An on-sky investigation into factors limiting the performance of Keck-NIRC2 for conducting infrared high-contrast imaging
Bibliographic record
Abstract
The most common instrument used by the exoplanet/brown dwarf direct imaging community at the W.M. Keck Observatory is currently the NIRC2 near-infrared imager. We document three on-sky testing results of non-uniform effects that exist in the NIRC2 system when operating in L and M-band that can affect the performance when conducting high-contrast imaging observations. First, we report the measurements of the throughput of the vector vortex L/M coronagraph. We quantify the throughput and additional background flux penalties, noting the effects of using the VVC in M-band are greater than in L-band. Second, we utilize the recently commissioned NIRC2 electronics upgrade to measure the L/M band sky variability at sub-second speeds. We find that the background varies at timescales of less than 30s, indicating that the electronics upgrade may improve opportunities for future surveys. Third, we document the contribution of the image derotator to the spatial non-uniformity in the background flux. We conclude by giving a set of how the Keck-NIRC2 high-contrast imaging community can adapt their observing strategies to improve the sensitivity of future surveys.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".