Post-coronagraph wavefront sensing for the TMT Planet Formation Imager
Bibliographic record
Abstract
Direct detection of exo-planets from the ground may be feasible with the advent of extreme-adaptive optics (ExAO) on large telescopes. A major hurdle to achieving high contrasts behind a star suppression system (10<sup>-8</sup>/hr<sup>-1/2</sup>) at small angular separations, is the "speckle noise" due to residual atmospheric and telescope-based quasistatic amplitude and phase errors at mid-spatial frequencies. We examine the potential of a post-coronagraphic, interferometric wavefront sensor to sense and adaptively correct just such errors. Pupil and focal plane sensors are considered and the merits and drawbacks of each scheme are outlined. It is not inconceivable to implement both schemes or even a hybrid scheme within a single instrument to significantly improve its scientific capabilities. This work was carried out in context of the proposed Planet Formation Imager instrument for Thirty Meter Telescope (TMT) project.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".