The Kilodegree Extremely Little Telescope (KELT): A Small Robotic
  Telescope for Large-Area Synoptic Surveys
Draft version October 3, 2018
Preprint typeset using LATEX style emulateapj v. 08/22/09
THE KILODEGREE EXTREMELY LITTLE TELESCOPE (KELT): A SMALL ROBOTIC TELESCOPE FOR
LARGE-AREA SYNOPTIC SURVEYS
Joshua Pepper
, Richard W. Pogge
, D. L. DePoy
, J. L. Marshall
, K. Z. Stanek
, Amelia M. Stutz
, Shawn
Poindexter
, Robert Siverd
, Thomas P. O’Brien
, Mark Trueblood
, & Patricia Trueblood
Draft version October 3, 2018
ABSTRACT
The Kilodegree Extremely Little Telescope (KELT) project is a survey for planetary transits of
bright stars. It consists of a small-aperture, wide-field automated telescope located at Winer Obser-
vatory near Sonoita, Arizona. The telescope surveys a set of 26◦×26◦ fields, together covering about
25% of the Northern sky, targeting stars in the range of 8 < V < 10 mag, searching for transits by
close-in Jupiters. This paper describes the system hardware and software and discusses the quality
of the observations. We show that KELT is able to achieve the necessary photometric precision to
detect planetary transits around solar-type main sequence stars.
Subject headings: Astronomical Instrumentation
1. INTRODUCTION
The scientific value of planetary transits of bright
stars is well known – for a comprehensive review
see Charbonneau et al. (2007). These transits pro-
vide the opportunity to study the internal structure
of planets (Guillot 2005), their atmospheric compo-
sition (Charbonneau et al. 2002), spin-orbit alignment
(Gaudi & Winn 2007), and the presence of rings or
moons (Barnes & Fortnoy 2004). Radial-velocity (RV)
surveys have searched the brightest stars in the sky for
planets and are probing increasingly fainter stars. Even
with significant multiplexing, however, RV surveys are
not able to search large numbers of stars fainter than
V ∼ 8 mag. To find planets around fainter stars, transit
surveys are more suitable, and a number of such surveys
are underway. These surveys typically have wide fields
of view and small apertures to simultaneously monitor
tens or hundreds of thousands of stars. These surveys
have so far discovered six planets transiting bright stars
(Alonso et al. 2004; Bakos et al. 2007; Cameron et al.
2007; McCullough et al. 2006; O’Donovan et al. 2006).
In order to discover more such scientifically valuable sys-
tems, we have begun a survey to discover transiting plan-
The Kilodegree Extremely Little Telescope (KELT)
is designed to meet the objectives described in
Pepper, Gould, & DePoy (2003) for a wide field, small-
aperture survey for planetary transits of bright stars.
That paper derives a model for the ability of a given
transit survey to detect close-in giant planets (i.e. “Hot
Jupiters”), and determines an optimal survey configura-
tion for targeting 8 < V < 10 mag main-sequence stars.
Based on the model of Pepper, Gould, & DePoy (2003),
we expect to detect roughly four transiting planets with
the KELT survey.
The KELT system has two different observing config-
Electronic address: pepper@astronomy.ohio-state.edu
1 The Ohio State University Department of Astronomy, 4055
McPherson Lab, 140 West 18th Avenue, Columbus, OH 43210-
2 Department of Astronomy, University of Arizona, 933 N.
Cherry Avenue, Tucson, AZ 85721-0065
3 Winer Observatory, P. O. Box 797, Sonoita, AZ 85637-0797
urations. The primary configuration is a “Survey Mode”
designed for wide area coverage, either in large strips or
an all-sky survey, with the goal of covering broad sec-
tions of the sky with a large field of view, at a cadence
of a few minutes on a nightly basis throughout most of
the observing year. This mode implements the primary
scientific driver of KELT and gives this telescope a wider
field of view and targets a brighter magnitude range than
other transit surveys of its kind. The second configura-
tion is a “Campaign Mode” that uses a smaller field of
view and is designed to conduct short duration inten-
sive observing campaigns on specific fields. In Campaign
Mode we have undertaken a 74-day campaign towards
the Praesepe open cluster.
In this paper, we describe the instrumentation, deploy-
ment, and operations of KELT (§2); we characterize the
performance of the different components and the overall
system in the field (§3); we show how precise our pho-
tometry is (§4); and we provide examples of lightcurves
for variable stars and transit-like events (§5).
2. KELT SYSTEM OVERVIEW
2.1. Instrument
KELT consists of an optical assembly (CCD detector,
medium-format camera lens, and filter) mounted on a
robotic telescope mount. A dedicated computer is used
to control the telescope, camera, observation scheduling,
and data archiving system tasks. One goal in assembling
KELT was to use as many off-the-shelf components and
software packages as possible to speed the development.
The KELT detector is an Apogee Instruments4 AP16E
thermoelectrically cooled CCD camera. This camera
uses the Kodak KAF-16801E front-side illuminated CCD
with 4096 × 4096 9µm pixels (36.88 × 36.88mm detec-
tor area) and has peak quantum efficiency of ∼65% at
600nm. The AP16E uses a PCI card and cable to control
the camera and thermoelectric cooler (TEC). According
to the camera specifications and confirmed by labora-
tory testing, the camera is operated at a conversion gain
of 3.6 electrons/ADU and delivers a measured readout
4 http://www.ccd.com
http://arxiv.org/abs/0704.0460v2
mailto:pepper@astronomy.ohio-state.edu
noise of ∼15 e−. The device is read out at 14-bit reso-
lution at 1.3MHz, which gives a full-frame readout time
of ∼30 seconds. The CCD specifications claim a full-well
depth of ∼100,000e−, but the 14-bit ADC saturates at
16383 ADU (∼59,000 e−). The TEC can cool the device
to ∼30◦C below the ambient air temperature. Nominal
dark current is 0.1 − 0.2 e− pixel−1 sec−1 at an operat-
ing temperature of −10◦C (typical for 20◦C ambient air
temperature).
