J/ApJ/992/93ivo://CDS.VizieR/J/ApJ/992/93CDSZhou T.Theissen C.A.Feeser S.J.Best W.M.J.Burgasser A.J.,Cruz K.L.Zhao L.2026-03-02T06:25:50Z2025-11-27T06:41:36ZCDS support team

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

cds-question@unistra.frbrown-dwarfsm-starsl-dwarfsstellar-spectral-typesinfrared-photometryvisible-astronomytrigonometric-parallaxLow-mass stars and brown dwarfs-spectral types (SpTs) M0 and later-play a significant role in studying stellar and substellar processes and demographics, reaching down to planetary-mass objects. Currently, the classification of these sources remains heavily reliant on visual inspection of spectral features, equivalent width measurements, or narrow/wideband spectral indices. Recent advances in machine learning (ML) methods offer automated approaches for spectral typing, which are becoming increasingly important as large spectroscopic surveys such as Gaia, SDSS, and SPHEREx generate data sets containing millions of spectra. We investigate the application of ML in spectral type classification on low-resolution (R~120) near-infrared spectra of M0-T9 dwarfs obtained with the SpeX instrument on the NASA Infrared Telescope Facility. We specifically aim to classify the gravity- and metallicity-dependent subclasses for late-type dwarfs. We used binned fluxes as input features and compared the efficacy of spectral type estimators built using Random Forest (RF), Support Vector Machine, and K-Nearest Neighbor (KNN) models. We tested the influence of different normalizations and analyzed the relative importance of different spectral regions for surface gravity and metallicity subclass classification. Our best-performing model (using KNN) classifies 95.5%+/-0.6% of sources to within +/-1 SpT, and assigns surface gravity and metallicity subclasses with 89.5%+/-0.9% accuracy. We test the dependence of signal-to-noise ratio on classification accuracy and find sources with SNR ~60 have ~95% accuracy. We also find that zy band plays the most prominent role in the RF model, with FeH and TiO having the highest feature importance.2025ApJ...992...93Zhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/992/93CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toII/246 : 2MASS All-Sky Catalog of Point Sources (Cutri+ 2003)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/992/93https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJ/992/93http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJ/992/93https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJ/992/93https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJ/992/93http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJ/992/93GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJ/992/93/table2 (SpeX Prism Library validation/testing sample)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJ/992/93/table2?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJ/992/93/table2?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJ/992/93/table2?GETtext/xml+votable180.050000true0.05641666425.9049990.0055555555555555566/10 48 67 77-78 96 116 186 196 207 222 233 266-267 281 283 295 320-322 331 369 374 399 439 445 463-464 466 474 485 487 544 548 580 608 627-628 672 702 733-736 743 749 762-763 771 776 780 812 826 840 849 858 872 882 906 935 965 990 1023 1028 1031 1040 1050 1054 1072-1073 1075 1079 1083 1114-1115 1159 1168 1170 1188 1280 1291 1539 1579 1594 1774 1873 1890 2017 2040 2044 2110 2149 2154 2164 2202 2206 2255 2258 2260 2291 2366 2434 2441 2502 2511 2538 2580 2608 2653 2678 2704 2753 2807 2978 3040 3101 3144 3192 3211 3441 3443 3764 4096 4106 4119 4136 4168 4183 4224 4226 4251 4253 4263 4267 4269 