METIS high-contrast imaging: design and expected performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the advent of 30- to 40-m class ground-based telescopes in the mid-2020s, direct imaging of exoplanets is bound to take a new major leap. Among the approved projects, the Mid-infrared Extremely Large Telescope (ELT) Imager and Spectrograph (METIS) instrument for the ELT holds a prominent spot; by observing in the mid-infrared regime, it will be perfectly suited to study a variety of exoplanets and protoplanetary disks around nearby stars. Equipped with two of the most advanced coronagraphs, the vortex coronagraph and the apodizing phase plate, METIS will provide high-contrast imaging (HCI) in L-, M- and N-bands, and a combination of high-resolution spectroscopy and HCI in L- and M-bands. We present the expected HCI performance of the METIS instrument, considering realistic adaptive optics residuals, and investigate the effect of the main instrumental errors. The most important sources of degradation are identified and realistic sensitivity limits in terms of planet/star contrast are derived.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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