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Draft: v1.5 (6 May. 17)
A STEP: White paper
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Antarctica Search for Transiting
Extrasolar Planets
White paper for internal use of the team for studies
report and prospects
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Antarctica Search for Transiting Extrasolar Planets
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A STEP: White paper
Executive summary
We present hereafter A STEP, an Antarctica Search for Transiting Extrasolar Planets. Our
goal is the detection of the extrasolar planets that transit in front of their parent star because
the measurement of their radius, and (by radial velocimetry) of their mass, informs us directly
on their composition and thus on the processes responsible for their formation.
We show that Dome C is potentially the best site on Earth for transit surveys because of the 3months continuous Antarctic night, excellent weather conditions, and relatively slow
variations of the environmental conditions. We show that present transit searches are limited
by day / night cycles and systematic errors in the photometry, errors which are not well
understood and appear to be different from one site to another. On the basis of this analysis,
we propose A STEP, a precursor mission to assess the potential capability of a future massive
transit search program from Dome C.
A STEP consists in a cold-qualified CCD camera, to be placed at the focus of a Newton 40cm
telescope at Dome C, for a continuous survey of ~10,000 stars of V magnitude 11 to 16.5
during the Antarctic winter. We aim at reducing systematic errors in the photometry to less
than 2 mmag, the level estimated for the best transit search program so far. Depending on the
properties of the site, and on the field of view that is necessary to achieve the highest
photometric accuracy, A STEP could detect up to several transiting extrasolar planets per
season.
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1. Scientific case
The field of extrasolar planets has grown extremely rapidly in the past 10 years, and we now
know of more than ~200 planets or planetary systems orbiting solar type stars in our
neighbourhood. The discovery of more planets, smaller planets and the ability to characterize
them directly impacts our ability to understand how planets form, how the Solar System
formed, and to better prepare future, more ambitious missions aiming at detecting habitable
planets and possibly biosignatures.
Among the planets that are known today, most are just detected through the wobble of their
parent star. To this date, eight of them have also been detected photometrically because they
transit in front of their star at each orbital revolution. This is extremely important because the
combined radial velocity and photometric transit measurements allow a measurement of both
the mass and radius of the planet, and therefore a first constrain on their composition. In fact
the transit method is the only one that is able to provide a constraint on the planetary radius in
the short and medium-range future.
It is on this basis that two space missions, COROT (launched in December 2006) and Kepler
(launch in 2008), have been selected by CNES and NASA, respectively. They should detect
tens, maybe hundreds of transiting extrasolar planets.
Given the fact that these space missions come on top of several tens of ground based transit
surveys (all of them unsuccessful so far, except two of them), why yet another ground based
survey? Our analysis is that the limitations of present surveys, but also of the soon to come
space surveys is due to unknown systematic effects of very different nature. We believe that
at Dome C, we can potentially design a transit search program that can compete with a spacebased program for a fraction of the cost. However, this depends on two things:
 our ability to really understand the limitations of the transit surveys and design an
ambitious proposal accordingly;
 the quality of the site for transit photometric surveys.
This is why we propose a project which has three goals:
 qualify the site specifically for planet transit surveys (i.e. obtain the level of red noise,
depending on various parameters-see next section);
 determine the main limitations of transit surveys at Dome C (e.g. seeing, differential
refraction, temperature fluctuations...etc.);
 if compatible with (1) and (2), detect several transiting giant planets per observation
season.
We are considering that the number of targets that will be probed in space is not high enough
to get enough discoveries to give statistical significance to distribution laws that will be
observed. Indeed, The CoRoT and KEPLER space missions are both limited by the amount of
data they could send back to the Earth, limiting their combined number of targets to 400000
stars, and thus a maximal combined possible yield of ~500 planets discovered, at different
periods, mass, radius, and around different kinds of stars. Even that maximal yield wouldn’t
be enough to statistically properly map the exoplanets distribution laws.
The document is as follows: Next section describes our current understanding of the limitation
of transit surveys. Then we present the advantages of Dome C, including results from ongoing
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winter period, for a Dome C based transit search. We eventually describe the A STEP
telescope configuration possibilities and our survey strategy.
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A STEP: White paper
A STEP: The team
Observatoire de la Côte d'Azur (Laboratoires Cassiopée et Gemini):
Tristan Guillot (PI)
Francois Fressin (IS)
Alain Blazit
Nicolas Crouzet
Vincent Morello
Djamel Mekarnia
Jean Gay
Yves Rabbia
Yves Bresson
Jean-Pierre Rivet
Alain Roussel
Yves Hugues
Dominique Albanese
Scientific preparation, operation supervision, modelling tools, analysis of the results
and scientific interpretation
Scientific preparation, telescope:mechanics, telescope:optics, camera, modeling
tools, analysis of the results and scientific interpretation
Responsible of the camera team; telescope:optics, softwares
Scientific preparation, telescope:optics, modelling tools, analysis of the results
Scientific preparation, modelling tools
Antarctization, Dome C logistics
Telescope:optics, modelling tools
Scientific preparation
Telescope: optics
Telescope environment, flat fielding system
Telescope: mechanics
Telescope: mechanics
Camera, softwares
Laboratoire Fizeau (Nice):
François-Xavier Schmider
Karim Agabi (PM)
Scientific and technical preparation (telescope), Dome C logistics, analysis of the
results and scientific interpretation
Technical preparation(Antarctization, telescope, softwares), Dome C logistics
Jean-Batiste Daban
Eric Fossat
Carole Gouvret
François Jeanneaux
Cécile Combier
Guillaume Cuissot
Lyu Abe
Yan Fantei
Responsible of the telescope team, technical preparation(teslescope, Control
systems)
Dome C logistics, analysis of the results and scientific interpretation
Optical studies, technical preparation(telescope)
Mechanical study of the camera environment
Softwares
Telescope: mechanics
Quality control, tests and installation
Softwares, data pipeline
Observatoire Astrophysique de Marseille Provence (LAM & OHP):
François Bouchy
Michel Boer
Alain Klotz
Claire Moutou
Magali Deleuil
Marc Ferrari
Antoine Llebaria
Hervé Le Corroler
Auguste Le van Suu
Jérome Eysseric
Claudine Carol
Scientific preparation, follow-up of transit candidates
Telescope control system, scientific interpretation
Telescope and camera control software, scientific interpretation
Scientific preparation, follow-up of transit candidates, photometric reduction
Scientific preparation, follow-up of transit candidates
Consulting on optical properties of the telescopes, tests and optical simulations
Image processing, stellar photometry
Scientific interpretation
Computer interfaces, telescope control system
System engineer
Computer engineer
Observatoire de Genève:
Frédéric Pont
Scientific preparation, analysis of the results, follow-up of transit candidates, scientific
interpretation
Deutsches zentrum für Luft und Raumfart (Berlin):
Anders Erikson
Data pipeline, camera, softwares, experience with BEST
Heike Rauer
Data pipeline, analysis of the results, scientific interpretation, experience with BEST
University of Exeter:
Suzanne Aigrain
Nick Tothill
Mark McCaughran
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Data pipeline, experience with SWASP and MONITOR, analysis of the results,
scientific interpretation
Antarctization, telescope: mechanics, experience with South Pole
Scientific preparation, scientific interpretation
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A STEP team: workpackages
Work Package 1: Mechanical studies
Responsible: JB Daban
- Design of the Newton 40 cm Telescope.
