The Berlin Exoplanet Search Telescope. II. Catalog of Variable Stars. III. Census of Variable Stars in a Puppis Field

Variable stars provide a variety of opportunities to use them as astrophysical laboratories and to improve our knowledge of stellar astrophysics, interior structure, evolution, contribution to galactic chemistry etc. Binary stars and pulsating variable stars are two fundamentally important groups of celestial objects. Observations of eclipsing binary stars allow us to determine the masses of stars and provide a wealth of information on the density and atmosphere (e.g., Hilditch 2004; Southworth 2012). Pulsating variable stars also provide information about the interiors of stars. They are also extremely useful as distance indicators, making it possible to measure the distance to the clusters and galaxies where they are found (e.g., Hubble 1925; Feast & Whitelock 2014). The study of stellar variability contributes to detections of transiting extra-solar planets because the light curves of their host stars are characterized by typical low-amplitude periodic events on a scale of a few days. In addition, a light curve may also contain variability from a close star and could lead to false transit candidate identification.

This work is the continuation of previously performed variable star censuses by the Berlin Exoplanet Search Telescope BEST/BEST II project. For the star censuses with BEST from the northern hemisphere, see Karoff et al. (2007), Kabath et al. (2007, 2008, 2009a, 2009b), and Pasternacki et al. (2011) and with BEST II from the southern hemisphere, see Fruth et al. (2012, 2013) and Klagyivik et al. (2013, 2016). Here, we present the variable star observations and classifications from an observing campaign from 2011 November to 2012 April performed by BEST II monitoring a field in the Puppis (Pup) constellation in the southern hemisphere.

This article is structured as follows: at first we give a short overview of the telescope configuration and the observation conditions. In Section 3, we explain the standard procedure for data calibration, photometry, and analysis. The results of the classification are presented in Section 4. In Section 5, we relate our classification with the recently released Gaia data. Section 6 exhibits the modeling results of some specific interesting binary stars. Finally, we summarize our results in Section 7.

The Berlin Exoplanet Search Telescope (BEST) is a ground-based photometric search project that was initiated in 2001 by the Institute for Planetary Research of the German Aerospace Agency (DLR). The prime use of the system was to provide robotic observational support to the CoRoT space mission by excluding false positives from the list of transiting planetary candidates prior to and during mission operation (Baglin et al. 2006; Deeg et al. 2009; Csizmadia et al. 2011). In addition, BEST observations should also point out potentially interesting objects for the CoRoT additional science programs, such as variable stars. In various time periods, the regular CoRoT support was not required, and independent surveys were performed. The first observations were carried out in the northern hemisphere at the Thüringer Landessternwarte Tautenburg (TLS), Germany, and later relocated to Observatoire de Haute-Provence (OHP), France, with the BEST telescope (Rauer et al. 2004). Since 2007, BEST II (Kabath et al. 2009a) has operated in the southern hemisphere at the Observatorio Cerro Armazones (OCA), Chile, located at an altitude of 2817 m above sea level. It has been supported by the Instituto de Astronomia de la Universidad Católica del Norte (UCN) in Antofagasta and the Astronomical Institute, Ruhr-Universität Bochum (AIRUB; Rauer et al. 2010).

The small aperture automatic BEST II system consists of a 25 cm Baker–Ritchey–Chrétien telescope with a focal ratio of f/5.0 on a German-equatorial mount. It is equipped with a CCD camera with 4096 × 4096 pixels. The field of view (FoV) of the telescope is 17 × 1°7, allowing for a large number of stars to be observed simultaneously.

The catalog of variable stars presented here was derived from an observation campaign between 2011 November 9 and 2012 April 6 performed with BEST II monitoring a target field in the Puppis (Pup) constellation (hereafter, field F20) located south of the Galactic plane. Based on lessons learned from former observing campaigns (Pasternacki et al. 2011; Fruth et al. 2012), this BEST II run was optimized for brighter targets to enable an easier radial velocity follow-up process and/or transit spectroscopy to characterize the atmospheric composition of transiting planets. For the target field F20, the exposure time was decreased to 45 s in order to shift the photometric range by 2 mag toward brighter target stars to 10–13 mag. Four subfields F20a, F20b, F20c, and F20d (see Figure 1) were observed during 61 nights in alternating sequences a-b-c-d (changing after every exposure) so that the decreased number of bright stars was compensated by an FoV that was four times larger. Flat, bias, and dark images were acquired at the beginning and end of each single night observation. All observations were obtained without any filter, i.e., in white light leading to a bandpass limitation by the quantum efficiency of the detector, which peaks in the red at ca. 650 nm (instrument magnitude R_B) close to the standard Johnson R-band at 658 nm. Figure 2 shows the duty cycle of the BEST II observations.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

The photometric quality of the acquired data is shown in Figure 3 by the example of subfield F20a. It shows the total noise σ_tot and the three major contributors' red noise σ_red, photon noise σ_phot, and background noise σ_bg. The light curves of the brighter stars are dominated by photon noise σ_phot, but the majority of light curves (fainter stars) are dominated by background noise σ_bg. The other subfields show similar behavior with negligible differences.

Zoom In Zoom Out Reset image size

Table 1 summarizes the subfield center coordinates, the time range of the observation, the number of good photometric nights with observations within this range, the number of acquired frames, and the number of total/low-noise light curves for each target field.

