Eclipsing Binary Populations across the Northern Galactic Plane from the KISOGP survey
Fangzhou Ren, Richard de Grijs, Huawei Zhang, Licai Deng, Xiaodian Chen, Noriyuki Matsunaga, Chao Liu, Weijia Sun, Hiroyuki Maehara, Nobuharu Ukita, Naoto Kobayashi
DDraft version February 4, 2021
Typeset using L A TEX default style in AASTeX62
Eclipsing Binary Populations across the Northern Galactic Plane from the KISOGP survey
Fangzhou Ren,
1, 2
Richard de Grijs,
3, 4, 5
Huawei Zhang,
1, 2
Licai Deng, Xiaodian Chen, Noriyuki Matsunaga,
7, 8
Chao Liu, Weijia Sun,
1, 2, 3, 4
Hiroyuki Maehara,
9, 10
Nobuharu Ukita, and Naoto Kobayashi
8, 12, 13 Department of Astronomy, School of Physics, Peking University, Yi He Yuan Lu 5, Hai Dian District, Beijing 100871, People’sRepublic of China Kavli Institute for Astronomy and Astrophysics, Peking University, Yi He Yuan Lu 5, Hai Dian District, Beijing 100871, People’sRepublic of China Department of Physics and Astronomy, Macquarie University, Balaclava Road, Sydney, NSW 2109, Australia Research Centre for Astronomy, Astrophysics and Astrophotonics, Macquarie University, Balaclava Road, Sydney, NSW 2109, Australia International Space Science Institute–Beijing, 1 Nanertiao, Zhongguancun, Hai Dian District, Beijing 100190, People’s Republic ofChina CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101,People’s Republic of China Department of Astronomy, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan Laboratory of Infrared High-resolution Spectroscopy (LiH), Koyama Astronomical Observatory, Kyoto Sangyo University, Motoyama,Kamigamo, Kita-ku, Kyoto 603-8555, Japan Okayama Branch Office, Subaru Telescope, National Astronomical Observatory of Japan, NINS, Kamogata, Asakuchi, Okayama, Japan Okayama Observatory, Kyoto University, 3037-5 Honjo, Kamogata, Asakuchi, Okayama 719-0232, Japan Okayama Astrophysical Observatory, National Astronomical Observatory of Japan, 3037-5 Honjo, Kamogata, Asakuchi, Okayama719-0232, Japan Kiso Observatory, Institute of Astronomy, School of Science, The University of Tokyo, 10762-30 Mitake, Kiso-machi, Kiso-gun,Nagano 397-0101, Japan Institute of Astronomy, Graduate School of Science, The University of Tokyo, 2-21-1 Osawa, Mitaka, Tokyo 181-0015, Japan (Received February 4, 2021; Revised February 4, 2021; Accepted February 4, 2021)
Submitted to AJABSTRACTWe present a catalog of eclipsing binaries in the northern Galactic Plane from the Kiso Wide-FieldCamera Intensive Survey of the Galactic Plane (KISOGP). We visually identified 7055 eclipsing binariesspread across ∼
330 square degrees, including 4197 W Ursa Majoris/EW-, 1458 β Lyrae/EB-, and 1400Algol/EA-type eclipsing binaries. For all systems, I -band light curves were used to obtain accuratesystem parameters. We derived the distances and extinction values for the EW-type objects from theirperiod–luminosity relation. We also obtained the structure of the thin disk from the distribution ofour sample of eclipsing binary systems, combined with those of high-mass star-forming regions andCepheid tracers. We found that the thin disk is inhomogeneous in number density as a function ofGalactic longitude. Using this new set of distance tracers, we constrain the detailed structure of thethin disk. Finally, we report a global parallax zero-point offset of ∆ π = − . ± . ± . µ as between our carefully calibrated EW-type eclipsing binary positions and those provided by Gaia
Early Data Release 3. Implementation of the officially recommended parallax zero-point correctionresults in a significantly reduced offset. Additionally, we provide a photometric characterization of ourEW-type eclipsing binaries that can be applied to further analyses.
Corresponding author: Fangzhou Ren, Huawei Zhang, and Richard de [email protected]@[email protected] a r X i v : . [ a s t r o - ph . S R ] F e b F.-Z. Ren et al.
Keywords:
Eclipsing binary stars – W Ursae Majoris variable stars – Distance indicators – Milky Waydisk – Catalogs INTRODUCTIONEclipsing binary systems (EBS) exhibit optical variability because of geometric properties rather than intrinsic phys-ical changes. EBS encompass almost all stages of binary evolution, covering timescales as long as 1–10 Gyr. Thisexplains their large numbers in the Galaxy. EBS analysis offers a good opportunity to obtain precise fundamental phys-ical parameters from their system properties by means of photometric and/or spectroscopic observations—includingtheir periods and distances, as well as accurate parameters for their components, like masses and radii (e.g. Torreset al. 2010). This enables us to study unique aspects of their stellar evolution and stellar activity.EBS can be divided into three types based on their light curve shapes, i.e., Algol (EA)-, β Lyrae (EB)-, and WUrsa Majoris (EW)-type EBS. The total luminosity of EA-type EBS remains almost constant outside the eclipses. EBtypes exhibit a continuous change in their total brightness outside eclipses while the depth of the secondary minimumis usually considerably smaller than that of the primary minimum. Meanwhile, EW-type light curves are characterizedby a smooth shape with symmetric eclipses, and some evolved systems show sinusoidal-like shapes.EW-type EBS can also be used as reliable distance indicators within the Milky Way. Since their two components fillthe system’s Roche lobes, their overall visual magnitude is related to the system’s orbital period (based on Roche lobetheory), which leads to a well-defined period–luminosity relation (PLR). Rucinski (1994) derived the first calibrationof such a PLR based on 18 systems, which they eventually improved to an accuracy of 12% (Rucinski & Duerbeck1997). Recently, Chen et al. (2018a) established PLRs in 12 optical to mid-infrared passbands based on Tycho–
