Dr. Kenneth Hanley Profile

Dr. Kenneth Hanley

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Publications (2)

Proceedings Article | 27 July 2016 Paper

Detection of faint companions in multi-spectral data using a maximum likelihood approach

Kenneth Hanley, Nicholas Devaney, Éric Thiébaut

Proceedings Volume 9909, 99097W (2016) https://doi.org/10.1117/12.2232550

KEYWORDS: Adaptive optics, Optical spheres, Stars, Coronagraphy, Point spread functions, Electronic filtering, Computer simulations, Detection and tracking algorithms, Data modeling, Signal to noise ratio

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Proceedings Article | 26 July 2016 Paper

Exploiting physical constraints for multi-spectral exo-planet detection

Éric Thiébaut, Nicholas Devaney, Maud Langlois, Kenneth Hanley

Proceedings Volume 9909, 99091R (2016) https://doi.org/10.1117/12.2233672

KEYWORDS: Optical spheres, Stars, Colorimetry, Speckle, Planets, Surface conduction electron emitter displays, Point spread functions, Data modeling, Physics, Device simulation

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We derive a physical model of the on-axis PSF for a high contrast imaging system such as GPI or SPHERE. This model is based on a multi-spectral Taylor series expansion of the diffraction pattern and predicts that the speckles should be a combination of spatial modes with deterministic chromatic magnification and weighting. We propose to remove most of the residuals by fitting this model on a set of images at multiple wavelengths and times. On simulated data, we demonstrate that our approach achieves very good speckle suppression without additional heuristic parameters.

The residual speckles^{1, 2} set the most serious limitation in the detection of exo-planets in high contrast coronographic images provided by instruments such as SPHERE³ at the VLT, GPI^{4, 5} at Gemini, or SCExAO⁶ at Subaru. A number of post-processing methods have been proposed to remove as much as possible of the residual speckles while preserving the signal from the planets. These methods exploit the fact that the speckles and the planetary signal have different temporal and spectral behaviors. Some methods like LOCI⁷ are based on angular differential imaging⁸ (ADI), spectral differential imaging^{9, 10} (SDI), or on a combination of ADI and SDI.11 Instead of working on image differences, we propose to tackle the exo-planet detection as an inverse problem where a model of the residual speckles is fit on the set of multi-spectral images and, possibly, multiple exposures. In order to reduce the number of degrees of freedom, we impose specific constraints on the spatio-spectral distribution of stellar speckles. These constraints are deduced from a multi-spectral Taylor series expansion of the diffraction pattern for an on-axis source which implies that the speckles are a combination of spatial modes with deterministic chromatic magnification and weighting. Using simulated data, the efficiency of speckle removal by fitting the proposed multi-spectral model is compared to the result of using an approximation based on the singular value decomposition of the rescaled images. We show how the difficult problem to fitting a bilinear model on the can be solved in practise. The results are promising for further developments including application to real data and joint planet detection in multi-variate data (multi-spectral and multiple exposures images).

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