Документ взят из кэша поисковой машины. Адрес оригинального документа : http://www.sai.msu.su/gcvs/digit/mdv/MDV1.pdf Дата изменения: Tue Dec 6 17:53:44 2011 Дата индексирования: Tue Feb 5 16:10:48 2013 Кодировка: Поисковые слова: annular solar eclipse

ACTA ASTRONOMICA Vol. 58 (2008) pp. 279­292

New Variable Stars on Digitized Moscow Collection Plates. Field 66 Ophiuchi (Northern Half) D. M. K o l e s n i k o v a 1 , L. A. S a t 2 , K. V. S o k o l o v s k y S. V. A n t i p i n 2,1 and N. N. S a m u s 1,2
1

2, 3, 4

,

4

Institute of Astronomy, Russian Academy of Sciences, 48, Pyatnitskaya Str., Moscow 119017, Russia 2 Sternberg Astronomical Institute, Moscow University, 13, University Ave., Moscow 119992, Russia e-mail: lsat@inasan.ru, ksokolov@mpifr-bonn.mpg.de, antipin@sai.msu.ru 3 Astro Space Center of Lebedev Physical Institute, Profsoyuznaya 84/32, 117997 Moscow, Russia Currently at: Max Planck Institute for Radio Astronomy, Auf dem HЭgel 69, 53121 Bonn, Germany Received June 9, 2008

ABSTRACT We initiated digitization of the Moscow collection of astronomical plates using flatbed scanners. Techniques of photographic photometry of the digital images were applied, enabling an effective search for new variable stars. Our search for new variables a mong 140 000 stars in the 10 в 5 northern half of the field centered at 66 Oph, photographed wi th the Sternberg Institute's 40-cm astrograph in 1976­1995, gave 274 new discoveries, among th em: 2 probable Population II Cepheids, 81 eclipsing variables, 5 high-amplitude Sct stars (HADSs), 82 RR Lyr stars, 62 red irregular variables and 41 red semiregular stars, 1 slow irregular var iable not red in color. Ephemerides were determined for periodic variable stars. We detected about 3 0 variability suspects for follow-up CCD observations, confirmed 11 stars from the New Catalog of Susp ected Variable Stars, and derived new ephemerides for 2 stars already contained in the General Cat alog of Variable Stars. Key words: Stars: variables: general ­ Surveys

1. Introduction Regular photographic observations of the sky for variable- star studies started in Moscow in 1895. Since then, several different telescopes were used to take direct sky plates for astrometry and for astrophysics. The Moscow p late archive now contains more than 60 000 direct photographs and objective- prism plates taken in Moscow, at other sites in Russia, and at the Sternberg Institute's observatory in Crimea, Ukraine.


280

A. A.

The most important part of the Moscow plate collection are direct sky photographs acquired in 1948­1996 with a 40-cm astrograph. Thi s instrument was ordered by Prof. C. Hoffmeister for Sonneberg Observatory ( Germany) and first installed there in 1938. 1658 plates from this telescope, taken in 1938­1945, are kept in Sonneberg (the GA series of the Sonneberg plate colle ction). In 1945, the telescope was taken to the Soviet Union as a part of the World War II reparations. It was initially installed in Simeiz (Crimea), then brought to Kuchino near Moscow, and in 1958 became the first instrument of the Crimean Laborat ory of the Sternberg Institute in Nauchny, Crimea. The total number of plates taken with the 40-cm astrograph after 1948 is about 22 500. A single attempt of direc t comparison between Sonneberg and Crimean plates of the 40-cm astrograph at a bli nk comparator was undertaken in 1980s (Samus 1983). The field of view of the 40-cm astrograph is 10 в 10 , on 30 в 30 cm plates (the focal length is 1600 mm). The typical exposure time for the variable-star fields was 45 minutes. The limiting magnitude of good-quality plates is about 17.5 ( B ). The instrument was mainly used for variable-star studies, i ncluding search for new variables. For some fields, rich series of plates exist (up to 500 plates). For variable stars that can be found in several fields, sometimes as many as 1000 photographic plates are available. The list of fields, with numbers of plates obtained, can be found in Internet (http://cataclysm.sai.msu.ru/www/plates/40.dat). Plates are kept in good conditions, most plates, initially of excellent quality, are still perf ect . The Moscow plate collection, like other major astronomical plate collections of the world, has been actively used for scientific research f or decades. It still contains a large amount of significant information never use d by researchers, as indicated by discoveries of interesting events missed at the time of observation, like the discovery of Nova Aql 1985 (V1680 Aql) made 17 years later (Antipin et al . 2002) . Guaranteed conservation of the vast amounts of information contained in the plate collection and its use by means of modern methods of image processing require digitization of plate archives. This work commenced i n Moscow, in 2004, after the purchase of two Creo EverSmart Supreme II scanners . The initial digitization plans, along with a more detailed description of the Moscow plate archive from different instruments, were presented in Samus et al. (2006). Most plates from the 40-cm astrograph were taken for variabl e-star studies. It was natural to search for new variable stars using digital im ages obtained in the process of scanning the Moscow collection plates. In our first experiments, we discovered 38 new variable objects (mostly variable stars, but also extragalactic objects) on test partial scans (several square degrees) of s tar fields photographed with the astrograph (Sokolovsky 2006, Manannikov et al. 2006, Kolesnikova et al. 2007a,b). We introduced preliminary designations for vari able stars discovered in this program with the prefix MDV (Moscow Digital Variable).


