Long time-series photometry on temperate sites
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Transcript Long time-series photometry on temperate sites
Long time-series photometry on
temperate sites
and what to gain from a move to Antarctica
ARENA workshop,
“Time-series observations from Dome C”
Catania
T.Granzer & K.Strassmeier,
Sep 17th, 2008
Outline:
Long-term stellar photometry:
Spot modelling
Cycle variations
Astroseismology
Transit searches,…
Robotic observations
Needs/gains
The perfect observation
Thermal/Antarctic
(Direct) Spot modelling:
Continuous, covering at least a
single rotation
*
Complementary to Doppler-Imaging
Strassmeier K. G., et al., 2002
Activity cycles:
Extremely long time scales, like
decades.
Constant data quality.
*
Olah, et al., 2008
Activity cycles cont‘d
Stellar activity
cycles like Sun.
Bright targets.
Data obtained with
75cm, photoelectric
robotic telescope
Transit searches:
Continuous observations (unknown
parameter space)
*
High precision on many targets.
Can be done in white light.
Winn, Holman &
Fuentes, 2006
*
Astroseismology:
Uninterrupted data sets to resolve
entire frequency spectrum.
*
Two colors.
Short exposure times.
29 frequencies found in BI CMi (Breger, et al., 2002)
Astroseismology (cont‘d):
‘Whole Earth Telescope’ to beat
day/night cycle.
Highest duty times with robotic
telescopes.
All APT observations with a
single, robotic telescope!
Fairborn Observatory
Washington Camp, Arizona,
1560m
14 robotic telescopes, 0.1-2m
First installation world-wide
Mainly Photometry
Twin-telescope STELLA
Tenerife / Teide
2400m Altitude
2x 1,2m telescopes
WiFSIP: 4kx4k imager
SES: high-R Echelle
STELLA
STELLA-I Instrumentation
Fiber-fed Echelle
spectrograph, fixed
format, fiber
entrance 50µm
(2.1"), R42000
STELLA-II Instrumentation
4kx4k CCD, 22’ FoV,
whole Strömgren, Sloan
& Johnson filter set +
H
Task: Feed light into fiber
STELLA-I Acquisition unit
Beam-splitter diverts 4% on guider
CCD (KAF-0402ME, uncooled).
Mirror around fiber entrance.
Optic wheel with flat mirror for
calibration light, glass pyramid for
focus.
Task: Feed light into fiber
Fiber entrance
At acquire, bring stellar image onto
fiber position
Hold it there during science exposure
Image from mirror around fiber
Image through beam splitter
Flat field exposure, guider image
Task: Pointing
Guider field-of-view ~2.5 arcmin
Pointing accuracy STELLA-I currently 15.8 arcsec
Classic pointing model
7-parameter model (alt/az mount), automatically
determined in STELLA at predefined intervals:
A Aoff AN sin A tan E AE cos A tan E N PAE tan E BNP sec E
E Eoff AN cos A AE sin A TF cos E
AN,AE…
NPAE…
BNP…
TF…
tilt of az-axis against N,E
non-perpendicularity of alt to az axis
non-perpendicularity of opt. axis to alt axis
tube flexure
Consequences
A stable mount is required for good pointing.
Temperature drifts in some parameters already on
rocky grounds.
Drifts of the ice will not be completely planeparallel and thus introduce drifts in the pointing
model with time.
Cannot use only the science observations, they
introduce bias.
Task: Acquire
Read-out stripes (shutter-less system)
Acquire on beam-splitter image
At acquire, 2-5 images are required.
Depending
Image from mirror
around fiberon star brightness, this
translates to ~10-40 sec.
Mirror image shows fiber
Beam-splitter causes the images to
be elongated in y-direction.
Image from beam-splitter
Acquire (cont.)
Acquire frames are bias and dark corrected.
A truncated gauss is used for star detection
(similar DAOfind).
Stars are discriminated from cosmics by
their elongation and sharpness.
Elongation criterion must be weak due to
beam-splitter.
Stars identified at prob. 0.443
Probability function defined by manual identification of stars on ~100
acquire frames
Task: Closed-loop guiding
Guiding is done on beam-splitter image
51 Peg, 20 min, ~1200 guider frames, average
Magnitude difference on added guider frames
allows estimate of light loss
Here: 32%
30 min @ LQ Hya, Gauss-filtered
Closed-loop guiding (cont.)
Each guider frame gives a single offset for
the two telescope axis
Up to ten single offsets are averaged
(target brightness depending).
This average offset is fed into a PID-loop
The PID output is applied to the telescope
at f=1/5 Hz.
Problems with high wind gusts.
Dependency of optimal PID parameters on seeing and
guider dead-time, from a telescope model
Currently, three PID parameter set per axis are used,
Task: Focus
A focus pyramid in the beam splits the
image into four parts.
At correct focus, the images have a
certain distance.
Pyramid is out-of focus, when star is in
focus (different optical path).
Measure diagonals or
Measure side length.
Not a perfect square, but distances
highly reproducible.
For STELLA-I, Δs=1px for
Δf=0.03933mm
5-20sec. for focusing.
Task: Scheduling
Scheduling currently simple, a few science
targets plus RV and flux standards.
Each run starts at solz > 0 with bias, followed by
flat-fields and ThAr.
During night, a ThAr plus an RV standard is taken
every 2h.
Approach:
Dispatch scheduling:
Picks target according to actual conditions.
Must run in real-time, but N
Allows easy reaction to weather changes.
Used on most robotic systems.
Robotic/Remote:
Robotic: (Almost) no human
interference.
Low bandwidth sufficient.
Unattended observations,
autonomous reaction to unforeseen
events (bad weather).
STELLA and many other projects show that it works!
What can we gain from polar
sites:
A simple example: Take a 75cm telescope from
Arizona to Dome-C.
The perfect observation:
No read-out noise, etc.
Ignore seeing (2nd order effect in photometry)
Remaining error sources: Scintillation, Photon noise,
Background noise.
Scintillation: ²~sec(Z)³N²T3/2 (Davids et al., 1996)
Photon noise: ²~N (Poisson statistics)
Background with Moon. Use a perfect comparison star.
Take one month around 21st Dec.
Take an object that passes the zenith.
Observe all night with hsun<-18°.
Model of a perfect time-series:
10 sec.exposures
Scintillation noise
limited
Periodogram:
Same for Dome C:
Use same scintillation law
(probably much better!)
Zenith-passing object now z<30°
Observe at hsol < -12°
51092 vs. 98692 measures:
Periodogram:
Detection probability:
The geographic uniqueness alone offers
profound advantages over low-latitude
sites for time-series observations.