Table Of Content

Astronomy&Astrophysicsmanuscriptno.gesicki February5,2008 (DOI:willbeinsertedbyhandlater) Planetary nebulae with emission-line central stars K.Gesicki,1 A.A.Zijlstra,2 A.Acker,3 S.K.Go´rny,4 K.Gozdziewski,1 andJ.R.Walsh5 1 CentrumAstronomiiUMK,ul.Gagarina11,PL-87-100 Torun,Poland e-mail:[email protected], [email protected] 2 SchoolofPhysicsandAstronomy,UniversityofManchester,POBox88,ManchesterM601QD,UnitedKingdom 6 e-mail:[email protected] 0 3 ObservatoireastronomiquedeStrasbourg,11ruedel’Universite,67000Strasbourg,France 0 e-mail:[email protected] 2 4 CopernicusAstronomicalCenter,ul.Rabianska8,PL-87-100Torun,Poland n e-mail:[email protected] a 5 SpaceTelescopeEuropeanCo-ordinatingFacility,ESO,Karl-Schwarzschild-Strasse2,85748Garching,Germany J e-mail:[email protected] 0 2 Received;accepted 2 v Abstract. Thekinematicstructureofasampleofplanetarynebulae, consistingof 23[WR]centralstars,21weakemission 9 linestars(wels) and57non-emission linecentral stars,isstudied. The[WR]starsareshowntobesurrounded byturbulent 3 nebulae,acharacteristicsharedbysomewelsbutalmostcompletelyabsentfromthenon-emissionlinestars.Thefractionof 4 objectsshowingturbulencefornon-emission-linestars,welsand[WR]starsis7%,24%and91%,respectively.The[WR]stars 1 showadistinctIRAS12-micronexcess,indicativeofsmalldustgrains,whichisnotfoundforwels.The[WR]-starnebulaeare 0 onaveragemorecentrallycondensedthanthoseofotherstars.Ontheage-temperaturediagram,thewelsarelocatedontracks 6 ofbothhighandlowstellarmass,while[WR]starstraceanarrowrangeofintermediatemasses.Emission-linestarsarenot 0 foundonthecoolingtrack.Onegroupofwelsmayformasequencewels–[WO]starswithincreasingtemperature.Fortheother / h groupsboththewelsandthe[WR]starsappeartorepresentseveral,independentevolutionarytracks.Wefindadiscontinuity p in the [WR] stellar temperature distribution and suggest different evolutionary sequences above and below the temperature - o gap.Onegroupofcool[WR]starshasnocounterpartamonganyothergroupofPNeandmayrepresentbinaryevolution.A r primefactordistinguishingwelsand[WR]starsappearstobestellarluminosity.Wefindnoevidenceforanincreaseofnebular st expansionvelocitywithtime. a v: Keywords.Planetarynebulae:general–Stars:evolution i X r 1. Introduction ary sequence [WC11]→[WO2] (Zijlstra et al. 1994, Acker a et al. 1996, Penã et al. 2001), followed by PG1159 stars Some central stars (cores) of planetary nebulae (PNe) show (Werner et al. 1992). Acker & Neiner (2003) propose a se- broad, stellar emission lines similar to Wolf-Rayet stars. quence:[WC11]→[WC4]→[WO4]→[WO1].Parthasarathyet Although superficially similar, they differ from classical WR al. (1998) have suggested that the wels are related to the starsintheirdegeneratestructure,muchlowermasses,awider PG1159stars:[WCL]→[WCE]→wels/PG1159→PG1159.But rangeoftemperatures,andbeinglimitedalmostexclusivelyto this sequence is by no means proved; the precise location carbon-richstars (there are very few counterpartsto the mas- of the wels in relation to the [WR] stars is under discussion siveWNstars).SimilartotheirmassiveWC-starcounterparts, (Marcolino & de Araujo 2003). Penã et al. (2001) also ar- theyaredeficientinhydrogen.Theyformaclassnamed[WC]- gue against too closely identifying wels with PG1159 stars type which historically was further divided into early [WCE] (seealsoKoesterke2001).NotallPG1159arehydrogen-poor andlate[WCL]groups.AlessnumerousclassofPNecentral (Dreizler et al. 1996), showing that not all PG1159 stars will starsshownarrowerandweakeremissionlinesthanthe[WR]- haveevolvedfrom[WR] stars.Neitherareallwelshydrogen- typestars.Thesearenamedwels(weakemission-linestars),as poor:adualevolutionarysequencemaybeexpected. definedinTylendaetal.(1993). The lack of hydrogen is often taken to indicate that the Theevolutionarystatusofthe[WR]-typestarsisstillvery [WR] stars have undergone a late thermal pulse (or helium uncertain, and it is unclear whether there is any evolution- flash), either duringthe post-AGBevolution(a so-calledLate ary relation to the wels. Nebular data suggest an evolution- Thermal Pulse or LTP) or on the white dwarf cooling track Sendoffprintrequeststo:K.Gesicki (Very Late Thermal Pulse or VLTP: Herwig 2001, Hajduk et 2 K.Gesickietal.:Planetarynebulaewithemission-linecentralstars al. 2005).Followingsucha pulse,the star rejuvenatesandre- 1997) while smaller for cooler [WC] objects (Leuenhagen et traces part of its earlier evolution. This predicts that nebulae al. 1996). The general tendency is always the same: the T , 2/3 around [WR] stars should be more evolved than around non- Teff or Zanstra temperatures are smaller than T∗. Despite this [WR]stars,butthisisnotconfirmedbyobservations;theprop- discrepancy we apply the Tb−b for further discussion since it erties of the PNe around [WR] stars do not differ from those hastheadvantageofprovidingauniformmeasureofthetem- aroundothercentralstars(Go´rny2001). peratureoverarangeofstellarclasses. Inthispaperwediscussamuchlargersampleof[WR]stars Thevelocitydistributionisassumedtovaryarbitrarilyand