Detecting Biosignatures of Nearby Rocky Exoplanets: Simulations of High Spectral Resolution Observations with the ELTs
Bibliographic record
Abstract
The imminent arrival of the Extremely Large Telescopes (ELTs) will finally deliver the observational power capable of assessing the habitability of nearby rocky exoplanets. The ELT presents us with the exciting opportunity of being able to spatially resolve the terrestrial exoplanet Proxima b, which lies in the habitable zone of Proxima Centuri. This would allow molecule mapping, a technique that uses the spatial separation plus cross correlation high resolution spectroscopy to disentangle the planet's spectrum from the host star and characterise its atmosphere. Here we present simulations in reflected light for the High Contrast Adaptive Optics (HCAO) mode of HARMONI/ELT, using model planet spectra from the Carl Sagan Institute designed specifically for Proxima b and its M-dwarf host star. HARMONI's resolution (R=17,385) is well suited to molecule mapping, with access to wavelengths covering multiple biosignatures. Our simulator shows that this first light ELT instrument can characterise the atmosphere of Proxima b, within a very reasonable time frame, but requires intervention on the focal plane masks in HARMONI's current instrument design. If changed, HARMONI has the potential to identify CO2, CH4, and H2O in Proxima b. Our simulator is highly versatile and we are extending to other instruments for the ELTs, including METIS/ELT and GMagAO-X+IFS/GMT.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".