### Abstract

Kepler has revolutionized our understanding of both exoplanets and their host stars.Asteroseismology is a valuable tool in the characterization of stars and Kepler is an excellent observing facility to perform asteroseismology. Here we select a sample of 35 Kepler solar-type stars which host transiting exoplanets (or planet candidates) with detected solar-like oscillations. Using available Kepler short cadence data up to Quarter 16 we create power spectra optimized for asteroseismology of solar-type stars. We identify modes of oscillation and estimate mode frequencies by 'peak bagging' using a Bayesian Markov Chain Monte Carlo framework. In addition, we expand the methodology of quality assurance using a Bayesian unsupervised machine learning approach. We report the measured frequencies of the modes of oscillation for all 35 stars and frequency ratios commonly used in detailed asteroseismic modelling. Due to the high correlations associated with frequency ratios we report the covariance matrix of all frequencies measured and frequency ratios calculated. These frequencies, frequency ratios, and covariance matrices can be used to obtain tight constraint on the fundamental parameters of these planet-hosting stars.

Original language | English (US) |
---|---|

Pages (from-to) | 2183-2195 |

Number of pages | 13 |

Journal | Monthly Notices of the Royal Astronomical Society |

Volume | 456 |

Issue number | 2 |

DOIs | |

State | Published - Feb 21 2016 |

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### Keywords

- Asteroseismology
- Planetary systems
- Planets and satellites: fundamental parameters
- Stars: evolution
- Stars: fundamental parameters
- Stars: oscillations

### ASJC Scopus subject areas

- Astronomy and Astrophysics
- Space and Planetary Science

### Cite this

*Monthly Notices of the Royal Astronomical Society*,

*456*(2), 2183-2195. https://doi.org/10.1093/mnras/stv2593

**Oscillation frequencies for 35 Kepler solar-type planet-hosting stars using Bayesian techniques and machine learning.** / Davies, G. R.; Silva Aguirre, V.; Bedding, T. R.; Handberg, R.; Lund, M. N.; Chaplin, W. J.; Huber, D.; White, T. R.; Benomar, Othman; Hekker, S.; Basu, S.; Campante, T. L.; Christensen-Dalsgaard, J.; Elsworth, Y.; Karoff, C.; Kjeldsen, H.; Lundkvist, M. S.; Metcalfe, T. S.; Stello, D.

Research output: Contribution to journal › Article

*Monthly Notices of the Royal Astronomical Society*, vol. 456, no. 2, pp. 2183-2195. https://doi.org/10.1093/mnras/stv2593

}

TY - JOUR

T1 - Oscillation frequencies for 35 Kepler solar-type planet-hosting stars using Bayesian techniques and machine learning

AU - Davies, G. R.

AU - Silva Aguirre, V.

AU - Bedding, T. R.

AU - Handberg, R.

AU - Lund, M. N.

AU - Chaplin, W. J.

AU - Huber, D.

AU - White, T. R.

AU - Benomar, Othman

AU - Hekker, S.

AU - Basu, S.

AU - Campante, T. L.

AU - Christensen-Dalsgaard, J.

AU - Elsworth, Y.

AU - Karoff, C.

AU - Kjeldsen, H.

AU - Lundkvist, M. S.

AU - Metcalfe, T. S.

AU - Stello, D.

PY - 2016/2/21

Y1 - 2016/2/21

N2 - Kepler has revolutionized our understanding of both exoplanets and their host stars.Asteroseismology is a valuable tool in the characterization of stars and Kepler is an excellent observing facility to perform asteroseismology. Here we select a sample of 35 Kepler solar-type stars which host transiting exoplanets (or planet candidates) with detected solar-like oscillations. Using available Kepler short cadence data up to Quarter 16 we create power spectra optimized for asteroseismology of solar-type stars. We identify modes of oscillation and estimate mode frequencies by 'peak bagging' using a Bayesian Markov Chain Monte Carlo framework. In addition, we expand the methodology of quality assurance using a Bayesian unsupervised machine learning approach. We report the measured frequencies of the modes of oscillation for all 35 stars and frequency ratios commonly used in detailed asteroseismic modelling. Due to the high correlations associated with frequency ratios we report the covariance matrix of all frequencies measured and frequency ratios calculated. These frequencies, frequency ratios, and covariance matrices can be used to obtain tight constraint on the fundamental parameters of these planet-hosting stars.

AB - Kepler has revolutionized our understanding of both exoplanets and their host stars.Asteroseismology is a valuable tool in the characterization of stars and Kepler is an excellent observing facility to perform asteroseismology. Here we select a sample of 35 Kepler solar-type stars which host transiting exoplanets (or planet candidates) with detected solar-like oscillations. Using available Kepler short cadence data up to Quarter 16 we create power spectra optimized for asteroseismology of solar-type stars. We identify modes of oscillation and estimate mode frequencies by 'peak bagging' using a Bayesian Markov Chain Monte Carlo framework. In addition, we expand the methodology of quality assurance using a Bayesian unsupervised machine learning approach. We report the measured frequencies of the modes of oscillation for all 35 stars and frequency ratios commonly used in detailed asteroseismic modelling. Due to the high correlations associated with frequency ratios we report the covariance matrix of all frequencies measured and frequency ratios calculated. These frequencies, frequency ratios, and covariance matrices can be used to obtain tight constraint on the fundamental parameters of these planet-hosting stars.

KW - Asteroseismology

KW - Planetary systems

KW - Planets and satellites: fundamental parameters

KW - Stars: evolution

KW - Stars: fundamental parameters

KW - Stars: oscillations

UR - http://www.scopus.com/inward/record.url?scp=84960839720&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84960839720&partnerID=8YFLogxK

U2 - 10.1093/mnras/stv2593

DO - 10.1093/mnras/stv2593

M3 - Article

VL - 456

SP - 2183

EP - 2195

JO - Monthly Notices of the Royal Astronomical Society

JF - Monthly Notices of the Royal Astronomical Society

SN - 0035-8711

IS - 2

ER -