andwelsthanhaspreviouslybeenavailable.Weapplyvelocity- smoothly with radius. In Gesicki & Zijlstra (2000) we com- fieldanalysistolocatetheobjectsonderivativesoftheHRdi- paredtheTorunmodelanalysiswithmoretraditionalmethods agram.InSect.2wedescribethemethodsappliedforanalysis of deriving the expansion velocities from the spectra. Since ofPNewithspecificattentiontowardsautomaticmodelfitting. long time it was known that different observed lines resulted Sect.3presentsthe33newlyanalyzedPNe.InSect.4wedis- in different velocities (e.g. Weinberger 1989) indicating a ve- cuss the nebular and stellar parameters for the full sample of locitygradient.Ourmodelhasthisadvantagethatitcombines 101PNe.InSect.5wediscusspossibleevolutionaryrelations. these data into a single velocity curve. Earlier it was not ob- Crowther et al. (1998) have refined the WC and the WO vious but the Torun models have shown that even the shape schemes used for WR stars and define a unified classification of a single line can indicate a velocity gradient. Good veloc- for massive WR and low-mass [WR] stars. Acker & Neiner ityfieldscanbeobtainedifalargernumberoflinesareavail- (2003) developed this scheme for a sample of 42 PN central able.Theresultingfieldsshowdetailedstructure,withvelocity stars,classifiedinto[WO1-4]and[WC4-11]stars.Thisclas- peaksattheouterandsometimesattheinnerradiusoftheneb- sification(usedinthepresentpaper)isbasedontheionization ula (Gesicki & Zijlstra 2003).If fewer lines are available,the level of the elements (depending on the wind-temperature of velocity field is less constrained and simplifying assumptions the PN core), showingessentially carbonlines for the coolest needtobemade.FromthefullvelocitycurveV(r)wederivea starsandoxygenlinesforthehottestones. singleparametercharacterizingthenebularexpansion.Wede- fine the expansion velocity as a mass-weighted average over the nebula, V . This parameter has been shown to be robust 2. Methods av againstthesimplifyingassumptions:itcanbeaccuratelydeter- We deriveinformationon the nebulaeusing a combinationof minedevenwhenthevelocityfielditselfisuncertain(Gesicki line ratios, diameters, and high resolution spectra. The diam- etal2003).Thisallowsustodefineakinematicagetotheneb- eters and line ratios are used to fit a photo-ionization model. ula. The model is constrained to reproduce the intensity distribu- tionofimages,ifanyareavailable.Lineprofilesareobtained 2.1.Thegeneticalgorithm fromthehighresolutionspectra,andarefittedusingtheemis- sivitydistributionsofthephotoionizationmodel,andassuming The Torun models were recently adopted to automate the avelocityfield.ThisisdoneusingtheTorunmodels(Gesicki search fora best-fitmodel,using an optimizationroutine.We etal.1996,2003).Thevelocityfieldsincludeseparatecontri- applied the method widely known as the genetic algorithm. butionsfromexpansionandturbulence.Turbulencealwaysin- While it is still not a very popular optimization technique, it cludestheinstrumentalbroadeningandthethermalbroadening has provedto be very effective and robustin many problems, (calculatedfromthephotoionizationmodel),butsomeobjects in particular of astrophysicalorigin. For a review,we refer to mayrequireadditionalturbulence. a paperbyCharbonneau(1995)whoisthe authorofthe pub- The models assume spherical symmetry. Some strongly liclyavailablecodePIKAIAforageneticalgorithm1,usedfor bipolarobjectscannotbefitted,becausetheyshowveryirreg- computationsinthiswork. ular velocity profiles. But the majority of objects can be well Thegeneticalgorithmshavebeeninventedasanoptimiza- reproducedwithasphericalmodel.Themodelcorrectsforthe tiontechniquemimickingtheprocessesofbiologicalevolution sizeoftheapertureusedforthespectroscopy,andincludessee- (e.g. Koza 1992). They lead to the selection and adaptation ingeffects. of life forms to the conditions of the natural environment. In The diameters and distances are adopted from the litera- this sense the evolutioncan be thoughtof as a powerfulopti- ture. The models find the density distribution, stellar temper- mizationalgorithm.The geneticoptimizationstarts with a set ature and the velocity field. The density as function of radius (population)ofrandomlychosenindividuals(parametersofthe is usually assumed in the shape of a reverted parabola, how- mathematicalmodelencodedinthe‘genomes’).Thewholepa- everifimageswereavailablewecomparedthecomputedsur- rameterspaceoftheproblemcreatestheenvironmentforthese facebrightnessandimprovedtherunofthedensity.Thestellar individuals. The likelihood of survival of a given individual temperature assumes a black-body spectrum energy distribu- is determined by its ‘fitness’ function f; usually, in the least tion – therefore we prefer to call it Tb−b instead of Teff. This squares minimization, f = 1/ χ2. Then the fitness of a par- assumption can be challenged, especially for the [WR] cen- ticularindividualisameasureopfgoodnessoffittothestudied tralstarswherethecomparisonbetweenthestellartemperature data set. The population evolves through a number of gener- T∗ obtainedfromnon-LTEmodellingandT2/3 whichrefersto