Extreme adaptive optics for the Thirty Meter Telescope
Bibliographic record
Abstract
Direct detection of extrasolar Jovian planets is a major scientific motivation for the construction of future extremely large telescopes such as the Thirty Meter Telescope (TMT). Such detection will require dedicated high-contrast AO systems. Since the properties of Jovian planets and their parent stars vary enormously between different populations, the instrument must be designed to meet specific scientific needs rather than a simple metric such as maximum Strehl ratio. We present a design for such an instrument, the Planet Formation Imager (PFI) for TMT. It has four key science missions. The first is the study of newly-formed planets on 5-10 AU scales in regions such as Taurus and Ophiucus - this requires very small inner working distances that are only possible with a 30m or larger telescope. The second is a robust census of extrasolar giant planets orbiting mature nearby stars. The third is detailed spectral characterization of the brightest extrasolar planets. The final targets are circumstellar dust disks, including Zodiacal light analogs in the inner parts of other solar systems. To achieve these, PFI combines advanced wavefront sensors, high-order MEMS deformable mirrors, a coronagraph optimized for a finely- segmented primary mirror, and an integral field spectrograph.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.014 |
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".