- Thermal enclosure for focal instrumentation
- Study of cold temperature qualification and differential stretching
- Interface with mount and concrete pillar
Work Package 2: Optical studies and camera
Responsible: A Blazit
- Study of the optimal PSF and pixel sample for transit photometry
- Optical study of the telescope image with environmental fluctuations (mechanical,
atmospheric)
- Tests of the Proline FLI16801E camera on CoRoTcam testbench
- Study of optimal photometry
- Guiding device
Work Package 3: Command and control softwares, hardware at Dome C
Responsible: K.Agabi
- Telescope command software
- Automated procedure for field following, flatfields, back rotation of the telescope each day
- Photometry quality check and daily report back to Europe.
- Dome C logistics and installation on site
Work Package 4: Data Pipeline, survey strategy, analysis and follow-up
Responsible: T.Guillot
- Re-use of BEST2 data pipeline, analysis of SWASP, Monitor, XO and OGLE pipelines
- Field selection and use of other observational information
- Follow up of transit candidates in radial velocimetry
2. The photometry of transits
Since the photometric detection of the transit of HD209458b in 1999, more than two dozen
photometric searches for surveys have been going on. On paper, the procedure seems trivial
enough: monitoring a few thousand stars for 20-30 nights would lead to the detection of
several transiting Hot Jupiters. When considering the score of projects devoted to the
detection of planets by transit photometry, the present harvest appears meager. The 11 planets
to date by ground-based transit projects (see table XXX), prove the detection of exoplanets
possible for a large array of observational strategies (from deep field several-meter telescopes
to wide field 10 cm reflectors), but the results of all these surveys is at least one order below
their respective initial expectation. The a-posteriori analysis of these surveys show four main
factors explaining the meager detection rates:
1. Due to technical problems or a limited number of good photometrical nights, most
operating surveys have not been able to meet the duty cycles required to detect
extrasolar planets.
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2. Dense stellar fields introduce severe crowding problems for transit photometry.Most
existing surveys have been designed without taking this problem into account, e.g. by
choosing a telescope/CCD combination that can not separate from each other a
substantial number of stars and therefore with low detection probabilities as a result.
3. The window function (i.e. observations only a few hours per day during the night),
which introduces a strong selection effect and prevents the detection of transiting
planets except at certain favorable periods (Gaudi et al. 2005, Pont & Bouchy 2005).
4. Systematic effects in the photometry, which impose a much higher threshold for the
detection of transit signals than initially estimated. The source of these systematics is
many-fold. They result from an interaction between the atmospheric parameters, like
airmass, extinction, temperature, seeing, sky background, and the instrumental
parameters, like the precision of the flatfield, individual pixel response, telescope
tracking, PSF shape.
Table XXX – Transiting planets known in 2006
2.1 Window function
Observations at Dome C are not affected by the day/night intermittence, and will be able to
operate more or less continuously. This makes an enormous difference for transit searches. It
not only quadruples the total time span of the observations (24h/day vs ~6hr day), it also
removes the period selection effects completely, and allows the detection of transiting planets
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regardless of their period (up to a certain cutoff period imposed by the total length of the
survey).
Importance of phase coverage
Detection
Probability
Transit Period (days)
Fig XXX - This diagram shows the detection probability of a transiting planet for a 60-day
coverage. The transit depth is one percent of the stellar magnitude. The black curve shows the
probability as a function of planet period for a telescope located in Chile. The red curve is the
probability for the same telescope with uninterrupted phase coverage at Dome C. As most
known hot Jupiter have periods around 3-4 days, continuous phase coverage is a crucial
point. The difference between the two curves is even larger for fainter transits, which
represent most of the cases
2.2 Systematic effects
In order to detect hot Jupiter transits with some efficiency, a photometric search much be able
to pick up transit signals of the order of 1 % with periodicity of a few days. The vast majority
of transit surveys have fallen far short of this target. On paper, their capacity to detect shallow
transit looked solid, but in actual fact, the shallowest detected eclipsing binary contaminators
are all deeper than 3% (for instance the UNSW survey, Webb 2005, the MACHO candidates,
Alcock et al 1997, the WASP candidates, Kane et al. 2004, the HATNet candidates, Hartman
et al. 2004). The reason for this mismatch is the presence of “systematics” in the photometry.
The OGLE survey, which did reach 1% transit depth and provided, additionally to the five
detected transiting hot Jupiters, more than one hundred shallow eclipsing binaries, has
permitted a much finer understanding of how systematics affect the detection threshold of
transit surveys (Pont et al. 2005, Pont 2006 OHP meeting). In short, trends at the
millimagnitude levels due to changing airmass, seeing, temperature, etc.., cause an increase of
the detection threshold by a factor up to 3-5 compared to theoretical estimates!
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Fig XXX – Level of noise for target stars in a SUPERWASP field as a function of magnitude.
Black points are the mean noise values during one exposure. Green points would be the noise
value integrated on 2 hours timescales if all the noise sources were Gaussian (white). The red
points are the real noise values integrated on 2 hours, showing a strong influence of red
noise. The lower panel shows the same noise levels after applying the SYS-REM (systematic
removal) procedure. The noise/magnitude curves for SUPERWASP are very similar to other
successful surveys.
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Fig XXX - Comparison of detection threshold with “white noise” (blue line), which does
not undergo temporal correlation and detection limit with “red noise” (linked to
systematic effects - green line) – The pink to red part of the diagram shows the density of
Hot Jupiter planets at given transit depth and target star magnitude.
These effects, combined with the unfavorable window function, severely lower the
detectability of hot Jupiter transits from the ground at normal latitudes. The detection rates are
down to values of about 1 per 10'000 targets even in the best surveys, and down to negligible
values for surveys with higher systematics. Given this new understanding, it can even be
questioned if ground-based transit surveys at low latitude (i.e. non-polar) with high
systematics are a reasonable use of resources.
Source of the systematics
The source of these systematics is many-fold. They result from an interaction between the
atmospheric parameters, like airmass, extinction, temperature, seeing, sky background, and
the instrumental parameters, like the precision of the flatfield, individual pixel response,
telescope tracking, PSF shape. They can be different for different surveys. The experience of
ground based transit searches, however, shows dominant tendencies:
 the systematics diminish with better sampling of target stars PSF. (ranging from about
10 mmag for one-pixel surveys to 1 mmag for 4-m class monitoring)
 the main component is related to airmass changes for the OGLE survey (Zucker
2005), and it has an important effect on photometry through differential colourextinction and refraction for other surveys (Irwin 2006)
 pixels answer and flatfielding may be main component for wide field surveys (XXXSuperwasp 2006)
The understanding of the principal factors influencing the level of systematics is still
incomplete at present. However, it is clear that they result from an interaction between
atmospheric and instrumental parameters. Moving to more stable atmospheric conditions -especially for the airmass factor -- is certainly going to reduce the levels of the systematic
trends. With its high latitude, Dome C allows the monitoring of southern fields during the
whole winter at almost constant airmass, a condition inaccessible to more equatorial locations.
3. Dome C characteristics and impact on transit
photometry
3.1 Duty cycle
The evident advantage of Dome C for photometry is the fact that you can cover a field during
several months. First of all because it is situated bellow the Antarctic polar circle, so the “full
night” is three months long.
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Fig XXX - Left panel: observed window for Dome C, taking into account the meteorological
conditions recorded in 2006 and the Sun altitude (at least 4± below horizon). The simulation
also considers 20 minutes overhead per day, at 12:00 local time, for calibration and back
rotation of the telescope. The right panel shows the variation with time of the duty cycle
averaged over 10-day periods (full line) and the integrated duty cycle (dashed line). (from
Mosser Aristidi 2006)
Even on June 21st, there is a time during the day in which the Sun comes closer to the
horizon. We can consider the night entirely dark when the sun is under -15° bellow the
horizon. There is a contamination of the sky brightness when it is over this limit. We are
considering the data affected by this increase of sky brightness differently and will try to
apply an accurate removal of this effect for the data retrived during the “twilight” hours, as we
can model it precisely. The height of the Sun below the horizon and its effect of sky
brightness probably creates systematic noise effects, but at much smaller scale than the
day/night intermittence for most of other ground based projects. We are also considering the
solution of using a polarizer and observe at 90° of the ecliptic plane. As we could expect the
sky brightness to be highly dominated by Rayleigh diffusion, and not by aerosols or particles
effects, the sky should be highly polarized. That solution should be tested on site at Dome C
before applying it.