ations. At everygeneration,the genetic algorithmevaluates f the radius R(τ = 2/3) shows differences. The differences Ross are significant for hotter [WO] stars (Koesterke & Hamann 1 http://www.hao.ucar.edu/Public/models/pikaia/pikaia.html K.Gesickietal.:Planetarynebulaewithemission-linecentralstars 3 work,Nisverysmallandthedeterminationofuncertaintieson thefittedisdifficult(andwithoutmuchmeaningintermsofthe formal, statistical approach). Therefore we did not perform a formalerroranalysisoftheresults.Nevertheless,inawellper- formedoptimizationsearchtheerroranalysisisasimportantas thedeterminationofthefitparameters. Tocheckthepossibledegeneracyofthesolutionsandtoob- tainanideaabouttheerrors,wecollectedthevaluestowhich the search process converged in many independent runs with thesamestart,andprojectedthemonchosenparameterplanes. The distribution of these parameters gives insight on the sig- nificance of the minima, whether they can be well localized and fixed in the parameterspace of the problem.In Fig.1 we present an example of fitting the photoionizationmodel for a singlePN(He2-113,PNG321.0+03.9).Resultsareplottedfor 40differentrunsofPIKAIA,usingthesamesetofobservables. Ascatterintheobtainedparametersisseen:fewofthepoints areoverlapping.Thesizeofthesymbolscorrespondstothefit quality.ForthisPN thetemperatureisbetterconstrainedthan thestellarluminosity.ThesituationforotherPNeissimilar.For Fig.1.Thebestfitluminosityandtemperatureforphotoioniza- highertemperaturesthemodelsseemtobebetterconstrained. tion models for a single object (He2-113, PNG321.0+03.9) WeestimatedtheaccuracyinTb−bas±2000KandinlogL/L⊙ for40differentPIKAIAruns.Thelargerthesizeofthecircle as±0.3. thebetterthefitquality. Similar test were performed for the velocity procedure. When fitting a simple velocity field (linear or parabola-like) resulting from each parameter set and processes information the PIKAIA routine repeats very well the results. More com- by applying to the genomes genetic operators like crossover, plicated velocity fields result in different shapes for different mutation and selection. The best fitted members of the pop- runs;howeverthelargestdiscrepanciesappearintheleastcon- ulation are used to producea new generation and the process strained parts of the velocity curves. Nevertheless the mass- continuesuntilsomeconvergencecriteriaisreached.Thanksto averaged expansion velocity remains well determined and is keepingthe memoryof the best fitted individuals,the genetic similar in all runs. From the distribution of models, we esti- algorithms are much more efficient than Monte Carlo based matetheaccuracyofVavasabout±2kms−1. search techniques. They are robust and especially well suited for multi-dimensional problems, models possessing multiple localextremaanddiscontinuities.Theyarenon-gradientmeth- 2.2.Observations odsandthusespecially wellsuitedformodelsdependentin a A large number of PNe have been analyzed in previous pa- sophisticatedwayontheirparameters.Detailsofpracticalap- persusingtheTorunmodels.Inmostcases thevelocityfields plicationofthetechniquearegiveninanexcellentintroduction weredeterminedfromthreelines(hydrogenHα6563Å,[N] byCharbonneau(2002). 6583Åand[O]5007Å)orfewer.Tothissampleweaddinthe The genetic optimization replaced the ’trial and error’ presentpaper 27 unpublishedCAT observations,which cover search of parameters applied in our earlier publications (e.g. only Hα and [N] 6583Å, supplemented with recent echelle Gesicki & Zijlstra 2003, Gesicki et al. 2003). The algorithm appeared very effective in comparison with the earlier work. NTT observations of 6 PNe with emission-line central stars. PNewithnewdataarelistedinTable1. We notealsothatbecauseofrandominitializationofthepop- ulationthemethodisnow freefrominitialbiases. The search The ESO Coude´ Auxiliary Telescope (CAT) was a procedureagainfollowstwosteps. FirstPIKAIAsearchesfor subsidiary 1.4m telescope feeding into the Coude´ Echelle thevaluesofthenebularmassandthestellartemperatureand Spectrograph(CES)locatedattheneighboring3.6mtelescope. luminositywhichoptimizethefittotheobservables,beforeat- The CAT observations of 27 objects were performed during temptingtofindthevelocityfieldwhichoptimizesthefittothe 1993 and 1994. The long camera was used, giving a spectral lineprofiles.Thefollowingexpressionisoptimized: resolutionof60000(correspondingto5kms−1).Theslitwidth was2′′.Theobservationsusealongslit,sampledwith2′′pix- 1 N O(i)−C(i) 2 els. However, the spectra analyzed here use only the central χ2 = , N−p−1 " σ(i) # row of pixels. (As the nebulae studied here are compact and Xi=1 the CAT was not an imaging-quality telescope, no spatial in- where O(i) are N observations(i = 1,...,N), C(i) are model formationwasexpected.)Thespectrumcoversoneorderofthe predictions dependent on p parameters and σ(i) are individ- echelle,coveringHαandthe [N] linesat6548Åand6853Å ualerrorsoftheobservations.Insomecasesconsideredinthis butnoothernebularlines. 4 K.Gesickietal.:Planetarynebulaewithemission-linecentralstars Fig.2.The observedandmodelledlines Hi6563Åand [Nii] Fig.3. The observed and modelled lines Hi and [Nii]. 