Wide Angle Telescope Transit Search (WATTS): A Low-Elevation Component of the TrES Network

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1 PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC, 122:41 48, 2010 January The Astronomical Society of the Pacific. All rights reserved. Printed in U.S.A. Wide Angle Telescope Transit Search (WATTS): A Low-Elevation Component of the TrES Network BRIAN OETIKER, MICHAEL KOWALCZYK, AND BRIAN NIETFELD Department of Physics, Sam Houston State University, Huntsville, TX; phy_bgo@shsu.edu, mwk006@shsu.edu, stdbpn12@shsu.edu AND GEORGI I. MANDUSHEV AND EDWARD W. DUNHAM Lowell Observatory, Flagstaff, AZ; gmand@lowell.edu, Ted.Dunham@lowell.edu Received 2009 October 27; accepted 2009 November 25; published 2010 December 14 ABSTRACT. The Wide Angle Telescope Transit Search (WATTS) is a low-elevation small aperture, wide-field ð5:5 5:5 Þ, transit search instrument capable of achieving the photometric precision needed to detect giant extrasolar planets. The system is designed to simultaneously observe tens of thousands of stars with R magnitudes between 10 and 13. In just over one year of operation, WATTS has completed five observing campaigns. During this period, 20 candidates have been identified from WATTS data. As the fourth component of the TrES network, WATTS significantly increases the efficiency of the survey when data are combined. 1. INTRODUCTION The observation of HD , the first transiting extrasolar planet, discovered by spectroscopic observations (Charbonneau et al. 2000; Henry et al. 2000), demonstrated the feasibility of large-scale planet search projects aimed at detecting transits. Shortly thereafter, wide-field surveys came to fruition (Konacki et al. 2003; Alonso et al. 2004), resulting in the first discoveries of extrasolar planets using the transit method. Subsequently, the number of ground-based transit surveys has increased (Bakos et al. 2006; Sahu et al. 2006; Wilson et al. 2006; Burke et al. 2007), accelerating the pace of discovery (Fig. 1). An important factor contributing to the rapid increase in the number of transit surveys is the decline in startup costs and increased availability of research grade components, facilitating implementation of search programs. As a result, transit search systems are now accessible to researchers at small institutions and amateur astronomers. The principal parameter that determines the efficiency of a photometric survey is time coverage. Because daylight and weather limit time coverage at a single site, the conventional means of increasing coverage is to conduct multiseason observations or to use multiple similar systems distributed over an array of longitudes. A network of systems is beneficial for a host of reasons: Overlapping independent observations of transit events provide immediate confirmation. Because weather is typically uncorrelated between sites, weather related down time is minimized. Distributing the systems over a wide range of longitudes improves the detection rate for transits that have periods close to integer multiple of days and increases the time coverage per day. This increases the efficiency of the observing campaign and allows for a greater number of fields to be surveyed. A number of transit search programs take advantage of these benefits (Bakos et al. 2002, 2004; Alonso et al. 2007), and more transit search networks are likely to follow. Ideally, the systems in a network are set up at traditional astronomical locations, that is, high-elevation, dark sky sites. However, in some cases, geography or lack of facilities at remote high-elevation locations may necessitate locating a system at a nontraditional, low-elevation site near a population center. While there are a number of challenges associated with operating a photometric survey at a nontraditional site, a number of benefits are realized by locating a system close to the observer s home institution. One benefit is reducing operating costs by minimizing travel to and from the system. The potential for data collection is greater because observing can be done on marginal nights and system malfunctions can be repaired quickly. The opportunity for student involvement in data collection is greater when the telescope is readily accessible. Finally, the potential for conducting surveys over long periods of time (many years) is greater if the system is close to the observer s institution. Besides extending the parameter space (in terms of transit period) of the transit survey, a number of spin-off projects may be done using long-term photometric data such as producing a complete sample of eclipsing binaries, pulsating stars, asteroids, and comets (Paczyński 2000). A short-term analysis aimed at identifying eclipsing binaries in the TrES data set has been done (Devor et al. 2008). This study includes data spanning durations shorter than 90 days, demonstrating the potential of a long-term photometric survey. 41

