Published in Nature, 2023
Discovery of a close-in planet that should have been consumed by its host star in the past
Recommended citation: Hon, M.; Huber, D.; Rui, N. Z. ; et al.. ”A close-in giant planet escaping engulfment by its star”, 2023, Nature, 618, 917
Published in The Astronomical Journal, 2022
Asteroseismology of the best and the brightest red giants in TESS
Recommended citation: Hon, M.; Kuszlewicz, J. S.; Huber, D.; et al.. ”HD-TESS: An Asteroseismic Catalog of Bright Red Giants within TESS Continuous Viewing Zones”, 2022, AJ, 164, 135
Published in The Astrophysical Journal, 2021
An all-sky search for oscillating giants from TESS, powered by machine learning.
Recommended citation: Hon, M.; Huber, D.; Kuszlewicz, J. S.; et al.. ”A ’Quick Look’ at All-Sky Galactic Archeology with TESS: 158,000 Oscillating Red Giants from the MIT Quick-Look Pipeline”, 2021, ApJ, 919, 131
Published in Monthly Notices of the Royal Astronomical Society, 2020
We use deep learning to determine precise asteroseismic ages of subgiants from stellar models.
Recommended citation: Hon, M.; Bellinger, E. P.; Hekker, S.; et al..“Asteroseismic inference of subgiant evolutionary parameters with deep learning”, 2019, MNRAS, 499, 2445
Published in Monthly Notices of the Royal Astronomical Society, 2019
This work searches for evolved Sun-like stars across the entire Kepler catalog using deep learning-based computer vision, finding many stars previously untargeted by the spacecraft.
Recommended citation: Hon, M.; Stello, D.; Garc ́ıa, R. A.; et al..“A search for red giant solar-like oscillations in all Kepler data”, 2019, MNRAS, 485, 5616
Published in The Astrophysical Journal, 2018
For the first time, we use deep learning-based computer vision to mimic the human visual ability in detecting solar-like oscillations in images of red giants power spectra. Thousands of stars can be analyzed in seconds with a human expert-level ability, making this method into an extremely powerful tool in the era of Big Data in asteroseismology.
Recommended citation: Hon, M.; Stello, D.; Zinn, J..“Detecting Solar-like Oscillations in Red Giants with Deep Learning”, 2018, ApJ, 859, 64.
Published in Monthly Notices of the Royal Astronomical Society, 2018
This work extends the red giant evolutionary state convolutional network towards K2- and TESS-like datasets, showing that high levels of accuracy can still being achieved for shorter observational data. The evolutionary states of around 15,000 Kepler red giants are additionally classified, doubling the number of red giants that given this analysis.
Recommended citation: Hon, M.; Stello, D.; Yu, J..“Deep learning classification in asteroseismology using an improved neural network: result on 15000 Kepler red giants and applications to K2 and TESS data”, 2018, MNRAS, 476, 3233.
Published in Monthly Notices of the Royal Astronomical Society, 2017
This work pioneers the use of deep learning pattern recognition in asteroseismology, where convolutional neural networks are used to identify core helium-burning or hydrogen-shell burning red giants with exceptional accuracy.
Recommended citation: Hon, M.; Stello, D.; Yu, J..“Deep learning classification in asteroseismology”, 2017, MNRAS, 469, 4578.
Published in Astronomy & Astrophysics, 2019
doi:10.1051/0004-6361/201935834
Recommended citation: Bonanno, A.; Corsaro, E.; Del Sordo, F.; et al. "Acoustic oscillations and dynamo action in the G8 sub-giant EK Eridani", 2019, A&A, 628, 7.
Published in The Astronomical Journal, 2019
Recommended citation: Huber, D.; Chaplin, W. J.; Chontos, A.; et al. "A Hot Saturn Orbiting an Oscillating Late Subgiant Discovered by TESS", 2019, AJ, 157, 14
Published in Monthly Notices of the Royal Astronomical Society, 2019
Recommended citation: Sharma, S.; Stello, D.; Bland-Hawthorn, J.; et al. "The K2-HERMES Survey: Age and Metallicity of the Thick Disc", 2019, MNRAS, accepted
Published in The Astrophysical Journal, 2019
Recommended citation: Campante, T. L.; Corsaro, E.; Lund, M. N.; et al. "TESS Asteroseismology of the known red-giant host stars HD 212771 and HD 203949", 2019, ApJ, accepted.
Published in Monthly Notices of the Royal Astronomical Society, 2019
Recommended citation: Elsworth, Y.; Hekker, S.; Johnson, J. A.; et al. "Insights from the APOKASC Determination of the Evolutionary State of Red-Giant Stars by consolidation of different methods", 2019, MNRAS, 489, 4641.
Published in Astronomy & Astrophysics, 2019
doi:10.1051/0004-6361/201834690
Recommended citation: Arentoft, T.; Grundahl, F.; White, T. R.; et al. "Asteroseismology of the Hyades red giant and planet host eps Tauri", 2019, A\&A, 622, 12
Published in Monthly Notices of the Royal Astronomical Society, 2018
Recommended citation: Silva Aguirre, V.; Bojsen-Hansen, M.; Slumstrup, D.; et al. "Confirming chemical clocks: asteroseismic age dissection of the Milky Way disc(s)", 2018, MNRAS, 475, 5487
Published in Monthly Notices of the Royal Astronomical Society, 2018
Recommended citation: Wu, Y.; Xiang, M.; Bi, S.; et al. "Mass and age of red giant branch stars observed with LAMOST and Kepler", 2018, MNRAS, 475, 3633
Published in The Astrophysical Journal Supplement Series, 2018
Recommended citation: Yu, J.; Huber, D.; Bedding, T. R.; et al. "Asteroseismology of 16,000 Kepler Red Giants: Global Oscillation Parameters, Masses, and Radii", 2018, ApJS, 236, 18
Published in The Astronomical Journal, 2017
Recommended citation: Wittenmyer, R. A.; Sharma, S.; Stello, D.; et al. "The K2-HERMES Survey. I. Planet-candidate Properties from K2 Campaigns 1-3 ", 2018, AJ, 155, 10
Published in Monthly Notices of the Royal Astronomical Society, 2017
Recommended citation: Sharma, S.; Stello, D.; Buder, S.; et al. "The TESS-HERMES survey data release 1: high-resolution spectroscopy of the TESS southern continuous viewing zone", 2018, MNRAS, 473, 2004