6583Å.Thecirclescorrespondtotheobservedprofile,theline ContinuationofFig.2 tothefittedmodel.Thelinefluxesarenormalizedtounity.The X-axisvelocityscalegiveninthelowestboxesisthesamefor allplots. ThedetailsofthedatareductionaregiveninGesicki&Zijlstra (2003). Six objectswithemission-linecentralstarswereobserved The profile fitting procedure requires specification of the with the ESO New TechnologyTelescope (NTT) duringJune centeroftheemissionlinewithzerovelocity.Wedidnotper- 2001. The echelle spectra were obtained using ESO Multi form the full radial velocity correction. Instead we assumed ModeInstrument(EMMI),withgrating14andcrossdisperser thezeropositioninthecentreofsymmetryforthealmostsym- 3, giving a resolution of 60000. The slit width was 1′′. The metriclinesandusuallylocatedthezeropositioninthecentre spectracoveredthewavelengthrange4300–8100Å.Thespec- between the two maxima of the asymmetric lines. In the sec- tra were summed over the slit length of 3′′. Exposure times ondcasethepresenceoftwo(ormore)spectrallineshelpedto were typically 120seconds. Between 3 and 7 lines per object locatethezeroposition,theobviouslyhopelesscaseswerenot showed high enough S/N to be used in the velocity analysis. analyzed. K.Gesickietal.:Planetarynebulaewithemission-linecentralstars 5 Table1.Theexpansionvelocitiesandotherdataconcerningthenebulaeandthecentralstars,basedonobservationsdescribed inthispaper.Thecolumn’remarks’indicateforPNeobservedwithEMMI,howmanyemissionlineswereusedfortheanalysis. PNG Name logTb−b logL Dist. Rout Mion Vav Vtrb Mcore tdyn Central Remarks [K] [L⊙] [kpc] [pc] [M⊙] [kms−1] [M⊙] [kyrs] star 000.9-04.8 M3-23 5.18 3.0 4.0 .11 .10 24 13 0.61 5.1 002.6-03.4 M1-37 4.40 3.9 8.0 .04 .08 27 0 0.60 1.7 [WC11]? 002.7-04.8 M1-42 4.92 3.0 4.0 .08 .16 13 0 0.60 5.4 003.6+03.1 M2-14 4.64 3.0 8.0 .05 .06 17 10 0.60 2.9 wels 6lines 004.6+06.0 H1-24 4.56 3.8 7.0 .08 .13 24 0 0.58 3.7 wels 006.4+02.0 M1-31 4.76 3.8 8.0 .06 .29 19 0 0.61 3.2 wels 008.2+06.8 He2-260 4.80 3.2 12.0 .06 .13 17 0 0.61 3.5 211.2-03.5 M1-6 4.60 3.5 4.0 .03 .05 24 0 0.62 1.4 217.4+02.0 St3-1 4.96 2.5 4.0 .14 .20 26 0 0.60 6.1 232.0+05.7 SaSt2-3 4.80 2.5 4.0 .02 .01 19 0 0.64 1.1 232.4-01.8 M1-13 5.04 2.9 4.0 .10 .19 14 0 0.60 6.5 253.9+05.7 M3-6 4.72 4.0 1.5 .036 .03 18 0 0.61 2.0 wels 258.1-00.3 He2-9 4.73 2.9 1.5 .015 .01 25 0 0.65 0.7 wels 261.6+03.0 He2-15 5.17 3.0 2.2 .13 .32 22 0 0.71 6.4 283.3+03.9 He2-50 5.12 2.9 5.1 .14 .32 17 0 0.59 8.1 292.4+04.1 PB8 4.76 3.6 5.0 .06 .18 22 9 0.61 2.9 [WC5-6] 300.7-02.0 He2-86 4.83 3.4 3.0 .03 .05 14 11 0.62 2.0 [WC4] 304.8+05.1 He2-88 4.72 2.8 4.0 .03 .03 23 0 0.62 1.4 309.0-04.2 He2-99 4.49 2.7 4.0 .16 .25 45 10 0.57 4.6 [WC9] 316.1+08.4 He2-108 4.51 3.8 4.0 .10 .14 21 9 0.57 5.0 wels? 321.0+03.9 He2-113 4.48 2.8 2.0 .01 .003 18 15 0.64 0.6 [WC10] 325.0+03.2 He2-129 4.87 3.8 7.0 .03 .08 18 13 0.63 1.7 325.8+04.5 He2-128 4.70 3.3 5.0 .06 .13 12 10 0.59 4.3 347.4+05.8 H1-2 4.96 3.9 7.0 .02 .06 13 10 0.64 1.4 wels 3lines 351.1+04.8 M1-19 4.72 3.2 11.0 .10 .20 26 0 0.61 4.3 wels 5lines 352.1+05.1 M2-8 5.11 3.2 7.0 .06 .16 14 14 0.61 3.9 [WO2-3] 7lines 355.9+03.6 H1-9 4.58 4.0 9.0 .04 .09 20 0 0.61 2.1 356.1+02.7 Th3-13 5.05 3.3 8.0 .03 .05 32 0 0.65 1.1 wels 3lines 356.5-02.3 M1-27 4.41 3.6 3.0 .04 .05 21 0 0.60 2.0 [WC11]? 357.1+03.6 M3-7 4.72 3.2 4.0 .05 .07 23 0 0.61 2.4 wels 3lines 357.4-03.2 M2-16 4.95 3.3 7.0 .09 .25 21 14 0.61 4.5 357.4-03.5 M2-18 4.64 3.5 7.0 .06 .09 24 0 0.60 2.8 359.1-02.3 M3-16 4.57 3.8 7.0 .08 .14 30 0 0.59 3.1 3. Themodelledplanetarynebulae soidalring1.5×2.5′′whichismodelledbyour2′′sphere.The multipolarlobesaswellastheextendedsphericalhaloarebe- Figures2–4 presentthe observedand modellednebularemis- yondouranalysis.WeobtainedalowertemperaturethanZhang sionlinesHi6563Åand[Nii]6583Å.Althoughfortheindi- &Kwok(1991)forthislowexcitationnebula. catedinthelastcolumnoftheTable1sixPNemorelineswere used for model fitting ([O] 5007Å and in some cases [O] PNG253.9+05.7(M 3-6,wels). The radio image(Zijlstra 6302Å, [S] 6732Å, [S] 6311Å, He 4686Å), we present etal.1989)revealsacomplicatedstructurewithfourmaxima. onlythetwolinesforaconsistentpresentation.Wedonotdraw Oursphericalmodelisdensitybounded,butthelineratiosare the modelradialdistributionsofthe velocity,densityandsur- notwellfittedandsuggestamixtureofionizationanddensity facebrightnessbecauseourmainresultsarethemass-averaged boundaries. A small central cavity is indicated. The best ve- expansion velocities. The [WR]-subclass and wels classifica- locityfieldwhichreproducesthemulticomponentstructureof tion is adoptedfromAcker & Neiner (2003)and for the low- the[N]lineshowsmultiplemaxima.Consideringthecompli- est temperature [WC11] stars from Go´rny et al. (2004). The catednebularimageourmodelshouldbetreatedwithcaution, summary of nebular and central star parameters are listed in butbecausethespectrallinesarealmostsymmetricthemass- Table1.Thelastcolumnindicateswhethermorethantwolines averagedexpansionvelocityisbelievedtobereliable. were used