2 42 OETIKER ET AL. 30 Active Projects Number of Detections Number Year FIG.1. Number of active transit search projects in 2 yr periods, and number of planets detected by the transit method during each period. Based on data from the Extrasolar Planets Encyclopaedia 1. Because of the possibility that future wide-field photometric surveys will be conducted at nontraditional sites at lower elevations, near population centers, it is useful to explore whether or not such a system is capable of producing the quality of data needed to detect transits. WATTS is the first wide-field planet search survey conducted at a nonstandard location, and its successful implementation demonstrates that as long as a suitable dark site can be found, a productive photometric search for planets may be conducted at low elevation near a large city. 2. SYSTEM DESCRIPTION AND DATA ANALYSIS The WATTS telescope is located at the Sam Houston State University (SHSU) Campus observatory approximately 15 km northeast of Huntsville, Texas. The observatory is at an elevation of 100 m and is bordered by pastureland, a lake, and national forest. As of 2007, the minimum sky brightness was 20.6 magnitudes per square arcsecond in the R band. Despite the high humidity and low elevation of this site, an average of seven clear nights per month have been observed, corresponding to 1=3 of dark sky nights yielding useful data System Hardware The WATTS telescope is designed to be part of the TrES network (Alonso et al. 2004). To facilitate data sharing within 1 FIG. 2. WATTS telescope. The CCD camera and other hardware are mounted to an optical bench plate. The lens on the right is the Canon lens used for wide-field imaging, and the telescope on the left is a Celestron C90 reflector used for precise polar alignment during setup. TrES, it is necessary for each system to image the same field of view and have similar bandpass and magnitude range. Therefore, the WATTS system has been designed to conform with the PSST (Planet Search Survey Telescope) (Dunham et al. 2004), Sleuth (O Donovan et al. 2004), and STARE (STellar Astrophysics & Research on Exoplanets) (Brown & Charbonneau 2000) systems and has incorporated design elements from all three systems. WATTS is assembled primarily from off-theshelf components. The only components customized for the system are the brackets used to stabilize the telescope lens. The WATTS detector is a PI Acton 2 PIXIS2048B thinned, back illuminated CCD with 13.5 μ pixels. The camera is configurable, with 12 gain settings through two output channels. When read through the low-noise channel at 2 MHz, the readnoise is 18e, with a full well of 110; 000e and nonlinearity of 1%. The chip is cooled to 60 C using built-in thermoelectric 2

3 WIDE ANGLE TELESCOPE TRANSIT SEARCH (WATTS) FWHM Temperature FWHM (pixels) T( C) RMS Time (minutes) 28.0 FIG. 3. Focus shift in WATTS system caused by nightly temperature variations. The FWHM is the average of eight stars scattered across the 90 s data images. cooling with water assist. At this operating temperature, the dark current is 1e pixel 1 minute 1. During the summer months, further cooling is achieved using a wall mounted air conditioning unit that cools the air inside the electronics box to 20 C. This unit prevents the computers from overheating and provides a heat sink for the CCD cooling lines. Vibrations from this unit produce no measurable effect on image quality or photometric errors. The telescope mount is a modified 12 inch Meade 3 LX200 GPS telescope. In place of the tube is a inch aluminum optical bench plate mounted to the forks using aluminum 90 brackets (Fig. 2). The optical bench plate is convenient because it has an array of threaded holes that facilitate placement of the optical components and other hardware. All components mounted to the plate, including the brackets, are attached using socket head cap screws. The system is placed in a roll-off structure that is opened and closed by a residential garage door opener. The opener is controlled by computer using ActiveHome Pro 4 software with a universal module. A Canon 5 EF300mm F2.8L camera lens is used for imaging, producing no greater than 50% vignetting in the corners of the images. The image scale of WATTS is 9:7 00 pixel 1 with an FWHM of 1.8 pixels. These parameters are only slightly different from the other systems in TrES and do not significantly reduce data crossover between systems. WATTS utilizes a Bessel R filter for imaging. Because WATTS is at a low-elevation site in a region with high humidity, the telescope is susceptible to dew and frost. This R Magnitude High Alt. Dark Site WATTS Low Alt. Bright Site Low Alt. Dark Site FIG.4. Expected