J/A+A/664/A38ivo://CDS.VizieR/J/A+A/664/A38doi:10.26093/cds/vizier.36640038CDSWang C.Bai Y.Yuan H.Liu J.Fernandez-Ontiveros J.A.Coelho P.R.T.,Jimenez-Esteban F.Galarza C.A.Angulo R.E.Cenarro A.J.,Cristobal-Hornillos D.Dupke R.A.Ederoclite A.Hernandez-Monteagudo C.,Lopez-Sanjuan C.Marin-Franch A.Moles M.Sodre L.JrVazquez Ramio H.,Varela J.2022-09-30T23:30:30Z2022-08-04T08:52:04ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frsurveyseffective-temperaturemetallicityStellar parameters are among the most important characteristics in studies of stars, which are based on atmosphere models in traditional methods. However, time cost and brightness limits restrain the efficiency of spectral observations. The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools to efficiently analyse large data sets, such as the one from J-PLUS, and enable us to expand the research domain to stellar parameters. The main goal of this study is to construct a Support Vector Regression (SVR) algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. The training data for the parameters regressions is featured with 12-waveband photometry from J-PLUS, and is cross-identified with spectrum-based catalogs. These catalogs are from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the Apache Point Observatory Galactic Evolution Experiment, and the Sloan Extension for Galactic Understanding and Exploration. We then label them with the stellar effective temperature, the surface gravity and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach in order to fully take into account the uncertainties of both the magnitudes and stellar parameters. The method utilizes more than two hundred models to apply the uncertainty analysis. We present a catalog of 2493424 stars with the Root Mean Square Error of 160K in the effective temperature regression, 0.35 in the surface gravity regression and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods.2022A&A...664A..38Whttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/664/A38CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/A+A/643/A149 : J-PLUS Ly{alpha}-emitting candidates (Spinoso+, 2020)J/A+A/658/A79 : J-PLUS white dwarf atmospheric parametersJ/A+A/659/A144 : J-PLUS. STAR-GALAXY-QSO Classification (Wang+, 2022)J/A+A/659/A181 : J-PLUS DR1 stellar param, and abundances (Yang+, 2022)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/664/A38https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/664/A38http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/664/A38https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/664/A38https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/664/A38http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/664/A38GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/664/A38/interpol (Classification interpolation stars)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/664/A38/interpol?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/664/A38/interpol?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/664/A38/interpol?GETtext/xml+votable180.050000true255.46834697222.76001387510.005555555555555556Cone search capability for table J/A+A/664/A38/extrapol (Classification extrapolation stars)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/664/A38/extrapol?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/664/A38/extrapol?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/664/A38/extrapol?GETtext/xml+votable180.050000true255.64128555822.75862265740.0055555555555555563/155 4/58 144-145 315 318-319 400-401 403 460 615 710 713 843 937 1115 1127 1131-1134 1138 1211-1212 1217 5/33-34 227 236 238-239 543 563 575 588 592 604-606 625 664 1237-1239 1241-1242 1244 1253 1255 1257-1259 1264 1266 1271 1319 1321-1324 1342-1343 1359 1368 1380 1384 1408 1423 1425 1427-1428 1432 1441-1444 1448-1450 1557-1559 1595 1597 1599 1608-1609 1611 1616-1617 1619-1621 1624 1626 1634-1637 1640 1642 1681-1685 1807 1816 1818 1827-1828 1831 2012 2019 2025 2367-2369 2455 2459 2526 2528 2530 2536 2538-2539 2545 2578 2731 2775 2779-2782 2791 2795-2798 2801-2802 2819 2831 2833 2835 2837-2839 2844-2845 2851 2856-2857 2859-2862 2864-2866 2880-2882 2945-2946 3357 3359 3362-3363 3366-3367 3369 3377-3378 3380 3384 3400 3727 3736 3738 3753 4459 4474-4475 4477-4478 4503 4507 4519 4523 4540-4542 4544-4546 4548-4549 4551 4556-4558 4560-4562 4576-4578 4825-4828 4830 4837-4839 4841 4852 4856 4865 4877 4880-4882 5043 5048 5110 8115 