Imaging habitable planets in optical/NIR with large ground-based telescopes: WFS/C challenges, opportunities and R&D activities

Olivier Guyon, Mark Chun, Damien Gratadour, Michael Fitzgerald, Nemanja Jovanovic, Julien Lozi, Jared Males, Frantz Martinache, Dimitri Mawet, Benjamin Mazin, Ananya Sahoo, Arnaud Sevin, Andy Skemer, Sebastien Vievard

Research output: Contribution to conferencePaperpeer-review

Abstract

Large ground-based telescopes (ELT, TMT, GMT) will have the angular resolution and sensitivity to image and characterize (spectroscopy) rocky planets in the habitable zones of nearby stars. The nearest M-type stars are particularly attractive targets thanks to moderate reflected light contrast levels and a large number of potential targets. Wavefront control and residual starlight calibration are the most significant challenges to be addressed, requiring performance levels beyond what current on-sky AO systems deliver. Extreme-AO systems will need to deliver 1e5 raw contrast within a few diffractive limits from the optical axis to allow for direct imaging of habitable planets. Differential detection techniques relying on spectroscopy, polarization and/or coherence will then be employed to separate planet signal from speckle noise. We describe technical solutions to meet the ExAO demands for direct imaging of habitable planets with ELTs.

Original languageEnglish (US)
StatePublished - 2019
Event6th International Conference on Adaptive Optics for Extremely Large Telescopes, AO4ELT 2019 - Quebec City, Canada
Duration: Jun 9 2019Jun 14 2019

Conference

Conference6th International Conference on Adaptive Optics for Extremely Large Telescopes, AO4ELT 2019
Country/TerritoryCanada
CityQuebec City
Period6/9/196/14/19

Keywords

  • Adaptive optics
  • Coronagraphy
  • Exoplanets
  • High contrast imaging

ASJC Scopus subject areas

  • Space and Planetary Science
  • Control and Systems Engineering
  • Mechanical Engineering
  • Electronic, Optical and Magnetic Materials
  • Astronomy and Astrophysics
  • Instrumentation

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