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There were several other attempts to search for variable obj ects on digitized photographic plates. Among them are: a search for QSOs on the base of optical variability and zero proper motion criteria (Scholz et al. 1997, Brunzendorf and Meusinger 2001), a search for long-term variability using S onneberg archival patrol plates (Vogt et al. 2004), a search for novae in M31 using Tautenburg Schmidt pl a t e s ( H e nz e e t al . 2008) . In this paper, we announce the discovery and study of 274 new MDVs in the northern half of the field 66 Oph of the 40-cm astrograph. 2. Scanning and Reductions The field 66 Oph (18 h 00.m 3, +4 22 , J2000.0) was photographed with the 40cm astrograph in 1976­1995, a total of 254 plates were acquir ed. All these plates were scanned with a resolution of 2540 dpi (1. 2 per pixel), providing 14 bit per pixel per color. Color images produced by th e scanner were saved in the TIFF (RGB) format using the scanner software operatin g in the Mac OS X environment. In our further reductions, we made use only of t he green channel of each image, selected empirically. The files were then moved to a Linux server equipped with a 5 TB RAID array for storage and subsequent analysis. The images were converted to the FITS format using custom-written soft ware . In this paper, we present our analysis of the northern half of the field ( 10 в 5 ) containing about 140 000 stars within our detection limits (see below). The response to a point source of a given brightness on a large -scale photographic plate is a subject to strong spatial variations. Obv ious reasons for that include abberations in the optics of the astrograph (coma, v ignetting, etc.), inhomogeneity in photographic emulsion coating, and differences in airmass for stars in different parts of a plate. All these factors are expected to be relatively weak functions of coordinates on a plate. To overcome these complexities, the 10 в 5 field was subdivided into 72 nearly-square subfields. The influence of systematic factors is assumed to be the same for all stars in a given subfie ld. Each subfield was analyzed separately using VA S T software (Sokolovsky and Lebedev 2005), the results were combined at the final stage. For star detection and aperture photometry, VA S T uses the well-known S E X T R AC T O R code (Bertin and Arnouts 1996). All objects identified by S E X T R AC T O R as blended or non-point sources were excluded from further c onsideration because such sources produce many false detections in a variab ility search. Aperture photometry was performed with a circular aperture. The aper ture diameter was automatically selected for each image to compensate for seeing variations. This method was preferred against the variable elliptical apert ure photometry (parameter MAG_AUTO) enabled by default in S E X T R AC T O R, because the addition of extra


