Galactic cold cores II. Herschel study of the extended dust emission around the first Planck detections

1.6 MB·English

by  M. Juvela

Astronomy&Astrophysicsmanuscriptno.15916 (cid:13)c ESO2011
January18,2011
Galactic cold cores II. Herschel study of the extended dust
⋆ ⋆⋆
emission around the first Planck detections
M.Juvela1,I.Ristorcelli2,V.-M.Pelkonen3,D.J.Marshall2,L.A.Montier2,J.-P.Bernard2,R.Paladini3,T.Lunttila1,A.
Abergel4,Ph.Andre´5,C.Dickinson6,X.Dupac7,J.Malinen1,P.Martin8,P.McGehee3,L.Pagani9,N.Ysard1,A.
Zavagno10
1 DepartmentofPhysics,P.O.Box64,FI-00014,UniversityofHelsinki,Finland,mika.juvela@helsinki.fi
2 CESR,ObservatoireMidi-Pyre´ne´es(CNRS-UPS),Universite´deToulouse,BP44346,31028ToulouseCedex04,France
1 3 IPAC,Caltech,Pasadena,USA
1 4 IAS,Universite´Paris-Sud,91405Orsaycedex,France
0 5 LaboratoireAIM,CEA/DSMCNRSUniversite´ParisDiderot,IRFU/Serviced’Astrophysique,CEASaclay,91191Gif-sur-Yvette,
2 France
6 JodrellBankCentreforAstrophysics,UniversityofManchester,OxfordRoad,Manchester,M139PL,U.K.
n 7 EuropeanSpaceAgency,EuropeanSpaceAstronomyCentre,VillanuevadelaCan˜ada,Madrid,Spain
a 8 CanadianInstituteforTheoreticalAstrophysics(CITA),60St.GeorgeSt.,TorontoONM5S3H8,Canada
J
9 LERMA&UMR8112duCNRS,ObservatoiredeParis,61Av.del’Observatoire,75014Paris,France

5 10 Laboratoired’AstrophysiquedeMarseille,38rueF.Joliot-Curie,13388MarseilleCedex13,France
1
ReceivedSeptember15,1996;acceptedMarch16,1997

]
A
ABSTRACT
G
Context. WithintheprojectGalacticColdCoreswearecarryingoutHerschelphotometricobservationsofcoldinterstellarclouds
.
h detectedwiththePlancksatellite.ThethreefieldsobservedaspartoftheHerschelsciencedemonstrationphase(SDP)providedthe
p firstglimpseintothenatureofthesesources.Theaimoftheprojectistoderivethephysicalpropertiesofthefullcoldcorepopulation
- revealedbyPlanck.
o Aims. WeexaminethepropertiesofthedustemissionwithinthethreefieldsobservedduringtheSDP.Wedeterminethedustsub-
r millimetre opacity, look for signs of spatial variations in the dust spectral index, and estimate how the apparent variations of the
t
s parameterscouldbeaffectedbydifferentsourcesofuncertainty.
a Methods. WeusetheHerschelobservationswherethezeropointofthesurfacebrightnessscaleissetwiththehelpofthePlanck
[
satellitedata.Wederivethecolourtemperatureandcolumndensitymapsoftheregionsanddeterminethedustopacitybyacom-

parisonwithextinctionmeasurements.Bysimultaneouslyfittingthecolourtemperatureandthedustspectralindexvalueswelook
1
forspatialvariationsintheapparentdustproperties.Withasimpleradiativetransfermodelweestimatetowhatextentthesecanbe
v
explainedbyline-of-sighttemperaturevariations,withoutchangesinthedustgrainproperties.
3
Results. TheanalysisofthedustemissionrevealscoldanddensecloudsthatcoincidewiththePlancksourcesandconfirmthose
0
detections.Thederiveddustopacityvariesintherangeκ(250µm) ∼0.05–0.2cm2g−1,highervaluesbeingobservedpreferentially
0
inregionsofhighcolumndensity.Theaveragedustspectralindexβis∼1.9–2.2.Thereareindicationsthatβincreasestowardsthe
3
coldestregions.Thespectralindexdecreasesstronglynearinternalheatingsourcesbut,accordingtoradiativetransfermodels,this
.
1 canbeexplainedbytheline-of-sighttemperaturevariationswithoutachangeinthedustproperties.
