Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys
- Authors:
-
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- Centre for Exoplanet Science, SUPA, School of Physics and Astronomy, University of St Andrews, St Andrews KY16 9SS, UK
- Institut d’astrophysique de Paris, UMR7095 CNRS, Université Pierre & Marie Curie, 98bis boulevard Arago, F-75014 Paris, France
- Observatoire de Genève, Université de Genève, 51 Chemin des Maillettes, CH-1290 Sauverny, Switzerland
- School of Physics & Astronomy, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
- Université Grenoble Alpes, CNRS, IPAG, F-38000 Grenoble, France
- Qatar Environment and Energy Research Institute (QEERI), Hamad Bin Khalifa University (HBKU), Qatar Foundation, Doha, Qatar
- Astrophysics Group, Keele University, Staffordshire ST5 5BG, UK
- Centre for Exoplanets and Habitability, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK, Department of Physics, University of Warwick, Coventry CV4 7AL, UK
- Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, P-4150-762 Porto, Portugal
- Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, 15236 Penteli, Greece
- Department of Physics, University of Warwick, Coventry CV4 7AL, UK, INAF – Osservatorio Astrofisico di Catania, Via S. Sofia 78, I-95123 Catania, Italy
- Department of Physics, Hobart and William Smith Colleges, Geneva, NY 14456, USA
- Department of Physics, University of Rome Tor Vergata, Via della Ricerca Scientifica 1, I-00133 Roma, Italy, Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg, Germany, INAF – Astrophysical Observatory of Turin, Via Osservatorio 20, I-10025 Pino Torinese, Italy, International Institute for Advanced Scientific Studies (IIASS), Via G. Pellegrino 19, I-84019 Vietri sul Mare (SA), Italy
- Instituto de Astrosfísica de Canarias (IAC), E-38205 La Laguna, Tenerife, Spain, Departamento de Astrofísica, Universidad de La Laguna (ULL), E-38206 La Laguna, Tenerife, Spain
- Observatoire de Genève, Université de Genève, 51 Chemin des Maillettes, CH-1290 Sauverny, Switzerland, Cavendish Laboratory, JJ Thompson Avenue, Cambridge CB3 0HE, UK
- INAF – Osservatorio Astrofisico di Catania, Via S. Sofia 78, I-95123 Catania, Italy
- Publication Date:
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Fuel Cell Technologies Office
- OSTI Identifier:
- 1490756
- Resource Type:
- Published Article
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Additional Journal Information:
- Journal Name: Monthly Notices of the Royal Astronomical Society Journal Volume: 483 Journal Issue: 4; Journal ID: ISSN 0035-8711
- Publisher:
- Oxford University Press
- Country of Publication:
- United Kingdom
- Language:
- English
Citation Formats
Schanche, N., Cameron, A. Collier, Hébrard, G., Nielsen, L., Triaud, A. H. M. J., Almenara, J. M., Alsubai, K. A., Anderson, D. R., Armstrong, D. J., Barros, S. C. C., Bouchy, F., Boumis, P., Brown, D. J. A., Faedi, F., Hay, K., Hebb, L., Kiefer, F., Mancini, L., Maxted, P. F. L., Palle, E., Pollacco, D. L., Queloz, D., Smalley, B., Udry, S., West, R., and Wheatley, P. J. Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys. United Kingdom: N. p., 2018.
Web. doi:10.1093/mnras/sty3146.
Schanche, N., Cameron, A. Collier, Hébrard, G., Nielsen, L., Triaud, A. H. M. J., Almenara, J. M., Alsubai, K. A., Anderson, D. R., Armstrong, D. J., Barros, S. C. C., Bouchy, F., Boumis, P., Brown, D. J. A., Faedi, F., Hay, K., Hebb, L., Kiefer, F., Mancini, L., Maxted, P. F. L., Palle, E., Pollacco, D. L., Queloz, D., Smalley, B., Udry, S., West, R., & Wheatley, P. J. Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys. United Kingdom. https://doi.org/10.1093/mnras/sty3146
Schanche, N., Cameron, A. Collier, Hébrard, G., Nielsen, L., Triaud, A. H. M. J., Almenara, J. M., Alsubai, K. A., Anderson, D. R., Armstrong, D. J., Barros, S. C. C., Bouchy, F., Boumis, P., Brown, D. J. A., Faedi, F., Hay, K., Hebb, L., Kiefer, F., Mancini, L., Maxted, P. F. L., Palle, E., Pollacco, D. L., Queloz, D., Smalley, B., Udry, S., West, R., and Wheatley, P. J. Thu .
"Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys". United Kingdom. https://doi.org/10.1093/mnras/sty3146.
@article{osti_1490756,
title = {Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys},
author = {Schanche, N. and Cameron, A. Collier and Hébrard, G. and Nielsen, L. and Triaud, A. H. M. J. and Almenara, J. M. and Alsubai, K. A. and Anderson, D. R. and Armstrong, D. J. and Barros, S. C. C. and Bouchy, F. and Boumis, P. and Brown, D. J. A. and Faedi, F. and Hay, K. and Hebb, L. and Kiefer, F. and Mancini, L. and Maxted, P. F. L. and Palle, E. and Pollacco, D. L. and Queloz, D. and Smalley, B. and Udry, S. and West, R. and Wheatley, P. J.},
abstractNote = {},
doi = {10.1093/mnras/sty3146},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 4,
volume = 483,
place = {United Kingdom},
year = {Thu Nov 22 00:00:00 EST 2018},
month = {Thu Nov 22 00:00:00 EST 2018}
}
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https://doi.org/10.1093/mnras/sty3146
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Cited by: 31 works
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