8120-8121 8149-8150 8153 8167 8170-8172 8174 6/47 131 140-142 144 146 160-161 757-759 764-765 767 902-903 905-907 920 922 948 950 1000 1002-1003 2133 2135 2169 2171 2246 2249 2251 2257 2260 2294-2295 2297 2299 2336-2337 2340-2341 2343 2356 2376 2407 2415 2428 2472 2474 2499 2508 2512 2613-2615 2618 2621 2634-2635 2638-2639 2645 2647 2652-2653 2655 2660-2662 2693 2695 2704-2706 2818-2819 2824-2826 4607 4863 4927 4943 4947 4963 4972-4974 4980-4981 4984-4985 5011 5019 5027 5060 5062 5068 5070 5083 5263 5271-5272 5274-5275 5283 5300-5302 5304-5306 5314-5315 5320-5322 5359 5367 5431 5435 5480 5482 5511 5517 5524-5525 5527-5528 5544 5568 5636-5638 5640-5642 5687 5691 5699 5704-5705 5707 5716 5720 5732 5763 5780 5784 5786-5787 5804 5808 5973 5975 5981 5983 6005 6227 6260-6261 6367 6379 6387 6393-6395 6440-6441 6472 6474-6475 6488 6500 6502 6508 6535 6552-6553 6555-6556 6564 6566 6572 6585-6590 6592 6723 6744-6745 6748 6753 6756 6912 7168 7222-7223 7226-7227 7268 7270 7276 7278-7279 7302-7303 7316-7317 7319-7321 7323 7345 7348-7349 7376 7378 7384 7392-7393 7396 7897-7900 7902-7903 7920-7921 7924 8025-8027 8030 8052 8073-8075 8089-8091 8094 8097 8099 8112-8113 8116 9301 9463 9480-9481 9484-9486 9488 9490 9634 9640 9814-9815 9817-9819 9829-9831 9833 9835 9877 9879 9885 9909 9911 9917 9919 10024 10026-10027 10078 10093-10095 10097-10100 10102 10108 10124 10126 10148 10150 10177 10179 10185 10188 10192 10307 10316 10318 10337 10743 10748-10749 10902-10903 10908-10909 10918-10919 10921-10923 10930 10936 10946 10952 11097-11099 11109-11111 11113 11115 11132 11158-11159 11161-11163 11173-11175 11177-11179 11196 11201-11203 11212 11216 11232 11275 11285 11288 11290 11296-11297 11299-11302 11317 11319 11322-11323 11328-11329 11337-11339 11344-11345 11347 11384 11386 11397-11399 11401-11403 11432-11433 11435 11452 11468 11472 11488 11532 11552 11777-11779 11788 11792 11808 12561 12564 12765 13422-13423 13425 13427 13433-13435 13442-13443 13458-13459 13462-13463 13473 13485 13505-13507 13516-13517 13524 13528 13544 13577-13580 13582 13584-13585 13587-13588 13604 13841 13844 14848 14850 14879 14901 14903 14907 14920 14922-14923 14948 14956 14989-14991 15009 15011 15017 15020 15024 15040 17831 17835 17887-17888 17890-17891 17894-17895 17907 17916-17917 18007 18023 18027 18071 18075 18091 18172-18174 18188 18190-18191 18201-18203 18236-18238 18252-18254 18256-18258 18272-18274 18316-18318 18320-18322 18336-18338 19263 19279 19290-19291 19299 19316 19318 19324 19343 19347 19373 19412 19416 19428 19432 19456-19457 19459 19468-19469 19471 19504-19505 19507 19516-19517 19532-19534 19536-19538 19552-19554 20149 20151 20166-20167 20169-20171 20196 20410-20411 20414 20429 20431 20446 20464-20465 20467-20468 32255 32439 32445 32459 32488-32489 32492-32493 32495 32498 32504 32506 32511 32591 32604-32606 32620-32621 32624-32626 32663 32667 32679 32692-32694 32700-32702 32706 32712-32714https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/664/A38?format=asciidefaultJ/A+A/664/A38/interpolClassification interpolation starsrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintIDJ-PLUS ID (NNNNN-NNNNN)meta.id;meta.maincharn_ID[*] * mean that the parameters are not very reliablemeta.notecharRAJ2000Right ascension (J2000.0)degpos.eq.ra;meta.mainindexedDEJ2000Declination (J2000.0)degpos.eq.dec;meta.mainindexedTeffRegressed effective temperatureKphys.temperature.effectivedoublee_TeffUncertainty of effective temperatureKstat.error;phys.temperature.effectivedoubleloggRegressed surface gravitylog(cm.s**-2)phys.gravitydoublee_loggUncertainty of surface gravitylog(cm.s**-2)stat.errordouble[Fe/H]Regressed metallicityphys.abund.Zdoublee_[Fe/H]Uncertainty of metallicitystat.error;phys.abund.FedoubleJ/A+A/664/A38/extrapolClassification extrapolation starsrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintIDJ-PLUS ID (NNNNN-NNNNN)meta.id;meta.maincharn_ID[*] * mean that the parameters are not very reliablemeta.notecharRAJ2000Right ascension (J2000.0)degpos.eq.ra;meta.mainindexedDEJ2000Declination (J2000.0)degpos.eq.dec;meta.mainindexedTeffRegressed effective temperatureKphys.temperature.effectivedoublee_TeffUncertainty of effective temperatureKstat.error;phys.temperature.effectivedoubleloggRegressed surface gravitylog(cm.s**-2)phys.gravitydoublee_loggUncertainty of surface gravitylog(cm.s**-2)stat.errordouble[Fe/H]Regressed metallicityphys.abund.Zdoublee_[Fe/H]Uncertainty of metallicitystat.error;phys.abund.Fedouble