for modelling. A few objects are discussed in the following. PNG321.0+03.9 (He 2-113, [WC 10]). The HST image PNG002.6-03.4 (M 1-37), [WC11]“?”). The density (Sahai et al. 2000) reveals complex, highly aspherical struc- structureis adoptedtoagreeapproximatelywiththe imageof tureswhichmakessphericalmodellingdoubtful.Nevertheless Sahai(2000).Thebrightestnebularstructureistheinnerellip- theaveragevelocitystillisausefulparameter.Inourobserva- 6 K.Gesickietal.:Planetarynebulaewithemission-linecentralstars Fig.5. Stellar photo-ionization temperatures versus [WO]- [WC]subclass. tion between emission-line stars and non-emission-line stars depends on the depth of the available spectra. It is therefore possiblethatsomeofthenon-emission-linestarswouldbeclas- sifiedaswelsstarswithdeeperspectra.Theeffectofdetectabil- ityofthestellarlinesontheclassificationisdiscussedbyGo´rny etal.(2004). 4.1.Temperatures The subclassofthe [WR] starsprovidesan indicationof stellar temperature,but it can not be used to predict unique temperatures. This can for instance be seen for the earlier subclasses(hotterstars) fromthedatainAcker&Neiner(2003). DeAraujoetal.(2002)showthatdeepspectraareneededfor accurate association of a [WR] subclass. In this paperwe use thephotoionization(equivalentblack-body)temperatureTb−b, rather than the [WR] subclass. This parameterhas the further advantagethatitisalsoavailableforthenon-[WR]stars.Fig.5 shows the relation between photoionization temperature and Fig.4. The observed and modelled lines Hi and [Nii]. [WR] ([WO] and [WC]) subclass. There is a good relation ContinuationofFig.3 overall, but the change in temperature is smaller for the later subclasses(8–11).OnediscrepantobjectisM2-43(27.6+04.2) tionsthisPNisunresolvedandtheemissionlinesaresymmet- wherethetemperatureismuchhigherthanthesubclass([WC ric. 7-8]) would suggest. The photo-ionizationmodel fits the line ratios reasonably well, and the strong [O] line with weak [N]requireahightemperature(Ackeretal.2002).Suchhigh 4. Derivedparameters temperaturewas also obtainedby non-LTEmodelanalysis of The newly analyzed data is combined with an earlier sample Leuenhagen&Hamann(1998).Thisobjectshowsadualdust discussed in Gesicki et al. (2003). Together with the 33 new composition(Go´rnyetal.2001).The[WC]subclassshouldbe PNe,thefullsamplecontains101objects(from73earlierob- checked. jectsweremovedthreeextragalacticPNe,andtwoPNearere- analyzed with the new spectra). The full sample contains 23 4.2.Expansionvelocities [WR],21welsand57non-emission-linecentralstars. Several objects were reclassified based on the work of Forthewholesampleof101PNe,theaverage(andthemedian) Acker & Neiner (2003) and Go´rny et al. (2004).The distinc- value of the mass-averaged expansion velocities is 22kms−1 K.Gesickietal.:Planetarynebulaewithemission-linecentralstars 7 Fig.6. Thenebular expansion(left)and turbulent(right)velocitiesversusstellar temperature.The filled circles present[WR]- type PNe, open circles wels stars, and pluses show non-emission-linestars. In the left panel the lines representthe sequences modelledbyScho¨nberneretal.(2005a),eachlinefordifferentinitialdensitydistribution.TheaccuracyofV isabout±2kms−1. av withstandarderroronthemeanof0.67kms−1.TheaverageV ation cannot be explained with simple models which assume av for[WR]PNeis25±2kms−1whileforwelsitis22±1kms−1. aninitialnebulardensitydistributiondescribedbyapowerlaw The1-σdifferenceinexpansionvelocityismuchsmallerthan ρ ∝ r−α with a fixed index α. Their conclusion is that the found in Penã et al. (2003a), who find an average expansion power-law index increases systematically with T (see their eff velocity for non-WR PNe of 21kms−1 (virtually the same as Fig.12).We plottheir modelsequencesforfourvaluesofthe ours) but for [WR] PNe 36kms−1. The difference can be ex- power law index in the left panel of Fig.6. The indexes are plained by their method of estimating the velocity: they use fromlefttoright:2.00,2.5,3.0and3.25.Ourdatafor101PNe the half-width at half maximum of the nebular lines and this overlap with the lines (the velocities are not defined exactly isaffectedbytheturbulenceinthevelocityfields(Ackeretal. in the same way). We do not confirm the Scho¨nberner et al. 2002). (2005a)conclusion,buttherangeofpowerlawindiceswhich Itisnaturaltoexplainthehigherthanaverageexpansionve- they deriveprovidesa goodfit to the spreadseen in our sam- locityof[WR]PNeintermsofstrongerstellarwindactingon ple.ThetrendinFig.6that[WR] starsdominatethedistribu- theswept-upshell.Mellema&Lundqvist(2002)studiedsuch tiontowardslowervaluesofTb−b/Vexp,incombinationwiththe interactionsandconfirmedtheabovetendencyprovidinganex- slopeof themodeltracks,suggeststhatsome[WR] PNe may ampleof[WR]PNexpansionof21kms−1versus17kms−1for havesteeperinitialdensitydistributionsthannon-emission-line non-[WR]PN.ThisdifferenceissmallerthanobtainedbyPenã PNe. etal.