LAMOST Spectroscopic Survey of the Galactic Anticentre (LSS-GAC): the second release of value-added catalogues

2.8 MB·

by  Maosheng Xiang

Mon.Not.R.Astron.Soc.000,1–22(2015) Printed20January2017 (MNLATEXstylefilev2.2)
LAMOST Spectroscopic Survey of the Galactic Anticentre
(LSS-GAC): the second release of value-added catalogues
7
1 M.-S. Xiang1⋆, X.-W. Liu2,3†, H.-B. Yuan4, Z.-Y. Huo1, Y. Huang2⋆, C. Wang2,
0
2 B.-Q. Chen2⋆, J.-J. Ren2⋆, H.-W. Zhang2, Z.-J. Tian2⋆, Y. Yang2,4, J.-R. Shi1,

n J.-K. Zhao1, J. Li5, Y.-H. Zhao1, X.-Q. Cui6, G.-P. Li6, Y.-H. Hou6, Y. Zhang6,
a
1 1 1 1 1 1 1
J W. Zhang , J.-L. Wang , Y.-Z. Wu , Z.-H. Cao , H.-L. Yan , T.-S. Yan , A.-L. Luo ,

9 1 1 1 1 1 1
H.-T. Zhang , Z.-R. Bai , H.-L. Yuan , Y.-Q. Dong , Y.-J. Lei , G.-W. Li
1

] 1KeyLaboratoryofOpticalAstronomy,NationalAstronomicalObservatories,ChineseAcademyofSciences,Beijing100012,P.R.China
A
2DepartmentofAstronomy,PekingUniversity,Beijing100871,P.R.China
G 3KavliInstituteforAstronomyandAstrophysics,PekingUniversity,Beijing100871,P.R.China
4DepartmentofAstronomy,BeijingNormalUniversity,Beijing100875,P.R.China
.
h 5DepartmentofSpaceScienceandAstronomy,HebeiNormalUniversity,Shijiazhuang050024,China
p 6NanjingInstituteofAstronomicalOptics&Technology,NationalAstronomicalObservatories,ChineseAcademyofSciences,Nanjing210042,P.R.China
-
o
r
t
s
Received:
a
[

1 ABSTRACT
v Wepresentthesecondreleaseofvalue-addedcataloguesoftheLAMOSTSpectroscopicSur-
9 veyoftheGalacticAnticentre(LSS-GACDR2).Thecataloguespresentvaluesofradialve-
0 locityVr,atmosphericparameters—effectivetemperatureTeff,surfacegravitylogg,metal-
4
licity[Fe/H],α-elementtoiron(metal)abundanceratio[α/Fe]([α/M]),elementalabundances
05 [C/H] and [N/H], and absolute magnitudesMV and MKs deducedfrom 1.8 million spectra
of1.4millionuniquestarstargetedbytheLSS-GACsinceSeptember2011untilJune2014.
.
1 Thecataloguesalsogivevaluesofinterstellarreddening,distanceandorbitalparametersde-
0 terminedwithavarietyoftechniques,aswellaspropermotionsandmulti-bandphotometry
7
fromthefar-UVtothemid-IRcollectedfromtheliteratureandvarioussurveys.Accuraciesof
1 radialvelocitiesreach5kms−1 forlate-typestars,andthoseofdistanceestimatesrangebe-
:
v tween10–30percent,dependingonthespectralsignal-to-noiseratios.Precisionsof[Fe/H],
i [C/H]and[N/H]estimatesreach0.1dex,andthoseof[α/Fe]and[α/M]reach0.05dex.The
X
large number of stars, the contiguous sky coverage, the simple yet non-trivial target selec-
r tionfunctionandtherobustestimatesofstellarradialvelocitiesandatmosphericparameters,
a
distances and elemental abundances, make the catalogues a valuable data set to study the
structureandevolutionoftheGalaxy,especiallythesolar-neighbourhoodandtheouterdisk.
Keywords: Galaxy:abundance– Galaxy:disk– Galaxy:evolution– Galaxy:formation–
techniques:spectroscopic
1 INTRODUCTION hundredsofbillionsofGalacticstarsaredistributedoverthewhole
sky,andourviewsintheGalacticdiskareseriouslylimitedbythe
Better understanding the structure, stellar populations, and the
interstellar dust extinction. Obtaining the full dimensional distri-
chemicalanddynamicevolutionoftheMilkyWayisbothachal-
butionofacompletestellarsampleisthusagreatchallenge.Itis
lengeandanopportunityofmoderngalacticastronomy.TheMilky
onlyrecentlythatcomprehensivesurveysofGalacticstarsbecome
Wayistheonlygalaxywhosedistributionofstellarpopulationscan
feasible,thanks totheimplementationof anumber of large-scale
bemappedoutinfulldimensionality—three-dimensionalposition
photometric and spectroscopic surveys, such as the Sloan Digital
and velocity, age, as well as photospheric elemental abundances.
SkySurvey(SDSS;Yorketal.2000),theTwoMicronAllSkySur-
However, owing to our location inside the Milky Way disk, the
vey(2MASS;Skrutskieetal.2006),theApachePointObservatory
GalacticEvolutionExperiment(APOGEE;Majewskietal.2010),
⋆ LAMOSTFellow theLAMOSTExperimentforGalacticUnderstandingandExplo-
† E-mail:[email protected]
2 Xianget al.
ration(LEGUE;Dengetal.2012;Zhaoetal.2012)andtheGaia very bright stars, making the sample a golden mine to study the
astrometricsurvey(Perrymanetal.2001). solar-neighbourhood.
Radialvelocitiesandatmosphericparameters(effectivetem-
As a major component of the LEGUE project, the LAM-
peratureT , surfacegravitylogg,metallicity[Fe/H])havebeen
OSTSpectroscopicSurveyoftheGalacticAnticentre(LSS-GAC; eff
deduced from the LSS-GAC spectra for A/F/G/K-type stars us-
Liuetal.2014;Yuanetal.2015)isbeingcarriedoutwiththeaim
ingboththeofficialLAMOSTStellarparameterPipeline(LASP;
to obtain a statistically complete stellar spectroscopic sample in
Wuetal.2011,2014)andtheLAMOSTStellarParameterPipeline
a contiguous sky area around the Galactic anticentre, taking full
atPekingUniversity(LSP3;Xiangetal.2015a).Typicalprecisions
advantage of thelargenumber of fibers(4,000) andfieldof view
oftheresults,dependingonthespectralsignal-to-noiseratio(SNR)
(20sq.deg.)offeredbyLAMOST(Cuietal.2012).Thesurveywill
andthespectraltype,areafew(5–10)kms−1 forradialveloc-
allowustoacquireadeeperandmorecomprehensiveunderstand-
ingofthestructure,originandevolutionoftheGalacticdiskand ityVr,100–200KforTeff,0.1–0.3dexforlogg,0.1–0.2dex
for [Fe/H] (Xiangetal. 2015a; Luoetal. 2015; Gaoetal. 2015;
halo,aswellasthetransitionregionbetweenthem.Themainsci-
Renetal. 2016; Wangetal. 2016b). Values of α-element to iron
entific goals of LSS-GAC include: (a) to characterize the stellar
abundance ratio [α/Fe], as well as abundances of individual ele-
populations,chemicalcomposition,kinematicsandstructureofthe
ments (e.g. [C/H] and [N/H]) have also been derived with LSP3
thin and thick disks and their interface with the halo; (b) to un-
(Lietal.2016;Xiangetal.2017),withprecisionssimilartothose
derstand the temporal and secular evolution of the disk(s); (c) to
achievedbytheAPOGEEsurveyforgiantstars(Xiangetal.2017).
probethegravitationalpotentialanddarkmatterdistribution;(d)to
Efforts have also been made to derive stellar parameters from
identifystaraggregatesandsubstructuresinthemulti-dimensional
LAMOSTspectrawithotherpipelines,suchastheSSPP(Leeetal.