ftp://scan.sai.msu.ru/pub/software/tiff2fits http://saistud.sai.msu.ru/vast


282

A. A.

degrees of freedom (the aperture shape and size determined f or each star separately) deteriorates the quality of measurements of faint stars. T H E S E X T R AC T O R parameters and the aperture diameter were selected to optimize me asurements of stars in the 13.5­16.5 mag in (B) range. This magnitude range was preferred because brighter variable stars in this particular field have mostly been already discovered ґ in the ASAS-3 (Pojmanski 2002) and ROTSE-I/NSVS (Wozniak et al. 2004) CCD ґ surveys, both covering the near-equatorial field of our plat es. The VA S T code automatically matches stars detected on an image by S E X T R AC T O R with stars detected on the reference image using the techniq ue of the search for similar triangles. One of the best photographs wa s chosen as a reference image. Magnitudes of stars were measured by S E X T R AC T O R in an instrumental scale with respect of the background level of the current ima ge. All measured magnitudes were converted to the instrumental system of the ref erence image by approximating the relation between magnitudes on the current and reference images with a parabolic function. All stars matched on the images were used to establish this relation. Visual inspection confirms that this approxi mation works well in the required range of magnitudes. The resulting light curves are characterized by an rms error of 0.05­0.15 mag for stars in the 13.5­16.5 mag range. 3. The Method of the Search for Variability and Its Limitations A light curve of a variable star is, obviously, characterize d by a larger scatter of magnitude measurements compared to non-variable stars m easured on the same series of images. However, the precision of magnitude measurements for a particular star is a function not only of its brightness but of ma ny different factors, like the presence of close companions and image defects. That is why a variability search based solely on magnitude scatter as a function of a star's magnitude is inefficient, at least for noisy photographic data, and will result either in dramatic incompleteness or in a very large number of false "positive" detections. To deal with the problem, we extensively use time information contained in our data, as described below. The search for variability in a sample of light curves was con ducted in several steps. First, the relation rms deviation ­ instrumental magnitude was constructed for each subfield. Stars with rms deviations in excess of the average for their magnitudes were selected using a soft criterion. The second ste p was to study time series for each selected star for periodicities using a numb er of complementary algorithms: ­ Our own version of the Phase Dispersion Minimization algorithm, developed by one of the authors (D.M.K.). ­ An Analysis of Variance (ANOVA, Schwarzenberg-Czerny 198 9, 1996) technique. We made use of the C code from D E B I L package (Devor 2005) implementing this algorithm.


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­ Box Least Squares algorithm (KovАcs et al. 2002) originally developed for search for transiting extrasolar planets. This algorithm h as proven to be useful in identifying Algol-type variables among photographic light curves. The listed algorithms provide means to judge on the statistical significance of detected periodicities. The period significance cut-offs for candidate selection were chosen for each algorithm using a number of previously found variable stars. Along with the periodicity search approach, we used the vari ability detection algorithm proposed by Welch and Stetson (1993) to search for slow (compared to typical time sampling of our photographic light curves) non -periodic brightness variations which are often found for post-AGB and AGB stars a nd for active galactic nuclei. This technique was used mostly as a complementary one but not as a main candidate-selection method. Surprisingly, we found that slow irregular variables could often be detected by spurious periodicities found by period-search techniques even if the light variations are non-periodic. These false periods are usually found around integer multiples of 1 day and they correspond t o beat frequencies between the typical light-curve sampling frequency and the characteristic frequency of real light variations. In such cases, visual inspection of a light curve readily reveals the true character of variability.

Fig. 1. The results of the search for variable stars in one of t he 72 subfields in the northern half of the 66 Oph field. Circled are the eight detected objects: No. 1 is V1077 Oph, No. 2, V2328 Oph, No. 3, MDV 92, No. 4, MDV 91, No. 5, MDV 72, No. 6, V940 Oph, No. 7, MDV 83, No. 8 is one of suspected variables for our future CCD studies.


284

A. A.

Fig. 1 shows the results of our variable-star search in a smal l subfield that gave 8 detections of variable stars (some of them known). Magnitudes of all detected variable stars were then convert ed to the B scale using a number of USNO-A2.0 stars (Monet et al. 1998). The relation between the instrumental magnitudes and the USNO-A2.0 B magnitudes for each subfield was, again, approximated by a parabolic function. This step was performed after the selection of variable-star candidates since possible errors on this stage could introduce additional noise into light curves. A sample calibration diagram for a subfield is displayed in Fig. 2.
17

16.5

16 USNO-A2.0 B magnitude

15.5

15

14.5

14

13.5

13 -15.6

-15.4

-15.2

-15

-14.8

-14.6

-14.4

-14.2

-14

-13.8

-13.6

-13.4

Instrumental magnitude

Fig. 2. A sample calibration curve for one of subfields. The da shed curve is the adopted magnitude calibration.