Gaia astrometric solution (TGAS) parallaxes, reaching an improved accuracy of 8%. PLRs provide us with a means todetermine the distances to EW-type EBS using only photometric light curves. Therefore, as one of the most numeroustypes of variable systems, EW-type EBS could be used as important Galactic distance tracers (Matsunaga et al. 2018).Observations of EBS have a long history. Many ancient cultures observed eclipsing systems (e.g. Jetsu et al. 2013). Inmodern astronomy, early-20th century measurements of both EBS and other variables were usually reported in papersdiscussing individual objects. After the 1980s, large surveys commenced, including the MAssive Compact Halo Objects(MACHO) survey (Cook et al. 1995) and the Optical Gravitational Lensing Experiment (OGLE; Graczyk et al. 2011;Pawlak et al. 2013; Pietrukowicz et al. 2013; Pawlak et al. 2016; Soszy´nski et al. 2016). The number of known EBSand other types of variable stars hence experienced a period of explosive growth. With the development of wide-fieldcameras, surveys that constantly monitor the entire accessible sky photometrically became commonplace, e.g. theAll Sky Automated Survey (ASAS; Pojmanski 1997; Paczy´nski et al. 2006) and the Robotic Optical Transient SearchExperiment (ROTSE; Akerlof et al. 2000), part of the Northern Sky Variability Survey (NSVS; Akerlof et al. 2000;Wo´zniak et al. 2004; Hoffman et al. 2008, 2009). In the near-infrared (NIR), the VISTA Variables in the V´ıa L´actea(VVV) Survey offers a less severely reddened window into EBS projected toward the Galactic Center (e.g. Minniti et al.2010; Alonso-Garc´ıa et al. 2015). In addition, some all-sky surveys, such as near-Earth object (NEO) surveys whoseprimary goal is to detect near-Earth asteroids and comets, are also well suited to discover and characterize variableobjects, including EBS. This way, candidates from the Lincoln Near-Earth Asteroid Research (LINEAR; Palaversaet al. 2013), the Catalina Sky Surveys (CSS; Drake et al. 2014, 2017), the Asteroid Terrestrial-impact Last AlertSystem (ATLAS; Heinze et al. 2018), the All-Sky Automated Survey for Supernovae (ASAS-SN; Kochanek et al. 2017;Jayasinghe et al. 2018), and the Wide-field Infrared Survey Explorer (WISE; Chen et al. 2018b) have been identified.Although the accumulation of EBS has multiplied, many previous surveys have avoided targeting the Galactic planedue to the high extinction there compared with less obscured regions. The few available surveys of the Galactic planetend to cover only a few degrees in Galactic latitude (e.g. Haas et al. 2012; Hempel et al. 2014). Measurements ofEBS are still lacking in the Galactic disk, particularly in the Galactic Anti-center direction. However, understandingthe formation and evolution of the Galactic disk, as well as its structure, is a key open issue, since in principle wecan investigate our own Galaxy’s structure in much greater detail than that of any other galaxy, thus providing abenchmark for understanding external galaxies.In this paper, we have collected the light curves of eclipsing binary candidates from the Kiso Wide-Field Camera(KWFC) Intensive Survey of the Galactic Plane (KISOGP), specifically in the northern Galactic Plane, and classified7055 EBSs. In Section 2, we discuss our data reduction procedures, the classification pipeline, and several parameterdistributions, e.g. of periods, magnitudes, and eclipse depths. We also discuss the quality of our EBS sample’s light clipsing Binaries in the Northern Galactic Plane
Gaia
Early Data Release 3 (eDR3) parallaxes derived from our EW-type analysis. Section 4concludes the paper. DATA REDUCTION AND RESULTS2.1.
Sample Selection
The catalog was compiled from observations taken as part of the KISOGP survey (Matsunaga 2017), acquired withthe KWFC on the Kiso 105 cm Schmidt telescope at Kiso Observatory, Japan. The KWFC has been designed forwide-field observations, taking advantage of the Kiso Schmidt telescope’s large focal-plane area. It mosaics eight CCDchips with 8k ×
8k pixels in total and covers an area of 2.2 ◦ × ◦ . Typically, for any object, more than 200 exposureswere acquired in the I band to a depth of I = 9 . ◦ to 210 ◦ in Galactic longitude, and from − ◦ to 1 ◦ in Galactic latitude. The region 70 ◦ < l < ◦ , ◦ < b < ◦ is also covered. (For the relevant maps and pointings,see Figure 1 of Matsunaga 2017).For each epoch, a 5 s exposure and three 60 s exposures are taken to optimally cover the full magnitude range. The5 s exposure is suitable for stars at the bright end ( I ∼ I = 11 mag down to I = 17 mag. A reference target list was established by combining all epochs. Candidatevariable stars were selected by considering three variability indices, including interquartile ranges, weighted standarddeviations, and von Neumann ratios (Sokolovsky et al. 2017). Among ∼ Eclipsing Binary Selection
To properly identify EBS, high-quality folded light curves are needed. The basic idea is to determine optimallyconstrained periods of variability. We adopted the Lomb–Scargle (LS) periodogram (Lomb 1976; Scargle 1982) andString–Length (SL) methods (Lafler & Kinman 1965; Clarke 2002) to obtain optimal periods for all candidates.The input periods ranged from 0.08 to 10 days in steps of 0.00001 days (for the LS method). The short-period limitfor known EW types is 0.16 days (Soszy´nski et al. 2015). Ultra-short-period EW types, which usually contain highlyevolved stars, usually exhibit sinusoidal-like light curves. In this situation, the primary and secondary minima mayhave similar depths. They are often misidentified as the same feature in phased light curves. This will result in anoutput harmonic or aliased period of the true period, where P output / P true is a ratio of integers, usually 1:2. For thisreason, we start at one-half of 0.16 days. Any harmonic period found will be corrected during our subsequent visualdetermination by multiplying the period to make sure that two eclipses occur within a single period.To further improve the accuracy of our period determination, the SL method was applied to the output periods fromthe LS method. We tried 2000 periods within 0.0002 days around the output period. This led to an improvement inthe fifth decimal place: the majority of our EBS (64.1%) have periods with errors smaller than 1 × − days. Theoutput periods will be used as input periods for our visual verification.2.3. Visual Verification
Armed with the periods thus determined, a visual check was done of the photometric parameters and type determi-nation based on phased light curves. EBS candidates were selected based on visual examination of their light-curvemorphology. We removed all objects classified as other types of variable stars, such as RR Lyrae, Cepheids, non-periodic variables, etc. Meanwhile, a visual check of the period (particularly for those objects for which we needto multiply the period to encompass two eclipses within a single period), a visual determination of the phase of theprimary eclipse (which will be shifted to 0 and represents t ), the system’s magnitude outside the eclipse, and theprimary and secondary eclipses were done. Subsequently, the objects’ types were determined.The order in which we examined the candidates was random, and all objects were processed randomly three times.If a system’s type determination was the same and the standard errors of the parameters were less than 0.02 mag or F.-Z. Ren et al. -0.2 0 0.2 0.4 0.6 0.8 1 1.2 phase m agn i t ude KISOJ214941.10+541354.2 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 phase m agn i t ude KISOJ201901.56+344325.1 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 phase m agn i t ude KISOJ041556.86+503217.4
Figure 1.
