4.7 Article

Confidence level and sensitivity limits in high-contrast imaging

Journal

ASTROPHYSICAL JOURNAL
Volume 673, Issue 1, Pages 647-656

Publisher

IOP PUBLISHING LTD
DOI: 10.1086/523839

Keywords

instrumentation : adaptive optics; instrumentation : high angular resolution; methods : data analysis; methods : statistical; planetary systems; stars : imaging; stars : low-mass, brown dwarfs; techniques : image processing

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In long adaptive optics corrected exposures, exoplanet detections are currently limited by speckle noise originating from the telescope and instrument optics, and it is expected that such noise will also limit future high-contrast imaging instruments for both ground- and space-based telescopes. Previous theoretical analyses have shown that the time intensity variations of a single speckle follow a modified Rician. It is first demonstrated here that for a circular pupil, this temporal intensity distribution also represents the speckle spatial intensity distribution at a fixed separation from the point-spread function center; this fact is demonstrated using numerical simulations for coronagraphic and noncoronagraphic data. The real statistical distribution of the noise needs to be taken into account explicitly when selecting a detection threshold appropriate for some desired confidence level (CL). In this paper, a technique is described to obtain the pixel intensity distribution of an image and its corresponding CL as a function of the detection threshold. Using numerical simulations, it is shown that in the presence of speckle noise, a detection threshold up to 3 times higher is required to obtain a CL equivalent to that at 5 sigma for Gaussian noise. The technique is then tested on data acquired by simultaneous spectral differential imaging with TRIDENT and by angular differential imaging with NIRI. It is found that the angular differential imaging technique produces quasi-Gaussian residuals, a remarkable result compared to classical adaptive optic imaging. Finally, a power law is derived to predict the 1 - 3 x 10(-7) CL detection threshold when averaging a partially correlated non-Gaussian noise.

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