We use two different lenses with KELT. For the wide-
angle survey mode, we use a Mamiya 645 80mm f/1.9
medium-format manual-focus lens with a 42mm aper-
ture. This lens provides a roughly 23′′ pix−1 image scale
and a 26◦×26◦ field of view. To provide a narrow-angle
campaign mode, we use a Mamiya 645 200mm f/2.8
APO manual-focus telephoto lens with a 71mm aper-
ture. This provides a roughly 9.′′5 pix−1 image scale and
effective 10.◦8×10.◦8 field of view. Both lenses have some
vignetting at the corners, and the image quality declines
toward the outer part of the field, so the effective field of
view is circular (see §2.5 and §3.3 for details).
To reject the mostly-blue background sky without
greatly diminishing the sensitivity to stars (which are
mostly redder than the night sky), we use a Kodak
Wratten #8 red-pass filter with a 50% transmission
point at ∼490nm (the filter looks yellow to the eye),
mounted in front of the KELT lens. The calculated re-
sponse function of the KELT CCD and filter is shown
in Figure 1. The transmission function for the Wrat-
ten #8 filter is taken from the Kodak Photographic
Filters Handbook (Kodak 1998), and the quantum effi-
ciency curve for the Kodak KAF-16801E CCD was pro-
vided by the Eastman Kodak Company. The effect of
atmospheric transmission on this bandpass is estimated
for 1.2 airmasses at the altitude of Winer Observatory
(1515m) using the Palomar monochromatic extinction
coefficients (Hayes & Latham 1975), which are for an al-
titude of 1700m. We did not estimate in detail the atmo-
spheric water vapor or O2 extinction terms, as these are
not important for our application. The effective wave-
length of the combined Filter+CCD response function
(excluding atmospheric effects) is 691nm, with an effec-
tive width of 318nm, computed following the definition
of Schneider, Gunn, & Hoessel (1983). This results in
an effective bandpass that is equivalent to a very broad
R-band filter.
The optical assembly (camera+lens+filter) is mounted
on a Paramount ME Robotic Telescope Mount manufac-
tured by Software Bisque5. The Paramount is a research-
grade German Equatorial Mount designed specifically for
robotic operation with integrated telescope and cam-
era control. According to manufacturer’s ratings the
periodic tracking error of the mount before correction
is ±5′′. That is smaller than the large pixels of the
KELT camera and therefore does not affect our obser-
vations. The mount can carry an instrument payload
of up to 75 kg, more than sufficient for the KELT cam-
era, which weighs approximately 9 kg. The Paramount
is installed on a stock 91 cm high steel pier using a stock
base adapter plate. The Paramount provides us with
a robust, complete mounting solution for our telescope.
The optical assembly is mated to the Paramount using
5 http://www.bisque.com
a custom mounting bracket that mounts directly on the
Paramount’s Versa-Plate mounting surface.
The CCD camera and mount are controlled by a PC
computer located at the observing site that runs the Win-
dows XP Professional operating system and the Bisque
Observatory Software Suite from Software Bisque. There
are three main applications that we use for KELT:
TheSky to operate the Paramount ME (pointing and
tracking); CCDSoft CCD camera control software to op-
erate the AP16E camera; and Orchestrate scripting and
automation software to integrate the operation of TheSky
and CCDSoft. Orchestrate provides a simple script-
ing interface that lets us control all aspects of a night’s
observing with a single command script. This software
lets us prepare an entire night’s observing schedule and
upload it to the KELT control computer during the af-
ternoon. A scheduled task on the computer starts up
the system at sunset and loads the observing script into
Orchestrate, after which the system runs unattended
for the entire night, weather permitting.
The observing site provides AC power and Internet
connectivity. To ensure clean AC power for the KELT
telescope and control computer at the observing site
(§2.2) we use a 1500VA Powerware 9125 Uninterrupt-
able Power Supply (UPS). This filters the line power
and protects the system against surges or brief power
outages. The control computer is connected to the
Internet through the observing site’s gateway, and its
internal clock is synchronized with the network time
servers at the Kitt Peak National Observatory using the
Dimension 4 network time protocol (NTP) client6. This
ensures sufficiently accurate timing for telescope point-
ing and time-series photometry. Since we observe at few-
minute cadences, we can tolerate few-second timing pre-
cision, which is easily within the typical performance of
Dimension 4 on the available T1 connection.
2.2. Observatory Site
The KELT telescope has been installed at the Irvin
M. Winer Memorial Mobile Observatory7 near Sonoita,
Arizona. Located at N 31◦39′53′′, W 110◦36′03′′, ap-
proximately 50 miles southeast of Tucson at an eleva-
tion of 4970 feet (1515meters), Winer Observatory has a
dedicated observing building with a 25×50-foot (7.6×15-
meter) roll-off enclosure and provides site and mainte-
nance services. Winer currently hosts four robotic tele-
scopes, including KELT. The KELT telescope pier is
bolted to the concrete floor, and its control cables are
run into a nearby telescope control room that houses the
control computer and UPS. Winer also provides Internet
access (currently via a dedicated DS/T1 line, but early
in the project the site used a slower ISDN link), that al-
lows us to remotely login to the control computer via a
secure gateway.
