Luminous Red Novae: population models and future prospects
Bibliographic record
Abstract
ABSTRACT A class of optical transients known as Luminous Red Novae (LRNe) have recently been associated with mass ejections from binary stars undergoing common-envelope evolution. We use the population synthesis code COMPAS to explore the impact of a range of assumptions about the physics of common-envelope evolution on the properties of LRNe. In particular, we investigate the influence of various models for the energetics of LRNe on the expected event rate and light curve characteristics, and compare with the existing sample. We find that the Galactic rate of LRNe is ∼0.2 yr−1, in agreement with the observed rate. In our models, the luminosity function of Galactic LRNe covers multiple decades in luminosity and is dominated by signals from stellar mergers, consistent with observational constraints from iPTF and the Galactic sample of LRNe. We discuss how observations of the brightest LRNe may provide indirect evidence for the existence of massive (>40 M⊙) red supergiants. Such LRNe could be markers along the evolutionary pathway leading to the formation of double compact objects. We make predictions for the population of LRNe observable in future transient surveys with the Large Synoptic Survey Telescope and the Zwicky Transient Facility. In all plausible circumstances, we predict a selection-limited observable population dominated by bright, long-duration events caused by common envelope ejections. We show that the Large Synoptic Survey Telescope will observe 20–750 LRNe per year, quickly constraining the luminosity function of LRNe and probing the physics of common-envelope events.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".