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Survey for Transiting Extrasolar Planets in Stellar Systems The Astronomical Journal, 132:1177Y1188, 2006 September A # 2006. The American Astronomical Society. All rights reserved. Printed in U.S.A. SURVEY FOR TRANSITING EXTRASOLAR PLANETS IN STELLAR SYSTEMS. IV. VARIABLES IN THE FIELD OF NGC 1245 Joshua Pepper and Christopher J. Burke Department of Astronomy, Ohio State University, Columbus, OH 43210; [email protected], [email protected] Received 2006 April 4; accepted 2006 May 9 ABSTRACT The Survey for Transiting Extrasolar Planets in Stellar Systems (STEPSS) project is a search for planetary transits in open clusters. In this paper we analyze the STEPSS observations of the open cluster NGC 1245 to determine the variable-star content of the cluster. Out of 6787 stars observed with V < 22, of which 870 are cluster members, we find 14 stars with clear intrinsic variability that are potential cluster members and 29 clear variables that are not cluster members. None of these variables have been previously identified. We present light curves, finder charts, and stellar/ photometric data on these variable objects. Several of the interacting binaries have estimated distances consistent with the cluster distance determined from isochrone fits to the color-magnitude diagram. Four stars at the main-sequence turnoff of the cluster have light curves consistent with Doradus variability. If these Doradus candidates are con- firmed, they represent the oldest and coolest members of this class of variable discovered to date. Key words: binaries: general — stars: variables: other — surveys — techniques: photometric Online material: extended figure sets 1. INTRODUCTION The STEPSS project observed NGC 1245 over the course of 19 nights in 2001 October and November. The observations were The dramatic increase in the number of surveys for plane- obtained with the MDM 8K mosaic imager on the MDM 2.4 m tary transits over the last 5 years has resulted in a wealth of high- Hiltner telescope, yielding a 260 ; 260 field of view with 0B36 res- precision stellar photometry (Horne 2003). Although primarily olution per pixel. In total, the data set consists of 936 I-band im- conducted to detect planetary transits, such surveys also produce ages, with typical exposure times of 300 s. For the color-magnitude data sets that allow for intensive investigation of stellar variabil- diagram (CMD), several supplementary B- and V-band images ity. Especially useful are surveys of clusters, which can be used were also obtained. None of the nights were photometric, and so to characterize the variability content of the cluster. Detections a second series of observations was taken in 2002 February to of eclipsing binaries can provide a check on the cluster’s dis- tance, as well as helping to characterize the mass-radius and mass- calibrate the cluster photometry. luminosity relationships. Many surveys of clusters have already published data sets 3. LIGHT CURVES AND STELLAR PROPERTIES of high-precision photometry, finding low-amplitude variables, We follow the procedure outlined in Burke et al. (2005) to eclipsing binaries, and other pulsating stars. The Planets in Stel- generate light curves, which develops a new method for differen- lar Clusters Extensive Search project has observed clusters NGC tial photometry given the demands of detecting transiting extra- 2158 and NGC 6791 (Mochejska et al. 2002, 2004, 2005). The solar planets (<0.01 mag precision). The main features of the Extrasolar Planet Occultation Research/Open Clusters project has method include allowing each star to have a unique comparison observed clusters NGC 2660 and NGC 6208 (von Braun et al. ensemble, minimization of the light-curve standard deviation as 2005). Other projects have observed or are observing NGC 7789, a figure of merit, and full automation. Applying this method yields 6819, and 6940 (Street et al. 2003; Bramich et al. 2005), NGC light curves that have precision to less than 1% for V < 18. 6633 (Hidas et al. 2005), and NGC 6705 (Hargis et al. 2004). Of the 6787 stars identified in the survey’s field of view, we The Survey for Transiting Extrasolar Planets in Stellar Sys- estimate that 870 belong to the cluster. This estimate comes tems (STEPSS; Burke et al. 2002) concentrates on searching open from scaling and subtracting star counts from a control field on clusters for planetary transits. Searching for transits in clusters is the outskirts of our field of view. Figure 1 shows the (V, B À V ) advantageous, since cluster members have similar metallicities CMD of the cluster field along with the best-fit isochrone from and ages and are therefore good laboratories for determining the Burke et al. (2004), derived from the theoretical isochrones of Yi distribution of planets without varying those measurable prop- et al. (2001). The CMD shown here uses the data from which the erties. Here we present an analysis of the observations of NGC light curves were derived, while a different data set that avoided 1245 to catalog the stellar variables in the cluster. saturation on the brighter stars was used to determine cluster properties such as the turnoff point. 