Multiwavelength imaging concepts for exoplanet detection
Bibliographic record
Abstract
Direct exoplanet detections are currently limited by speckle noise arising from residual atmospheric wavefront errors and optical aberrations. Simultaneous spectral differential imaging (SSDI) is a high contrast imaging technique that aims at reducing this noise by the subtraction of images obtained simultaneously in adjacent narrow spectral bands. SSDI performances are severely degraded by differential optical aberrations between channels. We discuss two novel approaches to implement SSDI in which there are no differential aberrations. The first uses a microlens array at the focal plane to sample the point spread function (PSF) and micro-filters on the backside of each microlens to separate colors. The micropupils are immediately imaged on the detector. The second preserves the microlens array at the focal plane but re-images the array of micropupils through a beam-splitter on the detector. In both concepts the PSF measurement is made at the microlens array, so all optics is common prior to the PSF measurement in all colors. A simple prototype was used to test the concepts; preliminary results yield noise attenuation of ~10-2.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".