Peremennye Zvezdy (Variable Stars) 45, No. 9, 2025 Received 6 June; accepted 11 June.	Article in PDF
	DOI: 10.24412/2221-0474-2025-45-84-98

Variable stars in the field in Orion

A. Samokhvalov

1. Sternberg Astronomical Institute, Moscow State University, Russia, e-mail: sav@surgut.ru

1. Introduction

Working at the program aimed at discoveries and studies of variable stars using the Small Photometric Telescope of the Caucasian Mountain Observatory, we studied a field in Orion with coordinates of center of the frame: . In this field, in size, we investigated 27 variable stars; for 15 of them, variability was discovered by the author. The general information on these stars is collected in Table 1, where equatorial coordinates were drawn from the Gaia DR3 catalog (Gaia Collaboration, 2022). Some of these stars, marked as "K", are currently contained in the AAVSO Variable Star Index (VSX) (Watson et al., 2006); for stars marked "N", variability was discovered in our study. Then follow the columns "Type" and "Period" (in days). The column "Magnitude" contains the variation range in the band derived from our photometric measurements. The web site of the Small Photometric Telescope (http://www.sai.msu.su/gcvs/telescope/) contains detailed information about these variable stars, including light curves, finding charts, and photometric measurements. The web site is constantly being updated and maintained.

Additional information about the program variable stars is given in Table 2. Its first column contains the number from Table 1. VSX Name for known variable stars was drawn from the corresponding database. Values in the columns "IR indices and spectrum" are based on infrared photometry from the 2MASS catalog of point sources, cf. Cutri et al. (2003). The , , and color indices are presented only for stars with the AAA 2MASS quality flag, Qflg. The estimated spectral types in the "Sp" column are based on Bessell and Brett (1988). Note that, in some cases (for example, for DSCT stars No. 2 and No. 16), these color-based spectral type estimates appear too late; this can result from considerable interstellar reddening for the stars close to the galactic plane. The absolute magnitude and distance from the galactic plane , in parsecs, are based on distances from the Sun given in Bailer-Jones et al. (2021).

2. Observations, primary reductions, and magnitude calibration

Our observations were carried out at the Caucasian Mountain Observatory (CMO) of M.V. Lomonosov Moscow State University (see Shatsky et al., 2020) using a 0.25-m remote controlled Ritchey-Chrétien telescope, equipped with a SBIG STXL-6303e CCD camera and an filter. A total of 768 images of the field with 600-second exposures were obtained on JD 2460614-2460785. Information concerning the number of images taken on each observing night is collected in Table 3.

For basic reductions for dark current, flat fields, bias, and for removing hot pixels and cosmic-ray hits, we used IRAF routines and primary reduction utilities from VaST software by Sokolovsky and Lebedev (2018). For calibration, each observing night, we obtained 100 bias frames, 16 dark frames, 16 flat fields, plus 16 dark frames corresponding to flat fields.

To search for new variable stars and to perform their photometry, we applied VaST software. All times in this paper are expressed in terrestrial time in accordance with IAU recommendations (resolution B1 XXIII IAU GA), with heliocentric corrections applied.

For magnitude calibration in band, we use data of the GAIA DR3 catalogue. We restrict ourselves to single, relatively bright stars, with no saturation of pixels for our CCD camera, no close neighbors, and demonstrating no brightness variations during the time interval of our observations. Detailed information about our calibration stars is collected in Table 4. Uncertainties in the column were derives from our photometry, the GAIA , , and magnitudes were drawn from the corresponding catalog. Magnitudes in the column were obtained using the equation:

which is based on Table 5.9 of Gaia Data Release 3, Documentation release 1.3 (https:// gea.esac.esa.int/archive/documentation/GDR3/).

3. Further reductions of observations

To derive periods of pulsating variable stars, we use Period04 software by Lenz and Breger (2005) that implements the discrete Fourier transform, very suitable for analisys of sine-like light curves of the pulsating variable stars with multiperiodicity.

To process observations of eclipsing variable stars, we use Peranso software by Paunzen and Vanmunster (2016) that implements the Lafler-Kinman method, very suitable for the analysis of asymmetric light curves, like those of Algol-type variable stars (cf. Lafler and Kinman, 1965). For DSCT variable stars with multiperiodicity (see Table 5), we searched for periodic signals in our observations in the frequency range between 3 and 20 cycles per day that was selected following recommendations by Breger (2000), and for GDOR stars, between 1 and 6 cycles per day. We continuously calculate significant frequencies: in the first iteration, based on the original data; in the following iterations, using residuals, as long as the signal-to-noise ratio for the corresponding peak in the Fourier frequency spectrum exceeds 4. This is the empirical criterium obtained from observational analysis by Breger et al. (1993), it ensures that the signal is a real feature. Parameters of the oscillations, corresponding to the equation:

were determined by least squares, they are collected in Table 5. In the first column of this table, we give the number of the star in the USNO-A2.0 catalogue, see Monet et al (1998); in the second, the number of photometric measurements of the star; in the third one, average error of photometric measurements; and in the fourth one, the mean magnitude corresponding to Eq. 2. The next five columns describe oscillations of each star. The column named contains the number of the significant frequency, which is given in column 5. Columns named and contain the phase and amplitude of the th oscillation, respectively. In the last column, we give the ratio for the th frequency, derived using the Period04 software. Only those frequencies that satisfy the criterion are kept.