Table 1.  BEST II Target Field F20 Information

FIELD	Center Coordinates (J2000.0)		Season	Nights	Frames	Stars
	α	δ				Total	σ ≤ 0.01m
F20a	${07}^{{\rm{h}}}{30}^{{\rm{m}}}{00}^{{\rm{s}}}$	−32° 33' 00''	09/11/2011–06/04/2012	61	2001	31,174	1608
F20b	${07}^{{\rm{h}}}{30}^{{\rm{m}}}{00}^{{\rm{s}}}$	−30° 51' 00''	09/11/2011–06/04/2012	61	1980	34,150	1887
F20c	${07}^{{\rm{h}}}{30}^{{\rm{m}}}{00}^{{\rm{s}}}$	−29° 09' 00''	09/11/2011–06/04/2012	61	1958	34,126	2004
F20d	${07}^{{\rm{h}}}{30}^{{\rm{m}}}{00}^{{\rm{s}}}$	−27° 27' 00''	09/11/2011–06/04/2012	61	2010	31,022	1096

Download table as:  ASCIITypeset image

To calibrate and reduce scientific images from the BEST II telescope, an automated photometric pipeline was applied as outlined in Rauer et al. (2010) and improved by Fruth et al. (2012). It was developed for the BEST project, but is intended to be applicable to any time-series astronomical data set.

To identify potential stellar variability from the huge data set of 130,472 observed stars we applied the method described by Fruth et al. (2012), which is based on the modified Stetson's j-variability index (Stetson 1996) according to Zhang et al. (2003). In our work, we set a cutoff limit for potentially variable stars of j > 0.1 based on experience with previous BEST II field characterization. The resulting 32,850 light curves were searched for significant frequencies in the range from 0.025 to 50 days by using the Algorithm of Variance (AoV) proposed by Schwarzenberg-Czerny (1996). From that AoV statistic, a modified quality parameter q was calculated giving lower weights to common periodic variability that is encountered in many light curves (see Fruth et al. 2012 for more details). Finally, 2412 light curves with q ≥ 10 were classified by visual inspection. In this process, many false alarms with periods of about 1 day, but no significant presence of stellar variability, were excluded. These are assumed to be mainly artifacts occurring at the sidereal day and caused by the observational duty cycle (Figure 2).

The classification of the detected variable stars is based on photometric information only, i.e., the shape, the period, and the amplitude of the brightness variation according to the General Catalog of Variable Stars (GCVS) by Samus et al. (2017). A first distinction has to do with the nature of the brightness variations: intrinsic variability is due to physical changes in the star or stellar system. Extrinsic variability is due to the eclipse of one star by another or the effect of stellar rotation.

In our analysis, we used the following subtypes of intrinsic variables: δ Scuti (DSCT), SX Phoenicise type (SXPHE), γ Doradus (GDOR), RR Lyrae (RR), δ Cephei (DCEP), and Long Period Variable (LPV) stars. The extrinsic variable stars we classified into (semi-)detached eclipsing binary systems or Algol-(EA), the semidetached β Lyrae-(EB), the contact binary or W Ursae Majoris-type (EW), the eccentric type (E), and the rotating ellipsoidal variables (ELL). Stars with typical features of star spots are marked as spotted (SP) and periodic PMS stars were marked as young stellar objects (YSOs). In case of doubts, we classified several pulsating-like stars as SP (Poretti et al. 2015). The light curves of the EW and DSCT classes may be indistinguishable with photometric data of a ground-based survey in some low-amplitude cases. For such uncertain classifications, the class of (EW/DSCT) was introduced. Remaining objects showing clear variability but for which no assignment is possible are classified as variable (VAR). This class also includes the semiregular (SR) and miscellaneous (MISC) variables. The classification is highly subjective and depends on the experience of the observer. The agreement with automatic classification is expected to be around 70% (Fruth et al. 2012). A summary of our classifications containing the counts of a variability class in each subfield is given in Table 2. In total, 1855 variable and 314 suspected variable stars have been detected.

Table 2.  Statistical Overview of All Detected Variable Stars

	F20a		F20b		F20c		F20d		Total F20
Total	31,174		34,150		34,126		31,022		130,472
Stars with $j\gt 0.1$	7004 ${}^{(23 \% )}$		8769(26%)		8481(25%)		8596(28%)		32,850(25%)
Stars with q > 10	550(1.8%)		635(1.9%)		659(1.9%)		568(1.8%)		2412(1.9%)
Intrinsic
DCEP	44	(3)	55	(12)	37	(5)	16	(2)	152	(22)
DSCT	105	(21)	85	(30)	119	(23)	56	(15)	365	(89)
GDOR	1	(0)	0	(0)	0	(0)	0	(0)	1	(0)
LPV	16	(1)	21	(2)	16	(0)	18	(1)	71	(4)
RR	57	(1)	49	(14)	47	(8)	36	(14)	189	(37)
SXPHE	2	(1)	7	(0)	0	(0)	1	(0)	10	(1)
Extrinsic
EA	69	(6)	90	(14)	107	(16)	76	(9)	342	(45)
EB	29	(1)	17	(3)	23	(2)	17	(2)	86	(8)
EW	58	(1)	69	(12)	58	(6)	48	(2)	233	(21)
EW/DSCT	4	(1)	7	(2)	6	(2)	26	(5)	43	(10)
E	0	(0)	0	(0)	5	(1)	1	(1)	6	(2)
ELL	6	(0)	9	(3)	16	(8)	2	(2)	33	(13)
SP	28	(9)	29	(4)	64	(9)	41	(23)	162	(45)
YSO	4	(1)	0	(0)	1	(1)	0	(1)	5	(3)
VAR	36	(1)	41	(6)	27	(5)	53	(2)	157	(14)
Total	459	(47)	479	(102)	526	(86)	391	(79)	1855	(314)
	1.5%	0.15%	1.4%	0.29%	1.5%	0.25%	1.3%	0.26%	1.4%	0.24%

