Recurrence quantification analysis as a post-processing technique in adaptive optics high contrast imaging

M. Stangalini; G. Li Causi; F. Pedichini; S. Antoniucci; M. Mattioli; J. Christou; G. Consolini; D. Hope; S. M. Jefferies; R. Piazzesi; V. Testa

doi:10.1117/12.2313355

10 July 2018 Recurrence quantification analysis as a post-processing technique in adaptive optics high contrast imaging

M. Stangalini, G. Li Causi, F. Pedichini, S. Antoniucci, M. Mattioli, J. Christou, G. Consolini, D. Hope, S. M. Jefferies, R. Piazzesi, V. Testa

Author Affiliations +

Proceedings Volume 10703, Adaptive Optics Systems VI; 107032V (2018) https://doi.org/10.1117/12.2313355
Event: SPIE Astronomical Telescopes + Instrumentation, 2018, Austin, Texas, United States

Abstract

Recurrence Quantification Analysis (RQA) is a non-linear time series analysis technique widely employed in many different research fields. Among the many applications of this method, it has been shown that it can be successfully employed in the detection of small signals embedded into noise. In this work we explore the possibility of using the RQA in astronomical high contrast imaging, for the detection of faint objects nearby bright sources in very high frame rate (1 KHz) data series. For this purpose, we used a real 1 kHz image sequence of a bright star, acquired with the SHARK-VIS forerunner at LBT. Our results show excellent performances in terms of detection contrasts even with a very short data sequence (a few seconds). The use of RQA in astronomical high contrast imaging is discussed in light of the possible science applications and with respect to other techniques like, for example, the angular differential imaging (ADI) or the Speckle-Free ADI (SFADI).

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M. Stangalini, G. Li Causi, F. Pedichini, S. Antoniucci, M. Mattioli, J. Christou, G. Consolini, D. Hope, S. M. Jefferies, R. Piazzesi, and V. Testa "Recurrence quantification analysis as a post-processing technique in adaptive optics high contrast imaging", Proc. SPIE 10703, Adaptive Optics Systems VI, 107032V (10 July 2018); https://doi.org/10.1117/12.2313355

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