The moon will mainly influence the choice of the target stellar fields. We will have to avoid
the proximity of a full moon to that field. It is still a contamination to add to the sky
brightness.
3.2 Cloud coverage during 2006 winter (Aristidi 2006)
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For the first time, estimations of the clear sky fraction were made this year. It was estimated
visually several times a day, using a scale from 0 (no visibility) to 1 (cloud-free sky).
Considering the period covered by the winterover (Jan 1st – Oct 31st), the clear sky fraction
was greater than 0.9 78% of the time. Other numbers are presented in Fig. 1. This excellent
clear sky fraction is of course of great importance for astronomical observations, in particular
for asteroseismology, where extremely long integration times (several weeks) are needed. A
simulation by B. Mosser (Observatoire de Paris) showed that Dome C asteroseismic
observations should provide performance better or similar to a 6-site network at mi-latitude (a
paper is was recently submitted to the Publ. of Ast. Soc. of Pacific).
Time % for clear sky > 0.9
> 0.85
> 0.5
# of consecutive clear days (fraction >0.9)
Average :
Max :
# of consecutive bad days (fraction <0.25)
Average :
Max :
78%
80%
91%
5.3
14.9
0.5
1.6
Figure XXX :Left: Statistics of the clear sky fraction during the period Jan 1st – Oct 31st .
Right: Time percentage for two given clear sky fractions as a funtion of the month.
Figure XXX :Clear sky fraction during the year 2006
3.3 Atmosperic fluctuations – seeing (Aristidi 2006)
The DIMM, or “Differential Image Motion Monitor” is a telescope equipped with a mask
with sub-apertures of diameter 6 cm distant 20 cm. This mask is placed at the top entrance of
the telescope. One of the holes is equipped with a small angle prism (deviation 30 arcsec), the
other one with a glass parallel plate.
We use a Schmidt-Cassegrain Celestron C11 telescope (diameter 280 mm) with a 2xBarlow
lens (equivalent focal length 5600 mm). It is placed on an equatorial mount (Astro-Physics
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900). The mounts is fixed to a massive wooden foot. The DIMM is operated from the top of a
5 m high platform to avoid the contribution of the ground layer turbulence.
A digital CCD camera is placed in a thermostated box (temperature around –20°C), the box
and the camera being located at the focus of the telescope.
All this equipment has been customized to work in Antarctic cold conditions.
Picture XXX : Left, the DIMM system. Note the 2 hole mask at the telescope top. The box at
telescope back contains the camera. Right : typical short-exposure frame of the star Canopus
at the focus. The two images move with turbulence, analysis of their differential motion
provides the seeing.
Seeing statistics for the winter 2006 (Feb 1st – Oct 31st )
The seeing conditions we found are similar to those of the previous winter. Statistics of the
last two winterovers are presented in the table hereafter. The behaviour of the seeing with the
time (see Fig. 2) is also similar to what was observed last year: very good values in summer
turn into poor seeing at spring and remain around 1.5 -- 2 arcsec until November.
Campaign
Number of data
Median seeing (“)
Mean seeing (“)
Std deviation (“)
Max (“)
Min (“)
WO 2005
WO 2006
55385
1.22
1.30
0.77
6.49
0.08
67305
1.34
1.51
1.02
9.61
0.09
Figure XXX : Left: seeing statistics for the last two winterovers. Right: monthly-averaged
seeing versus month for the two winterovers.
Day-by-day values are shown in figure 3. As it can bee seen, the DIMM ran almost every day
with short down time due to mechanical problems, bad weather (including wind speed > 8
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m/s) or loss of the star. The histogram of the seeing values is plotted in figure 3, and shows
the classical 2-bumps structure with a clear maximum near 2 arcsec that vanishes in summer
where the shape of the histogram becomes nearly a gaussian centered on 0.6 arcsec.
Figure XXX :Left: daily averages of the seeing during the winterover Right: seeing histogram.
3.4 Austral Auroras
Another asset we had to check was the exact influence of austral aurorae. There has been
several auroras observable from Dome C low on the horizon and not susceptible to affect
observations and only one visible in a larger part of the sky with potential annoying effects.
The cause of the low affectation of the site by these auroras is the fact that it is close to the
south magnetic pole. As auroras only appear on a ring centered on the magnetic pole, they are
mainly bellow the horizon from Dome C. They have been confirmed during 2005-2006 winter
campaigns to be a negligible nuisance at Dome C.
Picture XXX – The only significant Austral Aurora recorded in 2005.
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3.5 Temperature fluctuations at Dome C
Temperature fluctuations have similar amplitudes than in temperate sites, however, there is no
typical timescale for fluctuations as in temperate site linked to day/night cycles, where
periodic fluctuations of several hours can mimic planetary transits and therefore represent an
important source of noise. Fig XXX shows that there is a strong link between ground
temperature, wind speed and global sky cloud coverage.
Fig XXX – Clear fraction of sky, wind speed and temperature during the 2006 year. There is a
strong correlation of sky coverage with higher wind speeds and average temperatures. We
could anticipate dome enclosure from these two increasing indicators. (Aristidi 2006)
3.6 Dome C and environmental systematic effects
Systematic effects are linked to both environmental and instrumental issues. They can not be
removed properly as their timescale is close to transit length and smoothing lightcurves does
not remove them. We do not have the exact knowledge of what these effects are and which
ones are the most versatile, but we do know that they are strongly linked with environment of
the observations, i.e. temperature fluctuations, air mass variations and differential extinction
on target stars, seeing fluctuations. These effects are not properly removed through data
treatment and they are not reduced by adding successive measure points in the same night.
If we have not completely hierarchised these effects, we know they are closely linked to the
day / night cycle for other ground based programs. The extremely good atmospheric
conditions at Dome C and the full winter period should considerably reduce these
environmental systematic effects.
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4 A STEP photometry specifications
4.1 Image sampling
We believe that an optimal spatial sampling is crucial to a successful transit survey. Part of
the objective of the initial phases of the ASTEP project is to determine which is the optimal
sampling to get the best gain from the conditions at Dome C in terms of systematic trends in
the photometry. For small telescopes and reflectors choosing a wide field in order to have a
sufficient number of targets, inter-pixel differences and tracking drifts are likely to dominate
over atmospheric constraints. For large telescopes (diameter ~1 m) with deep fields, we know
from the OGLE survey that the sampling is sufficient (~10 pixel per seeing disc) so that the
limiting factor is atmospheric stability. It is not clear yet where the limit between these two
regimes is situated. The optimal instrument/observation strategy at Dome C will partly depend
on this limit, which we plan to determine as part of the A STEP project.
The following points are to be considered:
 First of all, a great number of target stars is mandatory, as even a 3 day period planet
only has a 10 % chance of transiting. On the basis of radial velocity surveys, one can
estimate the number of transiting planets in the Jupiter-Saturn mass range to be about
one in 1500 solar-type stars in the field.
 Ideally, one should choose a field as large as possible in order to detect planets around
bright stars. These are easier targets for the follow-up studies. Conversely, programs
running on very deep fields (mv>18) yield transit events that cannot be confirmed by
radial velocimetry and should be avoided.