Note. Given are the numbers of newly detected and already known variable stars for each subfield per variability class. Percentage values give the relative fraction compared to the total count whereas integers in brackets state the number of suspected variables.

Download table as:  ASCIITypeset image

All 2169 detected variable stars are listed in a catalog containing coordinates α, δ given for epoch J2000.0 and matched to the 2MASS catalog, 2MASS identification number 2MASS ID, instrument magnitude R_B, epoch T₀, period P, amplitude A, j-index, variability type, and other names where applicable. Stars contaminated with neighboring stars in the aperture, i.e., having overlapping point-spread functions, are marked by a c-flag, already known variables by a k flag, and suspected variables by an s-flag. Table 3 shows an excerpt of the catalog for guidance regarding its form and content. Some textbook light curves are shown in Figure 4. The complete catalog and figure set of all light curves are available online.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

View figure set (2169 panels)

Tarball of figure set images

Table 3.  Catalog of Variable Stars Detected in BEST II Field F20 (Excerpt)

BEST II ID	Flag	2MASS ID	α(J2000.0)	δ(J2000.0)	RB (mag)	T0 (rHJD)	P (day)	A (mag)	j-index	Type	Other Names
F20a
F20a_00022	c	07292719−3321460	${07}^{{\rm{h}}}{29}^{{\rm{m}}}27\buildrel{\rm{s}}\over{.} 2$	−33°21'460	14.09	75.779	0.09208 ± 0.00002	0.09 ± 0.02	1.85	DSCT
F20a_00116		07270084−3321238	${07}^{{\rm{h}}}{27}^{{\rm{m}}}00\buildrel{\rm{s}}\over{.} 8$	−33°21'238	13.53	75.772	0.12409 ± 0.00004	0.02 ± 0.02	0.936	DSCT
F20a_00123	s	07303529−3321151	${07}^{{\rm{h}}}{30}^{{\rm{m}}}35\buildrel{\rm{s}}\over{.} 3$	−33°21'151	12.28	75.741	0.035386 ± 0.000002	0.01 ± 0.01	0.942	DSCT
F20a_00185	s	07262353−3321067	${07}^{{\rm{h}}}{26}^{{\rm{m}}}23\buildrel{\rm{s}}\over{.} 5$	−33°21'068	13.23	83.286	1.113 ± 0.002	0.13 ± 0.03	3.72	EA
F20a_00221		07334829−3320207	${07}^{{\rm{h}}}{33}^{{\rm{m}}}48\buildrel{\rm{s}}\over{.} 3$	−33°20'208	14.60	80.179	0.925 ± 0.002	0.09 ± 0.05	1.11	GDOR
F20a_00234		07330344−3320285	${07}^{{\rm{h}}}{33}^{{\rm{m}}}03\buildrel{\rm{s}}\over{.} 4$	−33°20'287	15.75	80.382	0.8455 ± 0.0007	0.30 ± 0.06	1.29	EW
F20b
F20b_00200	c	07333340−3139432	${07}^{{\rm{h}}}{33}^{{\rm{m}}}33\buildrel{\rm{s}}\over{.} 4$	−31°39'431	14.97	84.891	0.3827 ± 0.0001	0.36 ± 0.04	3.23	EW
F20b_00215	cs	07314278−3140071	${07}^{{\rm{h}}}{31}^{{\rm{m}}}42\buildrel{\rm{s}}\over{.} 8$	−31°40'071	14.22	84.867	0.07747 ± 0.00002	0.02 ± 0.03	0.440	DSCT
F20b_00258	cs	07305675−3140047	${07}^{{\rm{h}}}{30}^{{\rm{m}}}56\buildrel{\rm{s}}\over{.} 8$	−31°40'047	11.91	84.902	0.4381 ± 0.0004	0.11 ± 0.02	7.66	RR
F20b_00259	c	07305736−3140034	${07}^{{\rm{h}}}{30}^{{\rm{m}}}57\buildrel{\rm{s}}\over{.} 3$	−31°40'035	12.76	84.952	0.4378 ± 0.0009	0.09 ± 0.04	4.03	RR
⋮
F20b_27380	k	07323060−3023200	${07}^{{\rm{h}}}{32}^{{\rm{m}}}30\buildrel{\rm{s}}\over{.} 6$	−30°23'200	11.50	75.830	0.56308 ± 0.00006	0.90 ± 0.03	50.3	EW	NSV 3636