Having selected the candidates, we then studied their brightness variations using the W I N E F K software written by Dr. V.P. Goranskij and kindly made available to us. This software permits to view light curves, to look for periodicities using several well-known algorithms (Deeming, Lafler­Kinman, etc.), to search for second periodicities. Our final decision if an automatically selected candidate was a real variable star was made only after a visual inspection of its light curve. The described variability search technique has a number of l imitations. First, it is not particularly sensitive to irregular light variati ons on time scales shorter than the light curve sampling time. Objects showing this type of variability can be detected solely on the base of large magnitude rms deviations if a careful inspection of images does not reveal any reason why this particular star was measured with a much worse precision than other stars. Without an aid o f the period search


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technique, this results in a much worse detection probabili ty for such variations. No such objects were found in the field described in this paper. However, T Tau variables found during a special search in the field of V451 Ta u show exactly this behavior. The results of the variability search in the V451 Tau field will be discussed elsewhere. The second limitation results from the properties of the VA S T software. This software constructs light curves only for those stars detec ted on the reference image for which the total number of detections exceeds 30. This approach effectively avoids many false star detections (because of plate flaws, dust, and large grains of the emulsion) but remains sensitive even to the faintest stars visible on the plates. However, this makes us completely insensitive to any transient phenomena (Novae, dwarf nova outbursts, etc.) that can be present on the plates . 4. Results

As expected, we detected rather many known variable stars. T hey were analyzed along with the new variables (see below), but this paper deals with only those of them for which our results significantly correct or append published information. We have discovered a total of 274 new variable stars (MDV 39 ­ MDV 312). They are presented in Table 1. Among these stars, there are 2 p robable Population II Cepheids, 81 eclipsing variables, 5 high-amplitude Sct stars (HADSs), 82 RR Lyr stars, 62 red irregular variables and 41 red semireg ular stars, 1 slow irregular variable not red in color (MDV 80). Our phased photographic light curves of the new periodic var iable stars (with the exception of some of the red semiregular variables) can b e found at the web site of our team (http://www.sai.msu.su/gcvs/digit/mdv/). Fig. 3 shows, as an example, the first eight phased light curves. Fig. 4 is the light curve of MDV 80. The observations of all the new variable stars are also avail able at our web site (http://www.sai.msu.su/gcvs/digit/mdv/data/).
B
15.6 15.9 16.2 16.5 0 0.5 1

MDV40 RRAB 0.759705

B
14.6 14.8 15 15.2 15.4

MDV41 RRAB 0.734964

B
15.4 15.6 15.8 16

MDV43 EB 0.528001

B
15.4 15.6 15.8

MDV45 EW 0.381209

0

0.5

1

0

0.5

1

0

0.5

1

B
15.6 15.8 16 16.2 16.4

MDV46 RRAB 0.404791

B
15.6 15.8 16 16.2

MDV47 EW 0.383012

B
15 15.5 16

MDV49 RRAB 0.612771

15.4 15.6 15.8 16 16.2 0 0.5 1 0 0.5 1

B

MDV51 RRAB 0.676667

0

0.5

1

0

0.5

1

Fig. 3. Sample phased light curves for the new regular variab le stars. Only the first 8 light curves are shown.


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Table1
New Moscow Digital Variables

A. A.

MDV 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 0 0 0 0 0 0 0 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7

Coord. (J2000)
h 40m 07. 8 s h 40m 29. 7 s h 40m 35. 5 s h 41m 18. 8 s h 42m 13. 9 s h 42m 21. 2 s h 42m 44. 8 s h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h

GSC / USNO-A2.0 A A A G A G A A A G A G A A G A A A G A G A A A A A G A A A A G G A A A A G A A A G A A A A A A A A A G G A G A A G A A A A A A A A A A 20 20 20 SC 20 SC 20 20 20 SC 20 SC 20 20 SC 20 20 20 SC 20 SC 20 20 20 20 20 SC 20 20 20 20 SC SC 20 20 20 20 SC 20 20 20 SC 20 20 20 20 20 20 20 20 20 SC SC 20 SC 20 20 SC 20 20 20 20 20 20 20 20 20 20 900-10266740 900-10281306 900-10285157 00423-01670 900-10351850 00423-00845 900-10372558 900-10385352 900-10416750 00424-00974 975-09664523 00424-00684 900-10497630 900-10509345 00428-00825 975-09739370 900-10583670 900-10584141 00428-01925 900-10597576 00428-00148 975-09759232 975-09761937 900-10611848 975-09777699 900-10627092 00428-00414 900-10653069 900-10656595 900-10697991 975-09829154 00428-01901 00994-01460 975-09851918 975-09853705 900-10744203 975-09859679 00424-00123 900-10756126 975-09867207 900-10760510 00424-01416 975-09878755 900-10781877 900-10786611 975-09887194 900-10800230 900-10808592 900-10763277 900-10812302 900-10823986 00429-02191 00429-02060 900-10847301 00429-01936 975-09945912 900-10874520 00425-01277 900-10884039 975-09978626 975-09980031 900-10928663 900-10939727 975-09994108 900-10948278 975-10003602 900-10962191 975-10012892

