Coronagraphic imaging in combination with moderate to high spectral resolution may prove more effective in both detecting extrasolar planets and characterizing them than a standard coronagraphic imaging approach. We envisage an integral-field spectrograph coupled to a coronagraph to produce a 3D datacube. For the idealised case where the spectrum of the star is well-known and unchanging across the field, we discuss the utility of cross-correlation to seek the extrasolar planet signal, and describe a mathematical approach to completely eliminate stray light from the host star (although not its Poisson noise). For the case where the PSF is dominated by diffraction and scattering effects, and comprises a multitude of speckles within an Airy pattern typical of a space-based observation, we turn the wavelength dependence of the PSF to advantage and present a general way to eliminate the contribution from the star while preserving both the flux and spectrum of the extrasolar planet. We call this method `spectral deconvolution'. We illustrate the dramatic gains by showing an idealized simulation that results in a 20-sigma detection of a Jovian planet at 2 pc with a 2-m coronagraphic space telescope, even though the planet's peak flux is only 1% that of the PSF wings of the host star. This scales to detection of a terrestrial extrasolar planet at 2 pc with an 8-m coronagraphic Terrestrial Planet Finder (TPF) in ~7 hr (or less with appropriate spatial filtering). Data on the spectral characteristics of the extrasolar planet and hence on its atmospheric constituents and possible biomarkers are obtained naturally as part of this process.

Imaging Spectroscopy for Extrasolar Planet Detection

We present new Gemini Planet Imager observations of the young exoplanet 51 Eridani b which provide further evidence that the companion is physically associated with 51 Eridani. Combining this new astrometric measurement with those reported in the literature, we significantly reduce the posterior probability that 51 Eridani b is an unbound foreground or background T-dwarf in a chance alignment with 51 Eridani to $2\times10^{-7}$, an order of magnitude lower than previously reported. If 51 Eridani b is indeed a bound object, then we have detected orbital motion of the planet between the discovery epoch and the latest epoch. By implementing a computationally efficient Monte Carlo technique, preliminary constraints are placed on the orbital parameters of the system. The current set of astrometric measurements suggest an orbital semimajor axis of $14^{+7}_{-3}$ AU, corresponding to a period of $41^{+35}_{-12}$ years (assuming a mass of $1.75$ $M_{\odot}$ for the central star), and an inclination of $138^{+15}_{-13}$ deg. The remaining orbital elements are only marginally constrained by the current measurements. These preliminary values suggest an orbit which does not share the same inclination as the orbit of the distant M-dwarf binary, GJ 3305, which is a wide physically bound companion to 51 Eridani.

Astrometric Confirmation and Preliminary Orbital Parameters of the Young Exoplanet 51 Eridani b with the Gemini Planet Imager

Photo-optical instrumentation. Present and future developments: Seminar proceedings, society of photo-optical instrumentation engineers (SPIE Seminar Proceedings, June 25–28, 1970, Vol. 22). S. Uyemura and F. P. Turner (Editors). SPIE, Tokyo, 1971, 173 pp., $22.00

The Palomar High-precision Astrometric Search for Exoplanet Systems (PHASES) monitored 51 subarcsecond binary systems to determine precision binary orbits, study the geometries of triple and quadruple star systems, and discover previously unknown faint astrometric companions as small as giant planets. PHASES measurements made with the Palomar Testbed Interferometer (PTI) from 2002 until PTI ceased normal operations in late 2008 are presented. Infrared differential photometry of several PHASES targets were measured with Keck Adaptive Optics and are presented.

The phases differential astrometry data archive. i. measurements and description

The SPHERE is an exo-solar planet imager, which goal is to detect giant exo-solar planets in the vicinity of bright stars and to characterize them through spectroscopic and polarimetric observations. It is a complete system with a core made of an extreme-Adaptive Optics (AO) wavefront correction, a pupil tracker and diffraction suppression through a variety of coronagraphs. At its back end, a differential dual imaging camera and an integral field spectrograph (IFS) work in the Near Infrared (NIR) Y, J, H and Ks bands (0.95 - 2.32μm), and a high resolution polarization camera covers the optical range (0.6 - 0.9 μm). The IFS is a low resolution spectrograph (R~50) working in the near IR (0.95-1.65 microns), an ideal wavelength range for the detection of giant planet features. In our baseline design the IFU is a new philosophy microlens array of about 145x145 elements designed to reduce as much as possible the cross talk when working at diffraction limit. The IFU will cover a field of view of about 1.7 x 1.7 square arcsecs reaching a contrast of 10-7, providing a high contrast and high spatial resolution "imager" able to search for planet well inside the star PSF.

SPHERE-IFS: The spectro differential imager of the VLT for exoplanet search .

Direct imaging of exoplanets provides valuable information about the light they emit, their interactions with their host star environment and their nature In order to image such objects, advanced data processing tools adapted to the instrument are needed In particular, the presence of quasi-static speckles in the images, due to optical aberrations distorting the light from the observed star, prevents planetary signals from being distinguished In this thesis, I present two innovative image processing methods, both based on an inverse problem approach, enabling the disentanglement of the quasi-static speckles from the planetary signals My work consisted of improving these two algorithms in order to be able to process on-sky imagesThe first one, called ANDROMEDA, is an algorithm dedicated to point source detection and characterization via a maximum likelihood approach ANDROMEDA makes use of the temporal diversity provided by the image field rotation during the observation, to recognize the deterministic signature of a rotating companion over the stellar halo From application of the original version on real data, I have proposed and qualified improvements in order to deal with the non-stable large scale structures due to the adaptative optics residuals and with the remaining level of correlated noise in the data Once ANDROMEDA became operational on real data, I analyzed its performance and its sensitivity to the user-parameters proving the robustness of the algorithm I also conducted a detailed comparison to the other algorithms widely used by the exoplanet imaging community today showing that ANDROMEDA is a competitive method with practical advantages In particular, it is the only method that allows a fully unsupervised detection By the numerous tests performed on different data set, ANDROMEDA proved its reliability and efficiency to extract companions in a rapid and systematic way (with only one user parameter to be tuned) From these applications, I identified several perspectives whose implementation could significantly improve the performance of the pipelineThe second algorithm, called MEDUSAE, consists in jointly estimating the aberrations (responsible for the speckle field) and the circumstellar objects by relying on a coronagraphic image formation model MEDUSAE exploits the spectral diversity provided by multispectral data In order to In order to refine the inversion strategy and probe the most critical parameters, I applied MEDUSAE on a simulated data set generated with the model used in the inversion To investigate further the impact of the discrepancy between the image model used and the real images, I applied the method on realistic simulated images At last, I applied MEDUSAE on real data and from the preliminary results obtained, I identified the important input required by the method and proposed leads that could be followed to make this algorithm operational to process on-sky data

Detection and characterization of exoplanets in high contrast images by the inverse problem approach

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Detection and characterization of exoplanets in high contrast images by the inverse problem approach