F20b_30270	k	07323023−3014599	${07}^{{\rm{h}}}{32}^{{\rm{m}}}30\buildrel{\rm{s}}\over{.} 2$	−30°14'598	10.66	83.035	3.912 ± 0.007	1.4 ± 0.2	32.5	EA	NSV 3640
F20c
F20c_00021		07302379−2959153	${07}^{{\rm{h}}}{30}^{{\rm{m}}}23\buildrel{\rm{s}}\over{.} 8$	−29°59'153	15.06	90.795	8.56 ± 0.06	0.32 ± 0.06	0.763	EA
F20c_00133	c	07324242−2958304	${07}^{{\rm{h}}}{32}^{{\rm{m}}}42\buildrel{\rm{s}}\over{.} 4$	−29°58'302	12.46	84.873	0.08876 ± 0.00003	0.02 ± 0.02	1.21	DSCT
F20c_00421		07284237−2958038	${07}^{{\rm{h}}}{28}^{{\rm{m}}}42\buildrel{\rm{s}}\over{.} 4$	−29°58'040	14.21	159.161	21.8 ± 0.3	0.39 ± 0.03	4.48	EB
F20c_00433		07331610−2957148	${07}^{{\rm{h}}}{33}^{{\rm{m}}}16\buildrel{\rm{s}}\over{.} 1$	−29°57'149	11.86	⋯	⋯	⋯	13.6	VAR
F20c_00457	s	07313726−2957330	${07}^{{\rm{h}}}{31}^{{\rm{m}}}37\buildrel{\rm{s}}\over{.} 3$	−29°57'328	12.42	84.993	0.16863 ± 0.00009	0.02 ± 0.02	1.20	DSCT
F20c_00518		07304424−2957278	${07}^{{\rm{h}}}{30}^{{\rm{m}}}44\buildrel{\rm{s}}\over{.} 2$	−29°57'278	14.50	84.927	0.13222 ± 0.00005	0.04 ± 0.03	0.415	DSCT
F20d
F20d_00027		07285717−2814566	${07}^{{\rm{h}}}{28}^{{\rm{m}}}57\buildrel{\rm{s}}\over{.} 2$	−28°14'566	15.08	85.213	0.6971 ± 0.0009	0.06 ± 0.04	0.372	EW
F20d_00102		07311699−2814309	${07}^{{\rm{h}}}{31}^{{\rm{m}}}17\buildrel{\rm{s}}\over{.} 0$	−28°14'310	14.47	85.073	0.3887 ± 0.0005	0.06 ± 0.03	0.937	SP
F20d_00146		07293598−2814338	${07}^{{\rm{h}}}{29}^{{\rm{m}}}36\buildrel{\rm{s}}\over{.} 0$	−28°14'340	14.79	147.795	20.5 ± 0.6	0.18 ± 0.03	2.33	DCEP
F20d_00178		07332303−2813562	${07}^{{\rm{h}}}{33}^{{\rm{m}}}23\buildrel{\rm{s}}\over{.} 0$	−28°13'562	12.75	85.356	2.472 ± 0.006	0.16 ± 0.03	2.77	EA
F20d_00359	s	07280939−2814056	${07}^{{\rm{h}}}{28}^{{\rm{m}}}09\buildrel{\rm{s}}\over{.} 4$	−28°14'056	14.44	87.510	1.506 ± 0.004	0.05 ± 0.02	0.319	EB
F20d_00373		07310476−2813489	${07}^{{\rm{h}}}{31}^{{\rm{m}}}04\buildrel{\rm{s}}\over{.} 8$	−28°13'493	12.35	⋯	⋯	⋯	4.52	LPV

Note. Variable stars in the F20 field sorted by BEST II ID with matched 2MASS ID, coordinates α, δ, instrument magnitude R_B, epoch T₀, period P, amplitude A, j-index, and variability type. Stars contaminated by neighboring stars are flagged with c. The s flag indicates stars suspected to be variable and the k flag marks previously known variable stars with the names from GCVS and/or VSX in the last column. The epoch T₀ is given in reduced Julian date (rHJD) in respect to T = 2455,800.0.

Only a portion of this table is shown here to demonstrate its form and content. A machine-readable version of the full table is available.

Download table as:  DataTypeset image

4.1. Known Variable Stars

The stars observed with BEST II have been cross-checked with the GCVS by Samus et al. (2017) and the international variable star index (VSX; Watson et al. 2015). Within the observed target field F20, a total of 26 previously known variable stars could be found. Table 4 shows the comparison of the classifications and the BEST II light curves are presented in Figure 5.

