Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys

ACC acknowledges support from STFC consolidated grant ST/R000824/1 and UK Space Agency grant ST/R003203/1.

[1]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[2]  D. F. Gray,et al.  The Observation and Analysis of Stellar Photospheres , 2021 .

[3]  G. Kov'acs,et al.  A box-fitting algorithm in the search for periodic transits , 2002, astro-ph/0206099.

[4]  Timothy M. Brown,et al.  Expected Detection and False Alarm Rates for Transiting Jovian Planets , 2003, astro-ph/0307256.

[5]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[6]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[7]  K. Stanek,et al.  HATNET Variability Survey in the High Stellar Density “Kepler Field” with Millimagnitude Image Subtraction Photometry , 2004 .

[8]  R. W. Noyes,et al.  A trend filtering algorithm for wide-field variability surveys , 2004 .

[9]  Tsevi Mazeh,et al.  Correcting systematic effects in a large set of photometric light curves , 2005, astro-ph/0502056.

[10]  B. Enoch,et al.  The WASP Project and the SuperWASP Cameras , 2006, astro-ph/0608454.

[11]  A. Collier Cameron,et al.  The SuperWASP wide-field exoplanetary transit survey: candidates from fields 23 h < RA < 03 h , 2006 .

[12]  A. Collier Cameron,et al.  A fast hybrid algorithm for exoplanetary transit searches , 2006, astro-ph/0609418.

[13]  Richard W. Pogge,et al.  The Kilodegree Extremely Little Telescope (KELT): A Small Robotic Telescope for Large‐Area Synoptic Surveys , 2007, 0704.0460.

[14]  R. G. West,et al.  Efficient identification of exoplanetary transit candidates from SuperWASP light curves , 2007, 0707.0417.

[15]  M. Auvergne,et al.  The CoRoT satellite in flight : description and performance , 2009, 0901.2206.

[16]  Howard Isaacson,et al.  Kepler Planet-Detection Mission: Introduction and First Results , 2010, Science.

[17]  Chih-Jen Lin,et al.  Dual coordinate descent methods for logistic regression and maximum entropy models , 2011, Machine Learning.

[18]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[19]  John McKean,et al.  American Astronomical Society Meeting Abstracts , 2011 .

[20]  P. Dubath,et al.  Random forest automated supervised classification of Hipparcos periodic variable stars , 2011, 1101.2406.

[21]  S. Perruchot,et al.  Higher-precision radial velocity measurements with the SOPHIE spectrograph using octagonal-section fibers , 2011, Optical Engineering + Applications.

[22]  P. Dubath,et al.  Automated classification of Hipparcos unsolved variables , 2012, 1301.1545.

[23]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[24]  Klaus-Robert Müller,et al.  Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.

[25]  P. Conroy,et al.  HATSouth: A Global Network of Fully Automated Identical Wide-Field Telescopes , 2012, 1206.1391.

[26]  G. Maravelias,et al.  Trawling for transits in a sea of noise: a search for exoplanets by analysis of WASP optical light curves and follow-up (SEAWOLF) , 2013, 1310.7586.

[27]  Paul M. Brunet,et al.  The Gaia mission , 2013, 1303.0303.

[28]  P. Giommi,et al.  The PLATO 2.0 mission , 2013, 1310.0696.

[29]  P. Tenenbaum,et al.  AUTOMATIC CLASSIFICATION OF KEPLER PLANETARY TRANSIT CANDIDATES , 2014, 1408.1496.

[30]  M. Smith,et al.  Machine Learning Classification of SDSS Transient Survey Images , 2014, ArXiv.

[31]  T. Murphy,et al.  AUTOMATIC CLASSIFICATION OF TIME-VARIABLE X-RAY SOURCES , 2014, 1403.0188.

[32]  Carl J. Grillmair,et al.  AUTOMATED CLASSIFICATION OF PERIODIC VARIABLE STARS DETECTED BY THE WIDE-FIELD INFRARED SURVEY EXPLORER , 2014, 1402.0125.

[33]  Mark Clampin,et al.  Transiting Exoplanet Survey Satellite , 2014, 1406.0151.

[34]  G. Desvignes,et al.  SEARCHING FOR PULSARS USING IMAGE PATTERN RECOGNITION , 2013, 1309.0776.

[35]  Laura Kreidberg,et al.  batman: BAsic Transit Model cAlculatioN in Python , 2015, 1507.08285.

[36]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[37]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[38]  K. Pichara,et al.  Photometric classification of quasars from RCS-2 using Random Forest , 2014, 1405.5298.

[39]  Jian Sun,et al.  Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[40]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[41]  Massimo Brescia,et al.  An analysis of feature relevance in the classification of astronomical transients with machine learning methods , 2016, 1601.03931.

[42]  Naonori Ueda,et al.  Machine-learning selection of optical transients in the Subaru/Hyper Suprime-Cam survey , 2016, 1609.03249.

[43]  E. Bachelet,et al.  SIDRA: a blind algorithm for signal detection in photometric surveys , 2015, 1511.03456.

[44]  Gaia Collaboration,et al.  The Gaia mission , 2016, 1609.04153.

[45]  Kyle A. Pearson,et al.  Searching for exoplanets using artificial intelligence , 2017, Monthly Notices of the Royal Astronomical Society.

[46]  Jie Yu,et al.  Deep learning classification in asteroseismology , 2017, 1705.06405.

[47]  David M. Kipping,et al.  Transit Clairvoyance: Enhancing TESS follow-up using artificial neural networks , 2017 .

[48]  Brett Naul,et al.  A recurrent neural network for classification of unevenly sampled variable stars , 2017, Nature Astronomy.

[49]  David J Armstrong,et al.  Transit shapes and self-organizing maps as a tool for ranking planetary candidates: application to Kepler and K2 , 2016, 1611.01968.

[50]  David W. Hogg,et al.  Using machine learning to explore the long-term evolution of GRS 1915+105 , 2017 .

[51]  Christopher J. Shallue,et al.  Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90 , 2017, 1712.05044.

[52]  T. A. Lister,et al.  Gaia Data Release 2. Summary of the contents and survey properties , 2018, 1804.09365.

[53]  A. Cameron,et al.  Hierarchical Bayesian calibration of tidal orbit decay rates among hot Jupiters , 2018, 1801.10561.

[54]  F. Bouchy,et al.  Discovery of WASP-174b: Doppler tomography of a near-grazing transit , 2018, Monthly Notices of the Royal Astronomical Society.

[55]  K. Sokolovsky,et al.  Machine learning search for variable stars , 2017, 1710.07290.

[56]  David J Armstrong,et al.  Automatic vetting of planet candidates from ground based surveys: Machine learning with NGTS , 2018, 1805.07089.

[57]  L. Hillenbrand,et al.  Three Small Planets Transiting the Bright Young Field Star K2-233 , 2018, 1803.05056.