0
1 Keywords. ISM:clouds–Infrared:ISM–Submillimeter:ISM–dust,extinction–Stars:formation–Stars:protostars
1
:
v
1. Introduction pendencies,weneedtostudyalargesampleofmolecularclouds
i
X andthepre-stellarcoreswithinthem.Themolecularlinesarea
Amajorquestioninstarformationstudiesishowthemainfea-
r central tool in the study of molecular clouds. However, in the
a tures of the process depend on the initial conditions in cold cloudcoresmanymoleculeshavefrozenontodustgrainsmak-
molecularclouds. The masses of the formedstars, the star for-
ing it difficultto carryout quantitativeanalysis with molecular
mationefficiency,thedifferencesbetweenclusteredandisolated
line data alone (e.g., Kramer et al. 1999). One has to resort to
star formation, and the timescales are all closely linked to the
observationsof the dust componentof the clouds, either using
propertiesofdensecloudcores.Inordertounderstandthesede-
theextinctionorthedustemissionasatracerofthemassdistri-
bution.
⋆ Planck (http://www.esa.int/Planck) is a project of the European
TherecentlylaunchedHerschelandPlancksatellitesrepre-
Space Agency – ESA – with instruments provided by two scientific
sentasignificantstepforwardinsub-millimeterstudiesbyelim-
consortia funded by ESA member states (in particular the lead coun-
inatingtheatmosphericeffectsfromobservations.Thesatellites
tries:FranceandItaly)withcontributionsfromNASA(USA),andtele-
enablesensitivemeasurementsofthedustemissionin Galactic
scopereflectorsprovidedinacollaborationbetweenESAandascien-
tificConsortiumledandfundedbyDenmark. interstellar clouds, Planck over the whole sky and Herschel in
⋆⋆ Herschel is an ESA space observatory with science instruments smallerregionsbutwithhigherangularresolution.Thesatellites
providedbyEuropean-ledPrincipalInvestigatorconsortiaandwithim- providethe complementarityneeded for a study of a full cross
portantparticipationfromNASA. sectionoftheGalacticcoldcorepopulation.Becauseofitshigh
2 M.Juvelaetal.:GalacticcoldcoresII.HerschelstudyoftheextendeddustemissionaroundthefirstPlanckdetections
Table1.Theobservedfields Likethespectralindex,alsotheabsolutevalueofthedustab-
sorptioncrosssection, κ, is expectedto be variable.Thiscould
Target RA(J2000) DEC(J2000) Mapsize(PACS/SPIRE) becausedbyachangeintheabundanceofdifferentdustpopula-
PCC249 222117.6 [phone]′/50′ tions,achangeinthegrainsizedistribution(see,e.g.,Steinacker
PCC288 225331.3 [phone]′/30′ etal.2010),orachangeinthecompositionofindividualgrains.
PCC550 122516.5 −714603 18′/30′ Forthesub-millimetreobservations,theeffectsshouldagainbe
strongestindenseandcoldregionswherethegrainsacquireice
mantles and may more easily coagulate to form larger grains
withκvaluesupto3–4timeshigher(e.g.,Ossenkopf&Henning
sensitivity and the coverage of the sub-millimetre wavelengths 1994, Krugel & Siebenmorgen 1994, Stepnik et al. 2003). An
dominatedbycolddustemission,thePlanck all-skymapspro- errorinκautomaticallytranslatestoasimilarfractionalerrorin
vide an unbiased census of cold dust clouds and, in particular, themassestimates.Theabsolutevalueofκ isnoteasytomea-
ofcompactpre-stellarcloudcores.Thesurveyofcoldcompact surebecauseitrequiresanindependentcolumndensityestimate
dustcloudsisoneofthegoalsintheGalacticscienceprogramme thatisequallyormorereliableovertheA rangeforwhichsub-
V
ofPlanck.IntheHerschelOpenTimeKeyProgrammeGalactic millimetreobservationsexist.
