High contrast imaging performance of E-ELT/METIS
Bibliographic record
Abstract
In the era of 8- to 10-m class telescopes, direct detection of exoplanets has become a reality: from the Keck/NIRC2 infrared camera to the Gemini Planet Imager, from the VLT/SPHERE to the Subaru/ SCExAO and the LBT/ LMIRCam , new and fascinating discoveries are announced at an increasing pace. Within the next 10 years, extremely large telescopes should provide the angular resolution and the sensitivity level to start addressing low-mass planets (potentially down to the super-Earth regime) in the habitable zone of nearby stars. In this context, the E-ELT first-light instrument METIS has a prominent role to play: its high contrast imaging design includes two of the latest evolutions of stellar coronagraphs, namely the Apodized Phase Plate (APP) and the vortex coronagraph, which are currently operating in several world-leading infrared camera (APPs at Magellan/CLIO, LBT/LMIRCam; vortex coronagraphs at VLT/NACO, VLT/VISIR, Keck/NIRC2, LBT/LMIRCam, Subaru/SCExAO). In this talk, we give an overview of the high-contrast imaging modes of the METIS instrument, the only MIR first-light instrument on any of the ELTs, and present L band end-to-end performance simulations of both the APP and vortex coronagraphic modes. The non-circular, centrally obstructed, segmented pupil challenges the coronagraphic performances. In our design study, we have thus identified and developed custom solutions to optimize the coronagraphic capabilities in realistic conditions. The effects of the adaptive optics residuals, including wind-induced pointing jitter, are included in our simulations to predict future on-sky performance. Finally, we will discuss the influence of non-common path aberrations on the final performance of the instrument for high-contrast imaging, and we will illustrate the scientific capabilities of METIS for the detection of low-mass planets and exozodiacal disks.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".