Examples of EA-, EB-, and EW-type EBS (left to right).
Table 1.
Eclipsing Binaries Catalog
ID Exposure Type Period err P t I max I pri I sec Ratio Distance A V ∆ m days 10 − days days mag mag mag kpc mag magKISOJ000009.94+612905.2 264 EA 1.4418015 67 56167.64799 13.660 14.039 13.833 0.456 ... ... ...KISOJ000010.73+621848.8 189 EW 0.3890992 38 56167.69297 15.414 15.562 15.538 0.838 2.387 0.860 0.021KISOJ000017.82+625339.6 184 EB 0.5820739 23 56167.31869 15.552 15.960 15.754 0.495 ... ... ...KISOJ000026.19+632139.0 43 EW 0.3180290 393 56175.60476 16.333 16.856 16.804 0.901 2.298 1.469 0.422KISOJ000039.63+622214.1 174 EW 0.2859520 1 56167.59347 16.137 16.458 16.390 0.788 1.646 1.778 0.253KISOJ000048.17+614603.1 178 EW 0.3024461 1 56167.77640 16.016 16.732 16.637 0.867 1.352 2.612 0.705KISOJ000053.24+613059.8 256 EW 0.2826091 1 56167.60270 16.093 16.441 16.378 0.819 1.747 1.497 0.041KISOJ000056.84+625228.4 267 EW 0.5717867 12 56167.37203 14.228 14.445 14.440 0.977 1.986 1.657 0.158KISOJ000111.08+625139.7 113 EB 1.0133044 1 56167.36126 16.160 16.758 16.492 0.555 ... ... ...KISOJ000112.76+623859.7 296 EA 1.3701021 99 56167.30771 14.589 14.835 14.819 0.935 ... ... ...KISOJ000123.66+613746.8 230 EW 0.3871284 8 56167.49329 15.738 16.049 16.004 0.855 3.088 0.401 0.153KISOJ000132.54+615234.2 78 EW 0.3660444 36 56251.31592 16.772 17.107 17.092 0.955 3.148 1.900 0.177KISOJ000135.90+624456.3 171 EB 0.7391682 1 56167.17345 16.514 16.946 16.700 0.431 ... ... ...KISOJ000138.55+615348.4 186 EA 0.7856778 147 56167.74912 12.237 12.485 12.405 0.677 ... ... ...KISOJ000145.92+614214.0 265 EB 0.3333018 2 56167.67988 12.087 12.746 12.382 0.448 ... ... ...KISOJ000208.16+630633.5 311 EW 0.3092946 1 56167.58121 12.957 13.164 13.141 0.889 0.577 0.639 0.080KISOJ000210.22+611924.2 175 EW 0.4997257 21 56167.51962 16.190 16.413 16.371 0.812 3.863 1.878 0.013KISOJ000233.43+614514.3 167 EW 0.3152875 1 56167.71510 16.774 17.297 17.199 0.813 3.119 1.019 0.060KISOJ000240.13+622844.5 285 EW 0.4282596 3 56167.75852 14.515 14.622 14.618 0.963 1.645 1.237 0.094KISOJ000250.76+624850.0 169 EW 0.2579880 407 56175.50704 15.813 16.165 16.162 0.991 1.330 1.441 0.060 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · Note —This table is available in its entirety in machine-readable form. t in units of the modified heliocentric Julian date (HJD-2400000.5; which sets the primaryeclipse at phase zero), the maximum magnitude outside eclipses, the magnitudes of both eclipses within one periodin the I band, and the depth ratio of the two eclipses. The objects’ distances, extinction values in the V band forEW-type systems, and the magnitude differences in the Two Micron All Sky Survey (2MASS; Skrutskie et al. 2006)photometric system will be described in Section 3.1.2.4. Distribution Map
The parameter distributions for all EBS are shown in Figure 2. Red points or bars represent EW types, while blackand blue symbols correspond to EB and EA types, respectively.The EBS distribution as a function of Galactic longitude is shown in Figure 2a. It is inhomogeneous in numberdensity. This inhomogeneity is caused by the presence of groups of stars associated with the Galaxy’s spiral arms,including the Orion Spur and the Perseus Arm. Since EBS variability is caused by the systems’ geometry, independently clipsing Binaries in the Northern Galactic Plane
60 80 100 120 140 160 180 200
Galactic longtitude(l) -10123 G a l a c t i c l a t i t ude ( b ) (a) Primary eclipse depth (mag) I ( m ag ) (f) I-Ks (mag) J - K s ( m ag ) (g) Figure 2.
EBS distributions. Red, black, and blue points and bars represent the 4197 EW-, 1458 EB-, and 1400 EA-typeEBSs, respectively. The green points with error bars in panels (f) and (g) indicate the representative error bars pertaining to allsamples in the respective panels. (top) Positions of all EBS in Galactic coordinates (in units of degrees). (middle left) Periods(logarithmic units). (middle center) Primary eclipse depths ( I mag). (middle right) Ratios of secondary to primary eclipses.(bottom left) Magnitudes outside eclipses (total EBS magnitudes in the I band). (bottom center) Scatter of the total I -bandmagnitude over primary eclipse depth for each EBS. (bottom right) Color–color diagram ( I − K s vs J − K s ; with J and K s magnitudes from 2MASS). of any other criteria associated with object position or selection bias, the EBS distribution is representative of thegeneral distribution of stars in the Galaxy (Rucinski 2006). Extinction also plays an important role in the observedinhomogeneity, since dust obscuration and scattering have a significant effect on stars in the Galactic plane. Onlynearby stars can be seen projected toward the most obscured regions. We will return to the inhomogeneous distributionof EBS in Section 3.2.There are obvious period differences among the three types of EBS in Figure 2b. EA types have the longest periods,ranging from 0.3 to 10 days, with a peak at several days. EW types have the shortest periods, i.e., shorter than one F.-Z. Ren et al. day; most EW types have periods around 0.3–0.5 days. Both the period range and the peak period of EB types arefound in the middle of the three types. Their period distribution also depends on their environment. EBS in theGalactic plane are thought to be less evolved and have longer periods than those outside the thin disk, since they areusually younger. This is shown in the left panel of Figure 3; see Section 2.5 for a discussion.For EA types, extremely wide period ranges have been reported in the literature (e.g. Graczyk et al. 2011), reachingup to thousands of days. Our detection approach prevents us from detecting such long-period variables. We areconstrained to a longest period of 50.22 days. For EA types with longer periods, it will be harder to fully cover theeclipses to identify their types. However, instead of continuous monitoring, only a few epochs are taken during agiven night for each object in our survey, which makes it harder to completely cover their full eclipses. Some EA-type candidates with extremely long periods may only have a few detections during their eclipses. The numbers ofdetections may be insufficient to characterize such an eclipse, and so such samples would fail to pass our selectioncriteria. Therefore, our catalog lacks long-period EA-type EBS.No clear differences in the distribution of the primary depths can be seen, but the distribution of the eclipse-depthratios varies significantly among the different EBS types (see Figure 2c-d). A clear plateau can be seen in the histogramof the eclipse-depth ratios of EA-type EBS between 0.1 and 1. Secondary eclipses may not be visible if the stars areconsiderably different in size. It is impossible to distinguish EA types with an invisible secondary eclipse from EBSfeaturing a double period characterized by similar eclipses solely based on light curves. This may be the reason forthe lack of a plateau at the shorter end of the eclipse-depth distribution. Nevertheless, the observed distributionunderscores that the EA-type eclipse-depth ratios are randomly distributed, while the ratio of EW types is close tounity, as expected.The histogram of the magnitudes outside eclipses, the scatter in magnitude during the eclipses, and a color–colordiagram exhibiting a roughly linear relation for all types of EBS are shown in Figure 2e-g. The lack of faint EBSwith shallow eclipses is caused by selection effects. Faint systems with shallow eclipses, whose magnitude errors duringevery single epoch are comparable to the eclipse depth, would not pass our selection procedure.2.5.
