Automated classification of variable stars in the asteroseismology program of the kepler space mission

J. Blomme; J. Debosscher; J. De Ridder; C. Aerts; R. L. Gilliland; J. Christensen-Dalsgaard; H. Kjeldsen; T. M. Brown; W. J. Borucki; D. Koch; J. M. Jenkins; D. W. Kurtz; D. Stello; I. R. Stevens; M. D. Suran; A. Derekas

doi:10.1088/2041-8205/713/2/L204

Automated classification of variable stars in the asteroseismology program of the kepler space mission

J. Blomme, J. Debosscher, J. De Ridder, C. Aerts, R. L. Gilliland, J. Christensen-Dalsgaard, H. Kjeldsen, T. M. Brown, W. J. Borucki, D. Koch, J. M. Jenkins, D. W. Kurtz, D. Stello, I. R. Stevens, M. D. Suran, A. Derekas

Astronomy & Astrophysics

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30 Scopus citations

Abstract

We present the first results of the application of supervised classification methods to the Kepler Q1 long-cadence light curves of a subsample of 2288 stars measured in the asteroseismology program of the mission. The methods, originally developed in the framework of the CoRoT and Gaia space missions, are capable of identifying the most common types of stellar variability in a reliable way. Many new variables have been discovered, among which a large fraction are eclipsing/ellipsoidal binaries unknown prior to launch. A comparison is made between our classification from the Kepler data and the pre-launch class based on data from the ground, showing that the latter needs significant improvement. The noise properties of the Kepler data are compared to those of the exoplanet program of the CoRoT satellite. We find that Kepler improves on CoRoT by a factor of 2-2.3 in point-to-point scatter.

Original language	English (US)
Pages (from-to)	L204-L207
Journal	Astrophysical Journal Letters
Volume	713
Issue number	2 PART 2
DOIs	https://doi.org/10.1088/2041-8205/713/2/L204
State	Published - 2010

All Science Journal Classification (ASJC) codes

Astronomy and Astrophysics
Space and Planetary Science

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10.1088/2041-8205/713/2/L204

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Blomme, J., Debosscher, J., De Ridder, J., Aerts, C., Gilliland, R. L., Christensen-Dalsgaard, J., Kjeldsen, H., Brown, T. M., Borucki, W. J., Koch, D., Jenkins, J. M., Kurtz, D. W., Stello, D., Stevens, I. R., Suran, M. D., & Derekas, A. (2010). Automated classification of variable stars in the asteroseismology program of the kepler space mission. Astrophysical Journal Letters, 713(2 PART 2), L204-L207. https://doi.org/10.1088/2041-8205/713/2/L204

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title = "Automated classification of variable stars in the asteroseismology program of the kepler space mission",

abstract = "We present the first results of the application of supervised classification methods to the Kepler Q1 long-cadence light curves of a subsample of 2288 stars measured in the asteroseismology program of the mission. The methods, originally developed in the framework of the CoRoT and Gaia space missions, are capable of identifying the most common types of stellar variability in a reliable way. Many new variables have been discovered, among which a large fraction are eclipsing/ellipsoidal binaries unknown prior to launch. A comparison is made between our classification from the Kepler data and the pre-launch class based on data from the ground, showing that the latter needs significant improvement. The noise properties of the Kepler data are compared to those of the exoplanet program of the CoRoT satellite. We find that Kepler improves on CoRoT by a factor of 2-2.3 in point-to-point scatter.",

author = "J. Blomme and J. Debosscher and {De Ridder}, J. and C. Aerts and Gilliland, {R. L.} and J. Christensen-Dalsgaard and H. Kjeldsen and Brown, {T. M.} and Borucki, {W. J.} and D. Koch and Jenkins, {J. M.} and Kurtz, {D. W.} and D. Stello and Stevens, {I. R.} and Suran, {M. D.} and A. Derekas",

year = "2010",

doi = "10.1088/2041-8205/713/2/L204",

language = "English (US)",

volume = "713",

pages = "L204--L207",

journal = "Astrophysical Journal Letters",

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publisher = "American Astronomical Society",

number = "2 PART 2",

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Blomme, J, Debosscher, J, De Ridder, J, Aerts, C, Gilliland, RL, Christensen-Dalsgaard, J, Kjeldsen, H, Brown, TM, Borucki, WJ, Koch, D, Jenkins, JM, Kurtz, DW, Stello, D, Stevens, IR, Suran, MD & Derekas, A 2010, 'Automated classification of variable stars in the asteroseismology program of the kepler space mission', Astrophysical Journal Letters, vol. 713, no. 2 PART 2, pp. L204-L207. https://doi.org/10.1088/2041-8205/713/2/L204

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T1 - Automated classification of variable stars in the asteroseismology program of the kepler space mission

AU - Blomme, J.

AU - Debosscher, J.

AU - De Ridder, J.

AU - Aerts, C.

AU - Gilliland, R. L.

AU - Christensen-Dalsgaard, J.

AU - Kjeldsen, H.

AU - Brown, T. M.

AU - Borucki, W. J.

AU - Koch, D.

AU - Jenkins, J. M.

AU - Kurtz, D. W.

AU - Stello, D.

AU - Stevens, I. R.

AU - Suran, M. D.

AU - Derekas, A.

PY - 2010

Y1 - 2010

N2 - We present the first results of the application of supervised classification methods to the Kepler Q1 long-cadence light curves of a subsample of 2288 stars measured in the asteroseismology program of the mission. The methods, originally developed in the framework of the CoRoT and Gaia space missions, are capable of identifying the most common types of stellar variability in a reliable way. Many new variables have been discovered, among which a large fraction are eclipsing/ellipsoidal binaries unknown prior to launch. A comparison is made between our classification from the Kepler data and the pre-launch class based on data from the ground, showing that the latter needs significant improvement. The noise properties of the Kepler data are compared to those of the exoplanet program of the CoRoT satellite. We find that Kepler improves on CoRoT by a factor of 2-2.3 in point-to-point scatter.

AB - We present the first results of the application of supervised classification methods to the Kepler Q1 long-cadence light curves of a subsample of 2288 stars measured in the asteroseismology program of the mission. The methods, originally developed in the framework of the CoRoT and Gaia space missions, are capable of identifying the most common types of stellar variability in a reliable way. Many new variables have been discovered, among which a large fraction are eclipsing/ellipsoidal binaries unknown prior to launch. A comparison is made between our classification from the Kepler data and the pre-launch class based on data from the ground, showing that the latter needs significant improvement. The noise properties of the Kepler data are compared to those of the exoplanet program of the CoRoT satellite. We find that Kepler improves on CoRoT by a factor of 2-2.3 in point-to-point scatter.

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JO - Astrophysical Journal Letters

JF - Astrophysical Journal Letters

IS - 2 PART 2

ER -

Automated classification of variable stars in the asteroseismology program of the kepler space mission

Abstract

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