Warm dusty discs: exploring the A star 24 <i>μ</i>m debris population
Bibliographic record
Abstract
Aims. Studies of the debris disc phenomenon have shown that most systems are analogous to the Edgeworth-Kuiper belt (EKB). In this study we aim to determine how many of the IRAS 25 μm excesses towards A stars, which may be indicative of asteroid belt analogues, are real, and investigate where the dust must lie and so build up a picture of what these systems are like.Methods. We observe using ground-based mid-infrared imaging with TIMMI2, VISIR, Michelle and TReCS a sample of A and B-type main sequence stars previously reported as having mid-infrared excess. We combine modelling of the emission spectrum from multi-wavelength photometry with a modelling technique designed to constrain the radial extent of emission in mid-infrared imaging to constrain the possible location of the debris.Results. We independently confirm the presence of warm dust around three of the candidates: HD 3003, HD 80950 and η Tel. For the binary HD3003 a stability analysis indicates the dust is either circumstellar and lying at ~4 AU with the binary orbiting at >14 AU, or the dust lies in an unstable location; there is tentative evidence for temporal evolution of its excess emission on a ~20 year timescale. For 7 of the targets we present quantitative limits on the location of dust around the star based on the unresolved imaging. We demonstrate that the disc around HD71155 must have multiple spatially distinct components at 2 and 60 AU. We model the limits of current instrumentation to resolve debris disc emission and show that most of the known A star debris discs which could be readily resolved at 18 μm on 8 m instruments have been resolved, but identify several that could be resolved with deep (>8 h total) integrations (such as HD19356, HD139006 and HD102647).Conclusions. Limits from unresolved imaging can help distinguish between competing models of the disc emission, but resolved imaging is key to an unambiguous determination of the disc location. Modelling of the detection limits for extended emission can be useful for targeting future observational campaigns towards sources most likely to be resolved. MIRI on the JWST will be able to resolve the majority of the known A star debris disc population. METIS on the E-ELT will provide the opportunity to explore the hot disc population more thoroughly by detecting extended emission down to where calibration accuracy limits disc detection through photometry alone, reaching levels below 1 zodi for stars within 10 pc.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".