Peremennye Zvezdy (Variable Stars) 27, No. 2, 2007 Received 2 December; accepted 20 March.

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Variable Stars in NSVS Database I. 86 New Variables in Andromeda

D. Dimitrov, V. Popov

Institute of Astronomy, Bulgarian Academy of Sciences, Sofia, Bulgaria
E-mail: dinko@astro.bas.bg, vaspop@mail.bg

1. Introduction

One of the most extensive sky surveys in the recent years is the Northern Sky Variability Survey (NSVS, Wozniak et al., 2004a). Light curves of about 14000000 objects with instrumental magnitudes between 8 and 15.5 are included in the database of that survey, for the period April 1999 - March 2000, covering all of the Northern hemisphere and reaching in the South.

Usually, search for new variables follows a standard procedure: a sample of stars from other sources (IR, X-ray surveys) is selected by some characteristics and then this selection is checked for variability in the NSVS database. This procedure does not reflect the whole variety of variable stars in the NSVS.

Several studies based on NSVS data have been published. Preliminary results of ROTSE-I (Akerlof et al., 2000) identified 1781 periodic variables of different types. The catalogue of red variables (Wozniak et al., 2004b) contains the greatest number so far: 8678 variable stars, 6474 of them newly discovered. Kinemuchi et al. (2006) studied 1188 RR Lyr stars, Wils, Lloyd and Bernhard (2006) identified 785 variables of the same type. The catalogue of Gettel et al. (2006) contains 1022 contact binaries. Otero et al. (2004, 2005a, 2005b, 2006a, 2006b) give information about new eclipsing variables from the NSVS. The NSVS database is also used for confirmation and determination of parameters of the objects from the GCVS and NSV catalogues (Kazarovets et al., 2005; Antipin et al., 2005).

Akerlof et al. (2000) estimate the total number of variables to be discovered using the NSVS as 32000, Samus (2006) gives an estimate of tens of thousands expected variables. One of the aims of our research is to estimate the total number of variables which can be extracted from the NSVS database.

2. Search area

As mentioned above, the search procedure adopted to create earlier catalogues makes use of data external to the NSVS to preselect variability candidates.

To look for different types of variables, we rely only upon internal NSVS data. We select an area on the sky and check for variability in the NSVS database. Our test area covers 46 deg in Andromeda, its coordinates are: 23 and (2000.0). The galactic latitude is in the range. The total number of NSVS light curves in this area is and every star has between 1 and 4 light curves, the mean value being 1.875 light curves per star. Our search is based on the variability parameter :

where is the scatter of measurements in the light curve and is the median value of the error of a single measurement. Both values are present in the on-line distribution of NSVS data in Sky Database for Objects in Time-Domain - the SkyDOT pages.

There are light curves in the selected field with , at which we cut off our manual examination. As our detection threshold, we accepted the amplitude for long-period or irregular variability and the amplitude plus the period for periodic variables.

Period analysis was performed with the PERANSO code (http://www.peranso.com) by the ANOVA method, most suitable for light curves with two minima. Table 1 summarizes the data for detected variables. Its first column presents ordinal numbers of variables detected in our search, the next two columns are identification numbers of the variables' light curves in the NSVS and the variability parameter of the respective light curves.

3. Results

Examination of all light curves revealed curves with variability, corresponding to variable stars (Table 2). In Table 2, the first column presents the number of the star from Table 1. We identified the variables with the Tycho/Tycho2 (for brighter stars) or USNO B1.0 (for fainter stars) catalogues, the identifications are presented in the second column. Coordinates from the 2MASS catalogue (USNO coordinates, if the 2MASS identification is not reliable) are in the third and fourth columns. As a consequence of low angular resolution of the observations in the NSVS database ( per pixel), some of the objects are blended and this makes it difficult to exactly determine to which star a certain light curve belongs. In such cases, NSVS coordinates may be considerably different from 2MASS coordinates. Next columns contain the instrumental stellar magnitude in maximum , the amplitude of variations in the light curve, the period , and the variability type. The NSVS data do not allow a detailed classification of the GCVS level of detail, so we adopted the somewhat simplified classification of Akerlof et al. (2000) and Wozniak et al. (2004b). The last column contains star names from the GCVS, NVS catalogues and those from Wozniak et al. (2004b) if they exist. A star number in column 1 marked with an asterisk refers to additional remarks following the Table.

Variables revealed in our search are distributed as follows:

• Variability of the light curves is detected for 28 of the total of 56 already known GCVS variables in the field. There are also 2 other stars from the GCVS, which show variability of their NSVS light curves, but their variation amplitudes are within measurement errors. The remaining 26 GCVS variables are too bright and have saturated images, making photometry impossible.
• There are 32 suspected variables in the field, according to the NSV catalogue, but only 3 of them show variability in the NSVS light curves. Additional 11 NSV stars have NSVS light curves without apparent variability. The remaining 18 NSV stars are either too bright for photometry or their type of variability cannot be derived from the NSVS set of observations.
• The Catalogue of Wozniak et al. contains 21 stars belonging to our field and 13 of them are new variables.
• For 4 of the variables, there is unpublished information in the on-line VSX database (http://www.aavso.org/vsx). One more variable is present in Dahlmark (1999), and there is also information about another star in the catalogue of Gettel et al. (2006).
• For 86 of 136 variables detected in our search, there are no previous publications or any information in ADS or SIMBAD and they may be regarded as new variable stars. This number includes: 52 variables of irregular or semiregular types, 24 eclipsing binaries, and 10 periodic variables of different types.

