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    Rights statement: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in onthly Notices of the Royal Astronomical Society following peer review. The definitive publisher-authenticated version M. Pitkin, D. Williams, L. Fletcher, S. D. T. Grant, A Bayesian method for detecting stellar flares, Monthly Notices of the Royal Astronomical Society, Volume 445, Issue 3, 11 December 2014, Pages 2268–2284 is available online at: https://doi.org/10.1093/mnras/stu1889

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A Bayesian method for detecting stellar flares

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A Bayesian method for detecting stellar flares. / Pitkin, M.; Williams, D.; Fletcher, L. et al.
In: Monthly Notices of the Royal Astronomical Society, Vol. 445, 01.12.2014, p. 2268-2284.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Pitkin, M, Williams, D, Fletcher, L & Grant, SDT 2014, 'A Bayesian method for detecting stellar flares', Monthly Notices of the Royal Astronomical Society, vol. 445, pp. 2268-2284. https://doi.org/10.1093/mnras/stu1889

APA

Pitkin, M., Williams, D., Fletcher, L., & Grant, S. D. T. (2014). A Bayesian method for detecting stellar flares. Monthly Notices of the Royal Astronomical Society, 445, 2268-2284. https://doi.org/10.1093/mnras/stu1889

Vancouver

Pitkin M, Williams D, Fletcher L, Grant SDT. A Bayesian method for detecting stellar flares. Monthly Notices of the Royal Astronomical Society. 2014 Dec 1;445:2268-2284. doi: 10.1093/mnras/stu1889

Author

Pitkin, M. ; Williams, D. ; Fletcher, L. et al. / A Bayesian method for detecting stellar flares. In: Monthly Notices of the Royal Astronomical Society. 2014 ; Vol. 445. pp. 2268-2284.

Bibtex

@article{3e5d3177b7ac4f5082da63c0865888d2,
title = "A Bayesian method for detecting stellar flares",
abstract = "We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of {\textquoteleft}quiet{\textquoteright} Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.",
keywords = "methods: data analysis, methods: statistical, stars: flare",
author = "M. Pitkin and D. Williams and L. Fletcher and Grant, {S. D. T.}",
note = "This is a pre-copy-editing, author-produced PDF of an article accepted for publication in onthly Notices of the Royal Astronomical Society following peer review. The definitive publisher-authenticated version M. Pitkin, D. Williams, L. Fletcher, S. D. T. Grant, A Bayesian method for detecting stellar flares, Monthly Notices of the Royal Astronomical Society, Volume 445, Issue 3, 11 December 2014, Pages 2268–2284 is available online at: https://doi.org/10.1093/mnras/stu1889",
year = "2014",
month = dec,
day = "1",
doi = "10.1093/mnras/stu1889",
language = "English",
volume = "445",
pages = "2268--2284",
journal = "Monthly Notices of the Royal Astronomical Society",
issn = "0035-8711",
publisher = "OXFORD UNIV PRESS",

}

RIS

TY - JOUR

T1 - A Bayesian method for detecting stellar flares

AU - Pitkin, M.

AU - Williams, D.

AU - Fletcher, L.

AU - Grant, S. D. T.

N1 - This is a pre-copy-editing, author-produced PDF of an article accepted for publication in onthly Notices of the Royal Astronomical Society following peer review. The definitive publisher-authenticated version M. Pitkin, D. Williams, L. Fletcher, S. D. T. Grant, A Bayesian method for detecting stellar flares, Monthly Notices of the Royal Astronomical Society, Volume 445, Issue 3, 11 December 2014, Pages 2268–2284 is available online at: https://doi.org/10.1093/mnras/stu1889

PY - 2014/12/1

Y1 - 2014/12/1

N2 - We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of ‘quiet’ Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.

AB - We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of ‘quiet’ Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.

KW - methods: data analysis

KW - methods: statistical

KW - stars: flare

U2 - 10.1093/mnras/stu1889

DO - 10.1093/mnras/stu1889

M3 - Journal article

VL - 445

SP - 2268

EP - 2284

JO - Monthly Notices of the Royal Astronomical Society

JF - Monthly Notices of the Royal Astronomical Society

SN - 0035-8711

ER -