performance of WATTS compared to a similar system at a traditional site and sites with skies slightly brighter and much brighter than WATTS. Sky brightness at a dark site is 21:5 mag arcsec 2. Sky brightness of WATTS is 20:6 mag arcsec 2. Sky brightness at a bright site is 19:5 mag arcsec 2. Low elevation is 100 m, and high elevation is the average elevation of current transit surveys (2500 m). is mitigated by a dew shield and heating element that keeps the air temperature above the lens greater than the dew point. This combination is effective at preventing loss of data from dew and frost buildup. Placing a heat source near the primary increases seeing; however this does not compromise the image quality or photometric precision of the WATTS system because the plate scale of the system is 9:7 00 pixel 1. Unlike most systems, WATTS does not use an autoguider to keep the field centered. Instead, a periodic error correction (PEC) is used to compensate for periodic tracking errors while the system is imaging. Periodic errors are a result of mechanical perturbations in the telescope mount drive system. The maximum period of these errors is equal to the time for one complete rotation of the worm gear in the telescope drive system. For the Meade LX200GPS mount, the cycle is approximately 8 minutes. PEC calibration and corrections are done using features included in the telescope mount operating system. Once calibrated, corrections are made automatically while the telescope is tracking. PEC effectively compensates for short and medium periodic errors but not long-term errors in the tracking rate. Because the exposure times are short (90 s), the long-term errors may be monitored using the data images. Shifts between each data image and a standard reference image are recorded throughout the night and saved in a log file. Whenever the shift becomes greater than a defined threshold, a correction is made by sending a guide signal to the telescope mount. The combination of PEC and long-term guiding allows the WATTS system to

4 44 OETIKER ET AL. TABLE 1 SUMMARY OF WATTS OBSERVATIONS Field N nights N hours Coverage (days) N st (σ 0:01) N cand P % 50 (days) Draco a 3.3 a Andromeda Auriga Ursa Majoris Draco a 3.3 a a Based on combined 2008 and 2009 data. maintain centering to within an average of 0.3 pixels in both right ascension and declination. This centering accuracy has remained stable for more than 1 yr of operation Telescope and Camera Control The WATTS CCD camera is controlled using PI Acton s WinView32 software, along with a FITS file converter supplied by the manufacturer. The imaging software is called from an AutoIt 6 V3 script that is used to control each night s observations. The observing script consists of a loop where the first step is to initiate imaging. After the first image is saved to disk, the script calls a Mathematica program that calculates and saves the fractional shift between the data image and a standard reference image. If the shift is larger than a threshold of 0.4 pixels in right ascension or 0.2 pixels in declination, the script sends a guide correction to the telescope to recenter the field. The next image is taken and the loop continues until the final image, after which the script parks the telescope and closes the dome. Shifts between the latest data image and standard reference image are calculated using Mathematica 7.0 to perform a crosscorrelation between pixel subsections at the centers of the latest data and reference images. The location of the peak of the inverse Fourier transform of the cross-correlation equals the integer shift between the two images. The fractional shift is calculated by fitting a Gaussian function to the inverse transform of the cross-correlation. The location of the peak in the Gaussian function is the fractional shift (Koekemoer et al. 2002). The telescope is controlled using ScopeDriver via an RS232 connection between the computer and telescope. This software is capable of pointing the telescope by coordinates or from a user-defined list of objects. Tracking rate, focus adjustment, and telescope park commands are also issued through ScopeDriver 3.2. All of these controls may be done manually or by the AutoIt scripting software. With the current configuration, the telescope has a pointing accuracy of 5 pixels in right ascension and declination The WATTS system is focused manually at the beginning of the night by sending commands to the focusing motor though ScopeDriver 3.2. The best focus is found by averaging the FWHM of eight bright stars distributed across a series of 5 s exposures. The system is then defocused slightly from best focus to accommodate focus drift as the temperature changes during the night. The amount of defocusing is estimated by the forecast change in temperature for that night. For a typical