023 October, collecting representative data for individual galaxies in Hα, [O iii], and [N ii]. In this paper, observations obtained for three targets (NGC 6946, NGC 891, and NGC 7479) are presented. These galaxies span a range of recessional velocities and foreground contamination levels, enabling a comprehensive evaluation of the experimental design. Diffuse Hα structures down to 10−19 erg s−1 cm−2 arcsec−2 on 10′ scales are mapped by our data. We report the discovery of new extended structures in diffuse Hα and [N ii] emission around NGC 6946 and NGC 891. We also map multiple new structures surrounding NGC 6946; however, due to the low recessional velocity of this object and the significant presence of galactic Hα emission at low galactic latitudes, we cannot confirm whether these gas clouds are associated with NGC 6946 or are of Galactic origin. We present a framework using the “sbcontrast” tool which can be broadly applied to evaluate the limiting depth of wide-field narrowband imaging observations. The surface brightness limits obtained with DSLM are consistent with our theoretical predictions and, in fields with low foreground contamination, the imaging depth is not limited by instrument systematics. Future dedicated surveys on galaxies selected by recessional velocity to avoid sky emission lines are projected to reach surface brightness limits of 10−20 erg s−1 cm−2 arcsec−2 on scales of a few arcmin, placing the circumgalactic medium of nearby galaxies within reach.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".