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<ri:Resource created="2024-08-16T12:29:48Z" status="active" updated="2025-05-19T09:50:00Z" version="1.2" xmlns:cs="http://www.ivoa.net/xml/ConeSearch/v1.0" xmlns:ri="http://www.ivoa.net/xml/RegistryInterface/v1.0" xmlns:vr="http://www.ivoa.net/xml/VOResource/v1.0" xmlns:vs="http://www.ivoa.net/xml/VODataService/v1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.ivoa.net/xml/ConeSearch/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/ConeSearch.xsd http://www.ivoa.net/xml/VOResource/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/VOResource.xsd http://www.ivoa.net/xml/VODataService/v1.1 http://vo.ari.uni-heidelberg.de/docs/schemata/VODataService.xsd" xsi:type="vs:CatalogService"><title>Periodic variable stars from LAMOST DR9</title><shortName>J/ApJS/272/1</shortName><identifier>ivo://CDS.VizieR/J/ApJS/272/1</identifier><altIdentifier>doi:10.26093/cds/vizier.22720001</altIdentifier><curation><publisher ivo-id="ivo://CDS">CDS</publisher><creator><name>Qiao P.</name></creator><creator><name>Xu T.</name></creator><creator><name>Wang F.</name></creator><creator><name>Mei Y.</name></creator><creator><name>Deng H.</name></creator><creator><name>Tan L.</name></creator><creator><name>Liu C.</name></creator><date role="Updated">2024-11-06T20:31:29Z</date><date role="Created">2024-08-16T12:29:48Z</date><contact><name>CDS support team</name><address>CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France</address><email>cds-question@unistra.fr</email></contact></curation><content><subject>variable-stars</subject><subject>two-color-diagrams</subject><subject>surveys</subject><subject>visible-astronomy</subject><subject>infrared-photometry</subject><subject>astronomical-models</subject><description>Identifying and classifying variable stars is essential to time-domain astronomy. The Large Area Multi-Object Fiber Optic Spectroscopic Telescope (LAMOST) acquired a large amount of spectral data. However, there is no corresponding variable source-related information in the data, constraining LAMOST data utilization for scientific research. In this study, we systematically investigated variable source classification methods for LAMOST data. We constructed a 10-class classification model using three mainstream machine-learning methods. Through performance comparison, we chose the LightGBM and XGBoost models. We further identified variable source candidates in the r band in LAMOST DR9 and obtained 281,514 variable source candidates with probabilities greater than 95%. Subsequently, we filtered out the sources of periodic variable sources using the generalized Lomb-Scargle periodogram and classified these periodic variable sources using the classification model. Finally, we propose a reliable periodic variable star catalog containing 176,337 stars with specific types.</description><source format="bibcode">2024ApJS..272....1Q</source><referenceURL>https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJS/272/1</referenceURL><type>Catalog</type><contentLevel>Research</contentLevel><relationship><relationshipType>IsServedBy</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/TAP">TAP VizieR generic service</relatedResource></relationship><relationship><relationshipType>IsServedBy</relationshipType><relatedResource>Conesearch service</relatedResource></relationship><relationship><relationshipType>related-to</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/II/246">II/246 : 2MASS All-Sky Catalog of Point Sources (Cutri+ 2003)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/II/328">II/328 : AllWISE Data Release (Cutri+ 2013)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/V/156">V/156 : LAMOST DR7 catalogs (Luo+, 2019)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/I/350">I/350 : Gaia EDR3 (Gaia Collaboration, 2020)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/II/366">II/366 : ASAS-SN catalog of variable stars (Jayasinghe+, 2018-2020)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/AJ/134/973">J/AJ/134/973 : SDSS Stripe 82 star catalogs (Ivezic+, 2007)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/414/2602">J/MNRAS/414/2602 : Automated classification of HIP variables (Dubath+, 2011)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/AJ/146/101">J/AJ/146/101 : LINEAR. III. Cat. of periodic variables (Palaversa+, 2013)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/213/9">J/ApJS/213/9 : Catalina Surveys periodic variable stars (Drake+, 2014)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/566/A43">J/A+A/566/A43 : EPOCH Project. EROS-2 LMC periodic variables (Kim+, 2014)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/580/A17">J/A+A/580/A17 : {alpha}-element abund. of Cepheid stars (Genovali+, 2015)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/249/18">J/ApJS/249/18 : The ZTF catalog of periodic variable stars (Chen+, 2020)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/249/22">J/ApJS/249/22 : Radial velocity variable stars from LAMOST DR4 (Tian+, 