(2003a),thevaluesarerathercomparabletoours. Penã etal. (2003b)arguethatthe expansionvelocitiesfor 4.3.Dynamicalages evolved[WR]PNearelargerthanforyoungerobjects.Inthat papertheexpansionvelocityisdefinedashalf-widthat1/10of The expansion velocity and radius of the nebula can be used themaximumintensity,a measureintroducedbyDopitaetal. toderivetheageofthenebula.Onecanusetheoutermostra- (1988). At this intensity level the emission lines are strongly diusandthemaximumexpansionvelocity,butthisisaffected broadened by a turbulent componentcommon for [WR] PNe by the acceleration caused by the overpressure in the ionized soitisnosurprisethatourvalues(correctedfortheturbulence) region. Instead we apply the mass-averaged velocity, and use are smaller. Penã et al. (2003b) arrive at their conclusion by for the radius 0.8 of the outer radius, roughly corresponding plottingstellartemperaturesversusexpansionvelocities.Inour tothemass-averagedradius.Toaccountfortheaccelerationof sample,nosucheffectisvisible(Fig.6,leftpanel),exceptthat thenebulaweaveragebetweenthecurrentvelocityandthatof the three highest expansion velocities in the sample are from theoriginaloutflowvelocitiesontheAsymptoticGiantBranch. [WR]stars.TheVexpandTb−bvaluesarespreadoverthewhole TheprocedureisdescribedinGesickietal.(2003).Wemadea range.However,thereisatrendforthe[WR]starstodominate simplifyingassumptionabouttheAGBoutflowvelocitysetting towardsthelower-rightcornerinthefigure,i.e.lowervaluesof itequalto10kms−1forallobjects. Tb−b/Vexp. Thistrendlooksverysimilar to thatfromFig.3 of Thedynamicalagescandirectlybecomparedbetweenthe Penãetal.(2003b).Howevertheir[WR]PNeclusteringinthe differentgroupsofstars.However,theymaynotbeequaltothe upper-rightcornerisnotsosimilar. trueagesofthenebulae,duetothevariousassumptionsmade. Scho¨nberneretal.(2005a)discusstheirobservationsof13 This problem was discussed together with non-LTE analysis PNe and concluded that expansion speed increases with the ofsomecentralstarsofPNe.Rauchetal.(1994)obtainedfor T of the central star, i.e. with the nebular age. Such a situ- the object K1-27 that the dynamical age was more than one eff 8 K.Gesickietal.:Planetarynebulaewithemission-linecentralstars order of magnitude smaller than the evolutionary age. In an- Among the wels we find both turbulentand non-turbulent other paper Rauch et al. (1999) analyzed four more PNe and objects.Ourfullsamplecontains21welsofwhich5showtur- obtaineddynamicalages a few times larger than evolutionary bulence and 16 do not. Of these 21 objects, 10 come from ages. The nebular and stellar ages were comparedon a much the new observations described here (3 turbulent and 7 non- bigger sample by McCarthy et al. (1990).They obtained that turbulent). generallytheempiricalageswerelargerthantheevolutionary oneshowevertheirmethodforestimatingdynamicalageswas Wealsofindwell-determined,turbulentsolutionsfor4PNe recentlystronglycriticizedbyScho¨nberneretal.(2005b).The not classified as [WR] nor wels (M2-16, M3-23, He2-128, contemporarysituationisfarfrombeingconclusive. He2-129).Notall[WR]-typePNeinthenewsampleshowtur- Intherecentarticlewefoundanicesupportforourmethod bulentmotions:M1-27andM1-37havegoodsolutions,with- for estimating nebular ages. Scho¨nberner et al. (2005b)show outrequiringturbulence.Thetwonon-turbulent[WR]PNeare thatbothradiiandvelocitiesincreasegraduallywithtimewhat bothclassifiedbyGo´rnyetal.(2004)as’[WC11]?’.Theyare justifies our averaging between original and current velocity. the coolest objects in our sample. However, the strong corre- For ionization bounded models (dominantin our sample) the lationbetweenemission-linestarsandturbulenceremains:the agesderivedfromions[O]and[N]divergeinoppositedi- fraction showing turbulence for non-emission-line stars, wels rections from true ages what supports our multi-line analysis and[WR]starsis7%,24%and91%,respectively. where such effects compensate.For density boundedPNe the situation is evenbetter since both linesresultin the same age Uncertaintiesin the [WR] identifications may affect these equaltotheevolutionaryone. fractions.Theturbulentnon-WRPNecouldhaveemission-line Thedynamicalageincombinationwiththestellartemper- centralstars.ThisisunlikelyforM2-16,awell-studied,highly ature gives the rate at which the central star is increasing in metal-rich PN (Cuisinier et al. 2000).He2-128 and He2-129 temperature.Thisrateisverysensitivetothecoremassofthe were studied spectroscopically by Dopita & Hua (1997): the star, with more massive stars evolvingmuch faster. To assign non-WRidentificationcannotbeattributedtoa lackofobser- a core mass, we interpolatebetweenpublishedtracks(see e.g vations,butfaintstellarlinesmayhavebeenmissed.Someob- Go´rny et al. 1997, Frankowski 2003). For a given dynamical jectsmayhavetoofewnebularlinestobeabletodetectturbu- age and stellar temperature we obtain the core mass (and lu- lence:avelocitygradientbroadensasinglelineprofilesimilar minosity). The dynamical ages and core masses are listed in toturbulence–weonlyacceptedturbulentsolutionswherethey Table1.Asfortheages,themassdeterminationsareinternally fitted clearly better the line shapes than non-turbulent ones. consistentbetweendifferentobjects,butmayshowsystematic