Searching for the next Galactic Luminous red nova
Bibliographic record
Abstract
ABSTRACT Luminous red novae (LRNe) are astrophysical transients believed to be caused by the partial ejection of a binary star’s common envelope (CE) and the merger of its components. The formation of the CE is likely to occur during unstable mass transfer, initiated by a primary star which is evolving off the main sequence (a Hertzsprung gap star) and a lower mass companion. In agreement with observations, theoretical studies have shown that outflows from the pre-CE phase produce a detectable brightening of the progenitor system a few years before the ejection event. Based on these assumptions, we present a method to identify Galactic LRNe precursors, the resulting precursor candidates, and our follow-up analysis to uncover their nature. We begin by constructing a sample of progenitor systems, i.e. Hertzsprung gap stars, by statistically modelling the density of a colour magnitude diagram formed from ‘well behaved’ Gaia DR2 sources. Their time-domain evolution from the Zwicky Transient Facility (ZTF) survey is used to search for slowly brightening events, as pre-CE precursor candidates. The nature of the resulting candidates is further investigated using archival data and our own spectroscopic follow-up. Overall, we constructed a sample of ∼5.4 × 104 progenitor sources, from which 21 were identified as candidate LRNe precursors. Further analysis revealed 16 of our candidates to be Hα emitters, with their spectra often suggesting hotter (albeit moderately extincted) A-type or B-type stars. Because of their long-term variability in optical and mid-infrared wavelengths, we propose that many of our candidates are mass-transferring binaries with compact companions surrounded by dusty circumstellar discs or alternatively magnetically active stellar merger remnants.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".