night, starting 0.2 pixels FWHM out of focus allows the system to drift into focus and remain focused for the duration of the night (Fig. 3). This procedure does not always produce data with consistent focus drift. However, these effects are corrected by the Difference Image Analysis (DIA) data pipeline described subsequently Data Processing and Analysis Data analysis for WATTS is an implementation of the Difference Image Analysis (DIA) package described in Dunham et al. (2004). DIA is a robust data analysis and photometry pipeline that compensates for point spread function (PSF) variations resulting from focus drift and subpixel image drift. Interpolation and image subtraction are performed using ISIS (Alard 2000; Alard & Lupton 1998) on a Linux-based PC with four processors. Much of the photometry generated by DIA is highly correlated as a result of atmospheric effects such as air mass and cloud cover and small telescope motions in position and focus. These errors are minimized using an Interactive Data Language (IDL 10 ) decorrelation routine that removes the correlation by regressing each star s light curve against the light curves of other stars in the sample (Dunham et al. 2004). 3. LOW-ELEVATION OBSERVING 3.1. Atmospheric Effects: Scintillation and Sky Brightness Two major concerns when making photometric measurements at a low-elevation site near a population center are increased errors associated with scintillation and sky brightness. Scintillation noise is estimated using the low-frequency

5 WIDE ANGLE TELESCOPE TRANSIT SEARCH (WATTS) 45 Fraction Recovered Fraction Recovered Fraction Recovered Days Days Days FIG.5. Comparing the performance of WATTS and PSST for a field in Auriga observed for 81 days. Top, the WATTS system; middle, PSST; bottom, both systems combined. component of scintillation (Young 1967). Because of the relatively small aperture of WATTS, one expects greater scintillation noise, possibly including higher-frequency effects. However, the low-frequency component dominates as long as the integration time is longer than the timescale for flying shadows to cross the telescope aperture (Dravins et al. 1998). For the 0.1 m aperture of WATTS, the corresponding timescale of 30 s is shorter than the 90 s exposures for the WATTS data images. For a given system, scintillation is primarily affected by elevation: σ 100 m σ 2500 m ¼ e ðh 100 m h 2500 m Þ=h o: (1) In the case of WATTS (elevation ¼ 100 m) compared to the average elevation of current photometric planet searches (2500 m), and a scale height of 8000 m, scintillation noise increases by 35%. For a 90 s exposure on the WATTS system, the expected scintillation noise is 3 magnitudes (Fig. 4). Because the noise of fainter stars in the sample is dominated by sky noise, increasing the scintillation noise does not significantly reduce the number of stars in the sample with rms scatter below 1%. Rather, the effect of larger scintillation noise is to increase the rms noise of all stars in the field, making it more difficult to observe extremely low-amplitude variability. Increased sky brightness is a more significant contributor to photometric noise (Fig. 4), especially for the fainter stars in the sample. For a dark observing site with a sky brightness of 21:5 mag arcsec 2, an expected rms error of 1% corresponds to a star with an R magnitude of At a site with a moderately dark sky of 20:5 mag arcsec 2, the magnitude drops to The bright sky site (19:5 mag arcsec 2 ), has an R magnitude limit of 11.6 corresponding to an expected rms error of 1%. To explore the effect this has on the observable sample size, consider a crowded field at a dark site that has 5000 stars with rms error less than 1%. The same field observed at a moderately dark sky site has 3845 stars with rms error less than 1%, whereas a bright sky site has 2646 stars with rms error less than 1%. Therefore, it is critical to choose a site with the darkest sky possible when conducting a wide-field photometric survey for extrasolar planets in order to maximize the number of low-noise light curves in the sample. WATTS is located at a moderately dark site with a sky brightness of 20:6 mag arcsec Effects of Weather The effects of weather are a consideration for any groundbased transit survey. While the DIA pipeline is capable of correcting the effects of relatively thin clouds, thicker clouds render some nights unusable, limiting the time coverage and efficiency of the survey. Because WATTS is located at a low-elevation site with high humidity, it is expected to experience more cloudy nights than a dry high-elevation site. Thus, fewer data are expected to be collected at this site. Preliminary results from the first 14 months of operation, including observations of four fields in five campaigns (Table 1), may be used for a quantitative