The weather conditions at Winer Observatory are
roughly as good as comparable sites in southern Arizona;
about 60% of all observing time is usable, with half of
that time being measurably photometric. Since our PSFs
are between 2 and 3 pixels, and the pixel scales are 9.′′5
and 23′′ (for the 200mm and 80mm lenses, respectively),
6 v5.0 from Thinking Man Software
(www.thinkman.com/dimension4/)
7 http://www.winer.org
atmospheric seeing variations (which are on the scale of
arcseconds) are not a factor in our observations.
2.3. Observing Operations
Observations with KELT are carried out each
non-clouded night using command scripts for pre-
programmed, robotic operation; we do not undertake
any remote real-time operations. The nightly observ-
ing scripts are created at Ohio State University (OSU)
using a script-generation program written in Perl, and
then uploaded to Winer Observatory where they are used
by Orchestrate to direct the telescope to observe the
specified fields for each night. Each night has a differ-
ent script, and we generally upload scripts in 3-4 week
batches during the main survey season, or more fre-
quently during pointed-target campaigns.
The suite of software programs we use to control the
telescope mount and camera works well, but has several
limitations. Most importantly, the Orchestrate script-
ing package does not provide the built-in ability to pro-
gram control loops or conditional branching, which is
why we use a Perl program to create the Orchestrate
scripts we upload to the control computer.
The scripts start the telescope each night based on the
local clock time. On nights when the weather is judged
to be good enough for observing, the observatory control
computer automatically opens the roof of the observatory
at nautical (12◦) twilight and the telescope begins obser-
vations on schedule. If the weather is not suitable for
observing, on-site personnel abort the command script.
If the weather appears good at first but degrades dur-
ing the night, the observatory computer closes the roof
and the personnel abort the script. All data acquired are
archived automatically at the end of the night.
When the script is loaded into Orchestrate, it first
waits until one hour before astronomical (18◦) twilight.
At that point the telescope takes five dark images and five
bias images, with the exposure times for the dark frames
the same as the exposure times of the observations for
the night. Once these calibration data are taken, the
telescope goes back to sleep until astronomical twilight,
at which point it slews to the first target field and begins
the nightly observing sequence. Unless the weather turns
bad, prompting the roof to close, observations continue
until astronomical dawn. At this time the telescope is
slewed to its stowed position, and five dark images and
five bias images are acquired, ending observing for the
night. (See §2.5 for a discussion of KELT flatfields.)
We have so far used KELT in two distinct operating
modes: campaign mode, using the 200mm lens, and sur-
vey mode, using the 80mm lens. In campaign mode, the
telescope intensively observes a single target field for an
entire night. In survey mode, the telescope observes a
number of fields that are equally spaced around the sky
at 2h intervals of Right Ascension centered on Declina-
tion +31◦39′ (the latitude of Winer).
In campaign mode, the observing script instructs the
telescope to wait until the target field is above 2 air-
masses, and to then observe the field continuously until it
sinks below 2 airmasses or astronomical dawn, whichever
happens first. In survey mode, the telescope begins ob-
serving after astronomical twilight, tiling between two
fields at a time. New fields are observed as they rise
above 1.4 airmasses. Provisions for Moon avoidance are
built into the scripts to prevent observations of any sur-
vey field when it is within 45◦ (two field widths from field
center) of the Moon.
An operational complication arises because the KELT
mount is a German Equatorial design. This means that
fields observed East of the Meridian are rotated by 180◦
relative to fields observed West of the Meridian. The
practical effect is that we must separately reduce pho-
tometry for fields taken in East and West orientations,
especially when we use difference-imaging photometry.
To avoid the complication of creating two separate data
pipelines to reduce data taken in survey mode, we in-
stead observe only fields in the Eastern part of the sky.
We lose some observation time due to periods when the
Moon is within 45◦ of all fields in the East above 1.4
airmasses, leading to downtime when no field is available
that meets the observing criteria. In those situations, the
scripts instruct the telescope to pause observing until the
next field becomes available. Overall, the loss to Moon
avoidance reduces the total amount of data acquired by
∼10%.
2.4. Data Handling and Archiving
Data acquired by the camera are immediately writ-
ten to a hard drive in the control computer, logged, and
then copied to one of two 250GB external hard drives
attached to the control computer by a USB interface. At
the end of the night, all new images are automatically du-
plicated onto the other external hard drive. During long
winter nights, the telescope can take as many as 500-600
images per night, depending on the exposure time, fill-
ing the drives every two weeks. Normally, however, bad
weather and downtime due to Moon avoidance reduce
the actual observing rate, so it typically takes 3-4 weeks
for both storage drives to reach capacity.
Data quality is monitored daily using automated
scripts running on the Windows observing computer at
Winer. At the end of the night, a Perl script selects three
images from the beginning, middle, and end of the night
and uploads them to a computer at OSU. These sample
images are analyzed for basic statistics: mean, median,
and modal sky value and the mean FWHM of stars mea-
sured across the images, and then visually inspected to
ensure that the camera and mount are operating cor-
rectly.
When the external drives approach full capacity, they
are disconnected from the computer. One of the drives
is a hardened drive made by Olixir Technologies (their
Mobile DataVault) that serves as the transport drive.