phasespace;(e)tomaptheinterstellarextinctionasafunctionof
2015) and the Cannon (Hoetal. 2016). Liuetal. (2015) refine
distance;(f)tosearchforandstudyrareobjects(e.g.starsofpecu-
the LASP estimates of log g using a support vector regression
liarchemicalcompositionorhypervelocities);(g)tostudyvariable
(SVR)modelbasedonKepler asteroseismicmeasurementsofgi-
starsandbinarieswithmulti-epochspectroscopy.
ant stars. Stellar extinction and distances have been deduced for
LSS-GACplans tocollect low-resolution (R ∼ 1800) opti- LSS-GAC sample stars using a variety of methods (Chenetal.
calspectra(λλ3700–9000Å) ofmorethan3millionstarsdown 2014;Yuanetal.2015;Carlinetal.2015;Wangetal.2016a),with
toalimitingmagnitudeofr ∼17.8mag(to18.5magforselected typicaluncertaintiesofEB−V ofabout0.04mag,andofdistance
fields)inacontiguousskyareaofover3400sq.deg.centredonthe between 10 – 30 per cent, depending on the stellar spectral type
Galactic anticentre (|b| 6 30◦, 150 6 l 6 210◦), and deliver (Yuanetal.2015).
spectral classifications, stellar parameters (radial velocity Vr, ef- Followingayear-longPilotSurvey,LSS-GACwasinitiatedin
fectivetemperatureTeff,surfacegravitylogg,metallicity[Fe/H], October,2012,andisexpectedtocompleteinthesummerof2017.
α-elementtoironabundanceratio[α/Fe],andindividualelemental TheLSS-GACdatacollecteduptotheendofthefirstyearofthe
abundances), as well as values of interstellar extinction and dis- RegularSurveyarepublicavailablefromtwoformalofficialdata
tanceofthesurveyedstars,soastobuild-upanunprecedented,sta- releases, namely the early (LAMOST EDR; Luoetal. 2012) and
tisticallyrepresentativemulti-dimensionaldatabasefortheGalactic first (LAMOST DR1; Luoetal. 2015) data release1. The LAM-
(disk) studies.ThetargetsofLSS-GACareselecteduniformlyin OSTEDRincludesspectraandstellarparametersderivedwiththe
theplanesof(g−r,r)and(r−i,r)Hessdiagramsandinthe(RA, LASPforstarsobservedduringthePilotSurvey,whiletheLAM-
Dec)spacewithaMonteCarlomethod,basedontheXuyiSchmidt OSTDR1includesstarsobservedbyJune,2013.Inaddition,there
TelescopePhotometricSurveyoftheGalacticAnticentre(XSTPS- isapublicreleaseofLSS-GACvalue-addedcataloguesforstarsob-
GAC; Zhangetal.2013, 2014; Liuetal. 2014; Yuanetal.2015), servedbyJune,2013,theLSS-GACDR12(Yuanetal.2015).LSS-
a CCD imaging photometric survey of ∼ 7000sq.deg. with the GACDR1presentsstellarparametersderivedwithLSP3,valuesof
Xuyi1.04/1.20mSchmidtTelescope.Starsofallcoloursaresam- interstellar extinction and stellar distance deduced with a variety
pledbyLSS-GAC.Thesamplingratesarehigherforstarsofrare ofmethods,aswellasmagnitudesofbroadbandphotometrycom-
colours, without losing therepresentation of bulk stars,given the piled from various photometric catalogues (e.g. GALEX, SDSS,
highsamplingdensity(& 1000starspersq.deg.).Thissimpleyet XSTPS-GAC,UCAC4,2MASSandWISE),andvaluesofproper
non-trivialtargetselectionstrategyallowsforastatisticallymean- motions from the UCAC4 and PPMXL catalogues and those de-
ingfulstudyoftheunderlyingstellarpopulationsforawiderange rivedbycombingtheXSTPS-GACand2MASSastrometricmea-
of object class, from white dwarfs (e.g. Rebassa-Mansergasetal. surements,and,finally,stellarorbitalparameters(e.g.eccentricity)
2015),mainsequenceturn-offstars(e.g.Xiangetal.2015b)tored computedassumingspecificGalacticpotentials.
clumpgiants(e.g.Huangetal.2015c),aftertheselectionfunction This paper presents the second release of value-added cata-
hasbeenproperlytakenintoaccount. logues of LSS-GAC (LSS-GAC DR2). LSS-GAC DR2 presents
Asanextension,LSS-GACalsosurveysobjectsinacontigu- the aforementioned multi-dimensional parameters deduced from
ousareaofafewhundredsq.deg.aroundM31andM33.Thetargets 1,796,819 spectra of 1,408,737 unique stars observed by June,
includebackgroundquasars,planetarynebulae(PNe),HIIregions, 2014.ComparedtoLSS-GACDR1,inadditiontoasignificantin-
globular clusters, supergiant stars, as well as foreground Galac- creaseinstellarnumber, several improvements tothedatareduc-
tic stars. In addition, to make full use of all available observing tionandstellarparameterdeterminationshavebeenimplemented,
time, LSS-GACtargetsvery bright (VB) starsof r < 14mag in including: (1)Anupgraded LAMOST2D pipelinehasbeenused
skyareasaccessibletoLAMOST(−10◦ 6 Dec 6 60◦)inpoor to process the spectra; (2) The spectral template library used by
observing conditions (bright/grey lunar nights, or nights of poor LSP3hasbeenupdated,addingmorethan200newtemplates.The
transparency).Thoseverybrightstarscompriseanexcellentsam-
plesupplementarytothemainone.Giventheirrelativelylowsur-
facedensities,atleastfortheareasoutsidethedisk,LSS-GAChas 1 http://dr1.lamost.org
achievedaveryhighsamplingcompleteness(50percent)forthose 2 http://lamost973.pku.edu.cn/site/data
3
atmospheric parameters for all template stars have also been re-
determined/calibrated; (3)Valuesofα-elementtoironabundance
ratio[α/Fe] have been estimated withLSP3; (4) Accurate values
ofstellaratmosphericparameters(T ,logg,[Fe/H],[α/Fe]),ab-
eff
solutemagnitudesMV andMKs,aswellaselementalabundances
[C/H]and[N/H],havealsobeenestimatedfromthespectrausing
a multivariate regression method based on kernel-based principal
componentanalysis(KPCA).
Thepaperisorganizedasfollows.Section2describestheob-
servationsincludedintheLSS-GACDR2,includingabriefreview
of the target selection algorithm and the observational footprint.
Section3 introduces the data reduction briefly. Section4 presents
adetaileddescriptionoftheimprovementsinstellarparameterde-
terminationsincorporatedinLSS-GACDR2.Section5brieflydis-
cussestheduplicateobservations,whichaccountsfornearly30per
Figure2.LSS-GACDR2footprintfortheverybright(VB)plates.Tore-
cent of all observations. Section6 introduces the determinations
ducethefigurefilesize,only1in10observedstarsareplotted.
of extinction anddistance. Section7presents proper motions and
derivationofstellarorbitalparameters.Theformatofvalue-added
cataloguesisdescribedinSection8,followedbyasummaryinSec- (∼4650Å)orthe(∼7450Å)partofthespectrum(Liuetal.2014).