analysis. The average number of hours observed per field by WATTS is 152 hrs, compared to an average of 203 hrs for the STARE system over a 3 yr period (Alonso et al. 2004). However, during the winter months when the weather is clearer at the WATTS site, the system averages 192 hrs per field, which is comparable to the STARE average. Thus, even though it is located at a nontraditional site, during seasons with good weather WATTS has the potential to produce nearly the same volume of data as a system experiencing average weather at a traditional astronomical site. The impact of weather on time coverage and system efficiency may be studied by comparing WATTS to PSST. This comparison is meaningful because both systems observed the same fields during the same observing campaigns. System efficiency is defined to be the detection rate for that system to observe three transit events of a given period. The detection rate is calculated using the time coverage for an entire observing campaign and a set of randomly distributed (in phase) transit events (Alonso et al. 2007). For observations of a field in Auriga, PSST observed 290 hrs over 38 days while WATTS observed 194 hrs over 27 days. The efficiency of WATTS (Fig. 5) is somewhat less than that of PSST in that the recovery rate for detecting three transits with a period of 4 days is 25% for WATTS compared to 50% for PSST. During a subsequent

6 46 OETIKER ET AL. weather on a transit survey can have a significant negative impact on a stand-alone system. However, even a system in a location with less than ideal weather significantly improves the detection rates of a network of systems. FIG.6. Plot of rms scatter for unbinned decorrelated light curves for Auriga field. The lines correspond to theoretical noise sources for the WATTS system. campaign, a field in Ursa Major was observed by PSST for 216 hrs over 33 days and 190 hrs over 27 days by WATTS. Because the two systems had similar time coverage on this field, the performance is similar: both have a recovery rate of 25% for observing three transits with a period of 4 days. Although the data are preliminary, there is an indication that systems at dry high-elevation sites are less limited by poor weather than lowelevation systems like WATTS. However, during the winter months when the weather is favorable at the WATTS site, the low-elevation system can operate at an efficiency comparable to the high-elevation sites. The tangible benefit of the WATTS system is realized when data generated by WATTS are combined with data from the other systems in TrES. Recovery rates for detecting three transits with a 4 day period jump to 90% for the Auriga field and 80% for the Ursa Majoris field. It is clear that the effects of m m - - Aur1_891 Aur1_4214 P=2.9091d P=1.9275d FIG. 7. Two eclipsing binaries in a field in Auriga. 4. SYSTEM PERFORMANCE Figure 6 is a plot of the rms scatter of decorrelated data versus apparent magnitude for stars brighter than R ¼ 14:5 in a field in Auriga. Also included on the plot are the estimated contributions of important sources of noise in the system. The fainter stars in the sample have rms values very close to those predicted by the theoretical noise estimates. The brighter stars have rms values approximately 1 magnitudes greater than the theoretical noise. This effect is also observed by the PSST system and may be a result of tracking errors or underestimating scintillation noise, as discussed in Dunham et al. (2004). Another explanation for this unexpected noise may be so-called pink noise (Pont et al. 2007), which is a combination of uncorrelated white noise and low-amplitude strongly correlated red noise that varies on timescales comparable to transits. If this error is not completely corrected, its contribution will be evident in the rms of the brightest stars in the sample because they have the smallest theoretical errors. Despite the slightly increased noise in the brighter stars, a significant number of light curves have noise less than 1% rms. As demonstrated by Figure 6, WATTS, using the DIA pipeline, is capable of routinely achieving the photometric precision needed to conduct a productive giant planet transit survey at its current low-elevation location. During the first 14 months of operation, four fields were observed in five campaigns. In the 374 days of operation 108 nights were clear, producing a total of 739 hrs of data. A total of 138,467 stars were observed, with 21,723 of them having photometric rms below 1%. Twenty light curves with transitlike features were identified by WATTS observations alone. Of these candidates, 16 have been ruled out by follow-up work, and the remaining 4 are currently being evaluated. Candidate light curves are evaluated first by careful inspection of the nonphased data to identify obvious eclipsing