On-sky vibration environment for the Gemini Planet Imager and mitigation effort
Bibliographic record
Abstract
The Gemini Planet Imager (GPI) entered on-sky commissioning and had its first-light at the Gemini South (GS) telescope in November 2013. GPI is an extreme adaptive optics (XAO), high-contrast imager and integral-field spectrograph dedicated to the direct detection of hot exo-planets down to a Jupiter mass. The performance of the apodized pupil Lyot coronagraph depends critically upon the residual wavefront error (design goal of 60nmRMS with <5 mas RMS tip/tilt), and therefore is most sensitive to vibration (internal or external) of Gemini's instrument suite. Excess vibration can be mitigated by a variety of methods such as passive or active dampening at the instrument or telescope structure or Kalman filtering of specific frequencies with the AO control loop. Understanding the sources, magnitudes and impact of vibration is key to mitigation. This paper gives an overview of related investigations based on instrument data (GPI AO module) as well as external data from accelerometer sensors placed at different locations on the GS telescope structure. We report the status of related mitigation efforts, and present corresponding results.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".