tion9. Thenumbersofspectraandstarshaveincreasedsignificantlycom-
pared to those of LSS-GAC DR1, which contains, for example,
225,522spectraof189,042uniquestarsofSNR(4650Å)>10for
the main survey, and 457,906 spectra of 385,672 unique stars of
2 OBSERVATIONS
SNR(4650Å)> 10fortheVBsurvey(cf.Yuanetal.2015).Due
Tomakegooduseofobservingtimeofdifferentqualitiesaswell to the overlapping of LAMOST fields of view of adjacent plates
as to avoid fibre cross-talking, LSS-GAC stars are targeted by 4 andtherepeatingofobservationsfailedtomeetthequalitycontrol,
typesofsurveyplatesdefinedinr-bandmagnitude(Liuetal.2014; thereisaconsiderable fractionof starsthat havebeen repeatedly
Yuanetal.2015).Starsofr<14.0magaretargetedbyverybright targeted several times. For LSS-GACDR2, amongst the 948,361
(VB) plates, and observed in grey/lunar nights, with typical ex- uniquestarstargetedbythemainsurvey,71.0,20.6,6.0,1.7,0.5,
posure time of (2 – 3) × 600s. Stars of 14.0 < r . 16.3mag 0.1percentofthestarsareobservedbyonetosixtimes,respec-
aretargetedbybright(B)plates,andobservedingrey/darknights, tively. The corresponding fractions for the M31/M33 survey are
withtypicalexposuretimeof2×1200s,whereasstarsof16.3 . 60.1,20.4,10.1,4.4,2.5,1.3percent,andthosefortheVBsurvey
r . 17.8mag,andof17.8 . r < 18.5magaretargetedrespec- are73.5,20.5,3.7,1.7,0.3,0.2percent.Forthoseuniquestarswith
tivelybymedium-bright(M)andfaint(F)plates,andobservedin SNR(4650Å)>10,thecorrespondingfractionsare83.6,13.2,2.4,
darknightsofexcellentobservingconditions(intermofseeingand 0.6, 0.1,0.03 per cent for theLSS-GACmainsurvey, 72.6, 19.2,
transparency),withtypicalexposuretimeof3×1800s. 5.6,1.7,0.7,0.2percentfortheM31/M33survey,and78.3,17.3,
By June, 2014, 314 plates (194 B + 103 M + 17 F) for the 2.9, 1.2, 0.2, 0.1 per cent for the VB survey. Note that there are
LSS-GAC main survey, 59 plates (38 B + 17 M + 4 F) for the alsoasmallfraction(∼ 0.8percent)ofstarsthataretargetedby
M31/M33surveyand682platesfortheVBsurveyhavebeenob- boththeLSS-GACmain(orM31/M33)surveyandtheVBsurvey.
served.Notethatspectraofafewplatescouldnotbesuccessfully Theseduplicateswerenot consideredwhencalculatingtheabove
processed with the 2D pipeline and are therefore not included in percentagenumbers.
theabovestatistics.Duringthesurvey,someobservingtime,onthe Figs.1and2plotthefootprintsofstarswitheitherablueor
level of one or two grey nights per month has been reserved for redspectralSNRhigherthan10forLSS-GACDR2.Thefootprints
monitoringtheinstrumentperformance(e.g.throughputandaccu- ofstarstargetedbyVB,BandMplatesareplottedinseparatepan-
racyoffibrepositioning; Liuetal.2014;Yuanetal.2015).Some els.Forthemainsurvey,thestrategyistoextendtheobservations
ofthosereservednightshavebeenusedtotargetsomeoftheLSS- of a stripe of Dec ∼ 29◦ to both higher and lower Declinations
GACplates,yieldinganother 94observedplates(79B/M/F+15 (Yuanetal.2015).ComparedtoLSS-GACDR1,LSS-GACDR2
V).Finally,43BorMorFLSS-GACplateswereobservedfrom hascompletedtwomorestripesforBandMplates,namelythose
SeptembertoOctober,2011,whentheLAMOSTwasbeingcom- ofDec ∼ 34◦ and∼ 24◦,respectively.AfewBandMplatesof
missionedbeforethestartofPilotSurvey.Forthose43plates,the Galacticlatitudeb > 35◦ wereobservedusingeitherthereserved
magnitudelimitsofassigningstarsinB/M/Fplatesarenotexactly timeorduringthecommissioningphase.FortheM31/M33survey,
the same as those adopted during the Pilot and Formal surveys. 7Band9MplateswerecollectedinthesecondyearoftheRegu-
Forconvenience,allplatesobservedusingreservedtimeaswellas larSurvey(September2013–June2014),leadingtoamuchlarger
thosecollectedduringthecommissioningphasehavebeengrouped skycoveragecomparedtoLSS-GACDR1.Significantprogressin
into,asappropriately,theLSS-GACmain,M31/M33andVBsur- theobservationofVBplatesisseeninLSS-GACDR2,intermof
vey,respectively,leadingtoatotalof395platesfortheLSS-GAC boththeareaandcontinuityoftheskycoverage.
main,100platesfortheM31/M33and697platesoftheVBsurvey, Figs.3 – 5 plot the density distributions of starstargeted, as
respectively. wellasthosesuccessfullyobserved(i.e.withaspectralSNRhigher
The total numbers of spectra collected and unique stars tar- than10, eitherintheblueorred),inthecolour –magnitudedia-
geted by those plates are listed in Table1. Table1 also lists the grams (CMDs) for the main, M31/M33 and VB surveys, respec-
numbersofspectraanduniquestarsthataresuccessfullyobserved, tively. For the main and M31/M33 surveys, the diagrams are for
defined by a spectral SNR of higher than 10 either in the blue colour–magnitudecombinations(g−r,r)and(r−i,r)usedtose-
4 Xianget al.
Table1.Numbersofspectraanduniquestars(inparentheses)observedbyLSS-GACbyJune,2014.
LSS-GACMainSurvey M31/M33Survey VBSurvey
AllSNRs 1,332,812(948,361) 305,226(171,259) 1,944,525(1,431,219)
SNR(4650Å)>10 510,531(423,503) 91,921(65,841) 1,194,367(922,935)
SNR(7450Å)>10 688,459(572,438) 68,380(58,197) 1,358,618(1,050,143)
SNR(4650Å)>10orSNR(7450)>10 763,723(618,924) 113,597(80,452) 1,397,538(1,075,677)
Figure1.LSS-GACDR2footprintsinaGalacticcoordinatesystemofstarsobservedrespectivelywithbright(B;leftpanel)andmedium(M;rightpanel)
plates.TheredlinedenotesaconstantDeclinationof30◦.Toreducethefigurefilesize,only1in10observedstarsareplotted.
lecttargets(Yuanetal.2015).Magnitudesofg,r,ibandsarefrom high sampling ratesof very bright stars(e.g. Xiangetal. 2015b),
theXSTPS-GACsurvey, except for afew platesofhigh Galactic andthefactthatstarsofallcolourshavebeenobservedwithouta
latitudes, for which magnitudes from the SDSS photometric sur- strongcolourbias,theselectionfunctioncanstillbewellaccounted
veyareused.Thefiguresshowthat,asplanned,starsofallcolours forwithsomeeffortandcare,ifnotstraightforwardly.
havebeenobserved.Figs.3–5alsoshowthatthedistributionsof Fig.6 plots the SNR distribution of spectra for the main,
starsthathaveeitherablueorredspectralSNRhigherthan10,as M31/M33 and VBsurveys, aswell asthose of thewhole sample
plottedinthemiddlepanelsofthosethreefigures,arequitesimi- fordwarfandgiantstars.OnlyspectrawitheitherSNR(4650Å)or
lartothosetargeted,plottedinthetoppanelsofthethreefigures, SNR(7450Å)higherthan10areplotted.Thenumberofspectrain
except forfaintones(r > 17.8mag).Notethatforthemainand logarithmicscaledecreasesapproximatelylinearlywithincreasing
M31/M33surveys,somestarsofeitherr >18.5orr <14.0mag SNR.SNRsoftheredpartofthespectraaregenerallyhigherthan
were observed during the commissioning phase. In contrast, the thoseofthebluepart.Also,spectraoftheVBsurveyhavegenerally
distributions of stars of SNR(4650) > 10 are quite different – higherSNRsthanthoseofthemainandM31/M33surveys.Distri-
therearefewerfaintstarsofredcolours.Thisiscausedbyacom- bution of SNRs for the giants are similar to those of the dwarfs.