Possible Contamination by Other Variables
We selected our EBS sample using the same method as that proposed by Chen et al. (2020). Contamination of oursample by non-binary objects is less than 1%, based on careful visual examination. Since different types of variablesexhibit different kinds of light curves, it is easy to distinguish EA- and EB-type EBS from other types of variables, evenwithout access to any color information. RRc Lyrae and EW-type EBS have similar periods and amplitudes. An RRcLyrae light curve with a nearly symmetric luminosity decrease may be misclassified as an EW-type EBS characterizedby two similar-depth eclipses at double the RR Lyrae’s period. As such, RRc Lyrae are the main possible contaminant.Here we evaluate the likely level of this type of contamination.
Figure 3.
Assessment of the possible contamination caused by RRc Lyrae. (left) EW-type color–period distribution. Green:Our EW-type sample objects; black and red: RRc Lyrae and EW-type systems, respectively, from Palaversa et al. (2013).(right) Skewness distribution of our sample. clipsing Binaries in the Northern Galactic Plane J − K s colors as green points (the extinction values were taken from Section 3.1),as well as the LINEAR RRc Lyrae and EW types (black and red points, respectively). Since all LINEAR objects arelocated at high Galactic latitude ( b > ◦ ), their extinction values are negligible in J − K s . Among our LINEARobjects, RRc Lyrae are generally bluer than EW-type EBS. Our EW-type sample objects are scattered from the top tothe right section of the color–period plane, where we see little contamination by RRc Lyrae; they match the LINEAREW types well. The skewness distribution is shown in the right panel. The adopted boundaries of the skewness, basedon the LINEAR sample, are − . − . DISCUSSION OF OUR EW-TYPE SAMPLE OBJECTS3.1.
Extinction and Distance
Lucy (1968a,b) proposed convective common-envelope evolution as the key idea underlying EW-type theory. Themodern model (Stepie´n 2006a; Yildiz & Do˘gan 2013) suggests that EW types form through both angular-momentumloss and nuclear evolution. EW types are in their late stage of evolution, and it has been shown observationally thatboth components have similar temperatures. EW-type binaries usually form a common envelope and they can thusbe regarded as a single structure. In the color–magnitude diagram, they appear as objects close to the main sequence(MS), although one or both components may be more advanced in their evolution (Stepie´n 2006a,b, 2009, 2011).Among stars in the Galactic disk, EW-type objects are usually found in old open clusters. Meanwhile, as one of themost numerous types of variables in the Galactic field, they can potentially be used to determine the Galactic disk’sstructure above and below the Galactic plane and to trace any age gradient across the plane (Chen et al. 2018a).However, studies of the distribution of EW-type systems in the Galactic plane are limited. With our sample, we cannow partially fill in the blanks.Since the publication of Eggen (1967), a number of attempts have been made to use EW-type period–luminosity–color relations as potential distance indicators. Rucinski made several attempts to derive PLRs from nearby EWtypes (Rucinski 1994), EW types with
Hipparcos parallaxes (Rucinski & Duerbeck 1997), ASAS catalogs (Rucinski2006), and TGAS parallaxes (Mateo & Rucinski 2017). To unify the PLRs obtained from different bands, optical-to-mid-infrared PLRs from Chen et al. (2018a), based on 183 nearby EW-type systems with TGAS parallaxes, wereadopted.Note that our sample objects are located in the Galactic disk, where the extinction is high and varies significantly.Although the KISOGP survey can efficiently reduce the impact of extinction in the I band compared with that in V band, extinction is expected to still have a sizeable effect on the resulting photometry.To derive accurate distances, we considered distance moduli ( µ ) and extinction values ( A λ as a function of passband, λ ) as variable parameters, i.e. m λ − a λ × log P − b λ = ( A λ /A V ) × A V + µ . (1)For a given passband λ , we take the PLR coefficients a λ and b λ from the maximum-magnitude coefficients of thePLRs of Chen et al. (2018a); the extinction law, A λ /A V , from Wang & Chen (2019); and the period, log P , from Table1 in Section 2.3. For the apparent magnitude, m λ , we adopt the maximum I -band magnitudes from Table 1, combinedwith JHK s -band data from 2MASS. However, 2MASS only provides single-epoch photometry, as well as a time stampfor the observation. Since observed color changes are very small during eclipses, the light-curve shape barely changesamong the different bands (Chen et al. 2016). This makes it possible to convert the single-epoch magnitudes to thecorresponding maximum magnitudes obtained from the full I -band light curves. The differences between the I -bandmagnitudes in the observational phase and the maximum I -band magnitudes are listed in Table 1. These photometricproperties also allow us to convert the 2MASS single-epoch photometry to the maximum JHK s -band magnitudes. F.-Z. Ren et al.
Armed with known or newly determined parameters pertaining to the
IJHK s bands, it is now possible to fit the( µ , A V ) combination for each system; for an example, see Figure 4. A similar method has been adopted by otherauthors (e.g. Madore et al. 2017). A /A V d i s t an c e m odu l u s ( m ag ) y=1.968x+11.329 Figure 4.
Example of our determination of extinction and distance. The intercept corresponds to the distance modulus, µ = 11 .
329 mag, while the slope reflects the extinction in the V band, A V = 1 .
968 mag.
