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Photographic plate archives contain a wealth of information about positions and brightness celestial objects had decades ago. Plate digitization is necessary to make this information accessible, but extracting it is a technical challenge. We develop algorithms used to extract photometry with the accuracy of better than ~0.1m in the magnitude range 130.2m) variable stars. The algorithms are implemented in the free software VaST available at http://scan.sai.msu.ru/vast/, Comment: 4 pages, 3 figures; proceedings of the IAU Symposium 339 Southern Horizons in Time-Domain Astronomy, 13-17 November 2017, Stellenbosch, South Africa

The new stage of work on digitizing the astronomical plates of the Sternberg Astronomical Institute’s collection and searching for new variable stars using the digitized photographic plates includes a considerable improvement of the automated search techniques for objects with variable brightnesses. In particular, the technique for taking into account the non-linear response of the photographic light detector has been improved. Applying the improved techniques to 182 digitized images of a 10° × 10° field centered at SA9, obtained from scanning photographic plates taken with the Sternberg Astronomical Institute 40-cm astrograph, has enabled the discover and study of 77 new variable stars (MDV 519–595). These include 3 Cepheids, 2 probable BY Draconis stars, 65 eclipsing binaries, 3RR Lyrae stars, 1 high-amplitude δ Scuti star (HADS), and 3 irregular variables. Special CCD observations have confirmed the presence of brightness variations in 7 of the 77 variables that were initially considered uncertain.

Photometric measurements are prone to systematic errors presenting a challenge to low-amplitude variability detection. In search for a general-purpose variability detection technique able to recover a broad range of variability types including currently unknown ones, we test 18 statistical characteristics quantifying scatter and/or correlation between brightness measurements. We compare their performance in identifying variable objects in seven time series data sets obtained with telescopes ranging in size from a telephoto lens to 1m-class and probing variability on time-scales from minutes to decades. The test data sets together include lightcurves of 127539 objects, among them 1251 variable stars of various types and represent a range of observing conditions often found in ground-based variability surveys. The real data are complemented by simulations. We propose a combination of two indices that together recover a broad range of variability types from photometric data characterized by a wide variety of sampling patterns, photometric accuracies, and percentages of outlier measurements. The first index is the interquartile range (IQR) of magnitude measurements, sensitive to variability irrespective of a time-scale and resistant to outliers. It can be complemented by the ratio of the lightcurve variance to the mean square successive difference, 1/h, which is efficient in detecting variability on time-scales longer than the typical time interval between observations. Variable objects have larger 1/h and/or IQR values than non-variable objects of similar brightness. Another approach to variability detection is to combine many variability indices using principal component analysis. We present 124 previously unknown variable stars found in the test data., Comment: 29 pages, 8 figures, 7 tables; accepted to MNRAS; for additional plots, see http://scan.sai.msu.ru/~kirx/var_idx_paper/