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Transit shapes and self organising maps as a tool for ranking planetary candidates : application to Kepler and K2
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Armstrong, David J., Pollacco, Don and Santerne, A. (2017) Transit shapes and self organising maps as a tool for ranking planetary candidates : application to Kepler and K2. Monthly Notices of the Royal Astronomical Society, 465 (3). pp. 2634-2642. ISSN 0035-8711.
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Official URL: http://dx.doi.org/10.1093/mnras/stw2881
Abstract
A crucial step in planet hunting surveys is to select the best candidates for follow up observations, given limited telescope resources. This is often performed by human ‘eyeballing’, a time consuming and statistically awkward process. Here we present a new, fast machine learning technique to separate true planet signals from astrophysical
false positives. We use Self Organising Maps (SOMs) to study the transit shapes of Kepler and K2 known and candidate planets. We find that SOMs are capable of distinguishing known planets from known false positives with a success rate of 87.0%, using the transit shape alone. Furthermore, they do not require any candidates to be dispositioned prior to use, meaning that they can be used early in a mission’s
lifetime. A method for classifying candidates using a SOM is developed, and applied to previously unclassified members of the Kepler KOI list as well as candidates from the K2 mission. The method is extremely fast, taking minutes to run the entire KOI list on a typical laptop. We make Python code for performing classifications publicly available, using either new SOMs or those created in this work. The SOM technique represents a novel method for ranking planetary candidate lists, and can be used both alone or as part of a larger autovetting code.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > Q Science (General) Q Science > QB Astronomy Q Science > QC Physics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Physics | ||||||||
Library of Congress Subject Headings (LCSH): | Planets--Detection--Data processing, Satellites--Detection--Data processing, Self-organizing maps, Extrasolar planets--Detection | ||||||||
Journal or Publication Title: | Monthly Notices of the Royal Astronomical Society | ||||||||
Publisher: | Oxford University Press | ||||||||
ISSN: | 0035-8711 | ||||||||
Official Date: | 2017 | ||||||||
Dates: |
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Volume: | 465 | ||||||||
Number: | 3 | ||||||||
Page Range: | pp. 2634-2642 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 9 November 2016 | ||||||||
Date of first compliant Open Access: | 22 May 2017 | ||||||||
Funder: | Seventh Framework Programme (European Commission) (FP7), Portugal. Fundação para a Ciência e a tecnologia [Foundation for Science and Technology] (FCT), Federación Española de Enfermedades Raras (FEDER), Marie Curie Intra-European Fellowship (IEF), United States. National Aeronautics and Space Administration (NASA) | ||||||||
Grant number: | 31301(FP7), . UID/FIS/04434/2013 (FCT), PTDC/FIS-AST/1526/201 (FCT), OCI-01-0145-FEDER-007672 (FEDER), POCI-01-0145-FEDER-01688 (FEDER), 627202 (IEF), NNX13AC07G (NASA) |
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