bination of the effects of low intrinsic fluxes in the blue of red Heretheclassificationofdwarfsandgiantsisbasedontheresults
stars and the lower throughputs of the spectrographs in the blue of LSP3(cf. Section 4). For the whole sample, about 36, 57 and
comparedtothoseinthered(Cuietal.2012).FortheVBsurvey, 73percentofthespectrahaveaSNRhigherthan50,30and20,
(g−r,r)and(J −Ks,J)diagramsareplotted.Theg,r,imag- respectively,inthebluepartofthespectrum.
nitudes are taken from the AAVSO Photometric All-Sky Survey
(APASS;Munarietal.2014),whichhaveabrightlimitingmagni-
tudeofabout10magandafaintlimitingmagnitude(10σ)ofabout
16.5mag ing,r,i-bands. For starsof r > 14.0mag, magnitudes 3 DATAREDUCTION
fromtheXSTPS-GACorSDSSsurveysareadoptedifavailable.A
TherawspectraofLSS-GACusedtogeneratethevalue-addedcat-
comparisonofstarscommontoXSTPS-GACandAPASSsurveys
alogueswereprocessedatPekingUniversitywiththeLAMOST2D
showsgoodagreementinbothmagnitudesandcoloursforstarsof
reductionpipeline(Luoetal.2012,2015)toextractthe1Dspectra.
14.0 < r < 15.0mag, with differences of just a few (< 5) per
Thisprocessincludesseveralbasicreductionsteps,includingbias
cent. Due to the heterogeneous input catalogs and magnitude cut
subtraction,fibretracing,fibreflat-fielding,wavelengthcalibration
criteriaused for theVBsurvey (Yuanetal.2015),themorpholo-
andsky subtraction. Both fibretracing andflat-fieldingwerefirst
giesofCMDdistributionsofVBplatesaremorecomplicatedthan
carried out using twilight flat-fields. The results were further re-
those of the main and M31/M33 plates. Nevertheless, due to the
visedusingskyemissionlineswhenprocessingtheobjectspectra
5
Figure3.Colour-codedstellardensitydistributionsinthecolour-magnitude Figure4.SameasFig.3butfortheM31/M33survey.
(g−r,r)and(r−i,r)diagramsfortheLSS-GACmainsurvey.Theupper
panels show allobservedstars,while themiddlepanels showthosewith
eitherSNR(4650Å)>10orSNR(7450Å)>10,andthelowerpanelsshow tingoffluxesmeasuredbytheindividualskyfibres.Themeasured
thosewithSNR(4650Å)> 10.Thehistogramsshowtheonedimensional
fluxesofskyemissionlinesintheobjectspectraarenormalizedto
distributions ofstars incolours (g −r)and(r −i)orinmagnitude r,
thoseofthesuper-skyspectrumtocorrectforpotentialdifferences
respectively,normalizedtothemaximumvalue.
of throughputs of fibresused to measure thesky and the objects.
Thecorrectionassumesthatthestrengthsoftheskyemissionlines
toaccountforthepotentialshiftsoffibretracesandthevariations areconstantacrosstheskyareacoveredbyagivenspectrograph,
infibrethroughput.Typicalprecisionoffibreflat-fielding,asindi- whichisaboutonesquaredegree,andanydifferencesinskyemis-
catedbythedispersionsofflat-fieldsacquiredindifferentdays,is sionlinefluxesasmeasuredbytheskyandobjectfibres,arecaused
betterthan1percent.Wavelengthcalibrationwascarriedoutus- byerrorsinflat-fielding.Thecorrectionalsoassumesthatforthe
ing exposures of a Cd-Hg arc lamp for the blue-arm spectra and skybackground,thecontinuumscaleswithemissionlineflux.
anAr-Nearclampforthered-armspectra.Typically,theresiduals The resultant 1D spectra were then processed with the flux
ofwavelengthcalibrationfortheindividualarclineshaveamean calibration pipeline developed specifically for LSS-GAC to deal
valueclosetozeroandastandarddeviationof∼0.02Å,whichcor- withfieldsoflowGalacticlatitudesthatmaysufferfromsubstantial
respondsto∼1kms−1invelocityspace.Whenprocessingtheob- interstellarextinction.Thepipelinegeneratesflux-calibratedspec-
jectspectra,skyemissionlinesareusedtoadjustthewavelengths tra as well as co-adds the individual exposures of a given plate
toaccountforanyresidualsystematicerrorsinthewavelengthcali- (Xiangetal. 2015a; Yuanetal. 2015). To deal with the interstel-
brationand/orpotentialwavelengthdriftsbetweenthearc-lampand larextinction,thepipelinecalibratesthespectrainaniterativeway,
object spectra. A comparison of stellar radial velocities with the usingF-typestarsselectedbasedonthestellaratmosphericparam-
APOGEE measurements for LAMOST-APOGEE common stars etersyieldedbyLSP3asfluxstandards.Thetheoreticalsynthetic
yieldsanoffsetof−3to−4kms−1(Xiangetal.2015c;Luoetal. spectrafromMunarietal.(2005)ofthesameatmosphericparame-
2015),andtheoffsetisfoundtobestableinthepastfewyears,with tersareadoptedastheintrinsicspectralenergydistributions(SEDs)
typicalnight-to-nightvariationsofabout2kms−1.Foreachofthe ofthestandards.Typical(relative)uncertaintiesofthespectralre-
16 spectrographs, about 20 fibres are typically assigned to target sponse curves (SRCs) thus derived are about 10 per cent for the
skybackgroundforskysubtraction.Thenumbersofskyfibresal- wavelengthrange4000–9000Å(Xiangetal.2015c).
located for sky measurement are higher for plates of low source Compared tothepipelines usedtogenerate LSS-GACDR1,
surface density, e.g. VB plates of |b| > 10◦. To subtract the sky afewimprovementshavebeenimplemented:(1)Severalfibresof
background, the 2D pipeline creates a super-sky by B-spline fit- Spectrograph#4arefound tobemis-identifiedbeforeJune, 2013
6 Xianget al.
Figure6.DistributionofspectralSNRsforthemain(topleft),M31/M33
(topright)andVB(bottomleft)surveys.Blueandredlinesrepresentspec-
tral SNRat 4650and7450Å,respectively. Thebottom right panel plots
SNR (4650Å) for the whole sample that have a spectral SNR (4650Å)
higherthan10fordwarfs(solidline)andgiants(dashedline),respectively.
Figure5.SameasFig3butfortheverybrightsurvey.Colour-magnitude
diagramsof(g−r,r)and(J−Ks,J)areshown.
