The Visibility of the Ōtautahi–Oxford Interstellar Object Population Model in LSST
Bibliographic record
Abstract
Abstract With a new probabilistic technique for sampling interstellar object (ISO) orbits with high efficiency, we assess the observability of ISOs under a realistic cadence for the upcoming Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST). Using the Ōtautahi–Oxford population model, we show that there will be complex on-sky structure in the pattern of direction and velocity revealed by the detected ISO population, with the expected enhanced northern flux complicating efforts to derive population parameters from the LSST’s predominately southern footprint. For reasonable luminosity functions with slopes of 2.5 ≤ q s ≤ 4.0, the most discoverable ISOs have H r ≃ 14.6−20.7. The slope of the luminosity function of ISOs will be relatively quickly constrained by the characteristics of the LSST detected population, such as the distributions of perihelia, velocity at infinity, and discovery circumstances. Discoveries are evenly split around their perihelion passage and are biased to lower velocities. After their discovery by LSST, it will be rare for ISOs to be visible for less than a month; most will have m r ≤ 23 for months, and the window for spectroscopic characterization could be as long as 2 yr. While these probabilistic assessments are robust against model or spatial density refinements that change the absolute numbers of ISO discoveries, our simulations predict a yield of 6–51 asteroidal ISOs, which is similar to previous works and demonstrates the validity of our new methods.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".