Multicolor Photometry of Tiny Near-Earth Asteroid 2015 RN<sub>35</sub> across a Wide Range of Phase Angles: Possible Mission-accessible A-type Asteroid
Bibliographic record
Abstract
Abstract Studying small near-Earth asteroids is important in order to understand their dynamical histories and origins as well as to mitigate the damage caused by asteroid impacts on Earth. We report the results of multicolor photometry of the tiny near-Earth asteroid 2015 RN35 using the 3.8 m Seimei telescope in Japan and the TRAPPIST-South telescope in Chile over 17 nights in 2022 December and 2023 January. We observed 2015 RN35 across a wide range of phase angles from 2° to 30° in the g, r, i, and z bands in the Pan-STARRS system. These lightcurves show that 2015 RN35 is in a nonprincipal axis spin state with two characteristic periods of 1149.7 ± 0.3 s and 896.01 ± 0.01 s. We found that the slope of the visible spectrum of 2015 RN35 is as red as asteroid (269) Justitia, one of the very red objects in the main belt, which indicates that 2015 RN35 can be classified as an A- or Z-type asteroid. In conjunction with the shallow slope of the phase curve, we suppose that 2015 RN35 is a high-albedo A-type asteroid. We demonstrated that surface properties of tiny asteroids could be well constrained by intensive observations across a wide range of phase angles. 2015 RN35 is a possible mission-accessible A-type near-Earth asteroid with a small Δv of 11.801 km s−1 in the launch window between 2030 and 2035.
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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 | 0.000 | 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) | 0.001 | 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".