conditions, may haveartificiallyhigh SNRs,yet thisratiocan be
(LuoA.-L.,privatecommunication). Asa result,thecoordinates, infact quitesmallfor thosespectra. Theflagisdenoted by ‘OB-
magnitudes,spectraandstellarparametersofstarstargetedbythose JECT_SKY_RATIO’inthevalue-addedcatalogues.Asecondflag
fibreswerewronglyassignedinLAMOSTDR1(Luoetal.2015) isusedtomarkfibresthatmaybepotentiallyaffectedbythenearby
aswellas LSS-GACDR1(Yuanetal. 2015). Thefibresare:#76 saturatedfibres.Saturationoccursforverybrightstars.Whenafi-
(87),87(79),79(95),95(84),84(76),44(31),31(46),46(26), bresaturates,spectraofnearbyfibres,especiallythoseoffaintstars,
26 (44), where the numbers in the brackets are the correct ones. canbeseriouslycontaminatedbyfluxcrosstalk,leadingtoincor-
Theerrorshavebeencorrected;(2)Thevaluesofinterstellarred- rectSNRsandwronglyestimatedstellarparameters.Whenafibre
dening of flux standard stars are now derived with the star-pair saturates, starsobserved by theadjacent 50 fibers(±25) arenow
method(Yuanetal.2015),replacingthosededucedbycomparing marked by flag ‘SATFLAG’in the value-added catalogues. Even
theobservedandsyntheticcolours,asadoptedinLSS-GACDR1. when afiber isnot saturated, crosstalk may stilloccur if theflux
Thechangeisbasedontheconsiderationthatthestar-pairmethod ofthatfibreisveryhigh.Toaccountforsuchsituation,athirdflag
for extinction determination is model-free, and yields in general isintroduced.IfthespectrumfromagivenfibrehasaSNRhigher
more robust results than the method adopted for LSS-GAC DR1 than300,thentheadjacent4(±2)fibresareassigneda‘BRIGHT-
(Yuanetal.2015);(3)ForthefluxcalibrationofVBplates,g,r,i FLAG’ value of 1; otherwise the flag has a value of 0. For each
magnitudesfromtheAPASSsurvey(Munarietal.2014)arecom- fibre,thevalueofmaximumSNRofthenearest5fibres(theadja-
bined with 2MASS J,H,Ks magnitudes to derive values of ex- cent4plusthefibreofconcernitself),isalsolistedas‘BRIGHT-
tinctionofflux-calibrationstandardstars.InLSS-GACDR1,only SNR’inthevalue-added catalogues. Finally,aflaghasbeen cre-
2MASSJ,H,Ksmagnitudeswereused.Thechangeshouldsignif- atedtomarkbadfibres.Amongthe4000fibresofLAMOST,some
icantlyimprovetheaccuracyofextinctionestimatesforstandards have very low throughputs or suffer from serious positioning er-
usedtoflux-calibrateVBplates. rors.Spectrayieldedbythose“bad”fiberscannot betrusted.The
ConsideringthattheSNRalonedoesnotgiveafullydescrip- numberofbadfibrescontinuouslyincreaseswithtime,andreaches
tion of the quality of a spectrum, a few flags are now added to about200byJune,2014.Thosefibersaremarkedby‘BADFIBRE’
image header of a processed spectrum. The first flag is the ratio inthevalue-added catalogues. Inaddition tothose newly created
of (sky-subtracted) stellarfluxtothefluxof(super-) skyadopted flags,informationofobservingconditionswithregardtothemoon
forsky-subtraction.Duetotheuncertaintiesinsky-subtraction,the (phase,angulardistance),theairmassandthepointingpositionof
spectraofsomestars,especiallythoseobservedunderbrightlunar thetelescopearenowalsoincludedinLSS-GACDR2.
7
4 STELLARPARAMETERDETERMINATION: parametersinordertoaccountforthesystematicsamongsttheval-
IMPROVEMENTSOFLSP3 uesfromthedifferentsources,thehomogenizationwascarriedout
for only a limitedtemperature range of 4000 < T < 6300K.
LSS-GAC DR1 presents values of radial velocity Vr and stellar Withmoredataavailable,thereisroomofconsidereaffble improve-
atmospheric parameters (effective temperature T , surface grav-
eff ment.
itylogg,metallicity[Fe/H])derivedfromLSS-GACspectrawith
Todealwiththelimitedwavelength coverage oftheMILES
LSP3.Sincethen,afewimprovementsofLSP3havebeenimple-
spectra and to improve the coverage and distribution of template
mentedandareincludedinLSS-GACDR2,including(1)Anum-
stars in the parameter space, an observational campaign is being
ber of new spectral templates have been added to the MILES li-
carried out to observe additional template stars that fill the holes
brary,andatmosphericparametersofthetemplatestarshavebeen
inparameterspace,toenlargethecoverageofparameterspace,as
re-determined/calibrated;(2)Severalflagsarenowassignedtode-
wellastoextendthespectralwavelengthcoverageto9200Å,using
scribe the best-matching templates that has the characteristics of
the NAOC 2.16m telescope and the YAO 2.4mtelescope (Wang
a,e.g.,variablestar,binary,double/multiplestarorsupergiantetc.
etal.inpreparation). Theprojectplanstoobtainlong-slitspectra
ofagiventargetspectrum; (3)Valuesof α-elementtoironabun-
covering3600–9200Åforsome900templatestarsnewlyselected
danceratio[α/Fe]havebeenestimatedbytemplatematchingwith
fromthePASTELcatalog(Soubiranetal.2010),acompilationof
a synthetic spectral library; (4) A multivariate regression method
starswithrobuststellarparameters,mostlyinferredfromhighres-
based on kernel-based principal component analysis (KPCA) has
olutionspectroscopy. Theprojectwillalsoextendthewavelength
been used to obtain an independent set of estimates of stellar at-
coverageofalltheoriginal MILESspectrato9200Å.Inthecur-
mosphericparameters,includingT ,logg,[M/H],[Fe/H],[α/M],
eff rentwork,267newtemplatespectraobtainedbythecampaignby
[α/Fe], absolute magnitudes MV and MKs as well as individual October, 2015havebeen added totheMILESlibrarytogenerate
elementalabundancesincluding[C/H]and[N/H].
parameter estimates presented in LSS-GAC DR2. In addition, to
reduce the systematic and random errors of the atmospheric pa-
rameters of the template stars, Huang et al. (in preparation) have
4.1 UpdatestotheMILESlibrary
re-calibrated/determined the atmospheric parameters of all tem-
TheoriginalMILESspectrallibrarycontainsmedium-to-lowres- plate stars, both old and newly selected. In doing so, the recent
olution (full-width-at-half-maximum FWHM ∼ 2.5Å) long-slit determinations of parametersof templatestarsavailablefromthe
spectraofwavelengthrange3525–7410Åfor985starsthathave PASTEL catalogues have been adopted, replacing the older val-
robust stellar parameter estimates in the literature, mostly deter- ues used by the original MILES library. The updated values of
minedwithhigh-resolutionspectroscopy(Sánchez-Blázquezetal. metallicityarethenusedtocalculateeffectivetemperaturesusing
2006; Falcón-Barrosoetal. 2011). TheMILES libraryisadopted thenewlypublished metallicity-dependent colour-temperature re-
by LSP3 as templates for estimation of atmospheric parameters lationsofHuangetal.(2015a),deducedfrommorethantwohun-
fromLAMOSTspectra.Comparedtoothertemplatelibrariesavail- dred nearby stars with direct, interferometric angular size mea-
able in the literature, MILES has two advantages. Firstly, the surementsandHipparcosparallaxes.Valuesofsurfacegravityare
MILESspectrahaverobustfluxcalibrationandthespectralresolu- re-determined using Hipparcos parallaxes (Perrymanetal. 1997;
tionmatcheswellthatofLAMOSTspectra.Secondly,thetemplate Anderson&Francis 2012) and stellar isochrones from the Dart-
stars cover a large volume of parameter space (3000 < T < mouth Stellar Evolution Database (Dotteretal. 2008). Values of
eff
40,000K,0<logg<5dexand−3.0<[Fe/H]<0.5dex). [Fe/H]arethenre-calibratedtothestandardscaleofGaia-ESOsur-
Still,forthepurposeofaccuratestellaratmosphericparame- vey(Jofréetal.2015).Fig.6plotsthenewlycalibrated/determined
terestimation,theMILESlibraryhasafewdefectsinwantofim- parametersofthetemplatestarsintheTeff–loggandTeff–[Fe/H]
provement.Oneisthelimitedspectralwavelengthcoverage.LAM- planes.NotethatingeneratingLSS-GACDR1,85oftheoriginal
OST spectra cover the full optical wavelength range of 3700 – MILESstarswereabandonedbecausetherewerenocompletepa-
9000Å, whereas MILES spectra stop at 7410Å in the red. As a rameterestimatesintheliteratures.Thosestarsarenowincludedin
result, LAMOST spectra in the 7400 –9000Å wavelength range thelibraryastheirparametershavebeenre-determined.Also,with
havehithertonotbeenutilizedforparameterestimation.Thereare thenewlyselectedandobservedtemplatesaddedtothelibrary,we
afewprominentfeaturesinthiswavelengthrangethataresensitive havenowdiscardedthe400interpolatedspectrausedwhengener-
abundanceindicators,including, e.g.theCaII λ8498,8542, 8664 atingLSS-GACDR1.
