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dc.contributor.authorGomez Gonzalez, Carlos Alberto*
dc.contributor.authorWertz, Olivier*
dc.contributor.authorAbsil, O.*
dc.contributor.authorChristiaens, Valentin*
dc.contributor.authorDefrère, D.*
dc.contributor.authorMawet, Dimitri*
dc.contributor.authorMilli, Julien*
dc.contributor.authorAbsil, Pierre-Antoine*
dc.contributor.authorVan Droogenbroeck, Marc*
dc.contributor.authorCantalloube, Faustine*
dc.contributor.authorHinz, Philip M.*
dc.contributor.authorSkemer, Andrew J.*
dc.contributor.authorKarlsson, Mikael*
dc.contributor.authorSurdej, Jean*
dc.date.accessioned2017-07-12T16:13:07Z
dc.date.available2017-07-12T16:13:07Z
dc.date.issued2017-06-12
dc.identifier.citationVIP: Vortex Image Processing Package for High-contrast Direct Imaging 2017, 154 (1):7 The Astronomical Journalen
dc.identifier.issn1538-3881
dc.identifier.doi10.3847/1538-3881/aa73d7
dc.identifier.urihttp://hdl.handle.net/10150/624676
dc.description.abstractWe present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular differential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompassing pre- and post-processing algorithms, potential source. position and flux estimation, and sensitivity curve. generation. Among the reference point-spread. function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithms capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization, which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR 8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP, we investigated the presence of additional companions around HR 8799 and did not find any significant additional point source beyond the four known planets. VIP is available at http://github. com/vortex-exoplanet/VIP and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library.
dc.description.sponsorshipEuropean Research Council Under the European Union's Seventh Framework Program (ERC Grant) [337569]; French Community of Belgium through an ARC; Millennium Nucleus grant [RC130007]; National Aeronautics and Space Administration as part of its Exoplanet Exploration Program; NASA's Origins of Solar Systems Program [NNX13AJ17G]en
dc.language.isoenen
dc.publisherIOP PUBLISHING LTDen
dc.relation.urlhttp://stacks.iop.org/1538-3881/154/i=1/a=7?key=crossref.f935c4cecf1d1177e95108ad4c831a0cen
dc.rights© 2017. The American Astronomical Society. All rights reserved.en
dc.subjectmethods: data analysisen
dc.subjectplanetary systemsen
dc.subjectplanets and satellites: detectionen
dc.subjecttechniques: high angular resolutionen
dc.subjecttechniques: image processingen
dc.titleVIP: Vortex Image Processing Package for High-contrast Direct Imagingen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Dept Astron, Steward Observen
dc.identifier.journalThe Astronomical Journalen
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
refterms.dateFOA2018-06-22T19:52:00Z
html.description.abstractWe present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular differential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompassing pre- and post-processing algorithms, potential source. position and flux estimation, and sensitivity curve. generation. Among the reference point-spread. function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithms capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization, which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR 8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP, we investigated the presence of additional companions around HR 8799 and did not find any significant additional point source beyond the four known planets. VIP is available at http://github. com/vortex-exoplanet/VIP and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library.


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