Time Series Photometry; Some Musings Steve B. Howell, NASA Ames
Research Center
Slide 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?
Slide 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
Slide 5
Good Time Sampling: Data Sampling is Important Sample: 7.5
hrs
Slide 6
Good Time Sampling: Data Sampling is Important Sample: 0.5
hrs
Slide 7
Long Time Coverage Some objects appear to be boring,
non-periodic and non-variable, but it is often a matter of
time..
Slide 8
Long Time Coverage: BOKS 45906 IB w/56.6 min period
Slide 9
%Variability vs. Phot. Precision() 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 ) - 39.52
Slide 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
Slide 11
Variable stars greatest hits V344 Lyr 1 minute Kepler
observations Discovery of asymmetric rise/fall shape at start/end
of cycle.
Slide 12
Variable stars greatest hits KIC 11390659 Quasi-periodic
source. Examining E, t at start of quasi-periods
Slide 13
(Non) Periodic Variables: Kepler data Variability across the
H-R Diagram - Stars brighter than 13, one month of observation, 30
minute sampling Top: 2 >2 Middle: 2 >10 Bottom: 2
>100
Slide 14
Variability of giants and dwarfs Standard deviations of 30
minute sampled light curves. These data span 33 days of time.
Slide 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
Slide 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
Slide 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
Slide 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
Slide 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
Slide 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.
Slide 21
Slide 22
Good Time Sampling: Data Sampling is Important Sample: 5
hrs
Slide 23
Good Time Sampling: Data Sampling is Important Sample: 0.5 hrs
RR Lyrae star Observed during K2 science verification