t ype LB RRA B RRA B SR: EB SRB EW RRA B EW LB RRA B LB RRA B SRB EW EW RRA B EW SR: EA EB RRC RRA B LB RRC: RRA B SRB: RRA B EW RRC SRB LB RRA B: RRC H AD S LB RRA B LB RRC EW EA L RRC RRC EW EW RRC SR: RRA B RRC EW EW LB RRC L B: RRA B RRA B CWB: RRA B RRC EB RRC EW RRA B RRA B: EW SR CWA:

max-min-min II 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 6 5 4 5 5 4 5 5 5 5 4 4 5 5 5 4 6 5 4 6 4 5 4 5 4 5 5 4 5 5 5 5 5 4 5 5 4 5 5 5 5 4 5 6 5 5 5 5 6 5 4 4 5 5 5 5 5 5 5 5 4 4 5 5 5 5 5 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 6 6 1 6 8 4 7 7 7 8 0 6 4 2 9 1 7 9 0 5 8 8 4 7 6 1 1 9 4 8 0 2 9 3 5 2 1 1 0 0 0 4 0 4 7 9 8 1 7 4 2 2 5 0 2 4 1 7 9 9 2 3 4 9 7 7 4 -16 -16 5-1 -15 -16 -15 -15 -16 -16 -16 -16 5-1 -16 -16 -15 -15 -17 5-1 -15 -16 5-1 -16 -16 -16 -15 -16 5-1 5-1 -16 -16 -16 -15 5-1 5-1 -15 -16 -15 -16 -15 -15 -15 -14 -15 -16 5-1 -16 -16 -16 -16 -16 -14 -14 -16 -15 -15 -16 -16 -15 -16 -16 5-1 5-1 -15 -16 -16 5-1 -16 -15 .6 .3 5. .6 .0 .1 .7 .3 .2 .8 .0 4. .2 .1 .8 .4 .0 6. .2 .5 5. .2 .0 .0 .2 .4 5. 4. .2 .0 .2 .7 5. 5. .9 .1 .6 .1 .7 .6 .6 .5 .8 .4 5. .0 .2 .4 .6 .2 .9 .6 .0 .9 .4 .1 .2 .6 .7 .4 5. 4. .9 .3 .2 6. .4 .8 5 3 -15.85 5 5-15.7 5 -16.2

epoch JD24... max max m in m in max m in max 4 4 8 4 7 .2 8 0 4 2 9 0 2 .5 1 2 4 4 4 9 1 .2 5 6 4 3 2 8 2 .4 5 2 4 3 2 8 5 .4 9 3 4 2 9 5 7 .4 6 9 4 2 9 2 2 .4 9 0 4 4 0 7 2 .3 9 1 4 4 4 4 4 4 4 4 2 4 3 4 6 5 2 2 8 0 2 0 3 9 9 8 7 2 8 2 4 4 3 9 6 7 3 5 4 1 3 2 . . . . . . . . 5 4 4 4 2 3 4 5 2 5 4 3 7 1 7 2

period 0 .7 5 9 7 0 5 0 .7 3 4 9 6 4 0 .5 2 8 0 0 1 0 .3 8 1 2 0 9 0 .4 0 4 7 9 1 0 .3 8 3 0 1 2

rem. 1

1 1 1 1 1 1 1

4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5

3 3 5 5 5 5 6 7 7 8 8 8 8 8 8 8 8 9 9 9 9 9 0 0 0 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 5 5 5 5 5 5 5 5 6

m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m

0 5 1 1 4 5 1 2 5 0 0 2 2 3 3 4 5 1 1 3 4 5 4 5 5 2 3 3 4 4 5 5 0 0 2 2 3 3 4 5 0 0 0 2 3 4 5 5 2 2 2 3 1 1 2 3 3 4 5 5 0

4 2 3 8 9 7 5 3 5 9 9 3 9 4 4 0 0 1 1 7 6 1 6 0 6 3 4 7 5 8 4 9 2 5 4 4 1 7 0 3 4 4 8 2 2 4 0 2 3 3 4 4 2 4 2 4 6 4 0 9 5

s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s .