In this example, the slope corresponds to the V -band extinction, A V , and the intercept is the best-fitting distancemodulus, µ . Since the PLR was fitted only to EW-type objects, our results are based on 3996 objects, having firstexcluded systems without 2MASS observations. The best-fitting distances and extinction values are listed in Table1. For some sources affected by low extinction, negative slopes implying negative extinction may result for numericalreasons; in those cases we set the extinction to zero.As an independent means to determine distances, EW-type PLRs have a wide variety of uses, including as a probesto map the structure of the Galactic plane and as benchmarks to crosscheck other means of distance determination.3.2. Mapping the Galactic Thin Disk Structure with EW types
Equipped with distance estimates from our PLR application, it is now feasible to derive the structure of the northernGalactic plane as traced by EW-type EBS. To minimize selection effects, we excluded KISOGP objects located at70 ◦ < l < ◦ , ◦ < b < ◦ to retain a uniform distribution across − ◦ < b < ◦ of the thin disk.The spatial and extinction distributions of EW-type tracers derived from application of the PLR are shown in thetop panel of Figure 5. Different colors represent different extinction values; all objects affected by A V ≥ A V = 2 mag, while objects in more distant regions are significantly more highly obscured. The spatialdistributions defined by different tracers, as well as that traced by our EW types, are shown in the bottom panel ofFigure 5. Members of high-mass star-forming regions (HMSFRs; Reid et al. 2014), Galactic Cepheids (Genovali et al.2014), and the 478 EA- and 454 EB-type objects from Table 1 with accurate Gaia parallaxes (0 < σ π /π < .
1) areshown as magenta diamonds, red circles, and cyan and black triangles, respectively. EW-type systems with distancesobtained from the PLR are also shown in the density map. The density map was constructed using MathWorks’‘scatplot’ tool , while colored data points and contours were plotted using Voronoi cells to determine the relevantdensities. Members of all groups are dispersed in the same region across the northern Galactic thin disk.The density distributions of EW-type and other tracers show that the Galactic thin disk appears inhomogeneous.This exercise can potentially help us to reveal substructures such as bubbles and filaments. Meanwhile, the components clipsing Binaries in the Northern Galactic Plane Figure 5.
Spatial distribution of EW-type EBS in the Galactic thin disk. (top) Space and extinction distributions lookingdown on the Milky Way, centered on the Sun. Different colors represent different extinction values as reflected by the colorbar. (bottom) Spatial distribution of the EW-type EBS as seen from the Galactic North Pole. A density map of our EW typesis shown as contours (from blue to yellow). The Sun is shown as a red star symbol. Some other tracers are also included forcomparison. High-mass star-forming regions (Reid et al. 2014) are shown as magenta diamonds, Galactic Cepheids (Genovaliet al. 2014) are shown as red circles, while EA- and EB-type EBS from Table 1 with accurate
Gaia parallaxes (0 < σ π /π < . F.-Z. Ren et al. of EBS usually form from MS stars, and their differences within each type of EBS are not affected by age (or at mostto a limited extent). Different EBS types are generally associated with different ages, in the sense that EA types areyounger, EB types are older, and EW types are the oldest tracers. Meanwhile, Cepheids are young stars and HMSFRsare very young. These different tracers can thus also be used as age tracers.The derived structure of the thin disk varies significantly as a function of direction. In some directions, e.g. toward l ∼ ◦ and l ∼ ◦ , EW types can be seen out to considerable distances given the slowly increasing extinctiontrends there. It appears that these directions offer low-extinction windows, reaching and even crossing the PerseusArm. These areas are known as diffuse regions (Wang et al. 2017, their Figure 1). In other directions, the extinctionincreases quickly and the largest visible distance from the Sun is small. For example, around l ∼ ◦ a clear lack ofobjects is caused by high extinction, A V > l ∼ ◦ and 93 ◦ are caused by significant extinction toward l ∼ ◦ , which prevents detectionsof objects. The Orion Spur happens to be located in this dense region (from a distance of 3 kpc toward l ∼ ◦ to2 kpc toward l ∼ ◦ ; for reference, the distance of the equidistant circle in the background image is 5000 light-yearsor about 1.5 kpc). Similarly rapidly increasing extinction values can also be seen toward l ∼ ◦ . Unlike the line ofsight toward l ∼ ◦ , star-forming activity is not found here. Figure 6.
Detailed distributions of EBS in different distances along three sightlines. Red, black, and blue bars represent EW-,EB-, and EA-type EBSs, respectively. (a) l = 70 ◦ . (b) l = 93 ◦ . (c) l = 150–210 ◦ . The equivalent numbers in this latter panelwere calculated from a combination of the relevant number density and the area covered, which is the same as for panels (a)and (b) at the same distance ( N equi = S a,b × NS c ). In general, the stellar distribution appears inhomogeneous as a function of direction along the Galactic plane. Forexample, for distances between 0.5 kpc and 3 kpc, compare the sector between l ∼ ◦ and l ∼ ◦ with a secondsector between l = 150 ◦ and l = 210 ◦ : see the bottom panel of Figure 5. The regions contained within the dashedrectangles have widths of 300 pc. The corresponding EBS distributions are shown in Figure 6. Figure 2(e) suggeststhat our sample’s completeness is higher for systems brighter than I = 16 mag, an upper limit we therefore adopt forour subsequent analysis.Figure 6a shows that the systems located along this specific sightline ( l ∼ ◦ ) are distributed inhomogeneously andtend to cluster on scales of several hundred parsecs, irrespective of EBS type. The distribution of EW types exhibitstwo ridges separated by a valley on a scale of approximately 1 kpc. The EB- and EA-type distributions also show tworidges, within about 2.5 kpc, although the details differ. Within our target sectors, the spatial clustering scale, i.e., thewidth of the nearby ridges, increases from EW through EB to EA types. Along the same direction, an age gradientcan also be discerned. Moreover, the extinction behavior also suggests that these clustering scales reflect reality.However, the sightline toward l ∼ ◦ shows a different pattern, as shown in Figure 6(b). All three types of EBSexhibit clustered distributions between 1 and 2 kpc, but only EA types show a rise beyond 2.5 kpc. Compared withFigure 6(c), which also offers some evidence of clustering behavior, the peak of the distribution along this sightline islocated at greater distances. We suspect that the peaked distributions of our EBS may be driven by the structure ofthe thin disk, as traced by EBS, rather than by sampling incompletenessAs such, it is clear that the EBS density distribution in the thin disk is not uniform. Future work should addressthe detailed structure of the Galactic thin disk based on a larger EBS sample. clipsing Binaries in the Northern Galactic Plane Absolute parameters
To arrive at homogeneous estimates of the physical parameters of the EW-type EBS in the Galactic plane, we createda model for each system using the 2015 version of the Wilson–Devinney (W–D) code (Wilson & Devinney 1971; Wilson1979, 1990; Sun et al. 2020). The input parameters of the models were based on the results listed in Table 1. Weexcluded systems with fewer than 150 photometric epochs given the limited accuracy of the resulting parameters. R e s i d u a l
1e 8
Diagram of q search M a g n i t u d e ( m a g ) Figure 7.