 However, the wide field approach is limited due to the generally poor photometry.
Among the more than 20 running surveys, OGLE is by far the most successful and
uses one of the smallest field of view (i.e 35’, for an average 6° for other surveys).
This shows that spatial sampling is important for the detection of extrasolar planets.
 We chose a compromise between field size and spatial sampling under the following
conditions:
o We are using a single camera instead of a difficult-to-operate matrix of CCDs,
with driving software already developed. We are thus limited to the 16 million
pixel sampling, the highest available number of pixels for commercial
cameras.
o We privilege optimal photometry to a really high number of targets. A number
of ~4000 cool main-sequence stars per field still is a requirement in order to
have enough targets to be in the conditions of differential photometry and
provide us a sufficient average amount of hot Jupiter in the fields to guarantee
a few detections. Sky background brightness, star photon noise and easiness of
the RV following limit the maximum magnitude of target stars at ~16. The
requirement for the field size thus is ~0.5 to 1°.
4.2 Optical simulations
4.2.1 Principle of the simulations
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In order to get an optimized photometry on a sufficient number of targets, with an easy-toantarctize telescope, we fixed a range of specifications for the optical combination. A Newton
telescope with a specific field corrector has been chosen for its simplicity and the weaker
dependence of its properties from differential stretching.
Here is the hierarchy of properties that have to be respected for the optical combination:
 We will use a simple Newton optical combination with an optimized 2 or 3 lenses
field correction.
 The star PSF will be broadened with defocusing the telescope.
 The field available should be unvignetted on at least 95 % of the camera
 The diagonal of the camera should be the projection of a 0.5 to 1.5° line on sky, range
in order to have a sufficient number of targets and keep a good angular resolution per
pixel.
 The shape of the image and its stability are the main parameters to optimize as a
function of:
o seeing fluctuations
o mechanical stretching of the optical components
 Secondarily, the homogeneity of the image across the field of view would make the
difference between two equivalent configurations.
 The central obstruction size does not have a fixed limit, but increasing the projected
diameter of the secondary mirror over 20 cm should be considered seriously for the
loss of global flux.
 A “coudé” configuration of the correction and focal plane instrumentation could be
chosen if it does not negatively alter the optical combination properties (i.e. through a
modification of the secondary mirror size), and effectively increases the compactness
of the telescope.
In order to qualify the quality of each star image before testing photometry with the optimal
ones (see section 3.3), a test could be done by integrating the difference in flux between the
star image and a “top hat” function of equal energy. Several values for “top hat” size will be
used for this test corresponding to the range of optimal star FWHM sizes estimated with the
single star photometry simulator. (from 1.5 to 3 pixels)
This “top hat” function is used because it corresponds to what is thought to be the optimal star
image in a relatively poorly pixel-sampled photometry. Indeed, most ground-based surveys,
often deeply under-sampled, use different techniques in order to broaden their star image (e.g.
raster-scan technique UNSW 2005, telescope circular moves during the exposure HATNET
2005). In the case of A STEP, with a smaller field of view, this PSF broadening will be
reachable just through defocusing.
We are using this function as the optimal shape template because:
 It increases the number of pixels considered for photometry, and thus lowers the
noises linked to pixel fluctuations and flat-fielding
 It lowers the saturation level of bright stars, allowing longer exposures.
 It has sharp edges, at a radius significantly smaller than the aperture of the
photometry.
 It has all the flux inside the aperture.
4.2.2 Results of the optical simulation
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Fig XXX – Optimized optical combination using a 3-lense field corrector for the Newton 40
cm telescope for the simple and coudé configurations. Spectral range goes from 550 to 900
nm (R+I bands) in this simulation.
Fig XXX – Defocused star image shape for the optimal configuration.
4.3 Single star photometry simulations
The aim of the study we did was to determine the individual effect of different noise sources
on a single star, in order to qualify:
 The best camera for transit photometry among the sample of high precision
commercial cameras.
 The requirements for the optimal point spread function.
4.3.1 Principle of the simulations
A grid of 100x100 pixels, representing a small part of the real CCD, is used to simulate the
influence of noise sources on photometry for a single source.
The optimal test should include realistic simulations of the different factors affecting
photometry:
 The size of the CCD electrodes, reflecting a part of incoming flux on the camera
(assumed to be a fraction of 30 % of surface in the case of front illuminated cameras)
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The color-dependant quantum efficiency of the camera
The pixel non-linearity (Gaussian distribution of 1 % mean value – peak 3 %)
The pixel non-uniformity (Gaussian distribution of 1 % mean value – peak 2 %)
The flat-fielding process and its effect reducing the pixel residual non-uniformity (see
section XXX)
The effective projected position of the star on the CCD and temporal motions (linked
to breathing and guiding errors) on the CCD. The temporal spectrum of motions of
stars is difficult to determine accurately without real tests. For our simulations, we
assume these moves to be a random walk of amplitude with a Gaussian law of 0.2
arcsec FWHM each 1 second.
We assume in those simulations two possible regimes for guiding:
o The use of a guiding camera, leading to re-adjust the image each 1 second at a
random position in the disk of 1/10 pixel size centered around the precedent
star position. This fraction is the usual precision obtained with SBIG guiding
devices.
o The use of the main camera to update the same way the image position but
each 20 seconds after readout of the precedent frame.
The stellar image is considered
o As the combination of 2 image outputs of the Zeemax telescope simulation
(considering optical correction, central obstruction, defocusing and diffraction
– see section3.2.1) for the spectral range cut into two parts of equal spectral
size. The two images will be called “blue” and “red” in the following text, they
are used to simulate colored effects at a first order.
o These two images are convolved with a Gaussian of FWHM equal to the
seeing value. The seeing is considered stable during one second time-frames.
The seeing values are an interpolation in a random sequence of measures
observed during the 2005 and 2006 winter campaigns.
The star image is integrated on the pixel grid, from which we calculate a number of
photo-electrons for each pixel on each 1 second frame.
A sky background level is added in each pixel, with time dependant fluctuations. We
assume a sky brightness equal to XXX
It is difficult to properly simulate the effect of subtraction of global or local frames,
frame to frame adjustment, and the different techniques of differential photometry.
However, we can simulate easily:
o Aperture photometry, that is conducted on each frame with different apertures
equal to 1,2,3 and 4 times the FWHM of the star image.
o The maximum signal to noise ratio (SNR) that could possibly be extracted for
each target star. In order to do so, we are adding each pixel signal and noise in
the neighborhood of the photocenter pixel of the star provided it increases the
global signal to noise ratio. Solutions considering a gradient in “statistical
weight” of each pixel as a function of its distance to the photocenter will be
tested to provide the configuration that offers the maximal signal to noise ratio.
4.3.2 Results of the simulations
XXX
4.4 Corotlux simulations for global survey strategy.
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We have used the CoRoTlux simulator, a code initially developed to predict the yield of
CoRoT space telescope (Baglin et al 2002) and quantify the need for follow-up observations.
We here apply this code to simulate the yield of A STEP survey. The CoRoTlux code is
described in details in Fressin et al. 2007. We summarize the assumptions made by the model
in order to simulate results of the A STEP survey:
 The stellar population, with multiple stars and background stars is generated from
Besançon model of the galaxy;
 We only consider massive planets (the mass of Saturn and more), as they are much
more well characterized by observations than the first few hot Neptunes discovered
recently;
 The giant planet distribution is set as a function of the metallicity of target stars
(Santos 2004);
 The planet mass-period distribution is a carbon-copy of the sample known from radial
velocimetry;
 The radius of the planets is calculated with the Guillot & Showman (2002) model of
planetary evolution. It depends on considering the mass, amount of flux the planet
receives from its host star, and the amount of heavy elements in the planet. With the
assumption that the amount of heavy elements is a function of the metallicity of the
host star, that model reproduces well the radii of known transiting exoplanets;
 The detection threshold considers the effect of time-correlated noise, or ‘red noise’, as
described by Pont et al. (2006). We tested our model with two different red noise
mean values of 2.2 and 1.5 mmag, a reasonable expectation in comparison with the
values observed a posteriori on most ground based projects (from 2 to 4 mmag
depending on telescope, environment and data treatment (from the analysis of
Superwasp, Monitor, Hatnet and OGLE systematics on photometry from Pont and the
ISSI team 2006)).