This drive is shipped via FedEx to the OSU Astronomy
Department in Columbus, Ohio, in a cushioned trans-
port box, as bandwidth limitations at Winer Observa-
tory preclude online data transfer. The second drive is a
conventional external USB drive without special mobile
packaging made by Maxtor Corporation which serves as
the backup drive and which is stored at Winer Obser-
vatory. Until the transport drive arrives at OSU and
its data have been successfully copied and verified, the
backup drive at Winer is stored and left idle. In the
event a transport drive arrives damaged, data from the
backup drive will be copied to another transport drive
and shipped. In the meantime, the removed drives are
replaced with two others of each type and operations
continue. At any given time, we have four external disk
drives in use: two drives in operation, one in transit,
and one stored as a backup. For transferring hundreds
of gigabytes of images every few weeks during the prime
observing season, this procedure has proven to be very
reliable and efficient. To date, out of dozens of drive ship-
ments, we have lost only two drives to damage in transit,
with no loss of data (both arrived damaged at Winer af-
ter their data were retrieved and copied at OSU).
When a transport drive arrives at OSU, the drive is
connected to our main data storage computer and all of
the images are copied and run though a series of data
quality checks. The image files are renamed, replacing
the cumbersome default file name created by the CCDSoft
application with a name indicating the field observed,
the UTC date, and an image number. The images are
then analyzed to measure image quality (modal sky and
mean FWHM). If the modal sky value is above 800 ADU
(due to moonlight, cloud cover, or other ambient light
sources), the image is discarded. The cutoff at 800 ADU
was determined using two months of representative data
showing that images compromised by excessive light con-
tamination consistently had sky values above that level
and were unsuitable for photometry. The cutoff is high,
with many poor images well below the cutoff, but we
choose to be conservative about eliminating images early
in the reduction process. The images that pass the initial
filter on sky values, and the trimmed sections of the bad
images, are stored on a multi-terabyte RAID storage ar-
ray at OSU, providing data redundancy and fast access
for data reduction and analysis.
2.5. Data Reduction
Here we describe the data reduction process in brief,
for the purposes of evaluating the performance of the
KELT camera. Detailed descriptions of the reduction
process will be included in an upcoming paper on the
scientific results of KELT observing campaigns (J. Pep-
per, in preparation).
The data reduction pipeline consists of three steps.
First, we process the images by subtracting dark frames
and dividing by a flatfield. Second, we identify all the
stars in the field and determine their instrumental mag-
nitudes. Third, we obtain the photometry on all images
using difference image analysis.
Dark images are created for each night by median-
combining 10 dark images – five from the beginning and
end of each night. In early testing we determined that we
can treat our dark frames as combined dark+bias. We
take bias frames separately to monitor their stability, but
do not incorporate them into the reduction process be-
cause the bias has been extremely stable. In cases where
dark frames were not taken or there were problems with
the images, we use good dark frames from nights brack-
eting the observations to create a substitute dark frame.
We confirmed that using dark images from nearby nights
did not significantly affect the statistics of the subtracted
images – our dark images are quite stable from night to
night.
The KELT system is challenging to accurately flatfield.
For the 200mm lens there is a combined decrease in flux
of ∼18% between the center of the image and the edges,
and a decrease of up to ∼26% between the center and
the corners. For the 80mm lens, the decrease is ∼23%
from the center to the edge, and ∼35% from the center
to the corners. Because of the large KELT field of view
(10.◦8 and 26◦ for the 200mm and 80mm lenses, respec-
tively), twilight flats are not useful for flatfielding since
the twilight sky is not uniform on those scales. Dome
flats using a diffuse screen produced reasonable results
with high signal-to-noise ratio. The flats are sufficiently
repeatable that we do not need to regularly take dome
flats. For relative photometry, the dome flats work ade-
quately, and we are able to absolutely flatfield our images
to ∼ 5% accuracy.
Once images have been dark-subtracted and flatfielded,
we can then create catalogs of images and measure the
brightnesses of stars on the images. This photometric
analysis is done in two basic steps. The first is to cre-
ate a high-quality reference image for a field by com-
bining a few dozen of the best images and then use the
DAOPHOT software package (Stetson 1987) to identify
all of the stars in the field down to a faint magnitude
limit and measure their approximate instrumental mag-
nitudes. See §4.1 for the details on how the instrumental
magnitudes are calibrated to standard photometry.
Once a template and DAOPHOT star catalog with
baseline instrumental magnitudes have been created, the
second step is to process the images with the ISIS image
subtraction package (Alard & Lupton 1998; Alard 2000).
Our reduction process is similar to that of Hartman et al.
(2004). The ISIS package first spatially registers all of the
images to align them with the reference image. The refer-
ence image is convolved with a kernel for each image and
subtracted, creating a difference image. The flux for each
star identified on the reference image is then measured
on each subtracted image using PSF-fitting photometry.
Image subtraction has been shown in limited tests to be
equal to or better than other photometric methods for
the purposes of transit searches (Bakos 2006). In section
§4 below, we provide additional information about the
reduction process to obtain relative photometry.
3. INSTRUMENT PERFORMANCE
In this section we quantify the performance of the
KELT system by assessing in turn the telescope mount,
the astrometric quality (geometric image quality), the
image quality (position-dependent PSF), and photomet-
ric sensitivity.
3.1. Telescope Performance
Since the telescope was installed at Winer in October
2004, the hardware has performed up to specifications.
There have been no significant problems with the mount
or the control software. The pointing has not been per-
fect: our fields are so large that minor pointing errors do
not significantly affect our scientific results, but during
normal operations the typical intra-night drift is ∼25′
in Declination and ∼9′ in Right Ascension. We believe
the drift is due to a slight non-perpendicularity between
the orientation of the camera and the axis of the mount.