triplet and the NaI λ8193, 8197 doublet. In addition, since LSS-
GACtargetsstarsofallcolours,especiallythoseinthedisk,about
4.2 [α/Fe]estimationbymatchingwithsyntheticspectra
30percentspectracollectedhavepoorSNRsinthebluebutgood
SNRsin the red. Those stars are either intrinsically red or suffer α-element to iron abundance ratio [α/Fe] is a good indicator of
fromheavyinterstellarextinction.Stellarparametersforthosestars theGalacticchemicalenrichmenthistory(e.g.Leeetal.2011),and
havecurrentlynotbeenderivedfromLAMOSTspectra,byeither thusvaluable toderive. Toestimateratios[α/Fe]fromLAMOST
LSP3orLASP,duetothefactthatboththeMILESandELODIE spectra, a method of template matching based on χ2-fitting with
(adoptedbyLASP)libraries,donothavewavelengthcoveragelong syntheticspectraisdevelopedforLSP3.Detailsaboutthemethod
enoughinthered.AnotherdefectoftheMILESlibraryisthein- androbustnesstestsofthededuced[α/Fe]valuesaredescribedin
homogenous coverage of stars in the parameter space. As shown Lietal.(2016).Herewebrieflysummarizethemethodandpoint
inXiangetal.(2015c),thereareholesandclustersinthedistribu- outafewimprovementsthatmayleadtobetterresults.
tionof MILESstarsintheparameter space, leading tosomesig- The synthetic library used to estimate [α/Fe] was generated
nificantartifactsintheresultantparameters. Finally,stellaratmo- withtheSPECTRUMcode(Gray1999)ofversion2.76,utilizing
sphericparametersoftheoriginalMILESlibraryarecollectedfrom theKuruczstellarmodelatmospheresofCastelli&Kurucz(2004).
varioussourcesintheliteraturethussufferfromsystematicerrors. Thesolar[α/Fe]ratioissettozero,andtheα-enhancedgridsare
AlthoughCenarroetal.(2007)havetakenefforttohomogenizethe generated by scaling the elemental abundances of O, Mg, Si, S,
8 Xianget al.
mentcontainsmainlyTifeatures,whilethatof5000–5300Åcon-
tainsmainlyMgIfeatures,aswellasafewfeaturesofCa,Tiand
Si.NotethatgiventhelowresolutionaswellaslimitedSNRsof
LAMOSTspectra,Ca,TiandSifeatureswithinthosetwospectral
segmentscontributeinfactonlyasmallfractionofthecalculated
valuesofχ2,andarethereforenot veryusefulforthedetermina-
tionof[α/Fe].Inmetal-richstars,theMgIbfeaturesareingeneral
prominentenoughforarobustdeterminationof[α/Fe].However,
inmetal-poor([Fe/H]< −1.0dex)stars,theMgIblinesbecome
lessprominent sothat the[α/Fe]havelargeruncertainties. Inthe
currentwork,inordertoimproveprecisionof[α/Fe]estimates,es-
pecially for metal-poor stars, we have opted to include the 3910
–3980ÅspectralsegmentthatcontainstheCaIIHKlinesinthe
calculationofχ2values.Meanwhile,asanoption,wealsoprovide
resultsyieldedusingtheexactlysamespectralsegmentsasLietal.
(2016). This is useful considering that the strong Ca II HK lines
inmodelspectraformetal-richstarsmaybenotaccuratelysynthe-
sized.
The resolution of LAMOST spectra from individual fibers
variesfromonetoanother,aswellaswithwavelength(Xiangetal.
2015c). To account for this in template matching, the synthetic
spectraaredegradedinresolutiontomatchthatofthetargetspec-
trum.Thelatterisderivedutilizingthearcspectrum.Thededuced
resolution as a function of wavelength is further scaled to match
theresolutionyieldedbyskyemissionlinesdetectedinthetarget
spectruminorder toaccount for systematicvariations of spectral
resolution between the arc and target exposures. Typically, for a
Figure7.DistributionsoftemplatestarsusedbyLSP3intheTeff –logg given spectrograph, fibre to fibrevariations of spectral resolution
andTeff –[Fe/H]planes.BlackdotsrepresentstarsintheoriginalMILES
amountto0.3Å,risingto0.5–1.0Åamongthedifferentspectro-
library,whilereddotsrepresent267newlyobservedtemplatesemployedin
thegenerationofLSS-GACDR2(seethetext). graphs.Systematicvariationsofspectralresolutionbetweenthearc
andtargetexposuresarefoundtobetypically0.2Å.
Inaddition,inordertoallowforpossibleuncertaintiesinthe
Table2.GridsofKURUCZsyntheticspectrafor[α/Fe]estimation. input atmospheric parameters Teff, log g and [Fe/H] yielded by
LSP3aswell asany possible mismatchbetween the LSP3atmo-
Parameter Range Step spheric parameters and those of the Kurucz stellar model atmo-
spheres,inthecurrentwork,wehaveoptednottofixtheinputval-
Teff [4000,8000]K 100 K uesofT ,loggand[Fe/H]asyieldedbyLSP3,butallowthemto
logg [0.0,5.0]dex 0.25dex eff
varyinlimitedrangesaroundtheinitialvalues.Therangesareset
[Fe/H] [−4.0,0.5]dex 0.2dexfor[Fe/H]<−1.0dex
to2σuncertaintiesoftheparametersconcerned,withlowerlimits
0.1dexfor[Fe/H]>−1.0dex
[α/Fe] [−0.4,1.0]dex 0.1dex of500K,0.5dexand 0.5dexand upper limitsof 1000K,1.0dex
and1.0dexforT ,log g and[Fe/H],respectively.Foreachgrid
eff
value of [α/Fe], the synthetic spectrum that has atmospheric pa-
Ca and Ti, and those of C and N abundances are also enhanced rametersTeff,log gand[Fe/H]withintheaboverangesandfitsthe
by theamount of α-elements. Linesfrommore then 15 diatomic targetspectrumbest(i.e.yieldingthesmallestχ2)istakenasthe
molecule species, including H , CH, NH, OH, MgH, AlH, SiH, choiceofsyntheticspectrumwhenfittingandderiving[α/Fe]using
2
CaH,C ,CN,CO,AlO,SiO,TiOandZrO,aretakenintoaccount thetechniquedescribedinLietal.(2016).
2
inthe calculation of the opacity. Isotope lines arealso taken into Valuesof[α/Fe]arederivedwiththeabovealgorithmforall
account. Intotal,320,000syntheticspectraaregenerated.Table2 LSS-GAC DR2 stars of a spectral SNR higher than 15. The left
liststheparameterrangesandstepsofthegrids.Notethatthegrids panel in the third row of Fig.9 plots the density distribution of
adoptedherehaveastepof0.1dexin[α/Fe],halfofthevalueused LSS-GAC DR2 dwarf stars in the [Fe/H] – [α/Fe] plane. Here
inLietal.(2016).Allthecomputedsyntheticspectrahaveareso- the [α/Fe] are those derived using spectra including the 3910 –
lutionof2.5ÅFWHM,andisinvariantwithwavelength. 3980Å segments. The figure shows an [α/Fe] plateau for metal-
ForatargetspectrumwithatmosphericparametersT ,logg poor([Fe/H] < −1.0dex)stars,atamedianvalueabout0.4dex.
eff
and[Fe/H]yieldedbyLSP3,thesyntheticspectraareinterpolated Formoremetal-richstars,[α/Fe]decreaseswithincreasing[Fe/H],
togenerateasetofspectrathathavethesameatmosphericparam- reaching amedian value of zero near thesolar metallicity, which
eters as the target for all grid values of [α/Fe]. Values of χ2 be- means that the zero-point offset, i.e. deviations of [α/Fe] values
tween the target and the individual interpolated synthetic spectra from zero at solar metallicity, is small, which is in contrast to
arethencalculated.AGaussianplusasecondorderpolynomialis Lietal.(2016)whofindazero-pointoffsetof−0.12dex.However,
thenusedtofitthededucedχ2asafunctionof[α/Fe].Thevalueof weindeedfindazero-pointoffsetofabout−0.1dexfor[α/Fe]de-
[α/Fe]thatyieldsminimumχ2istakentobethe[α/Fe]ratioofthe rivedusingonlythe4400–4600Åand5000–5300Åsegments,
targetspectrum.Tocomputeχ2,Lietal.(2016)usespectralseg- which is basically consistent with Lietal. (2016). The offset is
ments4400–4600Åand5000–5300Å.The4400–4600Åseg- found to be mainly contributed by the 4400 – 4600Å segment.