Table XXX shows a quantitative simulation established on 100 monte carlo draws for the A
STEP survey. The fiducial survey consists in a single field observation during the 2008
Antarctic winter and 3 alternate fields respectively during the 2009 and 2010 campaigns. We
assume the duty cycle to be 100 % of the three full winter months. These results show that a
permanent coverage on a field gives a higher average number of detections than an 8-out-of24-hours survey with the same total length of observation. Alternating different fields of view
with successive exposures during 15 minutes on each target field seems to be the best strategy
for giant planet catch optimization. Figure 1 shows the mass-period distribution of exoplanets
simulated for a 3-year A STEP campaign. As well as giving more statistical significance for
populations discovered by current transiting projects (no very close-in small radius planet), it
could provide detections at longer periods and lower size.
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Table XXX - Expected giant planets yield from CoRoTlux simulations
We chose here to present only reasonable expectations on close-in giant planets yield.
Estimating properly the possible yield of Neptune-size planets would require a better
knowlegde of the distribution and characteristics of these planets as well as a precise idea of
the photometric accuracy reachable at Dome C. Recent observations with microlensing and
with radial velocimetry as well as results from theoretical modelling of planet formation
indicate that Neptune-size planets may be more common than giant planets. Depending on
their frequency of occurence, A STEP may be able to detect several.
Figure XXX - Mass versus period of expected transiting giant planets for A STEP. Model
results are shown as black crosses for detectable events, and yellow crosses for those that are
considered undetectable based on the photometric signal (see text). The known transiting
exoplanets are shown as circles (red for deep field survey detections, orange for wide field
survey detections and blue for planets found by radial velocimetry and confirmed in transit).
The model results correspond to a 3-year campaign with 7 target fields observed.
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This analysis is done using red noise value as a “big box” containing all time-correlated noise
sources and systematics. As our knowledge of the different individual noises will increase, we
will add them individually to CoRoTlux simulations.
The further step of our global survey analysis will be the coupling of CoRoTlux planetarytransit-like events file with the single-star-photometry simulator. We will thus be able to add
proper noise sources for each monte-carlo simulated event (planet-star couple and
neigborhood).
The ultimate step will be the end-to-end simulator, with the proper addition to CoRoTlux of
individual noise sources (linked to environmental changes, motions of the field on the camera,
coloured effects …). We will then generate successive stellar field images on CoRoTlux, and
apply to them our data pipeline to extract light-curves and search for transit-like events.
That study will provide us accurate estimations for the yield of giant planets, for the number
of transit-shape like events from blend that will have to be discriminated through treatment
and follow-up. It will also be useful to optimize the survey strategy (linked to fields of view,
crowding, specific stars targeting) and qualify what would be the optimal 2nd generation
transit search mission.
5. A STEP telescope technical design
The science study has shown the need to design a precursor capable of achieving the highest
photometric precision, but at a moderate cost. We have identified a 40 cm Newton telescope
to be the best compromise for its simplicity, its suitability for intermediary wide fields (~1°),
and its lower dependence to differential stretching for stabilizing the image (in comparison
with Ritchey Chretien combination). The experience of our partner O&V on realization of
these telescopes for temperate sites is a plus too.
5.1 - 40 cm Newton telescope
XXX – Waiting input from Franck
The tube of the telescope is built in carbon fiber for weight, robustness at cold temperature
and extremely low dilatation coefficient between 0 and -100°. The mount of the telescope will
be a German equatorial ASTROPHYSCIS 1500. This is one of the most reliable mount
industrially produced and several tests have already been done by the LUAN team on this
mount at dome C.
5.2 Telescope mount and support
The Astro-Physics 900 and 1200 German-equatorial mounts have already been tested in
Antarctica at Dome C. Our team (Fizeau, O&V) has developed an antarctization procedure in
order to have them properly working at temperatures as low as -80°C. Still, there has been a
few breakdowns with those mounts, especially when heavily loaded, which is the case for the
INVAR tube on the CORONA experiment. The main failure causes were linked to motor
heating and encoders. No real test has been done about the precise vibration frequencies of
this mount on ice in Antarctica.
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The Astro-Physics company is developing a new prototype, that should be available in spring
2007. The main differences with the Astro-Ph 1200 mount are:
 Its fiducial payload is 100 kg instead of 60 kg for the Astro1200
 Its ceramic gears do not use grease and should not be affected by low temperature
 Its stability will be better than the Astro1200. From tests done with the Astro1200 by
F.Valbousquet in a temperate area in poor environmental conditions, the average
moves of the field of view on a camera have an average of 0.48 arcsec from one 4 s
exposure to the following one in both directions. Fig XXX shows the histogram of the
amplitude of the moves interpolated on 1 second scale. In our simulations for the
prototype mount fixed at Dome C, we assume these moves to be a Gaussian random
walk of 0.15 arcsec FWHM each second.
Fig XXX – Histogram of the amplitude of telescope moves interpolated on 1 second
timescales from F.Valbousquet’s tests on Astro-Physics 1200 Mount.
There has not been up today any vibration studies of telescopes on ice at Dome C, but we
know from the DIMM experiments that the amplitude of the vibrations on the platform are not
negligible. In order to minimize the possible vibration spectrum due to building on ice, the
summer 2006-2007 Dome C team (Agabi, Schmider, Valbousquet, IPEV) has installed a 4
meter concrete pillar (2 meter deep in the ice) on the compressed ice extension of the
Concordiastro dome.
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Picture XXX – Installation of the concrete pilar by the Dome C summer 2006-2007 team
5.3 Thermal enclosure for the optical plane instrumentation
In order both to keep all electronic devices in the specified temperature range and to stabilize
the temperature of the camera box and correction lenses, we will build a thermal enclosure
including all focal instrumentation:
 The scientific camera with its inside cooling device
 The 2-3 lenses used for optical correction
 The filter / dichroic + guiding camera
 The interface between USB2 output of the camera and fiber link to the command and
control computer
 A possible chemical desiccant deposit in order to ensure that no frost will appear on
the optical surfaces
 Temperature controls
 A glass shot of the aperture
The enclosure has to be both thermally isolated from the telescope tube and correctly
mechanically fixed on it, especially fixing the angle and distance from the first correction lens
to the secondary mirror.
5.4
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Choice of the camera
Our preliminary analysis opposed two kind of commercial cameras:
 2K x 2K pixels back illuminated cameras
 4K x 4K pixels front illuminated ones
The results of this analysis showed that a better photometric precision was achievable with a
better pixel sampling provided the simulated Gaussian-shape PSF was large enough (~2 pixel
FWHM) not to be limited by the differential fraction of flux reflected by the readout
electrodes as a function of the shape and moves of the PSF.
In the field of commercial high-number-of-pixels cameras, the Fingerlake PL 16801 E camera
shows better characteristics than other cameras for all considerations.
 Size 4096 x 4096 px, 36.88 x 36.88 mm.
 Pixel size 9 x 9 µm.
 1 output.
 Peak of quantum efficiency 67 %.
 Saturation limit 100 000 e- / px.
