A Bayesian method for detecting stellar flares

M. Pitkin*, D. Williams, L. Fletcher, S. D. T. Grant

*Corresponding author for this work

Research output: Contribution to journalArticle

8 Citations (Scopus)

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 '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.

Original languageEnglish
Pages (from-to)2268-2284
Number of pages17
JournalMonthly Notices of the Royal Astronomical Society
Volume445
Issue number3
Early online date17 Oct 2014
DOIs
Publication statusPublished - 11 Dec 2014

Keywords

  • methods: data analysis
  • methods: statistical
  • stars: flare
  • SYSTEMATIC-ERROR CORRECTION
  • WHITE-LIGHT FLARES
  • SOLAR-TYPE STARS
  • UV CETI STARS
  • PHOTOMETRIC VARIABILITY
  • OBSERVATIONAL DATA
  • KEPLER DATA
  • QUARTER 1
  • 1ST
  • STATISTICS

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