The Shape of M Dwarf Flares in Kepler Light Curves

Transcript

1. The Shape of M Dwarf Flares in Kepler Light Curves James R. A. Davenport @jradavenport NSF Postdoctoral Fellow Western Washington University
2. Kepler: Stellar Flare Machine • Complete samples of flares!
 (impossible from ground) • Huge range of flare energy!
 (look for Carrington-like events) • Long continuous light curves
 (up to ~4years) • Very precise photometry
 (~0.01%) • Enormous sample
 (>100,000 low-mass stars)
3. Walkowicz+ (2010) Flares Observed by Kepler 4 M-dwarfs
4. Hawley et al. (2014) Basic model of flare shape
 Fast Rise, Exponential Decay Relative Flux Time
5. Hawley et al. (2014) Relative Flux Basic model of flare shape
 Fast Rise, Exponential Decay Time
6. Time (days) GJ 1243, M4 Prot=0.59 days, ~300days 1-min data Davenport et al. (2014) Lots of flares! COLLECT THEM ALL!
7. Flares By EYE (FBEYE) Davenport et al. (2014) github.com/jradavenport/FBeye • Pick flare start/stop times • Assign classifications • Help train “autofinder”
8. Interesting to compare users Davenport et al. (2014) Time (days) Flux
9. Large Flare Sample! • 6107 unique flares, spanning 300 days of data
 most for any star, besides the Sun! • 15% flares are “complex”
 higher % for large energy flares! • wide energy range: Log E = 28-33 erg
 large solar flares around 1E32 erg Hawley et al. (2014) Davenport et al. (2014)
10. Hawley et al. (2014) No correlation between flares & starspot 1 month short cadence
11. 6107 flare events Saturation Flare Frequency Distribution Flares per Day See also Lurie et al. (2015) Energy (erg)
12. Flare Template: Study Morphology Davenport et al. (2014) 885 “clean” flares Time (FWHM)
13. Rise Phase 2 Decay Phases exponentials Fit with 4th order polynomial Energy budget: rise=20%, decay1=41%, decay2=39% Davenport et al. (2014) Time (FWHM) Time (FWHM)
14. Complex Flare Fitting Davenport et al. (2014) Time (days) works well for “classical” events
15. Complex Flare Fitting Use to objectively determine “complex” vs “classical” events & decompose events! Davenport et al. (2014) Time (days)
17. Relative Flux Some flares not well fit by template Caused by different physical morphology (e.g. arcade)? Active region rolling off limb? Davenport et al. (2014) Time (days)
18. Flare Energy Distribution
19. # of Flare Components 1 2 3 4 # of events
20. Energy2 Energy1 Time2 — Time1 39% 61% Flare Peak Order
21. Tell us about triggered flares? e.g. van Driel-Gesztelyi’s talk on Wednesday
22. Big questions still await us! • Dependence of flare morphology on stellar properties? • Structure of complex events? • “Triggered” flares? 
 “Sympathetic" flares? • Frequency of “Superflares”? • Flare rate vs age?
23. Age vs. Activity Lyra (2005) log Ca II Flux log age (yrs) ACTIVE! inactive Sun More Flares Fewer Flares
24. Magnetochronology: Train on Kepler. Apply to LSST.
25. Summary • Largest sample of flares ever for single star • Empirical flare template • Decompose complex vs classical events • No correlation with starspot phase • Training set for finding every flare in Kepler @jradavenport Time Time Flux Flux