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Authordc.contributor.authorGómez González, Carlos 
Authordc.contributor.authorWertz, Olivier 
Authordc.contributor.authorAbsil, Olivier 
Authordc.contributor.authorChristiaens, Valentin 
Authordc.contributor.authorDefrere, Denis 
Authordc.contributor.authorMawet, Dimitri 
Authordc.contributor.authorMilli, Julien 
Authordc.contributor.authorAbsil, Pierre Antoine 
Authordc.contributor.authorVan Droogenbroeck, Marc 
Authordc.contributor.authorCantalloube, Faustine 
Authordc.contributor.authorPhilip, Hinz 
Authordc.contributor.authorSkemer, Andrew J. 
Authordc.contributor.authorKarlsson, Mikael 
Authordc.contributor.authorSurdej, Jean 
Admission datedc.date.accessioned2018-05-17T21:55:16Z
Available datedc.date.available2018-05-17T21:55:16Z
Publication datedc.date.issued2017
Cita de ítemdc.identifier.citationThe Astronomical Journal, 154:7 (12pp), 2017 Julyes_ES
Identifierdc.identifier.other10.3847/1538-3881/aa73d7
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/147899
Abstractdc.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.es_ES
Patrocinadordc.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, NNX13AJ17Ges_ES
Lenguagedc.language.isoenes_ES
Publisherdc.publisherIOP Publishing Ltd.es_ES
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile*
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
Sourcedc.sourceThe Astronomical Journales_ES
Keywordsdc.subjectMethods data analysises_ES
Keywordsdc.subjectPlanetary systemses_ES
Keywordsdc.subjectPlanets and satellites detectiones_ES
Keywordsdc.subjectTechniques high angular resolutiones_ES
Keywordsdc.subjectTechniques image processinges_ES
Títulodc.titleVIP: Vortex Image Processing package for high-contrast direct imaginges_ES
Document typedc.typeArtículo de revista
Catalogueruchile.catalogadortjnes_ES
Indexationuchile.indexArtículo de publicación ISIes_ES


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Attribution-NonCommercial-NoDerivs 3.0 Chile
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Chile