The Gemini Planet Imager
Bibliographic record
Abstract
The next major frontier in the study of extrasolar planets is direct imaging detection of the planets themselves. With high-order adaptive optics, careful system design, and advanced coronagraphy, it is possible for an AO system on a 8-m class telescope to achieve contrast levels of 10-7 to 10-8, sufficient to detect warm self-luminous Jovian planets in the solar neighborhood. Such direct detection is sensitive to planets inaccessible to current radial-velocity surveys and allows spectral characterization of the planets, shedding light on planet formation and the structure of other solar systems. We have begun the construction of such a system for the Gemini Observatory. Dubbed the Gemini Planet Imager (GPI), this instrument should be deployed in 2010 on the Gemini South telescope. It combines a 2000-actuator MEMS-based AO system, an apodized-pupil Lyot coronagraph, a precision infrared interferometer for real-time wavefront calibration at the nanometer level, and a infrared integral field spectrograph for detection and characterization of the target planets. GPI will be able to achieve Strehl ratios > 0.9 at 1.65 microns and to observe a broad sample of science targets with I band magnitudes less than 8. In addition to planet detection, GPI will also be capable of polarimetric imaging of circumstellar dust disks, studies of evolved stars, and high-Strehl imaging spectroscopy of bright targets. We present here an overview of the GPI instrument design, an error budget highlighting key technological challenges, and models of the system performance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.041 |
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".