 Readout noise 2 Mpx/s 15 e- rms (with a 10 s readout).
 Dark current 0,014 e- / px.s at -40°C.
 Photoresponse non-uniformity 1 % rms.
CCD class and defaults
We have ordered a class C2 camera in order to test it on the CoRoTcam testbench before
ordering a class C1 camera for scientific use at Dome C. Class C2 one will be used for
redundancy and support. The only difference between these cameras is the number of
cosmetic defects of their pixels. Fig XXX shows the number of defects as a function of the
Quality of the CCD, with the following definition for defects:
 Point Defect Dark:
A pixel which deviates by more than 6% from neighboring pixels when illuminated to 70% of
saturation, OR Bright: A Pixel with dark current > 7,000 e/pixel/sec at 25C.
 Cluster Defect:
A grouping of not more than 5 adjacent point defects Column Defect A grouping of >5
contiguous point defects along a single column, OR A column containing a pixel with dark
current > 20,000e/pixel/sec, OR A column that does not meet the CTE specification for all
exposures less than the specified Max sat. signal level and greater than 2 Ke, OR A pixel
which loses more than 250 e under 2Ke illumination.
 Defect Separation:
Column and cluster defects are separated by no less than two2 pixels in any direction
(excluding single pixel defects).
 Defect Region Exclusion:
Defect region excludes the outer two (2) rows and columns at each side/end of the sensor.
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Fig XXX – Number of defects with tests performed at T=25°C.
Insertion of the camera in the thermal enclosure
As the thermal enclosure including all instrumentation will be cantilevered with the telescope
tube, its size and weight matter in order to equilibrate the telescope. Weighting 2.6 kg, its
dimensions are 158 x 158 x 102 mm as described in figure XXX
FIG XXX – Dimensions of FLI PL16801 E camera
The camera’s most critical piece according to mechanical issues is its shutter. It will have to
undergo ~1.000.000 shuts in a completed winter season. FingerLake is to provide us a new
shutter prototype specified for this number of shuts in spring 2007.
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Fig XXX - The PL 16801 E camera with CCD and full packaging. Its use in a thermalized
enclosure does not require specific conditioning, but these cameras have been successfully
tested down to -40°C, which could prove useful in case of breakdown or disfunction of
enclosure warming.
5.5 Spectral Range
The importance of atmospheric colored effects (differential refraction and extinction), the
chromatic effects linked to optical pieces in the different parts of the field of view and the
differential shape of defocused PSF as a function of stellar type are the three main factors that
point towards the use of a filter.
The sky brightness is thought to be an important source of red noise and limits the magnitude
of stars to be valuable targets. In their generic study of transit search, Pepper et al 2005 show
that the I filter is optimal for transit surveys as cool main sequence stars (G,K) are the main
targets. They are using a simple sky brightness site-generic estimation and do not have a
proper analysis of red noise, but I-band is considered optimal by several successful surveys
(OGLE, SWASP). Fig XXX shows classical sky irradiance for a night at a temperate site. No
real measurement has been published for sky brightness at Dome C.
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Fig XXX - Relative irradiance spectrum of the night sky in a temperate area. The integrated
flux in R band is 1.85 times higher than the flux in I band.
The assumption that I band is theoretically the best compromise is to be balanced with the fact
that commercial cameras all have lower quantum efficiencies in I band. The FLI16801E is
optimized in R-band (fig XXX). According to the Kodak specifications, there is a loss of 45
% of photons for a homogeneous source from R to I band.
Fig XXX – Quantum efficiency of Kodak-16801E CCD.
We have considered for our optical simulations a wide range from 550 to 900 nm,
corresponding to R+I filter. Defocusing the image has a differential chromatic effect. The
shape of stellar image will thus be different as a function of stellar types of targets, especially
the brighter ones (see fig XXX). Even if the integrated flux of cooler stars in R and I band is
similar, defocusing will increase the importance of chromatic atmospheric effects.
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Fig XXX – simulated monocolor defocused PSF images at the center of the field at 550 nm
and 900 nm.
Fig XXX – Normalized flux for stars with temperature of 3000, 4000, 5000, 6000, 7000, and
8000 K of equal R+I visual magnitude.
The Kodak 16801-E CCD should not be affected by fringing in I band, but it is not specified
for wavelength higher than 850 nm. We will test it up to 900 nm, but the fact to use it in a
higher spectral range than specified could result in increasing its pixel fluctuation.
A good compromise if optical simulations prove the necessity to decrease the spectral range,
could be the use of an intermediary filter, ranging from 600 to 800 nm, for which:
 Sky brightness is reduced (of 20 % in comparison with R-band)
 Main target stars (4000 to 6500 K) have a flat intensity profile as a function of
wavelength, thus less dependant to chromatic effects.
 CCD quantum efficiency is higher than 50 %
6 Survey strategy and data pipeline
6.1 Field of view
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As the airmass fluctuations may be one of the most important source of “red noise”, the fact
to choose a target field in the direction of the south pole would considerably reduce the
influence of that parameter.
Stellar density is mainly linked to the angular separation between galactic plane and target
field. In order to select the best compromise for sampling, an angular separation around 5
degrees seems to be a good solution, as the field offers an important number of target stars for
without making photometry dominated by crowding.
A field similar to Eddington1, located between the galactic plane and the South Pole, in the
Carina, is our nominal choice of field.
Our simulations may make us choose a field closer to South Pole for better sampling and
lower airmass fluctuations.
Fig XXX - Main target stellar field used for simulations 1° x 1° in Carina – Our target fields
will be located between the galactic plane and the south pole for low airmass fluctuations.
The chosen field offers a compromise between number of target stars and crowding inside the
CCD.
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The first results of our simulations showed how crucial sampling is. Conducting a survey with
several successive target fields is in a lot of cases a good alternative to a larger aperture.
A STEP optimal survey could consist on observing successive target fields, then going back
to the first one. As we need a sufficient number of measure points inside each transit and the
telescope is not designed for fast moves, the optimal number of target fields would probably
be around 3-4. In order to limit the possible failures during the failure causes during the first
year of operation, we will only observe one field continuously.
5.2 Calibration
Camera tests
Using the CoRoTcam testbench, we will test different parameters of the camera with different
colour sources and the integrating sphere. The different tests we want to operate are:
 Pixels different full well capacity
 Pixels non uniformity and non linearity
 Bad pixels, clusters, columns and check of the official specification list for class C2 –
class CCDs
 Readout noise test as a function of readout time
 Temperature control of the CCD and check of different behaviours
 Check of quantum efficiency and uniformity at different wavelengths from 550 to 900
nm.
The results of these tests will confirm the nominal use of the camera and provide the
knowledge of optimal on site calibration.
Flatfields (S.Aigrain)
The knowledge of the CCD pixels and their answer is determinant for good photometric
precision too. But getting valuable flats for wide fields experiments is tricky. Twilight flats
may be obtained by pointing north just above the horizon at noon each day, but it is not clear
exactly how bright the sky will be. Dark sky flats may be an alternative, provided 1) there
aren't too many stars to stack out, and 2) the flats are not dominated by fringing rather than
illumination response. It would also be possible to get dome flats every ~48h by setting up a
screen and a lamp, but it is extremely hard to get decent flat fields for wide-field purposes
using dome flats because it's practically impossible to get even illumination across the field.
According to J. Irwin 5cambridge, multiple data pipelines designer), provided the pointing is
highly repeatable, the illumination doesn't have to be perfectly uniform. The supernova
project at KPNO, which also depends on precise relative photometry across wide fields, use a
combination of dark sky and dome flats, and this may be our best bet if the pseudo-twilight
flats fail.