While the magnitude of the drift seems large, it repre-
sents a movement of ∼65 pixels, less than 2% of the size
of the field. It does not cause stars to move across large
portions of the detector, and therefore does not lead to
significant changes in the PSFs of individual stars. Since
our reduction method utilizes image subtraction, we do
lose the ability to take good photometry at the edges of
a field. However, because of PSF distortions and other
effects (see §3.3), we already have degraded sensitivity in
those regions. Therefore the loss of coverage and sensi-
tivity due to drift is quite small. Future alignment of the
telescope will attempt to reduce or eliminate the drift.
3.2. Astrometric Performance
Measurements of the positions of stars from the Tycho-
2 Catalog (Høg et al. 2000) are used to determine the
conversion between pixel coordinates and celestial coor-
dinates on the KELT images. We use the Astrometrix8
package to compute polynomial astrometric solutions
for our images following the procedure described by
Calabretta & Greisen (2002). To avoid stars that are sat-
urated on the KELT images, we consider Tycho-2 stars
with magnitudes 9.0 ≤ VTyc ≤ 10.0. From these we select
up to 1000 stars per image. A first attempt to compute a
global astrometric solution for the entire 4096×4096 im-
age produced large residuals for most of the outer parts
of the detector, with discrepancies between the predicted
and actual positions of Tycho-2 stars of many tens of pix-
els. Since our primary goal is to convert pixel coordinates
into celestial coordinates on a star-by-star basis, a global
solution is not required. We instead divide the image
into 25 subimages on a 5×5 grid and perform a separate
astrometric solution for each subimage. A third-order
polynomial astrometric fit is computed for each subim-
age using Astrometrix. The individual subimage fits
give much better results, with offsets between predicted
and measured positions of catalog stars at the subpixel
level except at the extreme corners of the field. The
subframes overlap by a few tens of pixels, and fits to
stars common to adjacent subimages are consistent at
the arcsecond level. For the 200mm lens, the typical
RMS residuals are ±0.′′8, or < 10% of the average pixel
size of ∼9.′′5. The 80mm lens has slightly worse RMS
residuals, ±5′′or ∼20% of a pixel size of 22′′, but still
well within tolerances for our purposes.
Having a good astrometric fit to the images permits
a quantitative assessment of the geometric performance
of the KELT optics; specifically, variation in pixel size
and shape across the field. Since this is a commercial
lens with proprietary optical designs, there is no way to
determine these propoerties a priori. This analysis will
therefore be useful for anyone contemplating using ssim-
ilar systems, and has implicatons for the potential use
of theis setup - for example, such a camera/lens com-
bination cannot be used to construct large-scale image
mosaics. Furthermore, while sky subtraction deals with
this effect, flatfielding does not.
For the 200mm lens, the effective pixel size decreases
by about 1% from center-to-edge from 9.′′537 near the
center to 9.′′450 at the edges of the field (∼9.′′40 at the
corners). Contours of constant effective pixel scale are
circular and centered on the intersection of the optical
axis of the 200mm camera lens and the CCD detector,
as shown in Figure 2. The square CCD pixels do not
perfectly project onto squares on the sky, but slowly dis-
tort systematically away from the center, showing the
characteristic signature of ∼0.5% pincushion distortion,
expected for the manufacturer’s typical claims for their
telephoto lenses. As Figure 3 shows, for the 80mm lens
the effective pixel size decreases by about 3.5% from
8 http://www.na.astro.it/$\sim$radovich/wifix.htm
center-to-edge, from 23.′′19 near the center to 22.′′40 at
the edges of the field (and ∼21.′′8 at the corners). This
effect is larger than the one seen with the 200mm lens,
consistent with ∼2% pincushion distortion in this lens,
typical of short focal-length wider-angle lenses. Contours
of constant effective pixel scale are also circular and cen-
tered on the CCD detector.
The effect of the optical distortion is that pixels project
onto smaller effective areas on the sky moving radially
outward from the center of the CCD, making the sky
appear non-flat (center-to-edge) at the ∼1.5% level for
the 200mm lens and at the ∼6% level for the 80mm lens.
There are two effects that act together to decrease the
background sky level per pixel as you go radially outward
from the center of the image: the decreasing pixel scale,
and hence decreasing pixel area on the sky, with radius,
and increasing vignetting with radius.
3.3. Image Quality
As expected for such an optically fast system, the
image PSF varies systematically as a function of posi-
tion. The small physical pixel size (9µm) implies that
the lens optics dominate the PSF, and we are insensitive
to changes in atmospheric seeing. For both lenses, the
systematic patterns in both the image full-width at half
maximum (FWHM) and more refined measures of image
quality (i.e. the 80% encircled energy diameter D80) can
be used to quantitatively assess the position-dependent
image quality.
For the 200mm lens, typical image PSFs have FWHM
of ∼1.8–2.9pixels, and 80% encircled energy diameters
of D80 =4.7-9pixels. The 80mm lens has a similar range
of FWHM for stellar image PSFs, and the 80% encircled
energy diameters range from D80 =6-10pixels. There
are significant changes in the detailed PSF shape across
each image from the center to the extreme edges of the
detector. Figure 4 shows representative stellar PSFs for
a 5×5 grid across the CCD for the 200mm lens. The
80mm lens shows more pronounced distortions, as shown
in Figure 5. Therefore, the 80mm lens has a roughly
24◦ diameter effective field of view with reasonably good
images and little vignetting, whereas the 200mm lens
works well over most of the CCD detector except at the
extreme corners.
Figures 6 and 7 show maps of the image FWHM as a
function of position for the 200mm and 80mm lenses,
respectively, derived from measurements of unsaturated,
bright field stars in representative images. The most ob-
vious feature in both is the strong vertical trend in in-
creasing FWHM, with nearly no differences horizontally.
