Spectroscopic and photometric observations of dwarf nova superoutbursts by the 3.8 m telescope Seimei and the Variable Star Network
Bibliographic record
Abstract
Abstract We present spectroscopic and photometric observations of 17 dwarf-nova superoutbursts obtained by KOOLS-IFU mounted on the 3.8 m telescope Seimei at the Okayama Observatory of Kyoto University and through the Variable Star Network collaboration (VSNET). Our spectroscopic observations for six outbursts were performed within 1 d of their optical peak. 11 objects (TCP J00590972+3438357, ASASSN-19ado, TCP J06073081−0101501, ZTF20aavnpug, ASASSN-19ady, MASTER OT J061642.05+435617.9, TCP J20034647+1335125, ASASSN-20kv, ASASSN-20kw, MASTER OT J213908.79+161240.2, and ASASSN-20mf) were previously unknown systems, and our observations enabled quick classification of their transient type. These results illustrate that the Seimei telescope has the capability to conduct quick follow-up observations of unknown transients. Our photometric observations yielded that 11 of the objects are WZ Sge-type dwarf novae and their candidates, and the other six are SU UMa-type dwarf novae and their candidates. The He ii 4686 Å emission line was clearly detected among ASASSN-19ado, TCP J06073081−0101501 and MASTER OT J213908.79+161240.2, the association of which with a spiral arm structure in an accretion disk has been suggested in previous studies. Our result suggests that a higher-inclination system shows a stronger emission line of He ii 4686 Å, as well as larger-amplitude early superhumps.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".