Luminous efficiency based on FRIPON meteors and limitations of ablation models
Bibliographic record
Abstract
Context. In meteor physics, the luminous efficiency τ is used to convert the meteor’s magnitude to the corresponding meteoroid’s mass. However, a lack of sufficiently accurate verification methods or adequate laboratory tests mean that discussions around this parameter are a subject of controversy. Aims. In this work, we aim to use meteor data obtained by the Fireball Recovery and InterPlanetary Observation to calculate the luminous efficiencies of the recorded meteors. We also show the limitations of the methods presented herein. Methods. Deceleration-based formulas were used to calculate the masses of the pre-atmospheric meteoroids. These can in turn be compared to the meteor brightnesses to assess the luminous efficiencies of the recorded objects. Fragmentation of the meteoroids is not considered within this model. Good measurements of the meteor deceleration are required. Results. We find τ -values, as well as the shape change coefficients, of 294 meteors and fireballs with determined masses in the range of 10 −6 –100 kg. The derived τ -values have a median of τ median = 2.17%. Most of them are of the order of 0.1–10%. We present how our values are obtained, compare them with data reported in the literature, and discuss several methods. A dependence of τ on the pre-atmospheric velocity of the meteor, v e , is noticeable with a relation of τ = 0.0023⋅ v e 2.3 . Furthermore, a dependence of τ on the initial meteoroid mass, M e , is found with negative linear behaviour in log–log space: τ = 0.48⋅ M e −0.47 . Conclusions. The higher luminous efficiency of fast meteors could be explained by the higher amount of energy released. Fast meteoroids produce additional emission lines that radiate more efficiently in specific wavelengths due to the appearance of the so-called second component of higher temperature. Furthermore, the negative dependence of τ on M e implies that the radiation of smaller meteoroids is more efficient. The results of this study also show the limitations of the ablation-based model for the determination of the luminous efficiency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".