Zoom In Zoom Out Reset image size

Table 4.  Known Variable Stars in the F20 Field

Identifier		RB	Period P (days)		Classification		References
BEST II	Ref.	(mag)	BEST II	Ref.	BEST II	Ref.
F20a
F20a_05669	ASAS J073332−3300.2	9.99	⋯	44.8	VAR	MISC	Pojmanski (2002), Skiff (2004)
F20a_15831	ASAS J073039−3231.0	10.59	⋯	74.8	LPV	MISC	Pojmanski (2002), Skiff (2004)
F20a_19297	ASAS J073035−3221.5	10.44	⋯	70.3	LPV	MISC	Pojmanski (2002)
F20a_19891	ASAS J073206−3219.7	12.38	0.47187(5)	0.471874	EW	EC∣ESD	Pojmanski (2002)
F20a_20477	ASAS J073004−3218.3	10.59	⋯	98.3	LPV	MISC	Pojmanski (2002)
F20b
F20b_02668	ASAS J073102−3130.8	12.89	0.39263(4)	0.392639	EW	EC∣ESD	Pojmanski (2002)
F20b_10156	ASAS J073206−3108.1	13.20	1.7825(7)	1.78254	EA	ESD∣EC∣ED	Pojmanski (2002)
F20b_12203	ASAS J072931−3103.2	10.70	⋯	83.1	LPV	MISC	Pojmanski (2002)
F20b_21665	ASAS J072830−3039.3	11.63	3.306(4)	3.3063	DCEP	DCEPS	Pojmanski (2002), Mel'nik et al. (2015)
F20b_24806	ASAS J072907−3030.8	10.17	⋯	77.3	VAR	MISC	Pojmanski (2002)
F20b_27380	NSV 3636	11.50	0.56308(6)	⋯	EW	Suspected	Strohmeier et al. (1964)
F20b_30270	NSV 3640	10.66	3.912(7)	⋯	EA	Suspected	Strohmeier & Knigge (1975)
F20b_33375	ASAS J073043−3005.6	10.23	0.779(2)	0.779260	RR	DCEP-FO∣EC∣ESD	Pojmanski (2002)
F20c
F20c_13759	ASAS J072840−2920.6	12.32	2.702(1)	2.7017	DCEP	DCEP	Pojmanski (2002), Mel'nik et al. (2015)
F20c_15448	V0448 Pup	10.37	⋯	⋯	VAR	SR:	Pojmanski (2002), Skiff (2004)
F20c_16945	ASAS J073328−2911.5	11.56	0.6704(1)	0.6704	EA	ED∣ESD	Pojmanski (2002)
F20c_19594	V0452 Pup	10.43	⋯	⋯	VAR	SR:	Skiff (2014), Takamizawa (2000)
F20c_22898	ASAS J073239−2856.1	11.66	3.061(3)	3.060854	EA	ED	Pojmanski (2002)
F20c_26155	ASAS J072837−2847.6	10.03		112.4	VAR	MISC	Pojmanski (2002), Skiff (2004)
F20d
F20d_01383	ASAS J073113−2811.0	16.13	4.71(8)	4.7092	DCEP	DCEP	Pojmanski (2002), Pietrukowicz et al. (2013)
F20d_07449	BY CMa	12.55	3.185(2)	3.18493	DCEP	DCEP	Pojmanski (2002)
F20d_27979	ASAS J072910−2653.3	10.39	⋯	313.	LPV	M	Pojmanski (2002), Skiff (2004), Henden et al. (2016)
F20d_29374	BO Pup	11.14	⋯	615.00000	LPV	M	Pojmanski (2002), van Hoof (1941)
F20d_29927	ASAS J072618−2643.4	9.96	⋯	41.22	VAR	MISC	Pojmanski (2002), Skiff (2004)
F20d_30252	ASAS J073109−2641.2	11.01	⋯	236.	VAR	MISC	Pojmanski (2002)
F20d_30704	V0451 Pup	10.57	⋯	⋯	VAR	SR:	Pojmanski (2002), Skiff (2004), Takamizawa (2000)

Note. Given are BEST II and the GCVS and/or VSX identifiers, the BEST II instrumental magnitudes R_B, periods P, and classifications (if available) as obtained within this work and by previous surveys as referenced, respectively.

Download table as:  ASCIITypeset image

In general, we confirm the previously determined periods and the stellar variability classes. For two known but only suspected variable stars, NSV 3636 (F20b_27380) (Strohmeier et al. 1964) and NSV 3640 (F20b_30270) (Strohmeier & Knigge 1975), we determine the type of variability as a contact binary system (EW) with an orbital period of 0.56308 ± 0.00006 days and a type of (semi-)detached eclipsing binary system (EA) with a period of 3.912 ± 0.007 days, respectively. For ASAS J073043-3005.6 (F20b_33375), we confirm the period of 0.779 ± 0.002 days but not the proposed classes of first-tone classical Cepheid (DCEP-FO), contact binary (EC) or semidetached eclipsing binary (ESD) as suggested by Pojmanski (2002). Clearly showing multiple aliases, the shape of the light curve does not support the classification as an eclipsing binary. We have classified it as RR Lyrae instead of a Cepheid because of a period less than 1 day following the GSCV variable type classification. The already known semiregular variables were classified as VAR in our BEST II catalog as we do not further distinguish. For a few variable stars, we are not able to give a period because of our short observation baseline, which resolves periods less than 50 days only, or unclear variability. The GCVS catalog lists them as Mira-type stars (M). We classify them as LPV—the parent class of that type of variable or as VAR.

4.2. Newly Detected Variable Stars

In Field F20, we detected 1829 new variable stars. In the catalog of BEST II target field F20, the most common types are of short period pulsators (DSCT, RR) with 554 objects and eclipsing binaries (EA, EB, EW) with 661 objects. This is approximately two-thirds of all detected variable stars in that field.