ColdCores,weusetheHerschelPACSandSPIREinstruments Inthispaperwestudythesequestionswiththehelpofpho-
to map aboutone hundredtargetfields that are selected on the tometricHerschelobservations.Westartbyderivingthecolour
basis of the Planck survey. This study was begun during the temperature (Sect. 3.1) and column density (Sect 3.2) maps of
HerschelScienceDemonstrationPhase(SDP)whenthreefields the threeSDP fields. This firstanalysisis donewith a constant
wereobserved. valueofthespectralindexβ.InSect.3.3weproceedtostudythe
ThemainfeaturesofthecompactsourcesfoundintheSDP evidenceforvariationsinthedustspectralindex.Withsimulta-
fieldswerereportedinJuvelaetal.(2010).Inthispaperwecon- neous fits of colour temperature and β, we calculate maps of
centrateonthedustemissionatlargescales.Weareinterestedin theapparentspectralindexpayingspecialattentiontotheerror
thecloudproperties,theirtemperatureandcolumndensitydistri- sourcesthatcouldaffecttheobtainedvaluesorthemorphology
butions.However,wealsowanttostudythedustcomponentit- of the β maps. By comparingthe results with the near-infrared
self.Thesearenotunrelatedquestionsbecausethederivedcloud reddeningof backgroundstars, we calculate maps of dust sub-
massesdependontheassumptionsofthedustopacityandspec- millimetreopacity(Sect.3.4).Tocomplementthisanalysis,we
tralindex.Conversely,thevariationsindustpropertiesshouldbe presentinSect.4asimpleradiativetransfermodelforthefield
relatedtothephysicalconditionswithintheclouds. PCC288 and use the results to estimate the difference between
Thedustspectralindexanditstemperaturedependencehave theapparentβandtherealspectralindexofthedustgrains.After
received much attention because they provide additional infor- adiscussioninSect.5wepresentourfinalconclusionsinSect.6.
mationonthechemicalcomposition,structure,andthesizedis-
tributionof interstellardustgrains(e.g.,Ossenkopf&Henning
2. Observations
1994; Krugel & Siebenmorgen 1994; Mennella et al. 1998;
Boudetet al. 2005; Me´ny et al. 2007; Compie`gne et al. 2011). ThePlancksatelliteisperformingallskysurveysatninewave-
The observations consistently show an inverse T − β relation lengths between 350µm and 1cm (Tauber et al. 2010). With
(e.g., Dupac et al. 2003, Hill et al. 2006, Venezianiet al. 2010 the detection methodsdescribed in Montier et al. (2010), three
and the initial Herschel results including Anderson et al. 2010 target fields were selected from the Planck First Light Survey
andRodonetal.2010).However,thereliabilityofthisrelation (see Table 1) for photometric observations with the Herschel
is notoriouslydifficultto estimate because anynoisepresentin PACS and SPIRE instruments (for details about Herschel, see
the measurementsproducesa similar anticorrelation(Schwartz Pilbrattetal.2010,Poglitschetal.2010,andGriffinetal.2010).
etal.1982,Dupacetal.2003,Shettyetal.2009a).Shettyetal. The Herschel observations were performed in November and
(2009b)studiedtheimportanceofobservationalnoiseandtem- December 2009. The field PCC249 was observed in the par-
peraturevariationsonthereliabilityofthederiveddustproper- allel mode and the fields PCC288 and PCC550 in the normal
ties. In the presenceof line-of-sighttemperaturevariations,the scanmapping,oneinstrumentatatime(seeJuvelaetal.2010).
observeddustspectralindexβwillunderestimatetherealspec- ThefieldsareshowninFig. 1. Thedatawere reducedwith the
tralindexofthedustgrains.Theestimatedcolourtemperatures Herschel Interactive Processing Environment (HIPE) v.2. The
are not onlybiased towardsthe warm regionsbut, for example PACSmapswerecreatedusingthemadmapalgorithm.Thepro-
inthetwocomponentmodelsofShettyetal.(2009b),couldbe cessing includessome highpass filtering.In orderto minimize
even higher than any of the real dust temperatures. Similar re- theremovaloflargescalestructure,thelengthofthefilterwin-
sults were obtained by Malinen et al. (2011) who studied syn- dowwaskeptequaltothescanlength.TheSPIREmapsarethe
theticobservationsproducedbycombiningMHDmodellingand product of direct projection onto the sky and averaging of the
radiativetransfercalculations.Theyconcludedthatthepresence timeordereddata.
ofprotostellarradiationsourcescanfurtherincreasethebiasin In order to study dust properties over the whole fields we
theobservedβvaluesandcanproduceanapparentinverseβ–T needtoestablishazeropointfortheintensityscales.Weusethe
relationthatisdifficulttoseparatefromanyintrinsicrelationthe Planckmaps(datareleaseDX4,availablewithinthePlanckcore
dustgrainsmayhave.Malinenetal.(2011)alsonotedthatwhen teams) at 350µm and 550µm and the Improved Reprocessing
thespectralindexvariesoverthe wavelengthrangeincludedin oftheIRASSurvey(IRIS,Miville-Deschenes&Lagache2005)
thespectralenergydensity(SED)fit,thederivedspectralindex maps at 100µm. The highest frequency Planck channels have
can rise even above the real β(λ) of the dust anywhere in that beencalibratedwithFIRAS(Piatetal.2002)andtheIRISdata
interval. Because an error in the spectral index is always asso- havebeencalibratedaccordingtoDIRBE.Whennecessary,we
ciatedwithacompensatingerrorinthetemperature,thisaffects interpolate these reference data for the Herschel bands using a
themassestimatesandcouldevenbiasthederiveddensitypro- modifiedblackbodycurve B ν2 fitted tothe nearesttwowave-
ν
filesofcompactobjects. lengthpoints.