2. CLUSTER PARAMETERS AND OBSERVATIONS Given the cluster age, metallicity, distance, and reddening, the See Burke et al. (2004) for a full discussion of the parame- best-fit isochrone transforms an observed apparent magnitude ters of the cluster. NGC 1245 is a rich open cluster with an age into the stellar properties, assuming the star is a cluster member. of 1:04 Æ 0:09 Gyr. It has a metallicity slightly less than solar, Using the stellar mass as the independent variable, we determine [Fe/H] ¼0:05 Æ 0:08. The cluster is at a distance of 2:8 Æ the stellar mass that minimizes the 2 distance between the ap- 0:2 kpc, with a distance modulus of (m À M )0 ¼ 12:27 Æ 0:12. parent magnitude and the best-fit isochrone magnitudes in the The core radius is rc ¼ 3A10 Æ 0A52 (2:57 Æ 0:43 pc). The total BVI passbands. cluster mass is M ¼ 2700 Æ 600 M . All errors given above are A caveat for assigning stellar properties based on the CMD is systematic and are larger than the statistical errors. the assumption that the detected stellar light arises from a single 1177 1178 PEPPER & BURKE Vol. 132 less stringent cut with higher sensitivity contains lower ampli- tude variables but also contains <7% false positives, which are later eliminated through visual inspection. 4.1. Eliminating Outlying Points The first stage of the analysis removes statistically outlying photometric measurements. Outliers are identified in the follow- ing manner: For each star we calculate the reduced 2 light-curve variability, Xn 2 1 (m À ) 2 ¼ k ; ð1Þ n 1 2 À k¼1 k where the sum is over n observations, with magnitude mk ,wither- ror k,and is the weighted average magnitude of the light curve, P n À2 Pk¼1 mk k ¼ n À2 : ð2Þ k¼1 k The 2 statistic measures the degree to which a constant light- Fig. 1.—(V, B À V ) CMD for NGC 1245. The best-fit isochrone to the clus- ter main sequence is shown with a solid line. Filled symbols represent cluster curve model approximates the light-curve data within the context variables, while open symbols represent field variables. The triangles show of the measurement errors. Light curves with intrinsic variabil- binary variables (see x 5.1), the circles show Doradus candidates (see x 5.2), ity result in high 2 values, denoting that a constant light-curve and the squares represent unclassified variables. model poorly represents the data. Before eliminating outlying 0 2 2 2 measurements we scale the errors by setting k ¼ k , thus main-sequence cluster member. The stellar properties contain enforcing 2 ¼ 1. The error scaling allows the Gaussian noise, significant systematic errors if the object does not belong to the systematic error, or intrinsic variability (whichever noise source cluster or if a portion of the stellar light arises from an unresolved dominates the scatter in the light curve) to set the scale for judg- stellar companion. The physical properties for the variable sources ing whether a measurement is a statistical outlier. This procedure detected in this study should be regarded with extra caution, con- can eliminate intrinsic variability that affects a small number sidering that most sources of variability result from the binary of the measurements. This hampers our ability to detect large- nature of an object (Sterken & Jaschek 1996) and thus have a amplitude eclipsing binaries when only a single eclipse occurred large probability for significant stellar companion contamination. during the observations. However, given our quantitative selec- 4. VARIABLE-STAR SELECTION tion criteria and documented analysis techniques, these biases can easily be accounted for with a more detailed inspection of the One of the great challenges in determining variability with data. high-precision photometry is the difficulty of distinguishing in- For each observation, we compute the deviation, k ¼jmk À 0 trinsic variability from noise and systematic errors. Common j/k . All photometric measurements with k > 3 are eliminated. classes of variable stars demonstrate both large amplitude var- We perform three iterations of the above procedure for each light iations and periodic behavior, making them both easily detected curve. The light curves with <750 measurements remaining and easily characterized. However, with the advent of surveys typically result from false stellar detections near the cores of that observe thousands of stars with millimagnitude photometry, bright isolated stars and are discarded. We also eliminate light robustly detecting variations at low noise levels requires a variety curves with rms < 0:3 mag, since no light curves with higher of statistical selection criteria. Some surveys, such as the All Sky scatter show any kind of coherent intrinsic variability.
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