Because this is seen with both lenses, which are of very
different design, we believe this is because the CCD is
tilted relative to the optical axis. Because the lens de-
signs are proprietary, we do not know precisely how much
the detector is tilted, nor the origin of the tilt at present.
This effect could be due to how the detector is mounted
inside the camera, or to the camera/lens mounting plate.
This apparent field tilt also affects the maps of the 80%
encircled-energy diameter D80, shown in Figures 8 and
The 80mm lens has very stable imaging performance
over time. The FWHM and D80 maps derived for im-
ages of the same field over a 11-month period show no
significant changes. We have, however, periodically ad-
http://www.na.astro.it/$\sim $radovich/wifix.htm
justed the focus when working with the telescope, which
my cause some discontinuities in the data for the survey
images. We will explore such effects in upcoming papers.
Unfortunately, the PSF is not stable across the image
over time for the 200mm lens. While intranight vari-
ations in the FWHM maps are quite small, there are
significant changes from night to night that have no ap-
parent correlation with hour angle, CCD temperature, or
any other physical or environmental parameter for which
we have measurements. The effect of the changes we see
is for the region of best FWHM (the base of the trough
seen in the FWHM map in Figure 6) to move vertically
on the CCD by many hundreds of pixels. We do not
yet know the cause. The main effect is to complicate
the difference-imaging reductions of the data. We will
discuss these complications and their mitigation in the
subsequent paper describing our results for the 200mm
lens Praesepe cluster observing campaign.
3.4. Photometric Sensitivity
Given the nature of the KELT bandpass (see Figure 1),
we calibrate our instrumental magnitudes to the R band.
We do so by rescaling our instrumental magnitudes by a
constant, such that
RK ≡ −2.5 log(ADU/sec) +RK,0 (1)
where the instrumental ADU/sec is measured using aper-
ture photometry with IRAF, RK is defined as an approx-
imate KELT R magnitude, and RK,0 is the zero-point.
We find that the RK magnitudes are within a few tenths
of a magnitude of standard R band photometry, with the
uncertainty dominated by the color term. Since we do
not have V −I colors for all our stars, we quote observed
magnitudes in RK , which can be considered equivalent
to Johnson R, modulo a color term defined by
V = RK + CV I(V − I) (2)
where CV I is the (V − I) color coefficient, and V/I are
in the Johnson/Cousins system. Since we do not have
previously measured R magnitudes of large numbers of
stars in our fields in our magnitude range, we relate RK
to known magnitudes by matching stars from our ob-
servations to the Hipparcos catalog, selecting only stars
with measured V and I colors in Hipparcos. We take the
mean instrumental magnitude from a set of high-quality
images, and match the known magnitudes to the mean
instrumental magnitudes, using Equations 1 and 2.
For the cluster observations with the 200mm lens, we
select 22 calibration stars, and measure their instrumen-
tal magnitudes on 76 high-quality images, resulting in a
magnitude zero-point of RK,0 = 16.38 ± 0.06 mag, and
CV I = 0.55± 0.2. For the survey observations with the
80mm lens, we use 59 stars on 77 images, resulting in a
magnitude zero-point of RK,0 = 15.15 ± 0.07 mag, and
CV I = 0.5 ± 0.3. Since the Hipparcos stars we use to
calibrate our data have (V − I) colors mostly between 0
and 1, we expect our calibrations to be less accurate for
redder stars. These measured zero-point uncertainties
suggest that the flatfield corrections are good to within
∼ 5% in absolute accuracy.
Tying together the full calibration process, we find that
a fiducial R = 10 mag star at the field center with (V −
I) = 0 has a flux of 356 counts per second with the
200mm lens, and 115 counts per second with the 80mm
lens. Scaling those numbers by the different aperture
sizes of the lenses (71mm aperture for the 200mm lens
and 42mm aperture for the 80mm lens), we find that the
200mm lens is about 8% more efficient than the 80mm
lens.
4. RELATIVE PHOTOMETRY
KELT was designed primarily for precision time-series
relative photometry (see Everett & Howell (2001) for
background). The crucial test for our instrument is the
ability to obtain long-term lightcurves with low noise and
minimal systematics. A simple test of KELT’s photo-
metric performance is to examine the root-mean-squared
(RMS) of the magnitudes of an ensemble of lightcurves as
a function of magnitude. We apply the ISIS image sub-
traction package to samples of our data to obtain relative
photometry, and measure the statistics of the resulting
lightcurves. Our criteria for the ability to detect plan-
etary transits is the presence of substantial numbers of
stars for which the RMS of the lightcurves are below the
2% and 1% levels.
4.1. Difference Imaging Performance
The instrumental magnitudes for the KELT lightcurves
are produced through a combination of ISIS and
DAOPHOT photometry. This process involves some
careful conversion between DAOPHOT and ISIS flux
measurements – see Appendix B of Hartman et al. (2004)
for the details of the conversion. First, we create a ref-
erence image by combining a number of high-quality im-
ages. DAOPHOT measures the instrumental magnitude
of the stars on the reference image mi(ref) based on PSF
fitting photometry, with the magnitude of each star i cal-
culated from the flux by mi(ref) ≡ 25− 2.5 log[fi(ref)] +
Cap, where fi is the flux measured by DAOPHOT and
Cap is an aperture correction to ensure that mi(ref) =
25 − 2.5 log(ci), where ci is the counts per second from
the star in ADU. ISIS then creates an ensemble of sub-
tracted images for the whole data set using the refer-
ence. To derive the full light curve, ISIS fits a PSF
for each star on each subtracted image j, to obtain a
flux fi(j). The DAOPHOT-reported instrumental mag-
nitudes for the reference images serve as the magnitude
baseline for the conversion of ISIS fluxes to magnitudes,
where the magnitude of the ith star on the jth image is
mi(j) = mi(ref)− 2.5 log[1− fi(j)/fi(ref)].