Finally, we compared the overall variability fraction of the F20 field to similar ground-based photometric surveys (see Table 5). The percentage of variable stars in the entire F20 data set of 130,472 stars amounts to 1.66% and is of the same order as in other photometric surveys, e.g., ASAS-2 with 2.7% and HAT 199 with 1.65%. Table 5 also gives a summary of the total yields of the BEST/BEST II search for light variations, which is now completed.

Table 5.  Variable Star Detection Yield in Comparison to Other Surveys

Project	${N}_{* }$	Nvar	${N}_{\mathrm{var}}/{N}_{* }$	Mag	References
BEST/BEST II
BEST	121,811	335	0.28%	11–15	Karoff et al. (2007), Kabath et al. (2007, 2008)
					Pasternacki et al. (2011)
BEST II (CoRoT)	395,818	4114	1.04%	11–17	Kabath et al. (2009a, 2009b), Fruth et al. (2012)
					Klagyivik et al. (2013, 2016)
BEST II (F17-F19)	209,070	3040	1.45%	11–17	Fruth et al. (2013)
BEST II (F20)	130,472	2169	1.66%	11–17	this work
Other Ground-based Surveys
UNSW	87,000	850	0.98%	8–14	Christiansen et al. (2008)
HAT 199	98,000	1617	1.65%	8–14	Hartman et al. (2004)
EROS II	1913,576	1362	0.07%	11–17	Derue et al. (2002)
ASAS-2	140,000	3800	2.71%	8–13	Pojmanski (2000)
ASAS-3	$1.7\times {10}^{7}$	50,099	0.29%	8–14	Paczyński et al. (2006)
OGLE-II	$1.65\times {10}^{7}$	68,194	0.41%	≤20	Zebrun et al. (2001)
OGLE-III	$2\times {10}^{8}$	193,000	0.10%	12–20	Soszyński et al. (2008, 2011)

Note. The table gives the number of surveyed stars N_*, the number of newly found and suspected variables N_var, and the corresponding ratio ${N}_{\mathrm{var}}/{N}_{* }$ for BEST/BEST II publications, this work, and selected references of important ground-based variable star surveys. If noted in the publication, N_var here includes known and new detections, i.e., the whole detection yield of a given survey. The column "Mag" gives each survey's approximate magnitude range.

Download table as:  ASCIITypeset image

Sometimes it is difficult to distinguish between different classes of variable stars and/or the classification is uncertain just by the light-curve shape, periods, and amplitudes. Additional astrometric and color information can help clarify and identify potential systematic problems by producing a CDM. Therein each variability class is associated with a well-defined position.

The Gaia mission (Gaia Collaboration et al. 2016), as an enormous stellar census, delivers us basic astronomical data of unprecedented scope, accuracy, and completeness. We produce CDMs of our BEST II field 20 with the help of the recently published Gaia DR2 (Gaia Collaboration et al. 2018a) and highlight our variable stars. The absolute magnitude M_G is derived from the Gaia magnitude, the Gaia parallax, and the extinction as reported by Gaia DR2. The color index ${({G}_{\mathrm{BP}}-{G}_{\mathrm{RP}})}_{\mathrm{corr}}$ is determined using the Gaia colors BP, RP, and reddening information, also part of the Gaia catalog. We could calculate the absolute Gaia magnitude for only 30%–40% of the BEST II target field F20 objects because of missing extinction information in the Gaia catalog.

Figure 6 shows the resulting BEST II field F20 CDMs for binary systems (upper panel) and pulsating stars (lower panel). In the binary CMD, one can see that binary systems occupy all branches of the diagram as we expect (see Gaia Collaboration et al. 2018b, Figure 4 therein). Their frequency on different branches are according to the expectations (e.g., Eggleton 2006). In the CMD for pulsating variables (lower panel) the δ Scutis are generally in a good position in the so-called instability strip. Many stars classified as RR Lyrae type stars by period and light-curve shape are actually main-sequence stars according to the Gaia data (see Gaia Collaboration et al. 2018b, Figure 2 therein). Therefore, we think the classification as RR Lyrae based on the photometric information has to be considered carefully. Maybe they have to be classified as spotted stars. According to their position in the CDM, many stars classified as Cepheids are red giants, but Cepheids are actually yellow hyper-giants. These Cepheids might also be reclassified as spotted or rotating stars. In general, we might have difficulties disentangling spotted stars from pulsating stars in our scheme. Finally, one sees a set of LPV and VAR stars with similar absolute magnitude (M_G ∼ −2 mag) and very red colors (${({G}_{\mathrm{BP}}-{G}_{\mathrm{RP}})}_{\mathrm{corr}}\gt 2\,\mathrm{mag}$). This may result from the error-affected Gaia color index and/or extinction.

Zoom In Zoom Out Reset image size

The cross-match with the Gaia DR2 information suggests that our classification is reasonable for eclipsing binaries, but not so reliable for pulsating variables; opposite of the automatic classification routine of Debosscher et al. (2009). However, one should consider that the Gaia DR2 data suffers from systematic errors, in particular, extinction (van Leeuwen et al. 2018). That is why we are limited in achieving our goal of cross-checking our classification and the result must be considered with reservation. A final conclusion can be drawn once the Gaia DR2 information has been validated. We also cannot exclude the possibility that the BEST II - Gaia DR2 cross-identification failed in some cases, since background stars can influence and distort the identification.