4 9 6 1 5 4 3 2 0 0 7 1 2 3 5 0 0 1 1 2 7 6 7 7 8 4 6 9 0 7 8 6 9 1 0 7 5 2 5 8 0 7 4 2 3 1 5 7 4 4 0 5 1 2 7 5 0 1 9 5 8

3 9 0 7 5 5 6 8 6 7 4 7 0 5 6 7 7 4 1 6 3 7 2 5 1 1 5 7 7 6 6 2 6 3 0 2 8 3 9 2 3 9 5 0 6 7 4 3 7 6 9 4 0 7 7 2 5 7 4 5 5 9 4 1 4 5 8 1

+4 +6 +6 +3 +5 +4 +4 +6 +6 +5 +8 +5 +5 +6 +6 +8 +5 +6 +6 +5 +6 +8 +8 +5 +8 +6 +6 +5 +7 +6 +7 +6 +8 +7 +8 +3 +9 +5 +3 +8 +4 +4 +9 +5 +7 +8 +4 +6 +6 +4 +4 +6 +7 +7 +6 +8 +6 +5 +4 +8 +7 +4 +7 +9 +5 +8 +4 +8

24 28. 0 55 42. 1 17 00. 4 49 25. 6 42 45. 2 18 42. 2 46 37. 4

1, 2 3 1, 4

5 3 0 1 1 0 1 1 1 0 0 3 2 3 0 2 5 2 0 5 3 1 0 5 2 2 4 4 4 2 2 5 4 3 3 1 0 2 2 2 1 1 3 0 0 0 1 1 1 2 0 3 3 5 0 1 0 5 1 0 1

4 6 3 4 3 2 4 0 5 8 9 7 9 0 9 9 9 4 3 1 0 6 7 1 1 5 0 4 7 6 6 6 9 3 1 6 1 0 8 4 4 3 2 0 8 0 3 1 3 1 5 1 0 5 0 9 4 9 1 2 1



4 0 1 2 4 4 1 2 5 3 0 2 1 2 4 0 2 2 5 4 5 4 5 1 1 0 3 0 5 3 1 2 5 2 5 1 1 4 0 3 3 4 0 0 3 5 2 2 1 4 4 4 4 0 2 3 1 2 0 2 3

4 2 5 0 9 5 4 6 8 3 9 9 6 5 0 6 0 6 3 4 6 1 7 0 9 2 0 1 4 3 4 2 1 2 7 6 8 9 6 4 2 5 4 1 4 2 7 5 3 5 4 3 9 0 3 3 4 9 9 8 5

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 3 6 9 9 6 5 7 3 3 8 5 8 4 9 0 3 2 0 2 5 1 8 8 7 5 7 5 8 6 8 6 6 1 8 1 0 9 2 4 0 7 2 1 7 6 1 7 0 3 6 4 7 6 2 0 8 5 9 8 3

1 0 .6 1 2 7 7 1 5 max -15.7 -15.35 3-16.25 5 0-14.8 m in m in max m in m in m in max max max max 6 5 -16.2 max m in max 0 5 0 0 0 0 4 0 0 0 0 0 0 5 0 0 0 4 .6 7 8 .5 .3 5 .3 1 .6 4 .2 5 8: .9 8 .4 7 .3 1 .6 4 .4 4 .6 1 4 .9 .7 2 .3 7 .3 9 7: 6 : 3 5 1 4 9 3 0 0 3 4 : 1 8 2 667 1, 6 4 7 8 5 3 0 2 7 7 8 2 8 5 2 9 5 1, 7 8 45

3 12 52 39

0 63 96 99

4 3 2 5 3 .5 1 7 4 2 9 3 3 .4 5 2 4 2 8 7 2 .4 9 4 4 2 8 7 6 .5 6 2 4 3 7 0 2 .3 9 2

354 422 473 639 512

1 9 1

1, 10 5

7 5

max max max max max m in m in max max m in m in max max max m in m in max max max max max max m in max m in max max m in max

4 2 9 5 4 .3 2 2 4 4 0 4 3 .4 3 1 4 3 1 9 8 .5 9 8 4 3 7 0 0 .3 1 7 4 4 0 8 7 .4 0 7 4 3 1 9 0 .5 9 7 4 9 9 4 9 .3 3 5 4 4 4 4 4 4 4 4 4 4 2 2 4 2 2 3 4 6 0 8 8 0 8 8 2 0 9 8 7 9 7 7 7 8 1 7 7 1 4 7 5 6 9 2 3 . . . . . . . . . 4 5 5 3 5 5 3 4 3 0 1 2 6 6 6 9 8 2 7 5 5 0 3 2 3 0 2

