1. Exoplanet- Asteroseismology Synergies Bill Chaplin, School of Physics & Astronomy University of Birmingham, UK EAHS2012, Oxford, 2012 March 15

2. Credit: IAC

3. Oscillations as clocks: FM stars Shibahashi & Kurtz (2012), MNRAS, submitted (arXiv:1202.0105)

4. Oscillations as clocks: V391 Peg Silvotti et al. (2007), Nature, 449, 189

5. Pulsations in the HR diagram Aerts, Christensen-Dalsgaard & Kurtz 2009

6. O-C diagram, prominent oscillation frequencies of V391 Peg Silvotti et al. (2007), Nature, 449, 189 Frequency #1Frequency #2

7. Understanding stellar systems like our own…

8. Jupiter: 1% area of the Sun (1/100 or 10,000 ppm) Earth or Venus: 0.01% area of the Sun (1/10,000 or 100 ppm) Photometry to detect transits

9. Evolution and properties of stellar systems  Precise, accurate fundamental stellar properties for modelling exoplanet systems: ­ Seismic densities, radii, masses, ages ­ Seismic log(g) for “boot strapping” spectroscopic analysis

10.  Internal rotation, stellar angle of inclination: ­ Constraints on dynamical histories of stellar systems Evolution and properties of stellar systems

11.  Intrinsic activity, variability of host stars, influence on local environment: ­ “Sound” stellar activity cycles ­ Depths of convective envelopes, tests of stellar dynamos Evolution and properties of stellar systems

12. asteroFLAG Hare and Hounds How Kepler would see Sun at v = 10

13. asteroFLAG Hare and Hounds Stello, Chaplin et al. 2009, ApJ

14. asteroFLAG Hare and Hounds

15. Asteroseismic ensemble tests Kepler Input Catalogue Finds an underestimation bias in KIC radii Verner et al., 2011, ApJ, 738, L28 KIC – seismic log g (dex) KIC – seismic radii (%)

16. Inferences on stellar activity, stellar cycles, activity of the “Sun in time”

17. Sun (SOHO/VIRGO) Kepler: G  type dwarf

18. Sun (SOHO/VIRGO)

19. Frequency spectrum of  Cyg Solar-like oscillations Granulation Activity Guzik et al. (2012), in preparation

20. Stellar activity suppresses oscillations Inference on magnetic fields and convection Detected oscillations?noyes Proxy for “stellar activity” Chaplin et al., 2011, ApJ, 732, 5L T eff (K)

21. Frequency spectra of 16 Cyg A & B Metcalfe et al. (2012), ApJ

22. Broomhall et al., 2009, ApJ, 700, L162 “Sounding” stellar activity cycles: Sun

23. Broomhall et al., 2012, ApJ, 420, 1405 Quasi-biennial variation After removal of 11-yr cycle signature

24. CoRoT reveals a short activity cycle in HD49933 García et al., 2010, Science, 329, 1032

25. One example from the seismic Zoo Oscillation amplitudes Oscillation frequencies Light curve Variation of seismic frequencies and amplitudes Courtesy Salabert (Elsworth et al., work in progress)

26.  Inference on distribution:  From frequency shifts of different modes  From frequency asymmetry of components of non-radial modes Inference: surface distribution of activity sizes and phases of frequency shifts depend on ( l, m) Chaplin (2011), Proceedings Tenerife Winter School

27.  Activity distribution: non homogeneous, preferred bands of latitude  Response of modes: depends on ( l, m) Inference: surface distribution of activity sizes and phases of frequency shifts depend on ( l, m) Chaplin (2011), Proceedings Tenerife Winter School

28. Effects of near-surface activity on modes Depends on spherical harmonic of mode ( l, m) (1,0)(1,1)(2,0) (3,0)(2,2) (2,1)

29. Chaplin et al. 2007, MNRAS, 377, 17 Spatial dependence of the frequency shifts Inference on active latitudes Predicted shifts simple model for latitudinal distribution surface activity Match to observed ratios

30. Chaplin et al. 2007, MNRAS, 377, 17 Spatial dependence of the frequency shifts Inference on active latitudes Predicted shifts simple model for latitudinal distribution surface activity Match to observed ratios

31. Chaplin et al. 2007, MNRAS, 377, 17 Spatial dependence of the frequency shifts Inference on active latitudes Predicted shifts simple model for latitudinal distribution surface activity Match to observed ratios

32. Chaplin et al. 2007, MNRAS, 377, 17 Spatial dependence of the frequency shifts Inference on active latitudes Predicted shifts simple model for latitudinal distribution surface activity Match to observed ratios

33. Inference: surface distribution of activity sizes and phases of frequency shifts depend on ( l, m ) Chaplin (2011), Proceedings Tenerife Winter School Sun-as-a-star data max =40 ± 10 degrees

34. Stellar activity squashes mode peaks! 3.0 0.15  = 0.0 1.5 0.4 See Chaplin et al., 2008, MNRAS, 384, 1668

35. Credit: IAC Asteroseismic analysis Kepler Objects of Interest (KOIs)

36. Seismology of exoplanet host stars HAT-P-7 Christensen-Dalsgaard et al. 2010 Kepler-10b Batalha et al. 2011

37. Howell et al. (2012), ApJ, 746, 123 Kepler 21b 1.6R E planet orbiting bright F-type sub-giant

38.  Brightest Kepler exoplanet host star  High-precision stellar properties from asteroseismology:  Stellar radius to 2.2%  Stellar mass to 4.5%  Stellar age to 12%  Planetary radius to 2.4% Kepler 21b 1.6R E planet orbiting bright F-type sub-giant

40. Kepler 22b 2.4R E planet in habitable zone of Sun-like star Borucki et al. (2012), ApJ, 745, 120 Strong signature of large frequency separation

41. Inclination affects mode visibility (1,0)(1,1)(2,0) (3,0)(2,2) (2,1)

42. Inclination affects mode visibility Gizon & Solanki, 2003, ApJ, 589, 1009 m=1m=1 0+1 m=2m=2 0 11 +2 l =1 l =2

43. Inference on stellar inclination Height ratios depend on angle 2 yrs

44. 1 month Need long datasets Inference on stellar inclination

45. Fin