4274 4285 4312 4329 4436 4448 4453 4457 4465 4473 4521 4534 4536 4608 4630 4635 4645 4661-4662 4669 4689 4716 4719 4727 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35902 35906 35923 35943 35951 35979 36009 36072 36142 36160 36176 36198 36204 36223 36250 36253 36265 36270 36343 36347 36359 36390 36418 36458 36467 36516 36560 36640 36669 36686 36718 36740 36772 36784 36830 36845 38012 38164 38172 38176 38237 38260 38310 38322 38325 38337 38340 38352 38369 38372 38472 38494 38603 38669 38673 38683 38708 38723 38757 38776 38779 38786 38812 38852 39128 39140 39147 39482 39485 39683 39736 39760 39829 40022 40191 40200 40273 40300 40313 40375 40379 40403 40416 40488 40513 40534 40692 40738 40779 40882 40901 40941 41908 41972 42261 42270 42287 42528 42628 42739 42909 42918 42925-42929 42931 42936 42938-42939 42982 42994 43004 43115 43134 43159 43166 43197 43205 43216 43315 43429 43445 43475 43482 43512 43536 43575 43613 43619 43634 43677 43707 43718 43977 44013 44027 44123 44139 44143 44153 44160 44226 44238 44251 44286 44289 44292 44301-44303 44306 44310 44314 44339 44348 44355 44358 44416 44433 44436 44456 44466 44486 44518 44603 44610 44740 44743 44773 44778 44801 44807 44896-44897 44929 44977 46054 46059 46068 46334 46363 46376 46384 46524 46607 46671-46672 46727 46729 46744 46781 46823 46836 46870 46896 46925 46929 47030 47357 47418 47512 47523 47582 47584 47640 47721 47810 47866 47895 47900 47906 47928 47939 47979 48081 48131 48171 48173 48203 48205 48231 48252 48270 48304 48409 48455 48462 48471 48474 48512 48551 48590 48611 48643 48721 48759 48778 48811 48817 48870 48883 48957 48985 49011 49013 49016 49072 49077 49104 49107 49112 49139-49140 491508.650015785639275e-20 1.7003137259100215e-19https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJ/992/93?format=asciiOpticalInfrareddefaultJ/ApJ/992/93/table2SpeX Prism Library validation/testing samplerecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintmoreindicates more SpType estimationsmeta.ref.urlcharNameSource identifiermeta.id;meta.maincharprimaryShortNameShort name (JMHHMM+DDMM)meta.idcharRAJ2000Right Ascension (J2000)degpos.eq.ra;meta.mainDEJ2000Declination (J2000)degpos.eq.dec;meta.mainANameDesignation (JHHMMSSss+DDMMSSs)meta.idcharSpTypeAdopted NIR spectral typesrc.spTypecharChi2Chi-square of spectral standard fitstat.fit.param;meta.modelleddoubleDwarfTypeDwarf type flagmeta.codeintSNRSpeX prism S/Nstat.snrintSpTypeB06Spectral type from Burgasser et al. (2006ApJ...637.1067B, Cat. J/ApJ/637/1067)src.spTypecharSpTypeC18Spectral type from Cruz et al. (2018AJ....155...34C, Cat. J/AJ/155/34)src.spTypecharSpTypeK10Spectral type from Kirkpatrick et al. (2010ApJS..190..100K. Cat. J/ApJS/190/100)src.spTypecharSpTypeSimbadSpectral type from SIMBADsrc.spTypecharr_SpTypeBibcode for SpTypemeta.ref;pos.framecharRefsReference codemeta.ref;pos.frameintplx? Trigonometric parallaxmaspos.parallax.trigfloatnullabler_plxBibcode for parallaxmeta.ref;pos.framechare_plx? Parallax uncertaintymasstat.error;pos.parallaxfloatnullableJmag? 2MASS J magnitudemagphot.mag;em.IR.JfloatnullableHmag? 2MASS H magnitudemagphot.mag;em.IR.HfloatnullableKmag? 2MASS Ks magnitudemagphot.mag;em.IR.KfloatnullableJMAG? Absolute J magnitude from Jmag and plxmagphot.magfloatnullableJ/ApJ/992/93/table7Classification ResultsrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintNameSource identifiermeta.id;meta.maincharSpTypeRFSSpectral type from Random Forest modelsrc.spTypecharSpTypeSVMSpectral type from Support Vector Machinesrc.spTypecharSpTypeKNNSpectral type from K-Nearest Neighbor modelsrc.spTypecharSNRSpeX signal-to-noise ratiostat.snrintSpTypeAdopted spectral typesrc.spTypechar