We then calculate the RMS variation of all the detected
stars in both the Praesepe data set and for a sample of
the survey data. Because of the night-to-night varia-
tions in the position of the best image quality on the
detector with the 200mm lens described at the end of
§3.3, we calculate the RMS for the Praesepe data from
a single night of observations, to better demonstrate the
intrinsic instrumental performance. In Figure 10 we plot
the distribution of RMS versus RK magnitude for 67,674
stars on 32 images with 60-second exposures from one
night. With this lens and exposure time, we obtain pho-
tometry of stars in the magnitude range RK = 8 − 16
mag. For stars brighter than about RK = 9.5mag,
systematics begin to dominate the light curves, mostly
due to saturation. Out of the 67,674 stars, 4,281 have
RMS< 0.02mag, and 1,369 have RMS< 0.01mag.
We perform the same analysis for one of the regu-
lar survey fields observed with the 80mm lens using
239 observations over 8 nights with 150-second expo-
sures. We obtain photometry on 49,376 stars in the range
RK = 6 − 14 mag, and plot the data in Figure 11. We
find 14,333 stars with RMS< 0.02mag, and 3,822 stars
with RMS< 0.01mag, with systematics dominating for
stars brighter than RK = 7.5mag.
Overall, the RMS performance is mostly as expected
from Poisson statistics except at the bright end. The best
precision just reaches the theoretical noise limit, with a
spread of RMS values above that limit due to real-world
effects. For the brightest stars in our data we see a floor
in which the RMS no longer decreases as the stars get
brighter, and instead becomes roughly constant at RMS
= 0.004 magnitudes. The RMS floor is indicative of a
fixed pattern noise component, caused by intrapixel sen-
sitivity on the CCD. The Kodak KAF-E series CCDs
are 2-phase front-side illuminated devices in which the
second poly-gate electrode on each pixel is a transparent
gate made of Indium-Tin-Oxide (ITO) to boost the over-
all quantum efficiency of the device (Meisenzahl et al.
2000). Over much of the wavelength regime of interest for
KELT, the ITO material is ∼2 times more transparent
than the regular silicon oxide material used on the first
poly-gate. The result is significant pixel substructure
in which the quantum efficiency varies stepwise across
each 9µm pixel, which introduces a component of fixed-
pattern noise that produces the observed RMS floor. We
note that more recent models of commercial CCD cam-
eras with the Kodak KAF-16801 detector are using a
newer version of this device that incorporate a front-
surface microlens array that mitigates the intrapixel step
in transmission, but persons contemplating similar sys-
tems to our own should be aware of the issue and take it
into account.
We do not expect to obtain high-precision photometry
for the very brightest stars in our data, but the RMS floor
is well below the 1% level and it should not significantly
affect our ability to detect transits. We plot noise models
in Figures 10 and 11, which include photon noise and
sky noise, along with the RMS floor. In the future we
will choose a lens focus that makes slightly larger FWHM
images to minimize these effects.
5. REPRESENTATIVE RESULTS
The RMS plots shown in Figures 10 and 11 demon-
strate that our telescope can obtain precision relative
photometry, with large numbers of stars measured at the
1% level. However, simply looking at the RMS informa-
tion does not prove that the data set can yield the con-
sistent quality with low systematics necessary for a tran-
sit search. To illustrate that we can fulfill that require-
ment, we show in Figure 12 the lightcurves of three sam-
ple variable stars we have discovered using the 200mm
lens while observing the field of Praesepe. Even with the
night-to-night variations discussed in §3.3, we are able
to achieve the consistent data quality that transit detec-
tion requires, and are able to clearly see features in the
phased lightcurves of a few percent or less.
An even better example of our ability to detect tran-
sits can be seen in Figure 13. Here we show two objects
we detected in our data from the Praesepe field which
exhibit transit-like dips in their lightcurves. These ef-
fects can be clearly seen at the level of a few percent.
These objects are not planetary: follow-up spectroscopy
indicates that the top object is an F star with a tran-
siting M dwarf companion, and the bottom object is a
grazing eclipsing binary (Latham 2007). However, they
demonstrate that we can confidently detect transit-like
behavior at the 1%-2% level with our telescope. A full
catalog of the variable stars and transit candidates from
the KELT observations of the Praesepe field will appear
in a forthcoming paper (J. Pepper, in preparation).
6. SUMMARY AND DISCUSSION
The KELT project has been acquiring data since Oc-
tober 2004. We observed the field of the Praesepe open
cluster with the 200mm lens for two months in early
2005, and have spent the rest of the time using the 80mm
lens for a survey of 13 fields around the Northern sky.
The KELT telescope, used in “Survey Mode” with the
80mm lens, reflects the design specifications called for
in the theoretical paper Pepper, Gould, & DePoy (2003).
The performance of the telescope as described in this pa-
per provides a real-world evaluation of the potential for
this telescope to detect transiting planets. In addition
to the lightcurves and RMS plots that show the tele-
scope’s abilities, we find that the total number of pho-
tons acquired from a fiducial V = 10 mag star over an
entire observing run is well above the number assumed
in Pepper, Gould, & DePoy (2003) with the parameter
gamma0.
