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Register a new userA New Method For Robust High-Precision Time-Series Photometry From Well-Sampled Images: Application to Archival MMT/Megacam Observations of the Open Cluster M37
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We introduce new methods for robust high-precision photometry from well-sampled images of a non-crowded field with a strongly varying point-spread function. For this work, we used archival imaging data of the open cluster M37 taken by MMT 6.5m telescope. We find that the archival light curves from the original image subtraction procedure exhibit many unusual outliers, and more than 20% of data get rejected by the simple filtering algorithm adopted by early analysis. In order to achieve better photometric precisions and also to utilize all available data, the entire imaging database was re-analyzed with our time-series photometry technique (Multi-aperture Indexing Photometry) and a set of sophisticated calibration procedures. The merit of this approach is as follows: we find an optimal aperture for each star with a maximum signal-to-noise ratio, and also treat peculiar situations where photometry returns misleading information with more optimal photometric index. We also adopt photometric de-trending based on a hierarchical clustering method, which is a very useful tool in removing systematics from light curves. Our method removes systematic variations that are shared by light curves of nearby stars, while true variabilities are preserved. Consequently, our method utilizes nearly 100% of available data and reduce the rms scatter several times smaller than archival light curves for brighter stars. This new data set gives a rare opportunity to explore different types of variability of short (~minutes) and long (~1 month) time scales in open cluster stars.
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We have conducted a deep ($15 la r la 23$), 20 night survey for transiting planets in the intermediate age open cluster M37 (NGC 2099) using the Megacam wide-field mosaic CCD camera on the 6.5m Multiple Mirror Telescope (MMT). In this paper we describe the observations and data reduction procedures for the survey and analyze the stellar content and dynamical state of the cluster. By combining high resolution spectroscopy with existing $BVI_{C}K_{S}$ and new $gri$ color magnitude diagrams we determine the fundamental cluster parameters: $t = 485 pm 28$ Myr without overshooting ($t = 550 pm 30 {rm Myr}$ with overshooting), $E(B-V) = 0.227 pm 0.038$, $(m-M)_{V} = 11.57 pm 0.13$ and $[M/H] = +0.045 pm 0.044$ which are in good agreement with, though more precise than, previous measurements. We determine the mass function down to $0.3 M_{odot}$ and use this to estimate the total cluster mass of $3640 pm 170 M_{odot}$.
We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modeled with a simple power-law power spectral density. This implementation builds on published methods, we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.
In the course of conducting a deep (14.5 ~< r ~< 23), 20 night survey for transiting planets in the rich ~550 Myr old open cluster M37 we have measured the rotation periods of 575 stars which lie near the cluster main sequence, with masses 0.2 Msun ~< M ~< 1.3 Msun. This is the largest sample of rotation periods for a cluster older than 500 Myr. Using this rich sample we investigate a number of relations between rotation period, color and the amplitude of photometric variability. Stars with M >~ 0.8 Msun show a tight correlation between period and mass with heavier stars rotating more rapidly. There is a group of 4 stars with P > 15 days that fall well above this relation, which, if real, would present a significant challenge to theories of stellar angular momentum evolution. Below 0.8 Msun the stars continue to follow the period-mass correlation but with a broad tail of rapid rotators that expands to shorter periods with decreasing mass. We combine these results with observations of other open clusters to test the standard theory of lower-main sequence stellar angular momentum evolution. We find that the model reproduces the observations for solar mass stars, but discrepancies are apparent for stars with 0.6 ~< M ~< 1.0 Msun. We also find that for late-K through early-M dwarf stars in this cluster rapid rotators tend to be bluer than slow rotators in B-V but redder than slow rotators in V-I_{C}. This result supports the hypothesis that the significant discrepancy between the observed and predicted temperatures and radii of low-mass main sequence stars is due to stellar activity.
We present a comprehensive re-analysis of stellar photometric variability in the field of the open cluster M37 following the application of a new photometry and de-trending method to MMT/Megacam image archive. This new analysis allows a rare opportunity to explore photometric variability over a broad range of time-scales, from minutes to a month. The intent of this work is to examine the entire sample of over 30,000 objects for periodic, aperiodic, and sporadic behaviors in their light curves. We show a modified version of the fast $chi^{2}$ periodogram algorithm (F$chi^{2}$) and change-point analysis (CPA) as tools for detecting and assessing the significance of periodic and non-periodic variations. The benefits of our new photometry and analysis methods are evident. A total of 2306 stars exhibit convincing variations that are induced by flares, pulsations, eclipses, starspots, and unknown causes in some cases. This represents a 60% increase in the number of variables known in this field. Moreover, 30 of the previously identified variables are found to be false positives resulting from time-dependent systematic effects. New catalog includes 61 eclipsing binary systems, 92 multiperiodic variable stars, 132 aperiodic variables, and 436 flare stars, as well as several hundreds of rotating variables. Based on extended and improved catalog of variables, we investigate the basic properties (e.g., period, amplitude, type) of all variables. The catalog can be accessed through the web interface (http://stardb.yonsei.ac.kr/).
The primary task of the 1.26-m telescope jointly operated by the National Astronomical Observatory and Guangzhou University is photometric observations of the g, r, and i bands. A data processing pipeline system was set up with mature software packages, such as IRAF, SExtractor, and SCAMP, to process approximately 5 GB of observational data automatically every day. However, the success ratio was significantly reduced when processing blurred images owing to telescope tracking error; this, in turn, significantly constrained the output of the telescope. We propose a robust automated photometric pipeline (RAPP) software that can correctly process blurred images. Two key techniques are presented in detail: blurred star enhancement and robust image matching. A series of tests proved that RAPP not only achieves a photometric success ratio and precision comparable to those of IRAF but also significantly reduces the data processing load and improves the efficiency.
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