0 .3 9 2 5 0 1 0 .3 2 2 9 0 2 0 .0 9 9 9 5 4 1 0 .4 8 7 9 6 1

11

1 -15.5 0 .3 1 8 2 4 0 0 .4 1 2 6 6 6 1 .6 8 1 4 9 0 0 0 0 0 1 0 0 0 0 .2 9 2 .3 3 6 .3 5 5 .4 2 9 .2 5 6 43: .5 8 4 .2 8 4 .6 7 7 .2 9 9 6 1 9 9 8 4 5 6 6 7 6 8 4 0 8 7 8 6 4 0 2 8 8 0 5 9 0 1 5 5 5 4 6 9 3 4 .4 2 5 4 4 4 4 4 4 4 4 4 4 4 4 2 6 6 2 3 6 4 3 5 2 4 9 9 6 8 4 9 3 2 9 9 9 2 7 1 9 2 7 9 5 4 6 1 2 9 8 4 6 2 7 3 1 3 . . . . . . . . . . . 2 4 4 4 5 2 3 4 5 3 3 5 9 6 6 2 2 1 1 1 1 3 6 0 5 5 6 6 5 7 2 2 0 .3 1 2 4 3 4 1, 13 0 0 4 0 0 0 0 0 0 0 0 1 1 .4 9 .6 0 .2 2 .5 5 .2 7 .5 8 .3 1 .5 4 .7 6 .9 4 .5 4 45 6 .5 2 3 8 5 4 0 2 5 1 5 2 6 4 5 5 0 9 4 4 5 8 0 4 7 8 1 5 1 2 2 3 3 9 2 0 7 14 7 6 8 0 2 5 5 5

5 9-15.9 5-16.0 5

8 12 9

1

5-14.9 5-14.6

25-15.1 8 -15.85

15

1-16.0

1

4 2 8 9 4 .5 3


Vol. 58
Table1
Continued

287

MDV 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8

Coord. (J2000)
h 56m 1 h 56m 4 h 56m 5 h 56m 5 h 57m 0 h 57m 3 h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h

GSC / USNO-A2.0 3 8 2 8 4 0 9 2 9 7 6 3 9 9 8 5 1 6 6 6 2 3 3 5 3 4 3 3 1 1 1 8 2 1 7 6 4 7 0 9 2 1 4 6 2 4 9 8 9 7 2 2 7 0 9 2 1 1 4 6 8 6 9 9 4 0 3 7 7
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

t ype H AD S LB RRC LB LB RRC: RRA B RRC: EW EB EB RRA B RRA B RRA B LB EB LB L B: LB EB EA RRC EA LB RRC RRA B EB LB EA SRB RRC EW LB RRA B SR: EW LB RRA B EA LB RRC: EW RRA B EW LB SRB: EB EW RRA B RRA B RRA B EW EW EW EB LB SRB LB EW LB LB EB LB LB SRB EW RRA B RRA B RRC

max-min-min II 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 4 4 5 4 5 5 5 6 4 5 3 5 5 5 5 4 5 5 5 5 5 5 5 4 6 5 5 5 4 3 5 3 4 5 4 5 5 4 5 5 6 5 4 5 4 5 5 6 4 4 4 3 5 4 5 5 3 5 4 5 4 5 4 4 4 5 5 5 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 7 7 6 8 5 8 1 9 9 6 1 3 6 9 4 7 0 4 4 3 6 0 3 0 0 5 2 8 7 3 7 6 4 8 0 1 4 5 5 2 3 4 6 5 2 6 0 0 8 6 8 1 0 8 0 9 4 2 2 7 6 6 6 9 1 1 2 2 5-1 -15 -16 -15 5-1 -16 -16 5-1 -15 -16 5-1 -16 -16 -16 -16 -14 -16 -15 -16 5-1 -15 -16 -16 -14 -16 -16 5-1 -15 -15 -14 -15 -14 -15 -16 -15 -15 -15 -14 -16 -16 5-1 -16 -15 5-1 -15 -15 -16 -16 -14 -16 -15 -14 -15 5-1 -16 -15 -14 -15 -14 -15 -15 -16 -15 -15 -15 5-1 -16 -16 -15 5. .3 .0 .1 6. .2 .6 6. .6 .5 4. .2 .0 .5 .5 .9 .3 .9 .5 5. .9 .2 .0 .7 .5 .0 6. .6 .4 .2 .9 .2 .0 .3 .3 .4 .5 .8 .4 .2 6. .1 .3 5. .0 .9 .1 .5 .9 .2 .5 .1 .6 4. .1 .5 .3 .8 .6 .8 .1 .2 .1 .1 .7 5. .1 .1 .8 3 5 3

