High-Contrast Imaging and Wavefront Control with a PIAA Coronagraph: Laboratory System Validation
Why this work is in the frame
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Bibliographic record
Abstract
The Phase-Induced Amplitude Apodization (PIAA) coronagraph is a high performance coronagraph concept able to work at small angular separation with little loss in throughput. We present results obtained with a laboratory PIAA system including active wavefront control. The system has a 94.3% throughput (excluding coating losses) and operates in air with monochromatic light. Our testbed achieved a 2.27e-7 raw contrast between 1.65 lambda/D (inner working angle of the coronagraph configuration tested) and 4.4 lambda/D (outer working angle). Through careful calibration, we were able to separate this residual light into a dynamic coherent component (turbulence, vibrations) at 4.5e-8 contrast and a static incoherent component (ghosts and/or polarization missmatch) at 1.6e-7 contrast. Pointing errors are controlled at the 1e-3 lambda/D level using a dedicated low order wavefront sensor. While not sufficient for direct imaging of Earth-like planets from space, the 2.27e-7 raw contrast achieved already exceeds requirements for a ground-based Extreme Adaptive Optics system aimed at direct detection of more massive exoplanets. We show that over a 4hr long period, averaged wavefront errors have been controlled to the 3.5e-9 contrast level. This result is particularly encouraging for ground based Extreme-AO systems relying on long term stability and absence of static wavefront errors to recover planets much fainter than the fast boiling speckle halo.
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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 | 0.000 |
| 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 it