Example of our parameter determination procedure. (left) Mass ratio search. The mass ratio associated withminimum residuals was adopted; here q = 0 . I -band magnitudes). The outliers are marked as orange crosses. For all systems, ‘Mode 3’ (contact mode, usually applied to systems in geometric contact without constraints onthe thermal contact configuration) was used to analyze the light curves. The input light curves were based on theparameters listed in Table 1. The effective temperatures of the primary components were taken from Pecaut &Mamajek (2013), based on their 2MASS ( J − K s ) colors and the extinction calculated previously. The distancesderived from the PLR were used to render absolute system parameters. The bolometric corrections are from Chenet al. (2019).EW types can be divided into two groups, split at a photospheric temperature of 6200 K (Marsh et al. 2017).The hotter objects correspond to stars dominated by radiative energy transport while cooler objects are stars withconvective envelopes. We set the gravity-darkening coefficients and the bolometric albedos to, respectively, g = 0 . A = 0 .
5, and g = 1 . A = 1 .
0, for stars with temperatures less and greater than 6200 K, respectively. Abolometric logarithmic limb-darkening law was applied. No spots, third bodies, or time derivatives of the orbital periodwere considered in our light-curve fitting.We used an extensive q -search method to find the best mass ratio, q = M /M . Mass ratios q from 0.1 to 10 weretried, in steps of 0.0125 from 0.1 to 1, 0.025 from 1 to 2, 0.125 from 2 to 5, and 0.5 from 5 to 10; see the left panelof Figure 7. The mass ratios are shown on the horizontal axis, while the residuals are shown on the vertical axis. Inthis example, the minimum residual occurs for a mass ratio q = 0 . i ), thetemperature of the secondary component ( T ), the potentials of both components (Ω , Ω ; Ω = Ω in the geometriccontact configuration), and the bandpass luminosities of the primary component ( L ) were treated as adjustableparameters. To arrive at a more reliable sample, we applied additional selection criteria. We visually checked allbest-fitting light curves and excluded those targets that were not well-matched. We did not retain sample objects withinclinations of less than 50 ◦ , since the best-fitting parameters for such low inclinations are unreliable.The results from our light-curve modeling are presented in Table 2. The first column corresponds to the sameorder as that in Table 1. The input effective temperature of the primary component, T o , was determined from itscolor, and the temperature of the other star, T o , was obtained from the best fit. Note that the color index wasused to calculate the temperature of the primary star, which may cause a level of bias in the temperatures of bothcomponents. We therefore calculated the combined temperature, T comb = [ L + L L /T o + L /T o ] / , where T o , T o , L , L F.-Z. Ren et al.
Table 2.
EW-type Parameters ID T T q M M R R M bol M bol L / ( L + L ) Ω = Ω A i
K K (M / M ) M (cid:12) M (cid:12) R (cid:12) R (cid:12) mag mag R (cid:12) ◦ KISOJ000039.63+622214.1 8157 6551 7.5 0.156 1.167 0.494 1.156 4.78 3.894 0.23 11.821 2.005 57.044KISOJ000048.17+614603.1 6129 7699 0.462 1.226 0.567 1.042 0.732 3.668 3.475 0.528 2.79 2.304 86.796KISOJ000053.24+613059.8 4607 4381 4.375 0.251 1.1 0.539 1.041 5.41 4.163 0.248 8.279 2.004 63.157KISOJ000056.84+625228.4 7337 7698 0.3 1.94 0.582 1.929 1.11 1.567 2.567 0.731 2.463 3.946 56.189KISOJ000123.66+613746.8 5771 5477 0.4 1.185 0.474 1.246 0.825 3.822 4.926 0.731 2.645 2.647 63.908KISOJ000208.16+630633.5 5285 5772 0.587 0.963 0.566 0.952 0.746 4.773 4.934 0.548 3.031 2.217 54.22KISOJ000210.22+611924.2 5312 5588 5.0 0.354 1.768 0.894 1.817 3.662 1.991 0.167 9.015 3.405 58.017KISOJ000233.43+614514.3 4917 4658 4.375 0.251 1.098 0.605 1.141 5.332 4.17 0.254 8.147 2.154 72.266KISOJ000250.76+624850.0 5126 5345 4.875 0.213 1.038 0.486 0.977 6.143 4.43 0.174 8.86 1.838 68.057KISOJ000300.42+631913.6 6261 5215 1.95 0.577 1.125 0.806 1.093 4.013 4.062 0.493 5.137 2.455 83.705KISOJ000308.44+622223.9 5126 5016 7.5 0.16 1.201 0.48 1.192 5.66 3.762 0.15 12.146 2.132 61.469KISOJ000329.49+613312.2 5632 5463 1.575 1.01 1.591 1.144 1.396 2.768 2.473 0.425 4.513 3.191 75.15KISOJ000356.37+611452.6 6356 5651 0.237 2.032 0.483 2.089 1.168 1.355 2.785 0.825 2.216 3.837 67.856KISOJ000359.11+615018.1 5394 5659 0.188 1.04 0.195 1.13 0.557 4.42 5.783 0.783 2.141 2.052 74.899KISOJ000401.47+613034.7 4962 5308 0.387 1.115 0.432 1.068 0.692 4.1 4.761 0.65 2.641 2.28 81.237KISOJ000417.46+620836.4 6733 6526 9.5 0.151 1.438 0.549 1.471 4.978 2.938 0.129 14.35 2.52 66.477KISOJ000429.77+630856.5 5771 5784 3.25 0.385 1.25 0.834 1.401 4.76 3.579 0.258 6.796 2.807 68.041KISOJ000441.52+623631.7 6829 6771 1.05 1.838 1.93 2.155 2.197 1.598 1.59 0.496 3.562 5.072 78.901KISOJ000501.27+611509.9 4729 4840 0.125 1.822 0.228 2.158 0.939 1.854 3.63 0.835 1.958 3.634 71.187KISOJ000505.12+630032.3 5903 5052 1.3 0.896 1.165 0.915 1.037 3.545 3.9 0.571 4.277 2.621 57.358 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
