1. Kernel-phase analysis: aperture modeling prescriptions that minimize calibration errors
- Author
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Nick Cvetojevic, Coline Lopez, David Mary, Mamadou N'Diaye, Romain Laugier, Jens Kammerer, Alban Ceau, Frantz Martinache, Joseph Louis LAGRANGE (LAGRANGE), Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Observatoire de la Côte d'Azur, COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), European Southern Observatory (ESO), Research School of Astronomy and Astrophysics [Canberra] (RSAA), Australian National University (ANU), Centre National de la Recherche Scientifique (CNRS)-Observatoire de la Côte d'Azur, Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA), Centre National de la Recherche Scientifique (CNRS), Observatoire de la Côte d'Azur (OCA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, Nice, France.
- Subjects
Aperture ,Calibration (statistics) ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,FOS: Physical sciences ,Context (language use) ,Astrophysics ,Residual ,01 natural sciences ,stars: low-mass ,instrumentation: high angular resolution ,0103 physical sciences ,010303 astronomy & astrophysics ,Instrumentation and Methods for Astrophysics (astro-ph.IM) ,Physics ,[PHYS]Physics [physics] ,010308 nuclear & particles physics ,Linear model ,Astrophysics::Instrumentation and Methods for Astrophysics ,Astronomy and Astrophysics ,methods: data analysis ,binaries: visual ,Interferometry ,Kernel (image processing) ,Space and Planetary Science ,[SDU]Sciences of the Universe [physics] ,Closure phase ,Astrophysics - Instrumentation and Methods for Astrophysics ,[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph] ,Algorithm - Abstract
Kernel-phase is a data analysis method based on a generalization of the notion of closure-phase invented in the context of interferometry, but that applies to well corrected diffraction dominated images produced by an arbitrary aperture. The linear model upon which it relies theoretically leads to the formation of observable quantities robust against residual aberrations. In practice, detection limits reported thus far seem to be dominated by systematic errors induced by calibration biases not sufficiently filtered out by the kernel projection operator. This paper focuses on the impact the initial modeling of the aperture has on these errors and introduces a strategy to mitigate them, using a more accurate aperture transmission model. The paper first uses idealized monochromatic simulations of a non trivial aperture to illustrate the impact modeling choices have on calibration errors. It then applies the outlined prescription to two distinct data-sets of images whose analysis has previously been published. The use of a transmission model to describe the aperture results in a significant improvement over the previous type of analysis. The thus reprocessed data-sets generally lead to more accurate results, less affected by systematic errors. As kernel-phase observing programs are becoming more ambitious, accuracy in the aperture description is becoming paramount to avoid situations where contrast detection limits are dominated by systematic errors. Prescriptions outlined in this paper will benefit any attempt at exploiting kernel-phase for high-contrast detection., Comment: 12 pages, 15 figures, accepted for publication by Astronomy & Astrophysics
- Published
- 2020
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