Combining high-dispersion spectroscopy with high contrast imaging: Probing rocky planets around our nearest neighbors
Why this work is in the frame
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Bibliographic record
Abstract
Context. Ground-based high-dispersion (R ~ 100 000) spectroscopy (HDS) is proving to be a powerful technique with which to characterize extrasolar planets. The planet signal is distilled from the bright starlight, combining ral and time-differential filtering techniques. In parallel, high-contrast imaging (HCI) is developing rapidly, aimed at spatially separating the planet from the star. While HDS is limited by the overwhelming noise from the host star, HCI is limited by residual quasi-static speckles. Both techniques currently reach planet-star contrast limits down to ~10-5, albeit for very different types of planetary systems. Aims. In this work, we discuss a way to combine HDS and HCI (HDS+HCI). For a planet located at a resolvable angular distance from its host star, the starlight can be reduced up to several orders of magnitude using adaptive optics and/or coronography. In addition, the remaining starlight can be filtered out using high-dispersion spectroscopy, utilizing the significantly different (or Doppler shifted) high-dispersion spectra of the planet and star. In this way, HDS+HCI can in principle reach contrast limits of ~10-5 × 10-5, although in practice this will be limited by photon noise and/or sky-background. In contrast to current direct imaging techniques, such as Angular Differential Imaging and Spectral Differential Imaging, it will work well at small working angles and is much less sensitive to speckle noise. For the discovery of previously unknown planets HDS+HCI requires a high-contrast adaptive optics system combined with a high-dispersion R ~ 100 000 integral field spectrograph (IFS). This combination currently does not exist, but is planned for the European Extremely Large Telescope. Methods. We present simulations of HDS+HCI observations with the E-ELT, both probing thermal emission from a planet at infrared wavelengths, and starlight reflected off a planet atmosphere at optical wavelengths. For the infrared simulations we use the baseline parameters of the E-ELT and METIS instrument, with the latter combining extreme adaptive optics with an R = 100 000 IFS. We include realistic models of the adaptive optics performance and atmospheric transmission and emission. For the optical simulation we also assume R = 100 000 IFS with adaptive optics capabilities at the E-ELT. Results. One night of HDS+HCI observations with the E-ELT at 4.8 μm (Δλ = 0.07 μm) can detect a planet orbiting α Cen A with a radius of R = 1.5 Rearth and a twin-Earth thermal spectrum of Teq = 300 K at a signal-to-noise (S/N) of 5. In the optical, with a Strehl ratio performance of 0.3, reflected light from an Earth-size planet in the habitable zone of Proxima Centauri can be detected at a S/N of 10 in the same time frame. Recently, first HDS+HCI observations have shown the potential of this technique by determining the spin-rotation of the young massive exoplanet β Pictoris b. Conclusions. The exploration of the planetary systems of our neighbor stars is of great scientific and philosophical value. The HDS+HCI technique has the potential to detect and characterize temperate rocky planets in their habitable zones. Exoplanet scientists should not shy away from claiming a significant fraction of the future ELTs to make such observations possible.
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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) | 0.001 | 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 | 0.001 |
| 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