Note —This table is available in its entirety in machine-readable form. are the temperatures and luminosities of both components. Next, the temperatures were corrected by dividing themby T comb /T o . A second run was initiated using these new temperatures. The results of the second run, T and T ,are the temperatures of the two stars in Table 2. In addition, q is the best-fitting mass ratio resulting in the smallestresiduals, and ( M , M , R , R ) are the absolute parameters of both stars in units of solar masses and solar radii,where we derived the masses from the mass—luminosity relation (Yildiz & Do˘gan 2013) and the mass ratio q . M bol1 and M bol2 are the absolute bolometric magnitudes of the primary and secondary stars, respectively. Ω = Ω arethe potentials of both stars. L / ( L + L ) is the ratio of the bandpass luminosities of the primary star to the totalbandpass luminosity, and A is the length of the semi-major axis, in solar radii, of the relative orbit, which is the sumof the two stars’ absolute semi-major axes, A = a + a ; i , in the final column, is the binary orbital inclination withrespect to the plane of the sky.We carried out a photometric analysis of all EW-type light curves in the Galactic plane and derived their parameters.This data set will be valuable for further analysis and comparisons with other EW-type EBS.3.4. Cross-check with
Gaia
The
Gaia mission (Gaia Collaboration et al. 2016, 2018, 2020) represents a leap forward for tests of stellar andGalactic astrophysics. In particular,
Gaia parallaxes, with precisions of 30 µ as or better for sources with G ≤ Gaia parallaxes. Lindegren et al. (2018) found a general,systematic parallax offset of ∆ π = 29 µ as from their quasar catalog. The Gaia eDR3 parallax solution is a significantimprovement compared with that affecting
Gaia
Data Release 2 (DR2): a typical 20% parallax improvement hasbeen reported for
Gaia eDR3 quasars (Fabricius et al. 2020). However, despite being the best benchmark for
Gaia parallaxes, quasars (typically with
G >
17 mag) are rather faint and their color distribution does not match well thestellar color distribution. Clearly, independent assessment of
Gaia parallaxes is important to fully characterize anylingering systematic errors. Since EW-type EBS are among the most numerous variables in the Milky Way that haveindependently determined distance measurements in the solar neighborhood, here we will use our EW-type distancesto check for zero-point offsets in the
Gaia eDR3 parallaxes. clipsing Binaries in the Northern Galactic Plane -1 0 1 2 3 4 Parallaxes from Gaia eDR3(mas) -1 -0.500.511.522.533.54 P a r a ll a x e s f r o m P - L r e l a t i on ( m a s ) (a) Figure 8.
Comparison of predicted EBS parallaxes derived from the PLR versus
Gaia eDR3 parallaxes. (a) Direct comparisonfor all EW types. Red points have uncertainties exceeding 20% or negative parallaxes. The cyan dashed line is the one-to-onelocus. (b) Distribution of the parallax offsets affecting
Gaia eDR3, ∆ π (Gaia eDR3 − PLR) = − . ± . µ as. (c) Parallax offsetsof corrected Gaia eDR3 parallaxes (Lindegren et al. 2020), ∆ π (Gaia correDR3 − PLR) = − . ± . µ as. (d) Equivalent distributionof Gaia
DR2 parallaxes, ∆ π (Gaia DR2 − PLR) = − . ± . µ as. The red curves in panels (b), (c), and (d) represent thebest-fitting Gaussian distributions. Of the 3996 EW-type EBS with distances from the PLR, 3920 have parallaxes available in
Gaia eDR3. Figure 8(a)shows a direct comparison of the EBS parallaxes derived from the PLR versus
Gaia eDR3 parallaxes. The cyan dashedone-to-one line is meant to clearly show the extent of the offset in distances. The deviation between the samples hintsat a clear offset in parallaxes, in the sense that the PLR parallaxes are larger on average than their
Gaia counterparts.After excluding objects with large errors and negative parallaxes ( σ π /π > . π < π Gaia − π PLR .4 F.-Z. Ren et al.
The distribution appears to be a roughly symmetric, normally distributed offset in the negative direction. The meanoffset is ∆ π = − . ± . µ as, where the error is the standard error on the mean for all sample objects. In otherwords, the Gaia parallaxes are systematically smaller.The
Gaia team has released a model allowing us to adjust this zero-point offset, which was based on an analysisof quasars, binary stars, and stars in the Large Magellanic Cloud (Lindegren et al. 2020). We also compared theparallaxes implied by our EW-type distances with the corrected
Gaia parallaxes (see Figure 8c) and found an offset of∆ π = − . ± . µ as. This suggests that the parallax zero-point correction provided by the Gaia team significantlyreduces but may not fully eliminate the prevailing bias in the
Gaia eDR3 parallaxes.Quantification of the parallax systematics in
Gaia
DR2 was based on careful analysis of a series of tracer objects,yielding: Cepheids, ∆ π = − ± µ as (Riess et al. 2018); nearby bright EBS,∆ π = − ± µ as (Stassun & Torres2018); stars with asteroseismically determined radii, ∆ π = − . ± . µ as (statistical) ± . µ as (systematic) (Zinnet al. 2019); and Bayesian distances for a radial velocity sample, ∆ π = − ± . µ as (Sch¨onrich et al. 2019)). Forcomparison, we similarly used our EBS sample as parallax tracer and found ∆ π = − . ± . µ as. This offset is similarto those of other authors’ concurrent, independent analyses based on different benchmark samples (e.g., Zinn et al.2019; Sch¨onrich et al. 2019). Our result should have similar systematic uncertainties as those determined by Zinn et al.(2019) and Sch¨onrich et al. (2019), since the maximum parallax differences among these three tracer populations isless than 2 µ as.We will now estimate the likely systematic error range pertaining to our PLR-based EW-type distances. Fivefundamental issues affect the level of the systematic uncertainties, including (i) the offset in the PLR, (ii) its internalspread, (iii) uncertainties in the photometric zero points, (iv) errors in our extinction evaluation, and (v) third-component effects.The PLR was obtained from 183 objects within 330 pc with an average parallax of 5.46 mas. Considering a 30 µ assystematic uncertainty (Gaia Collaboration et al. 2016), the systematic error contributed by the offset is about 0.5%.The systematic error associated with the internal spread in the PLR is of order 0 . / √ ≈ .