To have a deeper look into the properties of the detected eclipsing binaries and to determine the spot parameters of some of them at the epoch of the observation, eight systems, including the two newly classified binaries NSV 3636 (F20b_027380) and NSV 3640 (F20b_030270), were studied in more detail with the BinaryModel light-curve modeling code developed by Csizmadia et al. (2009). This code is very similar to the Wilson–Devinney Code (Wilson & Devinney 1971) and it uses a Roche-model to take the proximity effects into account. All details of the modeling not described here are the same as in Klagyivik et al. (2013). The systems for this section were selected on the basis of signal-to-noise (S/N) ratio, and obviously brighter targets with deeper eclipses produced higher S/N.

The effective temperatures of the primaries were calculated using the 2MASS J − K color index and they were fixed during the fitting procedure. Systematic errors can be present in these temperatures, owing to unknown reddening. R-band linear bolometric and quadratic limb darkening coefficients were chosen from van Hamme (1993) and Claret & Bloemen (2011), respectively, since this is the closest filter to our white response function. Below 6000 K stellar temperature, the gravity darkening exponents and Albedos were set to g = 0.32 and to A = 0.5, and over it to g = A = 1.0 (Lucy 1967; Ruciński 1969).

We fitted the mass ratio Q, inclination i, fill-out factors of the two components f1, f2 (Mochnacki 1981), effective surface temperature of the secondary star T2, epoch T₀, height correction h of the maximum brightness at the first quarter refining the normalization of the light curve and stellar spots to one or both of the components if needed. We tried all the possible combinations up to two spots in total (no spot, one spot on the primary star, one spot on the secondary component, etc.). The temperature of a spot is described as the temperature ratio of the spot and the star (temperature factor = ${T}_{\mathrm{spot}}/{T}_{\mathrm{star}}$). The fits with the smallest χ² values were accepted and summarized in Table 6, which gives detailed system parameters, and in Figure 7, which shows the resulting fits. Notice that mark ^a in Table 6 means that the system was found to be over-contacted when the two fill-out factors are equal to each other. The errors in Table 6 include only modeling uncertainties but no systematic errors of the input parameters.

Zoom In Zoom Out Reset image size

Table 6.  Characteristics of the Modeled Binary Systems

Catalog ID			NSV 3636	NSV 3640
BEST II ID	F20a_003678	F20a_027661	F20b_027380	F20b_030270	F20c_001601	F20c_015786	F20d_005502	F20d_026554
Classification	EW	EA	EW	EA	EA	EW	EA	EW
Measured Parameters
Magnitude RB (mag)	15.48	14.78	11.50	10.66	13.26	13.62	13.23	13.61
Epoch T0 (HJD-2455,800.0)	80.372	80.325	75.830	83.035	88.463	75.841	80.759	75708
Period P (day)	0.39492 ± 0.00008	1.6116 ± 0.0009	0.56308 ± 0.00008	3.912 ± 0.009	1.893 ± 0.002	0.26821 ± 0.00004	3.112 ± 0.005	0.41220 ± 0.00007
Amplitude A (mag)	0.46 ± 0.05	1.16 ± 0.05	0.90 ± 0.08	1.4 ± 0.4	0.25 ± 0.02	0.40 ± 0.04	0.52 ± 0.05	0.42 ± 0.04
System Parameter
Orbital eccentricity e	0 (circular orbit, fixed)
Temperature $T1(K)$	5388 (fixed)	4329 (fixed)	5370 (fixed)	4414 (fixed)	2285 (fixed)	4652 (fixed)	5731 (fixed)
Mass ratio Q	0.51 ± 0.04	4.1 ± 0.7	1.463 ± 0.015	5.48 ± 0.12	1.630 ± 0.018	5.1 ± 0.4	6.5 ± 0.3	4.3 ± 0.3
Inclination i (°)	70.0 ± 0.3	77.3 ± 1.4	86.6 ± 0.2	82.9 ± 0.2	90.0 ± 0.6	68.0 ± 0.5	72.16 ± 0.19	72.3 ± 0.7
Fill-out factor f1	0.22 ± 0.04	−1.70 ± 0.15	0.1087 ± 0.0008	−3.88 ± 0.07	−9.75 ± 0.12	0.2450 ± 0.0007	−2.00 ± 0.08	0.06 ± 0.06
Fill-out factor f2	0.22a	−4.2 ± 0.4	0.1087a	−20.7 ± 0.5	−1.71 ± 0.03	0.2450a	−7.1 ± 0.3	0.06a
Temperature $T2(K)$	5341 ± 34	3078 ± 65	5050 ± 3	2751 ± 21	2249 ± 3	4410 ± 28	3771 ± 7	3378 ± 20
Height correction h	0.0016 ± 0.0006	−0.0043 ± 0.0017	0.00097 ± 0.00017	−0.00177 ± 0.00017	−0.0009 ± 0.0003	−0.0023 ± 0.0003	0.0038 ± 0.0003	0.0030 ± 0.0007
${{ \mathcal X }}^{2}$	0.506448	4.08084	1.46310	5.47498	1.63041	5.05016	6.47662	4.34199
Spot 1 on what star?	⋯	Primary	Primary	⋯	⋯	⋯	⋯	Primary
Longitude λ1(°)		74 ± 40	149 ± 59					114 ± 20
Colatitude ϕ1 (°)		127 ± 51	302 ± 16					99 ± 10
Radius ds1		26 ± 11	11 ± 3					29 ± 3
Temperature factor 1		0.95 ± 0.04	0.6 ± 0.2					0.26 ± 0.03
Spot 2 on what star?	⋯	Secondary	Secondary	⋯	⋯	⋯	⋯	Primary
Longitude λ2(°)		23 ± 50	110 ± 33					40 ± 43
Colatitude ϕ2 (°)		196 ± 91	130 ± 85					245 ± 63
Radius ds2		169 ± 41	4 ± 44					54 ± 43
Temperature factor 2		0.96 ± 0.30	0.6 ± 0.3					1.02 ± 0.07
Stellar Fractional Radii
Primary
R1 (pole)	0.424 ± 0.004	0.1968 ± 0.0019	0.331 ± 0.003	0.1468 ± 0.0015	0.1139 ± 0.0012	0.240 ± 0.003	0.1704 ± 0.0017	0.245 ± 0.003
R1 (side)	0.486 ± 0.005	0.211 ± 0.002	0.383 ± 0.004	0.1522 ± 0.0015	0.1145 ± 0.0012	0.292 ± 0.003	0.1829 ± 0.0019	0.289 ± 0.003
R1 (back)	0.453 ± 0.005	0.201 ± 0.002	0.348 ± 0.004	0.1483 ± 0.0015	0.1142 ± 0.0012	0.251 ± 0.003	0.1737 ± 0.0018	0.255 ± 0.003
R1 (point)		0.215 ± 0.002		0.1532 ± 0.0015	0.1146 ± 0.0012		0.1862 ± 0.0019
Secondary
R2 (pole)	0.197 ± 0.002	0.334 ± 0.003	0.315 ± 0.003	0.217 ± 0.002	0.270 ± 0.003	0.455 ± 0.005	0.355 ± 0.004	0.435 ± 0.004
R2 (side)	0.197 ± 0.002	0.334 ± 0.003	0.315 ± 0.003	0.217 ± 0.002	0.270 ± 0.003	0.455 ± 0.005	0.355 ± 0.004	0.435 ± 0.004
R2 (back)	0.197 ± 0.002	0.334 ± 0.003	0.315 ± 0.003	0.217 ± 0.002	0.270 ± 0.003	0.455 ± 0.005	0.355 ± 0.004	0.435 ± 0.004
R2 (point)		0.334 ± 0.003		0.217 ± 0.002	0.270 ± 0.003		0.355 ± 0.004

