2. Time Series Photometry; Some Musings Steve B. Howell, NASA Ames Research Center

3. Photometric, Time-Series Surveys Photometric, Time-Series Surveys Surveys and variable objects are great ! Surveys and variable objects are great ! Discovery (vs. detailed study) & Large Samples (vs. single objects) Discovery (vs. detailed study) & Large Samples (vs. single objects) Detected transients and variables vary with Detected transients and variables vary with Filter / color Filter / color Galactic location Galactic location Etc. Etc. Detected sources also “vary”, and become more or less interesting, with our ability to understand them Detected sources also “vary”, and become more or less interesting, with our ability to understand them What about classification & follow-up? What about classification & follow-up?

4. Three items considered Time sampling Time sampling Allow additional science: e.g., Seismology, accretion physics, exoplanet transit models Allow additional science: e.g., Seismology, accretion physics, exoplanet transit models Time coverage Time coverage Long term changes Long term changes Transient discovery and behavior Transient discovery and behavior Photometric precision Photometric precision New types of variable sources discovered New types of variable sources discovered Better details and fitting of light curves Better details and fitting of light curves

5. Good Time Sampling: Data Sampling is Important Sample: 7.5 hrs

6. Good Time Sampling: Data Sampling is Important Sample: 0.5 hrs

7. Long Time Coverage Some objects appear to be boring, non-periodic and non-variable, but it is often a matter of time…..

8. Long Time Coverage: BOKS 45906 – IB w/56.6 min period

9. %Variability vs. Phot. Precision(σ) Periodic variables make up ~10% of all variables. Periodic variables make up ~10% of all variables. %Var (Kepler) ~72% %Var (Kepler) ~72% Still not at edge of variable universe %Var = -23.95 (log σ) - 39.52

10. Non-Periodic variables Non-periodic sources dominate variability Non-periodic sources dominate variability Some non-periodic sources are well known Some non-periodic sources are well known Flares, CV outbursts, granulation noise, SN Flares, CV outbursts, granulation noise, SN Most are not Most are not Two examples – fooled and hopeful Two examples – fooled and hopeful

11. Variable stars greatest hits V344 Lyr 1 minute Kepler observations Discovery of asymmetric rise/fall shape at start/end of cycle.

12. Variable stars greatest hits KIC 11390659 Quasi-periodic source. Examining ΔE, Δt at start of quasi-periods

13. (Non) Periodic Variables: Kepler data Variability across the H-R Diagram - Stars brighter than 13, one month of observation, 30 minute sampling Top: χ 2 >2 Middle: χ 2 >10 Bottom: χ 2 >100

14. Variability of giants and dwarfs Standard deviations of 30 minute sampled light curves. These data span 33 days of time.

15. Variability of giants and dwarfs Standard deviations of 30 minute sampled light curves. These data span 33 days of time. Histogram cuts of previous diagrams

16. Solar-like Exoplanet host stars H-R Diagram of a sample of Solar-like stars Note distribution of subgiants - lower gravity, RV jitter stars Larger convective cells, more variable

17. Solar-like Exoplanet host stars M-R relation for the sample of Solar-like stars Note distribution of subgiants - lower gravity, RV jitter stars. Jitter ~5-10 m/sec Spectroscopic variables

18. Solar-like Exoplanet host stars Variability of the sample of quiet Solar-like stars Red: sigma > 0.002 Blue: 0.001 to 0.002 Green: < 0.001 Note random distribution of variability; not all subgiants ~10 m/sec RV jitter = 0.001 mag

19. Conclusions Our expectations are sometimes wrong Our expectations are sometimes wrong Surveys all have biases, keep them in mind Surveys all have biases, keep them in mind Spectroscopy may not always provide an answer Spectroscopy may not always provide an answer Spectroscopic variable subgiants are (mostly) not photometric variables Spectroscopic variable subgiants are (mostly) not photometric variables Traditional analysis techniques tend to find traditional results Traditional analysis techniques tend to find traditional results Sonification of variability & other new research tools may reveal new insights Sonification of variability & other new research tools may reveal new insights Non-Periodic variables form ~90% of all variables Non-Periodic variables form ~90% of all variables Yet we know little about most of them Yet we know little about most of them

20. The End ?? Stayed Tuned for K2 !! Coming to a galaxy near you in 2014 K2 will be a repurposed Kepler mission K2 will point to 4-5 fields/year in the plane of the ecliptic K2 will stare at each ~100 sq. degree field for 75-85 days K2 will observe at least 10,000 to 20,000 targets in each pointing K2 will use 30 minute cadence with limited targets at 1 minute K2 will achieve better than 300 ppm (6 hr avg) at 12th mag K2 will be a community mission, selecting targets based on guest observer input. No exclusive use period.

22. Good Time Sampling: Data Sampling is Important Sample: 5 hrs

23. Good Time Sampling: Data Sampling is Important Sample: 0.5 hrs RR Lyrae star Observed during K2 science verification

24. Kep Mag brighter than 12 Top: chi^2 >2 Middle: chi^2 >10 Bottom: chi^2>100

25. Kep Mag brighter than 14 Top: chi^2 >2 Middle: chi^2 >10 Bottom: chi^2>100