27 July 2016 Detection of faint companions in multi-spectral data using a maximum likelihood approach
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Abstract
Direct, ground-based exoplanet detection is an extremely challenging task requiring extreme adaptive optics (AO) systems and very high contrast. Dedicated planet hunters, such as SPHERE and GPI have been designed with these requirements in mind. Despite this, direct detection is still limited due to the presence of residual speckles. Smith et al.1 described a maximum likelihood estimation technique for the detection of exoplanets in speckle data in which the planet appears to rotate about a host star when observing with an alt-az telescope. We propose the adaptation of this technique to operate on multi-spectral data, such as produced by the integral field spectrographs present on both SPHERE2 or GPI.3 As the speckle pattern approximately scales smoothly with wavelength, it is possible to resample data to a single reference wavelength in which speckles will remain fixed in the wavelength dimension while any companions that are present will exhibit radial motion in a predictable manner. We simulate data comparable to SPHERE and with this we compare the performance of our algorithm with another multi-spectral detection technique; spectral deconvolution. We compare the techniques using a ROC (Receiver Operating Characteristic) analysis.
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Kenneth Hanley, Nicholas Devaney, Éric Thiébaut, "Detection of faint companions in multi-spectral data using a maximum likelihood approach", Proc. SPIE 9909, Adaptive Optics Systems V, 99097W (27 July 2016); doi: 10.1117/12.2232550; https://doi.org/10.1117/12.2232550
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