binaries. A catalog search is also done to determine if the star is an eclipsing binary, variable, giant, or if there are any nearby bright variables within a radius of 10 (the image scale of WATTS observations) of the central star. Any stars not rejected by this initial inspection undergo follow-up observations, including high-spatial resolution photometry to resolve possible blends of eclipsing binaries with background stars less than 10 from the central star (Mandushev et al. 2007). Multicolor photometry identifies stars that are too hot to be viable candidates for planetary transits. Stars that pass follow-up photometric evaluation are then observed using lowresolution spectroscopy and then high-resolution spectroscopy if necessary (Rauer & Erikson 2007). A few light curves have been selected to show the capability of the WATTS system. Figure 7 shows two eclipsing binaries in Auriga observed by WATTS. The interesting features of these

7 WIDE ANGLE TELESCOPE TRANSIT SEARCH (WATTS) 47 Aur1_2378 And3_ P=1.9543d - P= d m m Aur1_3974 D ra1_394 - P=2.3017d - P= d m m FIG. 8. Light curves with transitlike features in Auriga. plots are the secondary eclipses, both of which have amplitudes similar to what would be produced by a transiting extrasolar planet. Figure 8 shows two light curves of stars in Auriga that were candidates because they have transitlike features that repeated three times or more. The star given identifier 2378 is a feature that has a period of 1.95 days, a depth of 8 mag, while the star given identifier 3974 has a period of 2.30 days, a depth of mag. A close inspection of the light curve of star 3974 revealed the star to be an eclipsing binary with primary and secondary eclipses of nearly equal depth. A phase plot using half of the actual period produces a light curve that looks very much like a transit. Star 2378 was ruled out using lowresolution spectroscopic observations that revealed the star to be an unresolved multiple system. Observations of a field in Andromeda produced a number of interesting candidates, of which the most interesting is star (Fig. 9a), which has a transitlike feature with a period of 1.31 days, a depth of 9 mag. Even though this star is one of the fainter stars in the sample (R ¼ 13:041) and has larger rms scatter, a low-amplitude periodic feature is observed in the light curve. Close inspection of the light curve revealed this star to be an eclipsing binary with unequal primary and secondary eclipses. The field in Draco produced four candidates, one of which is shown in Figure 9b. The transitlike feature in the light curve of star 394 in Draco has a very low amplitude (4 mmag) and is present in data covering two seasons. The field in Ursa Major contained fewer suitable stars, resulting in no candidates. FIG. 9. Top: A transitlike feature in a light curve of a fainter star in Andromeda. Bottom: A low-amplitude transitlike feature in light curve of a star in Draco. 5. CONCLUSION WATTS is a low-elevation component of the TrES network. Even though it is located at a nontraditional site, WATTS is capable of achieving the photometric precision needed to detect transiting giant extrasolar planets as demonstrated in five observing campaigns. While the efficiency of WATTS as a stand-alone system is highly dependent on the weather, when combined with other systems in the network, WATTS significantly improves the detection efficiency of the network. Benefits of increased efficiency include overlapping observations that provide confirmation of candidate transit events, greater sensitivity to transits with periods close to integer multiple of days, extending the range of transit periods that can be detected, and the potential to survey a greater number of fields. In the first year of operation, a number of candidates have been identified by WATTS, the majority of which have been found to be lowamplitude eclipsing binaries, variable stars, and blends. Research was supported by NASA subcontract of NASA grant NNX08AF24G under the auspices of the NASA Origins of the Solar System Program and by the Sam Houston State University Faculty Research Grant. Thanks to Candice Withrow for assisting with setting up the DIA pipeline and Travis Neeley for assisting with observations. Thanks to David Charbonneau provided the routine for calculating transit recovery rates. REFERENCES Alard, C. 2000, A&AS, 144, 363 Alard, C., & Lupton, R. H. 1998, ApJ, 503, 325 Alonso, R., Deeg, H. J., Brown, T. M., & Belmonte, J. A. 2004, Astron. Nachr., 325, 594 Alonso, R., et al. 2004, ApJ, 613, L , Transiting Extrapolar Planets Workshop, 366, 13 Bakos, G. Á., Lázár, J., Papp, I., Sári, P., & Green, E. M. 2002, PASP, 114, 974 Bakos, G. Á., Pál, A., Latham, D. W., Noyes, R. W., & Stefanik, R. P. 2006, ApJ, 641, L 57

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