This paper has described the KELT instrumentation
and performance, with both the 200mm lens used for
observing clusters and the 80mm lens used for conduct-
ing the all-sky survey. It is the widest-field instrument
that is currently being employed to search for transit-
ing planets, and we observe brighter stars than other
wide field surveys. The performance metrics demon-
strate that it is capable of detecting signals at the ∼1%
level needed to detect Jupiter size planets transiting
solar-type stars. Further refinements of our reduction
process promise to expand our sensitivity to transits,
such as applying detrending algorithms of the sort devel-
oped by Tamuz, Mazeh, & Zuker (2005). We also plan
to conduct a full analysis of red noise (i.e. temporally
correlated systematic noise, see Pont, Zuker, & Queloz
(2006) for a full description) for all KELT data.
To date, we have detected over 100 previously unknown
variable stars in our observations towards Praesepe, and
we have identified several lightcurves with transit-like be-
havior, of which we show two in Figure 13. Future pa-
pers will report on the success in discovering variable
stars and searching for planets in Praesepe, along with
the full transit search for the all-sky survey.
We would like to thank the many people who have
helped with this research, including Scott Gaudi, An-
drew Gould, Christopher Burke, and Jerry Mason. We
would also like to thank Apogee Instruments and Soft-
ware Bisque for supplying the camera and mount for the
telescope and for excellent service for the hardware. This
work was supported by the National Aeronautics and
Space Administration under Grant No. NNG04GO70G
issued through the Origins of Solar Systems program.
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0.1.2.3.4.5.6
Response
Fig. 1.— Calculated response function of the KELT CCD camera and Kodak #8 Wratten filter. The dashed curve is the response function
including atmospheric transmission at Winer Observatory for 1.2 airmasses. This response function does not include the transmission of
the camera lenses.
−10 0 10
X (mm)
9.525
9.500
9.475
9.537"/pix
Fig. 2.— Effective pixel scale in arcseconds pixel−1 for the KELT 200mm camera. Contours show curves of constant effective pixel scale.
The cross (+) marks the optical center of the field, where the pixel scale is 9.′′537 pix−1.
−10 0 10
X (mm)
21.68"/pix
Fig. 3.— Effective pixel scale in arcseconds pixel−1 for the KELT 80mm camera. Contours show curves of constant effective pixel scale.
The cross (+) marks the optical center of the field, where the pixel scale is 21.′′68 pix−1.
−14,14 −7,14  0,14 7,14 14,14
−14,7 −7,7  0,7 7,7 14,7
−14,0 −7,0  0,0mm 7,0 14,0
−14,−7 −7,−7  0,−7 7,−7 14,−7
−14,−14 −7,−14  0,−14 7,−14 14,−14
Fig. 4.— Representative stellar PSFs from the 200mm telephoto lens, shown as intensity contours of bright, unsaturated stars taken
with a 5×5 grid pattern on the CCD; the position of the center of each box, relative to the center of the image, is indicated in mm. Each
box is 15 pixels (135mm) on a side. The scale-bar in the center panel indicates 50µm on the detector (5.5 pixels). Contours show levels of
(5,10,15,20,25,30,40,50,60,70,80,90,100)% of the peak intensity.
−14,14 −7,14  0,14 7,14 14,14
−14,7 −7,7  0,7 7,7 14,7
−14,0 −7,0  0,0mm 7,0 14,0
−14,−7 −7,−7  0,−7 7,−7 14,−7
−14,−14 −7,−14  0,−14 7,−14 14,−14
Fig. 5.— Representative stellar PSFs from the 80mm wide-angle lens, displayed in the same format as in Figure 4. The images are more
severely distorted at the extreme edges of the field than with the 200mm lens.
−10 0 10
X (mm)
Fig. 6.— Contours of constant FWHM for stellar images in a representative 200mm lens KELT image, with FWHM given in pixels.
Contours are based on a smooth polynomial surface fit to measurements of ∼1200 bright, unsaturated stars distributed across the image.
Contour spacing is every 0.1 pixels, with particular contour level values in pixels as indicated.
−10 0 10
X (mm)
Fig. 7.— Contours of constant FWHM for stellar images in a representative 80mm lens KELT image, with FWHM given in pixels.
Format is the same as in Figure 6. Contours are based on measurements of ∼2100 bright, unsaturated stars.
−10 0 10
X (mm)
D80=4.7pix
Fig. 8.— Contours of constant 80% Encircled-Energy Diameter (D80) in pixels for stellar images in a representative 200mm lens KELT
image. Contours are based on a smooth polynomial surface fit to measurements of ∼1200 bright, unsaturated stars distributed across the
image.
−10 0 10
X (mm)
D80=6.12 pix
Fig. 9.— Contours of constant 80% Encircled-Energy Diameter (D80) in pixels for stellar images in a representative 80mm lens KELT
image. Contours are based on measurements of ∼2100 bright, unsaturated stars.
Fig. 10.— RMS plot for one night of data from the 200mm lens. Data are shown for 67,674 stars. The dashed lines show the limits for 1%
and 2% RMS. The solid line represents a noise model including photon noise and sky noise, along with an RMS floor of 0.004 magnitudes.
Fig. 11.— RMS plot for eight nights of data from the 80mm lens. Data are shown for 49,376 stars. The dashed lines show the limits
for 1% and 2% RMS. The solid line represents a noise model including photon noise and sky noise, along with an RMS floor of 0.004
magnitudes.
Fig. 12.— Three variable stars discovered with the 200mm lens in the field of the Praesepe open cluster.
Fig. 13.— Two transit candidates discovered with the 200mm lens in the field of the Praesepe open cluster. The lower panel of each
plot shows the data binned in 10-minute bins. Follow-up spectroscopy indicates that object (a) is an F star with a transiting K dwarf
companion, and object (b) is a grazing eclipsing binary.
