The Properties of Fast Yellow Pulsating Supergiants: FYPS Point the Way to Missing Red Supergiants
Bibliographic record
Abstract
Fast yellow pulsating supergiants (FYPS) are a recently-discovered class of evolved massive pulsator. As candidate post-red supergiant objects, and one of the few classes of pulsating evolved massive stars, these objects have incredible potential to change our understanding of the structure and evolution of massive stars. Here we examine the lightcurves of a sample of 126 cool supergiants in the Magellanic Clouds observed by the Transiting Exoplanet Survey Satellite (\tess~) in order to identify pulsating stars. After making quality cuts and filtering out contaminant objects, we examine the distribution of pulsating stars in the Hertzprung-Russel (HR) diagram, and find that FYPS occupy a region above $\log L/L_\odot \gtrsim 5.0$. This luminosity boundary corresponds to stars with initial masses of $\sim$18-20 $M_\odot$, consistent with the most massive red supergiant progenitors of supernovae (SNe) II-P, as well as the observed properties of SNe IIb progenitors. This threshold is in agreement with the picture that FYPS are post-RSG stars. Finally, we characterize the behavior of FYPS pulsations as a function of their location in the HR diagram. We find low frequency pulsations at higher effective temperatures, higher frequency pulsations at lower temperatures, with a transition between the two behaviors at intermediate temperatures. The observed properties of FYPS make them fascinating objects for future theoretical study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".