2020)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/259/11">J/ApJS/259/11 : LAMOST variable sources based on ZTF phot. (Xu+, 2022)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJS/267/7">J/ApJS/267/7 : YSO candidates from LAMOST LRS DR9 &amp; ZTF (Zhang+, 2023)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/A+A/675/A195">J/A+A/675/A195 : ZTF DR11 classif. in ZTF/4MOST sky (Sanchez-Saez+, 2023)</relatedResource></relationship></content><rights>https://cds.unistra.fr/vizier-org/licences_vizier.html</rights><capability><interface xsi:type="vr:WebBrowser"><accessURL use="full">https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJS/272/1</accessURL><mirrorURL title="VizieR at IUCAA: Pune, India">https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJS/272/1</mirrorURL><mirrorURL title="VizieR at SAAO: SAAO, South Africa">http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJS/272/1</mirrorURL></interface></capability><capability><interface xsi:type="vs:ParamHTTP"><accessURL 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31655 31660-31661 31663 31708-31709 31711 31724-31726 31756-31757 31759 31813-31815 31826-31827 31848-31849 31851 31936-31938 31960 31962-31963 32000 32002-32003 32041-32044 32058-32059 32064 32073 32075 32077-32078 32102-32103 32108-32110 32114 32119 32125-32127 32198 32219 32243 32250-32251 32380 32383 32388-32389 32392-32393 32416 32418-32419 32424 32426-32429 32431-32433 32435 32440-32441 32443 32446 32460-32461 32463 32468 32470-32471 32480-32482 32489-32491 32500-32502 32536-32538 32540-32541 32564 32566-32567 32581 32583-32584 32587 32597-32599 32609-32611 32672-32673 32675-32677 32682-32683 32696-32697 32704 32706-32707 32711 32740 32742-32745 32747 32749-32751 32756-32757 32759 32764 32766-32767 36719 36728-36729 36731-36732 36801 36803 36809 36814 36817-36818 36820 36827 36831 36844-36846 36849-36851 36854-36857 36859 40887 40891 40893-40895 40908 40913 40915 40921 40923-40926 40930-40931 40933-40934 40940-40942 40945-40948 40951-40952 40958-40959 44985 44987 45017 45019 45026 45041 45043 49011 49016 49023 49095 49105-49106 49109 49111 49117 49119 49141</spatial><footprint ivo-id="ivo://ivoa.net/std/moc">https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJS/272/1?format=ascii</footprint><waveband>Optical</waveband><waveband>Infrared</waveband></coverage><tableset><schema><name>default</name><table><name>J/ApJS/272/1/table6</name><description>*Classification results of variable stars for LAMOST DR9 based on LightGBM and XGBoost</description><column><name>gskew</name><description>Median-of-magnitudes based measure of the skew</description><ucd>stat.fit.param</ucd><dataType xsi:type="vs:VOTableType" arraysize="9*">char</dataType></column><column><name>MedBRP</name><description>[0.006/1] Fraction, photometric points within amplitude/10 of median (7)</description><ucd>phot;stat.median;arith.ratio</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>f1power</name><description>[0/1] f1 power (8)</description><ucd>stat.fit.param</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>recno</name><description>Record number assigned by the VizieR team. Should Not be used for identification.</description><ucd>meta.record</ucd><dataType xsi:type="vs:VOTableType">int</dataType></column><column><name>LAMOST</name><description>[101092/914316131] LAMOST DR9 source identifier</description><ucd>meta.id;meta.main</ucd><dataType xsi:type="vs:VOTableType">long</dataType></column><column><name>ZTF</name><description>ZTF DR11 Source identifier</description><ucd>meta.id.cross</ucd></column><column><name>RAJ2000</name><description>Right Ascension (J2000)</description><unit>deg</unit><ucd>pos.eq.ra;meta.main</ucd><flag>indexed</flag></column><column><name>DEJ2000</name><description>[-9.3/87] Declination (J2000)</description><unit>deg</unit><ucd>pos.eq.dec;meta.main</ucd><flag>indexed</flag></column><column><name>plx</name><description>[-9/52.1]? Gaia DR3 parallax</description><unit>mas</unit><ucd>pos.parallax</ucd><dataType xsi:type="vs:VOTableType">float</dataType><flag>nullable</flag></column><column><name>Per</name><description>[0.02/1000] Period, best derived period (1)</description><unit>d</unit><ucd>time.period</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>Type</name><description>Variable source type (2)</description><ucd>meta.code.class</ucd><dataType xsi:type="vs:VOTableType" arraysize="4*">char</dataType></column><column><name>IterStd</name><description>[0.0049/2.6] Recalculated standard deviation (3)</description><ucd>stat.stdev</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>Nobs</name><description>[50/1311] Number of observations</description><ucd>meta.number</ucd><dataType xsi:type="vs:VOTableType">int</dataType></column><column><name>Std</name><description>[0.007/2] Magnitude standard deviation</description><ucd>stat.stdev</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>Amp</name><description>[0.015/3.1] Amplitude (4)</description><ucd>src.var.amplitude</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>chi2</name><description>[0.4/29701] {chi}^2^ statistic</description><ucd>stat.fit.chi2</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>Cusum</name><description>[0.027/2.22] Range of magnitude cumulative sums (5)</description><ucd>stat.param</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>MAD</name><description>[0.003/1.7] Median Absolute Deviation</description><ucd>stat.stdev</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>sKurt</name><description>[-2.4/1341195100] Small sample kurtosis of the magnitudes</description><ucd>stat.fit.param</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>Eta</name><description>[0.01/2.7] Von Neumann statistic, Kim+ (2014, J/A+A/566/A43)</description><ucd>stat.fit.param</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>SWTest</name><description>[0.03/1] Shapiro-Wilk normality test statistics (Shapiro &amp; Wilk 1965, doi:10.1093/biomet/52.3-4.591)</description><ucd>stat.fit.param</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>KSVar</name><description>[0.2/1] Stetson K statistic (Stetson 1994PASP..106..250S)</description><ucd>src.var.index</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>HMAR</name><description>[0.03/24.7] Half magnitude amplitude ratio (6)</description><ucd>src.var.amplitude;arith.ratio;phot.mag</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>fu1std</name><description>[0.006/0.7] Fraction of observations beyond 1 standard deviation (D'Isanto+ 2016MNRAS.457.3119D)</description><ucd>stat.fit.param</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>PerAmp</name><description>[0.001/0.4] Largest difference, min or max magnitude and median (9)</description><ucd>meta.note</ucd><dataType xsi:type="vs:VOTableType">double</dataType></column><column><name>BP-RP</name><description>[-0.6/7.6]? Gaia DR3 color, BP-RP</description><unit>mag</unit><ucd>phot.color;em.opt.B;em.opt.R</ucd><dataType xsi:type="vs:VOTableType">double</dataType><flag>nullable</flag></column><column><name>G-BP</name><description>Gaia DR3 color, G-BP</description><unit>mag</unit><ucd>phot.color;em.opt;em.opt.B</ucd><dataType xsi:type="vs:VOTableType" arraysize="8*">char</dataType></column><column><name>G-RP</name><description>[-0.5/4.2]? Gaia DR3 color, G-RP</description><unit>mag</unit><ucd>phot.color;em.opt;em.opt.R</ucd><dataType xsi:type="vs:VOTableType">double</dataType><flag>nullable</flag></column><column><name>W1-W2</name><description>[-2.3/2.5] ALLWISE color, W1-W2</description><unit>mag</unit><ucd>phot.color;em.IR;em.IR</ucd><dataType xsi:type="vs:VOTableType">float</dataType></column><column><name>W2-W3</name><description>[-2.8/8.5]? ALLWISE color, W2-W3</description><unit>mag</unit><ucd>phot.color;em.IR;em.IR</ucd><dataType xsi:type="vs:VOTableType">float</dataType><flag>nullable</flag></column><column><name>W1-W3</name><description>[-2.9/8.5]? ALLWISE color, W1-W3</description><unit>mag</unit><ucd>phot.color;em.IR;em.IR</ucd><dataType xsi:type="vs:VOTableType">float</dataType><flag>nullable</flag></column><column><name>J-Ks</name><description>[-1.3/3.6]? 2MASS color, J-Ks</description><unit>mag</unit><ucd>phot.color;em.IR.J;em.IR.K</ucd><dataType xsi:type="vs:VOTableType">float</dataType><flag>nullable</flag></column><column><name>J-H</name><description>[-1.3/2.1]? 2MASS color, J-H</description><unit>mag</unit><ucd>phot.color;em.IR.J;em.IR.H</ucd><dataType xsi:type="vs:VOTableType">float</dataType><flag>nullable</flag></column><column><name>H-Ks</name><description>[-1.9/2.6]? 2MASS color, H-Ks</description><unit>mag</unit><ucd>phot.color;em.IR.H;em.IR.K</ucd><dataType xsi:type="vs:VOTableType">float</dataType><flag>nullable</flag></column><column><name>C20</name><description>Display data from Chen+ 2020 within 0.5"</description><ucd>meta.ref.url</ucd><dataType xsi:type="vs:VOTableType">int</dataType><flag>nullable</flag></column><column><name>DR7</name><description>Display data from LAMOST DR7 LRS (V/156) if any</description><ucd>meta.ref.url</ucd><dataType xsi:type="vs:VOTableType">int</dataType><flag>nullable</flag></column><column><name>WISEA</name><description>Display data from AllWISE (II/328) within 3"</description><ucd>meta.ref.url</ucd><dataType xsi:type="vs:VOTableType" arraysize="*">char</dataType></column><column><name>2M</name><description>Display the 2MASS data (II/246) within 3"</description><ucd>meta.ref.url</ucd><dataType xsi:type="vs:VOTableType" arraysize="*">char</dataType></column><column><name>Gaia</name><description>Display the Gaia EDR3 data (I/355) within 3"</description><ucd>meta.ref.url</ucd><dataType xsi:type="vs:VOTableType" arraysize="*">char</dataType></column><column><name>Skew</name><description>Skewness of light curves</description><ucd>stat.fit.param</ucd><dataType xsi:type="vs:VOTableType" arraysize="10*">char</dataType></column><column><name>Kurt</name><description>Kurtosis of the magnitude distribution</description><ucd>stat.fit.param</ucd><dataType xsi:type="vs:VOTableType" arraysize="10*">char</dataType></column></table></schema></tableset></ri:Resource>