Single Transit Detection In Kepler With Machine Learning And Onboard Spacecraft Diagnostics – Astrobiology – Astrobiology News
Best-fit transit models for all 8 of the visible transits within Kepler of KOI 1271.01. Overlaid with the models is a scatter plot of the normalized flux values for the 4-day window with the associated error bars given by Kepler. The models were found using EXOPLANET, and the only parameter that was fit for was the time of center transit. The title of each subplot is the epoch number along with the best-fit time of the transit center. We fit the models over a 4-day range around the predicted time of transit using the ephemeris of KOI 1271.01. Therefore, the location of the transit within the window gives a hint of the order of magnitude of the epochs TTV. astro-ph.EP
Exoplanet discovery at long orbital periods requires reliably detecting individual transits without additional information about the system. Techniques like phase-folding of light curves and periodogram analysis of radial velocity data are more sensitive to planets with shorter orbital periods, leaving a dearth of planet discoveries at long periods.
We present a novel technique using an ensemble of Convolutional Neural Networks incorporating the onboard spacecraft diagnostics of Kepler to classify transits within a light curve. We create a pipeline to recover the location of individual transits, and the period of the orbiting planet, which maintains >80% transit recovery sensitivity out to an 800-day orbital period.
Our neural network pipeline has the potential to discover additional planets in the Kepler dataset, and crucially, within the -Earth regime. We report our first candidate from this pipeline, KOI 1271.02. KOI 1271.01 is known to exhibit strong Transit Timing Variations (TTVs), and so we jointly model the TTVs and transits of both transiting planets to constrain the orbital configuration and planetary parameters and conclude with a series of potential parameters for KOI 1271.02, as there is not enough data currently to uniquely constrain the system.
We conclude that KOI 1271.02 has a radius of 5.32 0.20 R and a mass of 28.940.230.47 M. Future constraints on the nature of KOI 1271.02 require measuring additional TTVs of KOI 1271.01 or observing a second transit of KOI 1271.02.
Matthew T. Hansen, Jason A. Dittmann
Comments: 23 pages, 23 figures, submitted to AJ Subjects: Earth and Planetary Astrophysics (astro-ph.EP); Instrumentation and Methods for Astrophysics (astro-ph.IM); Machine Learning (cs.LG) Cite as: arXiv:2403.03427 [astro-ph.EP] (or arXiv:2403.03427v1 [astro-ph.EP] for this version) Submission history From: Matthew Hansen [v1] Wed, 6 Mar 2024 03:16:47 UTC (1,474 KB) https://arxiv.org/abs/2403.03427 Astrobiology,
Explorers Club Fellow, ex-NASA Space Station Payload manager/space biologist, Away Teams, Journalist, Lapsed climber, Synaesthete, NaVi-Jedi-Freman-Buddhist-mix, ASL, Devon Island and Everest Base Camp veteran, (he/him)
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Single Transit Detection In Kepler With Machine Learning And Onboard Spacecraft Diagnostics - Astrobiology - Astrobiology News
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