Deeperspectrawouldhelphere. offsetswithrespecttothetruemasses.Asacheckofthecon- sistencyoftheproceduretheluminositiescanbecompared.In Theonsetoftheturbulenceandthe[WR]phenomenonmay Gesicki et al. (2003) we obtained that the luminosities from notbecompletelysimultaneous.However,wefindnoevidence photoionizationmodellingareinmostcasessmallerthanthose that the turbulence increases for more evolved objects: Fig.6 interpolatedfromevolutionarytracks.Howeverthiscanbein- (rightpanel)showsnorelationbetweenturbulenceandstellar terpretedas leaking of the nebulae:the PN does notintercept temperature. andtransformallstellarionizingflux.Thispointstoasymme- tryorclumping. In trying to understandwhy the presence of turbulencein welsPNeissomixed,letusconsiderapossibilitythataPNcan 4.4.Turbulence switchbetweenturbulentandnon-turbulentregimesduringits lifetime. The transition time for this should be comparableto Foranumberofnebulae,satisfactoryfitstothevelocityfields the shocktraveltime acrossthe nebula.Assuminga radiusof could not be obtained. In these cases we used enhanced tur- 0.1pc and isothermal sound speed of 10kms−1 we obtain a bulence,abovewhatisexpectedfromthermalbroadeningand timeof104 years.Perinottoetal.(2004)statedthattheshock instrumental resolution. Indicative of turbulence is that lines frontvelocitycanbe3–4timesfasterthantheisothermalsound of all ions show Gaussian shapes of comparable width: ther- speed: this reducesthe time to a few thousandsyears. This is malbroadeninggivesmuchwiderlinesforthelightestelement comparable to the ages of our PNe. In our sample we have a (hydrogen). Comparing the Hα with metal lines is here cru- couple of (compact) objects with an age of about 1000 years cialbecausedifferencesinthermalbroadeningbetweendiffer- which havealready developedturbulence.Ackeret al. (2002) ent metal ions are small. Therefore we searched for turbulent proposed that turbulence in PNe is triggered or enhanced by solutionsonlyforthosePNewithHαandatleastonemetalline [WR] stellar wind inhomogeneities.The nebulae surrounding available.Turbulencewas indicatedfor30ofthe 101nebulae veryactive[WR]coresareturbulent.Thelessactivewelswith inthefullsample. much weaker winds, if they could change their wind charac- Gesicki & Acker (1996) and Acker et al. (2002)find that teristics, they would develop turbulence, or exhibit decaying [WR]-typePNe arecharacterizedbystrongturbulentmotions turbulence, over the lifetime of the PN. Thus, the mixed oc- whilenon-emission-linePNearenot.Thisgeneraltendencyis currenceof turbulencein wels is compatiblewith a transitory confirmed in the present analysis, but there are some excep- status, not unlikely a [WR]-star progenitor, provided the life tions. timeofthephasedoesnotexceed∼103yr. K.Gesickietal.:Planetarynebulaewithemission-linecentralstars 9 PB 8 M 1-25 Fig.7. IRAS colours for the [WR] stars (filled circles, wels (open circles) and non-emission-line stars (plus symbols), with asterisksareoverplottedtheturbulentPNe.Theboxesindicatesourceclassificationsfordifferentcolours,takenfromZijlstraet al.2001.BoxIIareplanetarynebulae,boxIIIpost-AGBstars,boxIVOH-MirasandBoxVbipolaroutflowsources.Thedashed linesshowsimpleevolutionarysequences,explainedinthetext.LabeledaretwoindividualPNediscussedinSect.6.2. 4.5.IRAScolours cool[WC]PNe,buttheir25/12-microncoloursareverydiffer- ent. We constructed dust models following the nebular expan- Planetary nebulae are strong infrared emitters, due to their sion occurringas the star heats up. We used a r−2 wind, with heateddust.Thedustcoloursfollowtheevolution:astheneb- themodelandrecipeofSiebenmorgenetal.(1994).Themodel ulaexpands,thedustcoolsandthedustcoloursredden.Zijlstra calculates the IRAS fluxes at any particular time. The results (2001)hasshownthat[WR]starsarestrongerinfraredemitters areshowninFig.7,foracarbonrich(longdashes)andaoxy- thanotherPNe,withatendencyforbluercolours.Thebright- genrich(shortdashes)nebulardust.Theevolutionaryprogres- estinfraredPNearetheIR-[WR]stars,asubgroupofthecooler sionfromcoolstarswithbluerIRAScolourstohotstarswith [WC]stars. (more evolved) redder IRAS colours is visible for the [WR] Fig.7showsthecolour-colourdiagramforthepresentsam- stars,butnotforthenon-emission-linestarsandthe(lesspop- ple. Different symbols distinguish the [WR] stars (filled cir- ulated)welsgroup(Zijlstra2001). cles), the wels (open circles) and the non-emission-line stars Detection statistics show the differences between the (pluses). In addition, overplotted star symbols indicate turbu- groups.Outof the101stars, 60 havethreegoodIRASdetec- lent nebulae. We excluded the confused source M2-6 where tions. The detection rates are 28 out of 57 non-emission-line the IRAS colours appear to be those of a nearby AGB star. stars, 12 out of 21 wels and 20 out of 23 [WR] stars: respec- The boxes are source classification regions of Zijlstra et al. tively49%,57%and87%.Thisshowsthatthe[WR]starsare (2001).PlanetarynebulaefallinboxII.Thecooler[WC]stars onaveragemuchstrongerIRASemitters. Ifwe onlyconsider arefoundmainlytowardstheleftinthediagram,inthreecases 25 and 60 micron, the detection rates become 89%, 86% and withcolourslike thoseof(young)post-AGBstars.