Pixel non linearity
Nonlinearity is supposed to be stable and do not need to be calibrated often, and a lot of the
time one never needs to bother since there are worse systematic effects to worry about.
However, if we do need to do it, that would require a very stable light source, or some method
of measurement of the illumination - that would be possible using a bootstrap method if
strong vignetting is present.
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Dark correction
Kodak cameras could have roving hot pixels to the NIR arrays, and if the amps are not off
during integration there will be a glow at the readout corner. Our data analysis could require
dark correction in this case. The required frequency of dark correction is difficult to estimate,
this will need to be tested.
5.3 Exposure time
The main limitation to exposure time is the saturation of brighter stars in the field, and the
possible annoying effects linked to overwhelming the pixels affected by saturation.
Here is a calculation of the order of time for exposures to have stars of magnitude 11 in the
considered spectral band saturating, with the following assumptions:
 The global loss of optical efficiency of atmosphere extinction mirrors and filters is 40
%
 The spectral range is 250 nm wide
 The central obstruction is 40 % in radius of the telescope aperture
 The CCD quantum efficiency in the considered band is 50 %
 The flux in the brightest pixel is 20 % of the global flux
 The star has an homogeneous flux as a function of wavelength
 The real full wheel capacity is 50000 photo-electrons per pixel
> In those conditions, a star of magnitude 11 in the considered band would saturate in 10 s.
Real data will soon be fixed to get the exact saturation limit, but this result is a linear function
of most of this parameters and the real saturation limit should be of the same order.
As saturating a small number of stars in the field could also be an acceptable issue, the exact
exposure time will be completely defined after the study of:
 The exact number of stars of low magnitude (below 12) in the target field of view
from the study of the 2Mass catalog
 The effect of saturating pixels on the local cluster and columns, that will be simulated
with the CoRoTcam test bench
There are a few other considerations to take into account for exposure time:
 If the scientific camera is used for tracking, it might be good to consider shorter
exposures.
 Asteroseismology as a secondary scientific topic requires exposures as short as
possible.
From the specification file for the Proline camera 16801E, it is readable from 1 to 10 MHz for
its 16Mpixel. A readout time of 4s (4Mhz) seems reasonable as readout noise is still a
negligible noise source at that readout speed.
5.4 PSF broadening
Undersampling the PSF of target stars is one of the main causes of poor photometry for
ground-based surveys. We believe that we could broaden the PSF to the optimal size just
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through defocusing, as A STEP fiducial sampling is larger than most ground-based projects.
Still, defocusing increases coloured effects and is only valuable up to a certain size without
losing a too high proportion of global flux and keeping the image homogeneous. For these
reasons, we are also considering to test the broadening of the PSF using mechanical moves of
the telescope.
It is not clear whether intrapixel variations will mater given ASTEP's relatively well-sampled
PSF. However, it could be a good thing to test a rastering pattern, as routinely used by the
UNSW transit search on the 0.5m APT at Siding Spring Observatory. How this is to be
implemented depends on the system. If guiding, use the guide star to move the field around by
1 pixel in a square pattern. A quantitative comparison of the pink noise level with and without
rastering is a desirable thing.
Rastering or mechanically broadening the image during the exposure could be valuable
solutions to test and depends of the speed at which we want to move the telescope during
exposure, as multiplying the moves of the telescope in Antarctic conditions could be a source
of technical nuisance.
Fig XXX – Example of PSF broadening of HATNET telescope (Bakos 2003). The telescope
executes a moving pattern during the exposure. The pixel size is 14”. The amplitude of tiny
movements is 10”. Consecutive numbers represent the successive moves of the telescope. The
size of dots is proportional to the time spent at the respective grid points. The inner
concentric circle shows the FWHM of a typical intrinsic PSF (1.7 pixels) and the outer circle
shows the FWHM of the broadened PSF of 2.3 pixels, which is considered as much better for
HATNET photometry.
5.5 Guiding
The aim of guiding is to place each star on the same pixel, or as close to it as we can, in each
exposure, to minimise drift across the CCD, because any such drifts are likely to induce red
noise if the flat-field correction is imperfect, which is always at the ~1% level.
The original thought is to use the target field for guiding, using a dichroic beam splitter inside
the thermal enclosure to send some of the flux to a guide camera. It has the advantage of using
an additional camera in the same conditions than the scientific camera, but there may be about
chromatic effects if guiding in a different bandpass to the one used for observing. This use
requires the results of the proper study of chromatic effects, as they are of the order of one
arcsec for 300 nm differences in wavelength.
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There are two additional things to take into account with that solution:
 Fluxes in blu-er wavelength band maybe significantly uncorrelated to the one of target
stars, with its strong link to spectral type and sky brightness
 Chromatic differential effects as a function of time and position on the camera may
both change the position of guiding stars of ~1 arcsec. It would be possible to quantify
these effects in consider them in the guiding pipeline, but there would be a residual
guiding error.
 A good dichroic could be delicate to realize for a large aperture (~f/3) as dichroic do
not working perfectly with converging beams
6 Data processing
6.1 Generating Light curves (S. Aigrain)
Co-located aperture photometry - Always pacing the apertures on the same position on the
sky, as opposed to centroiding on each frame.
Variable aperture size - We compute light curves using a range of aperture size, and for each
star we select the aperture giving the "best" light curve. We use rms as a measure of the
quality of the light curve, but it may make sense to use a diagnostic more appropriate for
transit surveys, such as pink noise on the timescale of transits. Note that it may also be a good
idea to keep the light curves in all the apertures: Dave Wilson (from Keele, working on the
SuperWASP project) has come up with a neat way of identifying blended eclipsing binaries
mimicking transits by comparing the light curves in the different apertures.
Non-standard background estimation: we don't use the standard annulus technique, instead
we interpolate across a grid of 64x64 pixel regions, where the background level is estimated
using an iterative k-sigma clipping procedure. In our experience, this works better than the
annulus technique, especially in crowded fields, though there will be a limit to how crowded
one can go before the procedure starts to have problems too.
Frame offset subtraction. As described in the paper, in each frame we generate a map of
residuals from the medians of individual star's light curves, fit an nth-order 2-D polynomial to
this map as a function of x-y position (weighted as appropriate to minimise influence from
real variables). Actually, the biggest impact is from the zero-th order, but we typically use a
2nd order polynomial, and WASP uses a 3rd order.
Storage format: We use a single fits file per field, each row of which contains the data for one
object. The time, magnitude and error arrays are contained in columns of the table, each cell
of which contains an array. This format is convenient for performing on-the-fly selection on
any of the columns using the FITSIO extended filename syntax, but the file size may get
unwieldy if you have only one field and huge numbers of data points, so you may want to
adopt a format with a single object per file, or a tile, containing a certain fraction of the field.
6.2 Data flow & on-site pipeline
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A small amount of data can be transferred North over a satellite link on a daily basis, the only
possible shipment are diagnostics that photometry is done well. We therefore need to have an
automated pipeline running at the telescope, using baseline calibration frames as well as a first
order reduction pipeline in order to get out daily diagnostics, as well as a final reduction
pipeline which can be more sophisticated and less automated if necessary. The questions for
the automated version of the pipeline are then
 which steps the automated pipeline includes? All steps of the pipeline are already fully
automated in most ground surveys data pipelines, and they are probably needed to
compute the various quality check parameters to send back to France and for alarmmode on site.
 how and how often the calibration frames it uses are generated ? The master frame
only needs to be made once per field, so this could be done manually either on-site by
the person operating the telescope or remotely, if a selection of good images is sent
North.
 what are the diagnostics to send back to Europe ? On a daily basis, we would want to
send north the standard set of data quality check parameters, as well as frame offsets
and rms. We will also send North the light curves of a selection of stars, to monitor
that everything is behaving as expected, and enable us to carry out tests such as the red
noise analysis. This selection should include stars spanning a range of magnitudes and
present in 2Mass catalogue - of colours, not particularly variable, across the entire
CCD. Finally, we should also send north the master and calibration frames, on
whatever basis they are generated, to check that they are fine.
