DIGITAL TRACKING OBSERVATIONS CAN DISCOVER ASTEROIDS 10 TIMES FAINTER THAN CONVENTIONAL SEARCHES
Bibliographic record
Abstract
We describe digital tracking, a method for asteroid searches that greatly increases the sensitivity of a telescope to faint unknown asteroids. It has been previously used to detect faint Kuiper Belt objects using the Hubble Space Telescope and large ground-based instruments, and to find a small, fast-moving asteroid during a close approach to Earth. We complement this earlier work by developing digital tracking methodology for detecting asteroids using large-format CCD imagers. We demonstrate that the technique enables the ground-based detection of large numbers of new faint asteroids. Our methodology resolves or circumvents all major obstacles to the large-scale application of digital tracking for finding main belt and near-Earth asteroids. We find that for both asteroid populations, digital tracking can deliver a factor of ten improvement over conventional searches. Digital tracking has long been standard practice for deep Kuiper Belt surveys, but even there our methodology enables deeper integrations than have yet been attempted. Our search for main belt asteroids using a one-degree imager on the 0.9m WIYN telescope on Kitt Peak validates our methodology, delivers sensitivity to asteroids in a regime previously probed only with 4-meter and larger instruments, and leads to the detection of 156 previously unknown asteroids and 59 known objects in a single field. Digital tracking has the potential to revolutionize searches for faint moving objects ranging from the Kuiper Belt through main belt and near-Earth asteroids, and perhaps even anthropogenic space debris in low Earth orbit.
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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 | 0.001 | 0.001 |
| 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 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".