The light curves of new variable stars are presented in Fig. 1 (irregular or semiregular variables), Fig. 2 (eclipsing binaries), and Fig. 3 (other periodic variables).

4. Analysis

We subdivide all the light curves into 19 subsets for different ranges of (Table 3). The first column of Table 3 contains the range for the subset. The next column is the number of light curves, , belonging to the subset. Columns 3 and 4 contain the cumulative number of light curves, , and . The number of light curves with variability, , cumulative number, , and its logarithm, , are presented in the next three columns. The last column shows the predicted number of light curves with variability, , for the respective subset. The data from Table 3 are graphically presented in Fig. 4, as the function:

Diamonds in Fig. 4 represent data for subsets with . Some of the light curves of variable stars with multiple light curves have , such data are displayed as crosses.The relation (2) for lower values of can be linearly approximated as:

Its extrapolation to gives an estimate for the expected number of light curves with variability in the selected field. Thus, the predicted total number of curves with detectable variability is . This number correspond to variable stars, i.e. 23 variables can be detected if the search covers the rest of the range. Thus, the concentration of variables per light curve in the field appears to be:

If we assume this approximation to be valid for all NSVS data, and the concentration to be uniform for the survey, then an estimate of the total number of variable stars can be made. There are about light curves in the NSVS, and the total number of variable stars that can be expected to be extracted from the survey is:

If we take into consideration only really detected variables, i.e. , then , and this number corresponds to the total number of variables , which may be considered a lower limit to the total number of variables detectable in the NSVS.

Acknowledgements

This publication makes use of the data from the Northern Sky Variability Survey created jointly by the Los Alamos National Laboratory and University of Michigan. The NSVS was funded by the Department of Energy, the National Aeronautics and Space Administration, and the National Science Foundation. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This research also has made use of the SIMBAD database, operated at CDS, Strasbourg, France, NASA's Astrophysics Data System Abstract Service, and the USNOFS Image and Catalogue Archive operated by the United States Naval Observatory, Flagstaff Station (http://www.nofs.navy.mil/data/fchpix/). The authors thank Dr. N. Samus for critically reviewing the manuscript.

References:

Akerlof, C., Amrose, S., Balsano, R., et al. 2000, Astron. J., 119, 1901

Antipin, S., Pastukhova, E., and Samus, N., 2005, IBVS, No. 5613

Dahlmark, L., 1999, IBVS, No. 4734

Gettel, S., Geske, M., and McKay, T., 2006, Astron. J., 131, 621

Kazarovets, E., Pastukhova, E., and Samus, N., 2005, PZ, 25, 2

Kazarovets, E., Samus, N., Durlevich, O. et al., 2006, IBVS, No. 5721

Khruslov, 2005, PZS, 5, 6

Kinemuchi, K., Smith, H., Wozniak, P., and McKay, T., 2006, Astron. J., 132, 1202

Otero, S., Hoogeveen, G., and Wils, P., 2006a, IBVS, No. 5674

Otero, S., and Wils, P., 2005a, IBVS, No. 5630

Otero, S., Wils, P., and Dubovsky, P., 2004, IBVS, No. 5570

Otero, S., Wils, P., and Dubovsky, P., 2005b, IBVS, No. 5586

Otero, S., Wils, P., Hoogeveen, G., and Dubovsky, P., 2006b, IBVS, No. 5681

Samus, N., 2006, ASPC, 349, 3

Samus, N., Durlevich, O. et al., 2004, Combined General Catalogue of Variable Stars

Wils, P., Lloyd, Ch., and Bernhard, K., 2006, MNRAS, 368, 1757

Wozniak, P., Vestrand, P., Akerlof, C. et al., 2004a, Astron. J., 127, 2436

Wozniak, P., Williams, S., Vestrand, W., and Gupta, V., 2004b, Astron. J., 128, 2965

Remarks:

5: Information in the VSX database (reported by J.S. Shaw, D. Hou).

7: NSV14395=W8400, Mira type, with and .

11: AZ And=W8405.

19: Discovered by Gettel et al. (2006).

23: Information in the VSX database (discovered by M. Nicholson).

32: The other name is SAO 52758.

34: Very big amplitude , but not found as variable by Wozniak et al. (2004b).

41: The period in the GCVS is .

50: Visual binary, separation , the other component with the 2MASS coordinates: 23172958, +442622 5. The NSVS data accuracy is insufficient to determine which component varies.

51: AO And=W8491, the period in the GCVS is .

52: A multiple-period star. The primary period in the GCVS is , but this period cannot be found in the NSVS data. The third GCVS period based on the NSVS data is .

59: The other name is SAO 52908.

60: The NSV coordinates are shifted by approximately from the NSVS position.

77: DH And=W8526.

85: V338 And=W8533.

88: AL And=W8538.

89: The GCVS describes DI And as type IS (a rapidly changing irregular variable). Khruslov (2005) found a period .

91: USNO coordinates.

94: X-ray source 1RXS J232827.5 +452242.

95: USNO coordinates.

99: DL And=W8549.

108: V339 And=W8565.

118: Information in the VSX database (discovered by M. Nicholson).

124: Information in the VSX database (discovered by M. Nicholson).

127: The NSVS coordinates are influenced by a close object of similar brightness, USNO 1337-0498237.

128: X-ray source 1RXS J234155.0 +441047.

136: Discovered by Dahlmark (1999). The NSVS coordinates are influenced by a close object of similar brightness, USNO 1335-0498064.

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