In case of the occurrence of an unpredicted event that difficult to identify, we will have a
simple procedure which would reboot for a new survey on the same field. Then, we will get
back all the data at the end of the season.
6.3 Data storage and treatment
Computer facilities
As it is not possible to transfer any big amount of data from Dome C for the moment, we are
planning to store all the data of one season at Dome C and completely treat them getting back
the computer hard disks. We will define a survey procedure before the winter season for the
telescope and we will only have safety precautions to monitor the survey with alarm signals,
and reboot procedures. We are planning to use several computers dedicated to different tasks:
 A computer for operation control, telescope pointing, guiding, tracking.
 A telescope dedicated to camera readout.
 A computer dedicated to data storage.
 Another two computers for redundancy with separate storage facilities.
Data Storage
Our data storage is directly linked to the frequency of data we want to get. We estimate that 510 measure points inside the transit are enough to discover it with classical algorithms, but a
larger number of measurements may be useful for event characterization, and blend
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discrimination. From our experience in transit search algorithms, 5-10 points seems to be a
minimal value in order to characterize the shape of the event found.
That limit would imply a higher limit in sampling rate of 10 to 20 minutes for a one field
survey. We would have to divide it by the number of target fields for a multiple-fields survey.
Let us consider the amount of data for a simultaneous survey of 4 different fields with 2
minutes sampling in each field every ten minutes for a 4096 x 4096 pixel CCD. That would
make an amount of 24.4 Go per day, which is to take into account. We do not think we can
gain more than a factor 2 with data compression. We will need redundancy in our data storage
which would at least double that amount. That maximal value we obtain still is in range to
classical data storage facilities. The way we are planning for is multiple hard-disk storage and
everyday couple of days/week DVD engraving. Stellar seismology requires shorter exposure
times than transits, and the number of possible targets increases as a function of exposures
shortness – having A STEP efficient in that secondary field may imply switching to larger
storage facilities.
Our exposure is limited by the saturation level of bright stars in the target field. A strategy to
get both events for bright stars and fainter ones would be to alternate short and a long poses,
as it is done for BEST. Still, we can sum different poses if precise temporal sampling is
proven not to be crucial.
7. Future prospects and link with future programs
7.1 GIORDANO BRUNO - KEOPS
GIORDANO BRUNO is the name given to the group of projects which lead to the
implementation of large scale interferometry at Dome C. It implies several teams in different
observatories. The LUAN is highly implicated in that project (KEOPS – the final part of it).
A STEP and Giordano Bruno main links are the scientific goal, i.e. the discovery and
characterization of exoplanets, and the fact these two projects are both conducted by
laboratories from Nice. As the LUAN has most of the experience of “antarctisation”
procedures and astronomical work on site, we will work in close link with LUAN team and
share our results and experiences.
7.2 ICE-T
The first draft of the German project ICE-T, conducted by Strassmeier, from Postdam
Observatory, has just been released to potential collaborators. ICE-T is a project that would,
by 2009, install two fully-automatic 60 to 80 cm telescopes at Dome C. These telescopes
would be equipped with two 105 millions pixels CCD camera, with a principal scientific
objective of detecting planetary transits.
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Appendix B – Instrumental noise sources
Intra pixel variations
Recent reports for currently running surveys proved the fact that intra-pixel fluctuations may
be a majoring noise source for transit surveys. (UNSW – xx)
In our simulations, we adopted intrapixel values as described by C. Karoff master thesis –
Improving the Accuracy of space based photometry – Intra-pixel structure)
Example of a longitudinal scan of EEV42-80 CCD pixel
Ten scans of the same pixel with red light. The upper panel shows the scan in the vertical
direction and the lower in the horizontal direction. The dots are the measurements, the red line
is the mean at each scan position and the error bars show the variance of the mean. The y-axis
shows the normalized number of counts.
B.2 Inter pixel fluctuations
An accurate map of the CCCD response is essential. The success of the project will probably
be linked with the knowledge we have of the CCD we use. That map would drastically reduce
the remaining inter-pixel variations.
We are thinking about working together with a team having to test similar CCDs and
generically test all CCDs. COROTCAM team and PICARD - SPACE team are respectively
conducting or planning to make tests on CCDs EEV 42-80.
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B.3 Filter and Spectral range
First limit we have is linked with the capacities of the CCD we are thinking to use. Here is the
average quantum efficiency of the CCD EEV42-80:
We have no other limit for high wavelengths. As the sky is brighter at short wavelengths, we
are considering cutting low frequencies and specializing our survey to G, K stars.
B.4 Temperature control of the CCD
Even if temperature during winter at Dome C is comparable with typical temperatures for
cooled down CCDs, we have to control and regulate this temperature.
We are going to test a classical one step Pelletier device on the twin telescope CCD, in order
to have it work at a temperature around -50°. Testing it with thermometers will give us an
idea of temperature fluctuations of this device.
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Appendix C: “White” noises
C.1 Photon noise
For unweighted aperture photometry, the variance in flux due to Poisson noise
 2  ( f  s) / g
is P, f
where f and s are the counts in the effective photometry aperture due to

the star and sky respectively ( P, f , f, and s all in ADU), and g is the CCD gain. Expressed as
an RMS variation in magnitude, provided
 P, f
<< f, this becomes:
P 
a
f
f s
g
where a = 2.5/ ln 10 ≈ 1.086, and the magnitude of the star is m = z − 2.5 log f. The
magnitude zero point, z, is the magnitude of a star which results in one ADU of detected flux
at zero airmass.
C.2 Scintillation
Scintillation sets the theoretical minimum noise level for the brightest (unsaturated) stars. The
magnitude scatter due to scintillation is given by (Kjeldsen & Frandsen 1992)
 sc int  (0.09mag ) D 2 / 3  3 / 2 t 1 / 2 e  h / 8
where D is the telescope diameter in centimetres,  is the airmass, t is the exposure time in
seconds, h is the altitude of the observatory in km. Using typical values for our observing
program with A STEP (D = 40,  = 1, t = 900, h = 3.2), the estimated scintillation limit is
0,15 mmag RMS for a 15 minutes exposure.
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Appendix D. Astrophysical noises
D.1 Stellar variability
Blind tests done for Corot satellite transit search algorithms indicated stellar variability as it
was modeled is not a major noise for transit detection. On the other hand, recent results from
MOST satellite indicated that stellar variability was really under-evaluated.
D.2 Background stars and eclipsing binaries
Background stars are a critical noise as we can not identify them. They undergo different
fluctuations than the main target stars as they do not have the same color. They create a
background noise that is a strong limitation for high magnitude stars.
The expected most critical point for “second generation” transit search is the eclipsing
binaries, and the transit blends create. In order to discriminate them, we can use radial
velocity follow-up with HARPS instrument (which can point dome C targets). That follow-up
is unavoidable because it provides the confirmation and the characterization of the planet
(mass, radius, density). But for future transit search programs, two main problems will
emerge:
 It will be technically impossible to confirm the fainter candidates.
 It won’t be possible to confirm a too long list of candidates.
Once again, a good spatial sampling can considerably reduce the number of blends mimic-ing
transits. A good point for dome C is the fact that we can keep all the data, which is impossible
for space missions that have to sum their pixel before sending back their data.
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Appendix E. Schedule of main actions for A STEP
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