epoch JD24... max max 4 3 2 4 9 .5 4 8 4 4 3 9 7 .4 1 5

period 0 .1 0 7 9 2 7

rem. 1

5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

7 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 0 0 0 0 0 0 0 0 0 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 4 4 4 4 4 4 4

m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m

4 4 4 5 0 0 0 0 2 2 2 3 3 4 4 5 1 1 1 1 2 2 2 3 4 4 0 0 0 1 3 3 3 5 5 0 0 0 1 1 1 1 2 2 3 4 4 5 5 5 0 0 1 2 2 5 0 1 2 3 3 4 5

7 1 0 6 1 2 2 4 6 8 1 5 7 9 1 2 8 4 4 0 8 9 1 2 5 9 2 9 9 9 7 8 0 3 7 2 2 7 7 6 9 0 5 3 1 2 3 4 3 9 6 1 9 4 7 9 5 7 0 4 4 1 4 6 2 4 9 3 1

s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s . s .

8 0 8 5 5 5 6 8 8 8 2 4 9 4 3 5 5 1 7 0 4 3 5 1 9 7 5 3 4 8 7 5 7 7 8 4 6 0 8 8 3 8 6 9 4 5 5 0 1 4 9 8 9 9 0 8 9 1 5 1 6 4 7 5 4 1 6 4 2

8 5 7 3 7 3 6 4 2 9 9 1 4 4 6 5 8 0 3 5 6 0 8 8 5 1 0 6 1 1 6 1 5 1 2 9 8 1 3 5 8 3 0 3 2 0 4 3 4 7 8 5 8 0 7 0 8 7 2 3 7 8 0 3 3 2 2 3 4

+6 +5 +8 +4 +6 +5 +4 +7 +5 +4 +5 +9 +8 +8 +6 +5 +6 +6 +5 +4 +7 +4 +9 +7 +5 +7 +5 +4 +8 +4 +9 +8 +7 +4 +4 +6 +6 +8 +5 +9 +7 +4 +6 +7 +7 +6 +6 +8 +8 +7 +5 +4 +8 +6 +6 +7 +5 +4 +3 +5 +6 +8 +3 +8 +8 +4 +7 +5 +8

22 4 53 5 08 0 19 0 15 2 19 2

2 3 5 0 4 0 2 0 3 5 1 0 0 5 1 2 0 5 1 5 0 3 4 5 2 1 2 4 3 2 5 5 0 2 2 0 2 0 2 4 5 1 0 1 3 3 4 3 0 2 0 2 5 1 4 0 5 2 1 4 3 5 0

3 2 5 9 9 2 2 5 5 3 0 2 1 4 6 0 1 2 3 1 7 2 5 9 2 0 6 1 0 6 0 5 6 1 1 7 1 8 6 8 2 2 1 2 2 3 3 4 2 2 3 0 7 6 0 5 4 3 2 3 1 3 3



5 5 2 4 2 3 5 0 0 1 0 5 0 1 4 0 5 0 1 0 3 3 4 5 4 4 2 2 2 2 2 0 0 2 2 5 1 0 4 1 5 1 3 4 1 0 5 1 0 0 0 4 1 5 5 3 1 3 3 2 0 2 5

0 0 0 5 6 2 1 6 1 6 7 3 0 5 4 2 1 6 0 7 6 2 0 4 7 9 1 2 8 3 9 3 0 4 0 1 0 7 7 9 4 8 1 6 7 4 5 4 6 6 0 0 7 1 7 3 3 4 6 1 6 6 7 1 0 6 3 3 8

A G A G A A A A A A G A A A A G A G G A A A A G A A A G A G A G G A A A G G A A A A A A G A A A A A A G A A A G G A A G G A G G G A A A A

20 SC 20 SC 20 20 20 20 20 20 SC 20 20 20 20 SC 20 SC SC 20 20 20 20 SC 20 20 20 SC 20 SC 20 SC SC 20 20 20 SC SC 20 20 20 20 20 20 SC 20 20 20 20 20 20 SC 20 20 20 SC SC 20 20 SC SC 20 SC SC SC 20 20 20 20

900-1097