Note.

^asystem was found to be over-contacted when the two fill-out factors are equal to each other. The temperature of a spot is described as the temperature ratio of the spot and the star (temperature factor = ${T}_{\mathrm{spot}}/{T}_{\mathrm{star}}$).

Download table as:  ASCIITypeset image

F20a_003678, F20b_027380, F20c_015786, and F20d_026554 are contact binaries (EW), two of them spotted. We report the spot parameters in Table 6. The spot evolution can be further studied via long-term photometry, and all-sky ground (e.g., PannStarrs, ASAS) and space (e.g., TESS) surveys provide additional data at different epochs, and thus our 2011/12 observations may serve as a baseline extension. The detached binaries (EA) F20a_027661, F20c_001601, and F20d_005502 exhibit stable light curves and probably would be good targets for subsequent radial velocity studies to measure the components' masses precisely. F20b_030270 shows unexplained light-curve variations during primary transit, which deserves further multicolor light-curve studies.

The BEST II telescope was used to search for stellar light variations within the Puppis (Pup) constellation close to the Galactic plane. Data collected in 61 nights between 2011 November 9 and 2012 April 6 were processed and comprehensively analyzed to classify all variable stars in the observed target field. We identified 2169 variable stars, including 1829 new, 26 previously known, and 314 suspected stars determining epoch, period, amplitude, and variability class. For the two previously known but unclassified variables NSV 3636 and NSV 3640, we were able to provide periods and classification as eclipsing binaries.

To verify the variable classification of our BEST II target field F20, we cross-matched it with the recently published Gaia DR2 information by producing a CDM wherein the different variability classes populate well-defined regions. This cross-match indicates that our classification is reasonable for eclipsing binaries, and less reliable for pulsating variables. However, no reliable statements are possible because of missing or systematic error-affected Gaia data. But, in general, it emphasizes that a classification of variable stars combining both photometric and astrometric information increases its accuracy.

In addition, we presented the light-curve modeling results for eight eclipsing binary systems, including NSV 3636 and NSV 3640.

Our variable star census is fully available in an online catalog that can be used for further studies. With the results reported here, the search for light variation by the BEST/BEST II telescopes has been completed and the project closed.

We thank Thomas Pasternacki for his efforts during the BEST II Field F20 observations. Sz.Cs. acknowledges participation to the Hungarian OTKA Grant K113117.

This work has made use of the 2MASS, GCVS catalog, the AAVSO variable star search index (VSX), and the data from the European Space Agency (ESA) mission Gaia, processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC has been provided by national institutions, in particular, the institutions participating in the Gaia Multilateral Agreement.