016 mag. Here, 0.21mag is the mean spread in the
IJHK s -band PLRs. As regards the photometric zero points, the I -band systematicerror is most important, given that the JHK s -band PLR and KISOGP EW data both came from 2MASS; our I -bandphotometric data for all EBS PLRs was based on the USNO-B catalog. We correlated our I -band data for all sampleEBS with that published in the USNO-B catalog. We found that the KISOGP I -band magnitudes are systematically0.009 mag brighter than the corresponding USNO-B I -band magnitudes for the 6894 targets in common.Since we make use of the IJHK s bands, here we consider an average extinction corresponding to 0 . A V . We alsoadopt a 10% uncertainty in the extinction determination, which reflects uncertainties owing to the choice of extinctionlaw. For a mean observed extinction of A V = 1 . mag , these choices lead to an uncertainty of 1.94 mag × ×
10% = 0.0437 mag. Next, if a third component can be discerned, a study of 75 nearby EW-type EBS (D’Angelo et al.2006) has shown that this will affect the systematic uncertainty at the median distance of our sample by about 0.3%.As neither our KISOGP sample objects nor those contributing to the PLR explicitly excluded third-body effects, thebias caused by third- or higher-order multiplicity should not differ much between both sets of EBS. We estimate thatthe associated systematic uncertainty is less than 0.3%. As such, the systematic uncertainty range affecting our resultsis σ = 581 µ as × [(0 . + (0 . × ln(10) / + (0 . × ln(10) / + (0 . × ln(10) / + (0 . ] / = 12 . µ as.The offset we found based on our catalog of 2334 EW-type EBS is well within the prevailing uncertainties and alsofully consistent with a systematic error below 100 µ as as reported by the Gaia team. Our EW-type EBS in the Galacticplane result in a larger offset than that derived from quasars ( − µ as), but the offset can be reduced significantly byapplication of the official parallax zero-point correction. The Gaia team found that the parallax zero-point dependson a target’s magnitude, color, and position, and hence the small difference we found between EBS and quasars isnot surprising. The difference may come from the details of the distribution of the parallax zero-point, since quasarsare fainter and bluer than our EBS, which are all located in the Galactic plane. In addition, for faint sources outsidethe Galactic disk parallax calibrations are estimated directly from the quasar sample. However, the parallax bias forobjects in the Milky Way is derived indirectly, based on binary stars and stars in the Large Magellanic Cloud.Stassun & Torres (2021) found a mean parallax offset of − ± µ as, which decreased to − ± µ as followingthe official corrections based on 76 EBS. Their result matches our result well, which is particularly encouraging sinceour result is affected by small statistical errors and based on a large sample. Our EBS sample can be used as usefultracers for further work on the zero-point offset of Gaia parallaxes. In addition, our result is based on EW-type EBSin the Galactic plane, which most other studies try to avoid. It can therefore serve as a useful reference for other clipsing Binaries in the Northern Galactic Plane Extinction from PL relation E x t i n c t i on f r o m G r een Figure 9.
Extinction comparison ( A V , mag) between the values derived from the PLR and from Green et al. (2019). studies that need to deal with the Gaia zero-point offset in the Galactic plane and complement studies of the zero-pointdistribution across the sky.In conclusion, we found a
Gaia eDR3 zero-point offset of ∆ π = − . ± . ± . µ as, based on 2334EW-type EBS covering a wide range of magnitudes and extinction values in the northern Galactic plane. The officialparallax zero-point correction can significantly reduce the bias in eDR3 parallaxes to − . ± . ± . µ as(for our sample). 3.5. Extinction compared with 3D extinction map
Green et al. (2019) presented a three-dimensional (3D) dust reddening map of the northern sky derived from
Gaia parallaxes and stellar photometry from Pan-STARRS 1 and 2MASS. Green et al.’s 3D extinction map happens tooverlap with the KISOGP survey’s spatial coverage. In Figure 9, we compare the extinction derived from our PLRanalysis with that from the 3D extinction map.As shown in Figure 9, a linear correlation is clearly discernible. The extinction values from both studies fit wellwithin the relevant scatter envelopes. This scatter may originate from various sources. First, the error in the extinctionfrom both our PLR analysis and that in the 3D extinction map cannot be ignored. Second, the error in distance usedas input into the 3D extinction map may exacerbate the intrinsic errors in the extinction from the 3D map. Finally,the distances and spatial resolutions pertaining to the 3D map are coarse, with distance modulus steps of 0.5 mag andangular resolutions of several arcminutes. These steps lead to non-negligible errors when comparing the extinctionvalues for single objects, particularly for our sample in the Galactic plane where the extinction is usually high. In anycase, given the prevailing uncertainties, both methods are mutually consistent. CONCLUSIONWe have presented a new catalog of EBS in the northern Galactic plane based on the KISOGP survey. We visuallyidentified 7055 EBS spread across ∼
330 deg , including 4197 EW-, 1458 EB-, and 1400 EA-type EBS. For all sampleobjects, we used their I -band light curves to determine accurate parameters, including their periods (accurate to betterthan the fifth decimal place), a reference t , the depths of the two eclipses, etc.We also examined the spatial distribution of our sample objects. We found an inhomogeneous density distributionof EBS in the thin disk at different Galactic longitudes. In addition, we found a random distribution of the ratiosof the eclipse depths for EA types and a concentration tending to unity for EW-type EBS. Moreover, we checkedthat the distributions of their periods vary among different EBS types, increasing from EW to EB and EA type.We also obtained the distribution of the eclipse depths, the I -band magnitudes, etc. Finally, we tested the level ofcontamination of our sample by other types of variables, which we found to be negligible.6 F.-Z. Ren et al.
We derived the distances and extinction values pertaining to the EW types in our sample using their PLRs, reachingdistances in excess of 6 kpc and V -band extinction values exceeding A V = 9 mag. We combined our EBS sample withHMSFRs and Cepheids to trace the structure of the thin disk. Stars of the same type (including but not limited toEBS) tend to cluster on spatial scales of several hundred parsecs. Using different tracers, we revealed some structuralproperties of the thin disk.As an independent distance measurement, our EBS distance analysis offers a complementary measurement of theglobal parallax offset affecting Gaia eDR3. We found ∆ π = − . ± . ± . µ as based on a carefulanalysis of 2334 EW-type EBS. Our newly derived offset is consistent with the results from the Gaia team. We alsofound that the official parallax zero-point correction can significantly reduce the bias affecting the eDR3 parallaxes.Finally, we performed a photometric analysis of all EW-type light curves using the W–D method to derive individualsystem parameters, and we cross checked our extinction values with Green et al.’s 3D extinction map.We acknowledge long-term support for the KISOGP project from the staff at Kiso Observatory, Japan. We aregrateful for research support from the National Key Research and Development Program of China through grants2019YFA0405500 and 2017YFA0402702. This work was also partially supported by the National Natural ScienceFoundation of China (NSFC) through grant 11973001. N. M. acknowledges financial support from Grants-in-Aid(Nos. 26287028 and 18H01248) from the Japan Society for the Promotion of Science. X. C. acknowledges supportfrom NSFC grant 11903045. REFERENCES
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