For plotting light curves, Fourier spectra, and population distribution diagrams, we applied our own routines, written in Python 3 programming language using the NumPy (Harris et al., 2020), Matplotlib (Hunter, 2007), and Seaborn (Waskom, 2021) libraries.

4. Classification of variable stars

Classification of variable stars given in Table 1 is based on the GCVS classification system, see Samus et al. (2017). During our analysis of photometric measurements, we found out that most known variable stars require clarification of their type of variability, because the variability types given in VSX do not correspond to their photometric behavior, or to their absolute magnitude, or to the estimated spectral type (see Table 2). The variability types suggested by us are given in Table 1. An additional instrument of classification are population distribution diagrams. Based on VSX and 2MASS catalogs, we draw population distribution diagrams of two types of variable stars as function of infrared colors derived from 2MASS photometry: see Fig. 1 for DSCT (DSCT, DSCTC, and HADS) stars and Fig. 2 for GDOR stars. Only stars with good 2MASS photometry (AAA) and reliably determined type of variability (without ":" in the VSX type) were used. All new variable stars also have the AAA 2MASS quality flag and are located on this diagram near the core of maximum population density, in the green and blue zones. This can be considered one of the signs of really belonging to the corresponding type of variability.

Based on VSX data and distances from the Galactic plane, derived using the distance from the Sun given in Bailer-Jones et al. (2021), we draw a population distribution diagram of GDOR variable stars as a function of period duration (Fig. 3, panel a) and as a function of distance from the galactic plane (Fig. 3, panel b). Period of the variable star USNO-A2.0 1050-03171745 (see Table 1) is located near the maximum of the distribution of periods of GDOR stars, and its distance from the galactic plane (see Table 2) also corresponds to the maximum of the distribution of distances of GDOR stars. This also can be considered as an important sign of this star belonging to the GDOR variability type.

5. Interesting variable stars

Here we provide information about the most interesting variable stars from Table 1 that deserve special attention.

5.1. USNO-A2.0 1050-03153864

Variability of this star was discovered in our study. The star's multiperiodicity was detected, see Table 5. This is one of the faintest star with multiperiodic pulsations detected in this field, and we found only two significant frequencies.

Figure 4 presents the frequency spectrum of USNO-A2.0 1050-03153864 and its theoretical light curve (solid curve) with superposed data points corresponding to individual observations.

The phased light curve of USNO-A2.0 1050-03153864 with the following light elements:

in filter is presented in Fig. 5.

5.2. USNO-A2.0 1050-03171745

This is a known variavle star, it is contained in the GAIA DR3 Variability Catalog, though without period. Using our photometric measurements, we found four pulsation modes with frequencies satisfying the criterion (Table 5).

Figure 6 presents the frequency spectrum of USNO-A2.0 1050-03171745 and its theoretical light curve (solid curve) with superposed data points corresponding to individual observations. Light curve variations are easy to notice, they are reproduced with the model rather well.

The phased light curve of USNO-A2.0 1050-03171745 with the following light elements:

in filter is presented in Fig. 7.

5.3. USNO-A2.0 1050-03175801

Variability of this star was discovered in our study. During the observing campaign, the star did not demonstrate variability, but it flared by 035 on 2025 January 31 (Fig. 8). The actual amplitude may be higher than the given value because the exposure time of a single image, 600 seconds, can reduce amplitudes of fast flares.

The 2MASS color indices and absolute magnitude in filter (see Table 2) correspond to a dwarf of a K or M spectral type, typical of UV Ceti variable stars.

5.4. USNO-A2.0 1050-03179017

Variability of this star was discovered in our study. We detected multiperiodicity (Table 5). The frequency spectrum of USNO-A2.0 1050-03179017 and its theoretical light curve (solid curve) with superposed data points corresponding to individual observations are shown in Fig. 9. Light curve variations are easy to notice, they are reproduced with the model rather well.

The phased light curve of USNO-A2.0 1050-03179017 with the following light elements:

in filter is presented in Fig. 10.

5.5. USNO-A2.0 1050-03184500

Variability of this star was discovered in our study. We detected multiperiodicity (see Table 5). Fig. 11 presents the frequency spectrum of USNO-A2.0 1050-03184500 and its theoretical light curve (solid curve) with superposed data points corresponding to individual observations.

The phased light curve of USNO-A2.0 1050-03184500 with the following light elements:

in filter is presented in Figure 12.

6. Conclusion

We studied 27 variable stars, among which, three DSCT stars and one GDOR star demonstrate reliable signs of multiperiodical pulsations. We also observed one flare of a new UV Ceti star. All detected frequencies of multiperiodic pulsating stars are real features of their oscillations.

For 11 known variable stars in the observed field, we clarified the type of variability. The number of interesting variable stars in a small field (0.42 square degrees) being that large is a good reason to continue the program aimed at searching for variable stars and studying variable stars at low galactic latitudes in dense star fields. All materials of the present study, including finding charts, light curves, photometric measurements, etc. are available at the web site of the Small Photometric Telescope
(http://www.sai.msu.su/gcvs/telescope/).

Acknowledgements: I would like to thank Prof. N. N. Samus for helpful discussion. The study was conducted under the state assignment of Lomonosov Moscow State University.

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