9
Thecausesofthisdifferencearenotfullyunderstandyet.Wesus- estimation of absolute magnitudes (MV and MKs) directly from
pecttheremaybesomeunrealisticinputsineithertheatmosphere LAMOST spectra; (3) A sample of LAMOST-Kepler common
modelortheatomicandmoleculardatausedtogeneratethesyn- stars with accurate asteroseismic log g measurements for the es-
theticspectra.Notethathereweoptnottointroduceanyexternal timation of logg of giant stars; and (4) A sample of LAMOST-
corrections on the estimated [α/Fe].Random errorsof [α/Fe]in- APOGEE common stars for the estimation of metal abundance
ducedbyspectralnoises,asestimatedbycomparingtheresultsde- [M/H],α-elementtoiron(metal)abundanceratio[α/Fe]([α/M]),
ducedfromduplicateobservations,areafunctionofspectralSNR and of individual elemental abundances including [Fe/H], [C/H]
andatmosphericparametersT ,logg and[Fe/H],andhavetyp- and[N/H]forgiantstars.Adetaileddescriptionoftheimplemen-
eff
ical values that decrease from ∼0.1 to ∼0.05dex as the spectral tation and test of the method is presented in Xiangetal. (2017).
SNRincreasesfrom20toavaluehigherthan50.Toprovideareal- Here we note two updates of the implementation with respect to
isticerrorestimatefor[α/Fe],therandomerrorinducedbyspectral thoseofXiangetal.(2017).Oneisthataunifiednumberofprinci-
noisesiscombinedwiththemethoderror,whichisassumedtohave palcomponents(PCs)of100isadoptedexceptfortheestimation
aconstantvalueof0.09dex,estimatedbyacomparisonwithhigh- ofabsolutemagnitudeswiththeLAMOST-Hipparcostrainingset,
resolutionmeasurements(cf.Lietal.2016). forwhichboth100and300PCsareadopted.Anothermodification
Forgiantstars,[α/Fe]estimatedwiththeabovealgorithmex- isthatadditionaltrainingstarshavebeenaddedtotheLAMOST-
hibitsazero-pointoffsetsbetween0.1and0.2dex,probablycaused KeplerandLAMOST-APOGEEtrainingsetsasaresultthatmore
byinadequaciesofthesyntheticspectraforgiantstars.Inthiswork, commonstarsbecomeavailableasthesurveysprogress.Bothtrain-
nocorrectionsforthoseoffsetsareapplied.Notethatforgiantstars, ingsetsnowcontain(exactly)3000stars.
[α/Fe]valuesarealsoestimatedwiththeKPCAregressionmethod Comparedtotheweighted-meanresults,loggand[Fe/H]de-
using the LAMOST-APOGEEcommon stars as the training data rivedwiththeKPCAregressionmethodusingtheMILEStraining
set(cf.§4.3), andtheresultant values arepresented astherecom- sethavebeenfoundtosufferfromlesssystematics,andthusbet-
mendedones(cf.§4.6). terforstatisticalanalyses.Acomparisonwithasteroseismicmea-
surements shows that for stars of T < 6000K and [Fe/H] >
eff
−1.5dex, uncertainties of KPCA logg estimatescan be assmall
4.3 StellaratmosphericparametersestimatedwithKPCA
as0.1dexforspectralSNRshigherthan50.Theuncertaintiesin-
method
creasesubstantiallyastheSNRdeteriorates,reaching∼0.2dexata
TheLSP3versionusedtogenerateLSS-GACDR1estimatesstel- SNRof20(Xiangetal.2017).Similarly,comparisonswith[Fe/H]
laratmosphericparametersT ,loggand[Fe/H]withaχ2-based determinationsfromhighresolutionspectroscopyshowthatuncer-
eff
weighted-meanalgorithm.Thealgorithmachievesahighprecision tainties of KPCA [Fe/H] estimates are ∼0.1dex for good SNRs.
inthesensethatrandomerrorsofthededucedparametersinduced Formetal-poor([Fe/H]<−1.5dex)orhot(Teff >8000K)stars,
byspectralnoisesarewellcontrolled,evenforstarsofSNRsaslow KPCA estimates of both logg and [Fe/H] become less reliable,
as10.Nevertheless,parametersestimatedwiththeweighted-mean and should beused withcaution. Systematicdifferences between
algorithm suffer fromseveral artifacts. One isthe so-called ‘sup- KPCAand weighted-mean estimatesof Teff exist for starshotter
pressioneffect’–valuesofthederivedloggarenarroweddownto than∼6500K,withdeviationsreachasmuchas∼300Kforstars
anartificiallysmallrange.Thisispartlycausedbythefactthatχ2 ofTeff ∼7500K.Morestudiesareneededtounderstandthecause
calculated from a LAMOST spectrum with respect to a template ofdeviations. Forthetimebeing, werecommend weighted-mean
spectrumisonlymoderatelysensitivetologg,thusthesetsoftem- Teff valuesastheyareestimatedinastraightforwardwayandwell
platesusedtocalculatetheweighted-meanvaluesoflog gforthe validated(Xiangetal.2015c).However,notethatweighted-mean
individual target sources often have similar distributionsin logg. estimates of Teff suffer from clustering effect so that they may
Anotherartifactistheso-called‘boundaryeffect’–parametersof weakly clump in the parameter space on the scale of a few tens
starswithtrueparametersthatpassorareclosetotheboundaryof Kelvin,whiletheKPCAestimatesofTeff donothavesuchprob-
parameter space covered by the templates are often either under- lem.
estimated or overestimated systematically by the weighted-mean Surface gravitiesof giant starsof Teff < 5600 and logg <
algorithm.Thiseffectisespeciallyseriousfor[Fe/H]andloggesti- 3.8dexareestimatedwiththeKPCAmethodusingtheLAMOST-
mation.Finally,duetotheinhomogeneousdistributionoftemplates Kepler trainingset.HerethecutsofTeff andlogg arebased on
intheparameterspace,moderateclusteringeffectisalsoseeninthe valuesyieldedbytheweighted-meanmethod.TheKPCAestimate
deducedparametervalues. of logg is likely to be accurate to 0.1dex given a spectral SNR
To overcome the above defects of the weighted-mean algo- higherthan50.Theuncertaintyincreasesto∼0.2dexataSNRof
rithm,aregressionmethodbasedonKernel-basedPrincipalCom- 20(Huangetal.2015b;Xiangetal.2017).