(Thethree 100%,i.e.the differenceisratherreduced.Thenumbersindi- objectsareBD+303639,M4-18andHe2-142.)Thewelsare catethat[WR]starsaremuchbrighterat12-micron,butlessso shifted to redder colours, and their distribution is similar to attheotherbands. those of normal PNe. Note that the cooler non-emission-line The wels have the same detection rate as other non-[WR] stars in our sample have 60/25-micron colours similar to the stars.However,all5welswithturbulencehavethree-bandde- 10 K.Gesickietal.:Planetarynebulaewithemission-linecentralstars distribution for hydrogen burning 0.605M⊙ track of Blo¨cker (1995).Thepredictednumberofobjects(perlogarithmictem- peraturebin)graduallyincreasestowardshighertemperatures, as expected from the increasing width of the bins and from slowingtheevolution. When compared to the observational data we see that no singlegroupofPNeproducesahistogramsimilartothemod- els.ThesolidlineinthebottompanelofFig.8showsthatthe sumofallclassesproduceahistogrammostsimilartothethe- oreticallyexpecteddistribution.Thus,thefullsampleisrepre- sentative for a uniformlysampled Blo¨cker track. The flat distribution of the emission-line stars implies that this group is biassedtowardslowertemperatures,relativetostandardevolu- tion. The wels as a separate groupshow a strong temperature preferenceandcannotrepresentafullevolutionarytrack. Itis possiblethatourobservationsmisrepresentthe oldest PNe withthehottestcores.Oursampleismainlyrestrictedto the spherical PNe with an ionization boundary while for old PNe the ionization front breaks through and may cause frag- mentation of a nebula making it notsuitable for our analysis. Fig.8. Temperature distribution of [WR], wels and non- We also cannotexclude a systematic error of our Tb−b values whichmayshiftthemaximumoftheobserveddistribution,and emission-line stars, in logarithmictemperature bins. The bot- thiserrormayalsodependontemperature. tompanel,discussedfurtherinthetext,comparestheobserved datawiththehistogramobtainedfromH-burningevolutionary modelsofBlo¨cker(1995). 5.2.DynamicalagesofthePNe tections; their colours are similar to the [WO] stars. All wels Evolutionarytracksshouldconnectobjectsalongsequencesof without12-microndetectionarenon-turbulentobjects. increasing dynamical age and increasing stellar temperature, untilthestarsreachthekneeintheHRdiagram,afterwhichthe stellar temperature slowly decreases. Helium-burning tracks 5. Evolutionaryparameters generallyalsofollowsthissequence,butthestarsevolveafew 5.1.Temperaturedistributions timesslower(factorof3accordingtoBlo¨cker1995);thedetails dependontheprecisetimingofthethermalpulseprecedingthe The temperature distribution of the three groups of stars, de- switchtoheliumburning. finedasinsection4.1,isshowninFig.8.The[WR]starsshow someclusteringatlowandhightemperatureswithagapinbe- Fig.9 plots the dynamical age versus the temperature for tween(see upperpanel).Thisgaphasbeennotedbeforelong the stars in our sample. The interpolated (hydrogen-burning) time (see e.g. Go´rny 2001). The wels stars, in contrast, peak evolutionary tracks are overplotted with a solid line. As in precisely in this gap. In contrast, the non-emission-line stars Fig.7differentsymbolsdistinguishtypesofstarsandindicate showapeakintheirdistributionathightemperature(seecen- turbulence. tralpanel). Thefigureshowsthatsomeregionsinthisage-temperature Summing the two groups of emission-line stars (cen- planearedominatedbycertaintypesofobjects.The[WR]stars tral panel), we find a flat distribution (in logarithmic bins!). are mainly foundin the narrowregionbetweenthe 0.605and Summingallthreegroupstogether(bottompanel,drawnline) 0.625M⊙tracks,withafewfurtherobjectsatlowtemperatures showsanincreasingnumberofobjectswithlogT. and a range of ages. The wels stars are spread mostly out at We compare the temperature distribution of the various intermediatetemperatures.Thenon-emission-linestarstendto PNesampleswiththatpredictedbytheevolutionarytracksof avoidthelowtemperatureregion,butcoveraregioninthetop- Bloo¨cker(1995).Weinterpolatethetrackstoconstanttemper- rightcornerwhichtheotherstarstendtoavoid. aturesteps,inordertocalculatethepredictednumberofstars per temperature range (proportional to the time spent in the Thestatisticsofourfullsampleof101PNeshowsthatthe range). The model tracks have to first order a fairly constant average dynamical age of non-emission-line central stars and temperature increase, dT/dt. In logarithmic bins, this means of wels is 3200 years while for [WR]-stars it is 2800 years, thatthenumberofstarsperbinincreaseswithtemperature.To with standard error on the mean of about 300 years in both beconsistentwithourmodelanalysisweonlyusethethehori- cases. This difference is not significant and the result may be zontalpartoftheevolutionarytrack,beforethekneeintheH-R contaminatedbyaselectioneffectbecauseitiseasiertodetect diagram.Fig.8(bottompanel,dottedline)showsthepredicted a[WR]staratlowertemperatures(seeGo´rnyetal.2004).