A Fresnel propagation analysis of NFIRAOS/IRIS high-contrast exoplanet imaging capabilities
Bibliographic record
Abstract
The thirty meter telescope (TMT) has the potential to find new planetary systems and to study them in greater details. It could also possibly image super-Earth planets around the closest stars or still accreting distant protoplanets around stars in very young star forming regions. Since no first generation dedicated exoplanet finding instrument has been selected for the TMT, initial direct exoplanet imaging will have to rely on the NFIRAOS facility adaptive optics (AO) system and IRIS spectro-imaging near-infrared (NIR) camera. End-to-end Fresnel NFIRAOS simulations are presented using their current optical designs to evaluate the system multi-wavelength high-contrast imaging capabilities. Long exposures have been simulated using the expected AO-corrected phase screens and the estimated speckle lifetime. It is shown that NFIRAOS/IRIS may achieve contrasts close to the Gemini planet imager (GPI, an optimized NIR planet-finding instrument that will soon be installed on the Gemini South 8-m telescope), but needs to rely on multi-wavelength processing (by a factor 50) to achieve that goal, a challenging requirement. Without a coronograph and a better treatment of the in-band static speckle noise, it is unlikely that NFIRAOS/IRIS will be able to achieve GPI-like contrasts at very small inner working angles, which is potentially accessible with a large 30-meter telescope. However, TMT, with its bigger aperture and better angular resolution, along with the current NFIRAOS/IRIS designs, should be able to acquire higher SNR spectra and achieve three times better astrometric accuracy than GPI for medium to bright planets, resulting in better atmospheric characterization and faster orbital parameter determination of a sample of GPI planets.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".