ponentAnalysis(KPCA)hasrecentlybeenincorporatedintoLSP3 Absolute magnitudes MV and MKs of all stars with a
(Xiangetal.2017).Themethodisimplementedinamachinelearn- weighted-mean effectivetemperaturelower than12,000Karees-
ingscheme.Atrainingdatasetisfirstdefinedtoextractnon-linear timated directly from LAMOST spectra using the LAMOST-
principalcomponents(andtheloadingvectors)aswellastobuild- Hipparcostrainingset.Twosetsofabsolutemagnitudesaregiven,
upregressionrelationsbetweentheprincipalcomponents andthe correspondingtorespectively100and300PCsadoptedforparam-
targetparameters.Fourtrainingdatasetsaredefinedforthedeter- eterestimation.Forabsolutemagnitudesestimatedusing100PCs,
mination of specific sets of parameters of specific types of stars. typical uncertainties are 0.3–0.4mag inboth MV and MKs for a
They are: (1) The MILES library for the estimation of T and spectralSNRhigherthan50,andthevaluesincreaseto∼0.6mag
eff
[Fe/H]ofA/F/G/Kstars,andfortheestimationofloggofstarsthat ataSNRof20.Forabsolutemagnitudesestimatedusing300PCs,
haveloggvalueslargerthan3.0dexasgivenbytheweighted-mean uncertaintiesareonly0.2–0.3magforaspectralSNRhigherthan
algorithm.Thelatterstarsaremainlydwarfsandsub-giants;(2)A 50,buttheresultsaremoresensitivetoSNR,withatypicaluncer-
sampleofLAMOST-Hipparcoscommonstarswithaccurateparal- taintyof∼0.7magataSNRof20.
lax (thus distance and absolute magnitude) measurements for the Asignificantadvantageofestimatingabsolutemagnitudesdi-
10 Xianget al.
Metal (iron) abundance [M/H] ([Fe/H]), α-element to metal
(iron) abundance ratio [α/M] ([α/Fe]), as well as abundances
of carbon and nitrogen, [C/H] and [N/H], are estimated using
the LAMOST-APOGEE training set. Xiangetal. (2017) have
demonstrated that the results have a precision comparable to
thosededucedfromAPOGEEspectrawiththeASPCAPpipeline
(GarcíaPérezetal. 2015; Holtzmanetal. 2015). Specifically, es-
timates of [M/H], [Fe/H], [C/H] and [N/H] have a precision bet-
terthan0.1dexgivenaspectralSNRhighthan30,and∼0.15dex
foraSNRof20.Wenotehowever,sincetheAPOGEEstellarpa-
rameters are not externally calibrated except for [M/H], any sys-
tematicsintheAPOGEEresultspropagatedintooursthroughthe
training set. As pointed out by Holtzmanetal. (2015), APOGEE
estimatesofelementalabundancesmaysufferfromsystematicbi-
asesofabout0.1–0.2dex.For[M/H],theAPOGEEvaluesarecal-
ibrated to [Fe/H] measurements of star clusters for [Fe/H] range
[−2.5,0.5]dex.Nevertheless,itisfoundthat[Fe/H]([M/H])esti-
matedwiththeLAMOST-APOGEEtrainingsetare0.1dexsystem-
aticallyhigherthanthoseestimatedwiththeMILESlibrary.Such
an overestimation is also confirmed by examining common stars
withhighresolutionspectroscopic[Fe/H]measurementsavailable
from thePASTELcatalogue. The discrepancy islikely due to an
offsetinabsolutevaluebetweentheAPOGEEandMILES(PAS-
Figure8.Comparisonofabsolutemagnitudesanddistanceswiththosein-
TEL)metallicities.Theestimated[α/M]([α/Fe])valueshaveatyp-
ferredfromGaiaTGASparallaxfor50,000LAMOST-TGAScommonstars
icalprecisionof0.03–0.06dexgivenaspectralSNRhigherthan
thathaveaTGAS-basedmagnitudeerrorsmallerthan0.2mag.Theupper
20. Xiangetal. (2017) have demonstrated that, as a consequence
panelsshowscolour-codedcontoursofstellarnumberdensityinlogarith-
ofsuchahighprecision,acleardistinctionbetweenthesequences
micscale.Crossesinredaremedianvaluesofourestimatescalculatedin
binsoftheTGAS-basedvalues.Thelowerpanelsplotdistributionofdiffer- ofthickandthindiskstarsisseeninthe[M/H]([Fe/H])–[α/M]
encesofmagnitudesanddistancesbetweenourestimatesandtheTGAS- ([α/Fe])plane,quitesimilartothatrevealedbyresultsfromhigh-
basedvalues.RedlinesareGaussianfitstothedistribution,withthemean resolution spectroscopy.Note however that, for stars with [α/M]
anddispersionoftheGaussianmarkedintheplot. higher than 0.30dex or lower than 0.0dex, the KPCA values are
probablysystematicallyunderestimatedoroverestimatedduetoa
lackof trainingstarsof suchabundance ratios.Inaddition, given
rectlyfromtheobservedspectraisthatthemagnitudesaswellas thatAPOGEE[α/M]([α/Fe])valuesarenotexternallycalibrated,
theresultant distancemoduli,aremodel independent. Fig.8plots theremayalsobesomesystematicshidedinourresults.
a comparison of the estimates of MKs for 300 PCs as well as
the distances thus estimated with results inferred from the Gaia
4.4 Estimationofparametererrors
TGAS parallaxes (Lindegrenetal. 2016) for a sample of 50,000
LAMOST-TGAS common stars that have a TGAS-based magni- Errorsofthededucedstellarparametersareestimatedinastatisti-
tudeerrorsmallerthan0.2mag.HeretheTGASdistancesandMKs calway. Parametererrorscontributed bybothspectralnoisesand
values are derived using values of interstellar extinction derived inadequaciesofthemethodaretakenintoaccount.ForTeff,logg
withthestarpairmethod(cf.Section6.1).Thefigureshowsvery and[Fe/H]estimatedbytheweighted-meanalgorithm,orthoseby
goodagreementbetweenourestimatesandtheTGASresults.Sys- the KPCA method using the MILES training set, as well as MV
tematicsinbothMKsanddistanceestimatesarenegligible,andthe and MKs estimated by the KPCA method using the LAMOST-
dispersion isonly0.26magfor MKs,12 per cent for distance. A Hipparcostrainingset,parametererrorsinducedbyspectralnoises
similarcomparisonofresultsyieldedusing100PCsyieldsamean andthosebythemethodareestimatedseparately. Errorsinduced
differenceof0.04magandadispersionof0.29maginMKs,and by spectral noises, as in the case of LSS-GAC DR1, are esti-
ameandifferenceof−2percent andadispersionof13percent mated by comparing results derived from duplicate observations
indistanceestimates.Ofcourse,spectralSNRsfortheLAMOST- made in different nights, and are estimated separately for giants
TGAScommonstarsareveryhigh,whichhaveamedianvalueof (logg < 3.5dex) and dwarfs (logg > 3.5dex). The results are
150,asthestarsareverybright.NotethatFig.8showsalsoaposi- fitted with a second-order polynomial function of SNR, Teff and
tivenon-GaussiantailinthedifferenceofMKs,withacorrespond- [Fe/H],
ing negative tail in the difference of distance. This non-Gaussian σ=c0+c1×SNR+c2×Teff +c3×[Fe/H]+c4×SNR2
tailislikelycausedbybinarystars,forwhichtheestimatesofab-
solutemagnitudesfromLAMOSTspectraareonlymarginallyaf- +c5×Te2ff +c6×[Fe/H]2+c7×SNR×Teff
fected,whereasthephotometricmagnitudesareunderestimatedre- +c8×SNR×[Fe/H]+c9×Teff ×[Fe/H]
specttothoseassumingsinglestars.NotethatnotalltheLAMOST- (1)
TGASstarsusedforthecomparisoncanbefoundintheLSS-GAC Hereloggestimatedwiththeweighted-meanalgorithmisusedto
value-addedcataloguesasmanyofthemaretargetedbyothersur- group starsinto giantsand dwarfs. Generally, the errorsdecrease
veyprojectsofLAMOST.Thespectraofthosestarshavebeenpro- significantlywithincreasingSNR,andhotormetal-poorstarshave
cessedwithLSP3andthedataareonlyinternallyavailableforthe largererrorsthancoolormetal-richones.
moment. Themethoderrorsarededucedfromtheresidualsobtainedby