M.Juvelaetal.:GalacticcoldcoresII.HerschelstudyoftheextendeddustemissionaroundthefirstPlanckdetections 3
Table2.Theuncertaintiesofthemapzerolevels 3. Observationalresults
In this section we presentthe colourtemperature,columnden-
Target Wavelength Zeroleveluncertainty
(µm) MJysr−1 sity,andspectralindexmaps.Therelationbetweentheseandthe
intrinsicdustpropertiesisdiscussedinthelatersections.
PCC288 100 14.3
160 10.3
250 3.1
3.1.Colourtemperaturemaps
350 1.2
500 0.4
The colour temperature maps of the large grain emission were
PCC550 100 0.81
estimated using the 100µm, 160µm, 250µm, 350µm, and
160 1.41
500µm observations.Thecolourtemperatureswerefirst calcu-
250 0.43
350 0.23 lated with a constant value of the spectral index, β = 2.0. The
500 0.08 validity of this approximation is investigated in Sect. 3.3. The
PCC249 100 4.4 useofaconstantβcanbejustifiedevenwhentheassumptionis
160 2.6 notstrictlytruebecauseitenablesmorerobustestimationofone
250 2.9 colourtemperaturethatcharacterizesthefields.Asdiscussedin
350 0.7 Sect.4,thecolourtemperatureisoftenanimprecisetracerofthe
500 0.21
physicaldusttemperatures.
1Zerolevelcalculatedusingmapaverages.
All data were smoothed to the resolution of the SPIRE
500µm map (37′′) using a Gaussian kernel. As discussed in
Sect.2,thedeterminationofthezeropointsofthesurfacebright-
ness scales and the correction for the VSG contribution were
The 100µm band contains a contribution from very small
doneiterativelytogetherwiththecalculationofthecolourtem-
grains (VSG). The effect is approximately similar in the IRIS
peratures. In the fit the relative weight of the data are set as-
and PACS 100µm bands and does not affect the calibration
suming 10%uncertaintyfor the SPIRE and 20%for the PACS
comparisonat that wavelength.However,the presenceof VSG
measurements.ThetemperaturemapsareshowninFig.2.
at 100µm could bias the values interpolated to 160µm and
250µm. Therefore, before the interpolation, we subtract from
the IRIS 100µm data the VSG contributionestimated with the 3.2.Columndensitymaps
De´sertetal.(1990) dustmodel.Theradiationfieldisscaledso
that the model reproducesthe observed temperature of the big Thecolumndensitieswerecalculatedusingthemodifiedblack-
grains(BG)thatdominatetheemissionwavelengthslongerthan bodyfitsthatresultedinthecolourtemperaturemapsofFig.2.
100µm.ThepredictedratioofVSGandBGemissionat100µm Like the spectral index, the dust absorption cross section may
is used to correct the IRIS data. Because the ratio depends on varyfromregiontoregionbuttheanalysiswasperformedusing
theestimatedBG temperature,thecorrectionhastobedoneit- a constant value of κ850=0.02cm2g−1 (see Juvela et al. 2010).
eratively. Finally, we do a least squares fit to Herschel surface With a ν2 dependence this corresponds to κ250=0.23cm2g−1.
brightness (convolved to a resolution of 4.3′) vs. Planck/IRIS The column density maps are presented in Fig. 3 where we
andusetheoffsettosetthezeroleveloftheHerschelmapswhile alsoshow9arcmindiametercirclesaroundthepositionsofthe
keeping the original gain calibration. For the PCC550 PACS Planckdetections.ThesewereusedinJuvelaetal.(2010)toes-
observations the fits remained uncertain because of the small timatethemassesoftheregions.
amountofsurfacebrightnessvariation.Inthiscasethezeropoint The column densities were transformed into mass with the
wasestimatedusingthedifferenceintheaveragesurfacebright- distances adopted by Juvela et al. (2010), 800pc, 225pc, and
ness rather than the extrapolation to zero Planck/IRIS surface 800pc forPCC288, PCC550,andPCC249,respectively.Inthe
brightness. sameorder,thetotalmassesoftheareasdisplayedinFig.3are
InthecomparisonbetweenPlanckandIRIS,thedatashould ∼890M⊙,∼31M⊙,and∼3800M⊙.Themassesabovethegiven
be colour correctedbecause this could affect the quality of the columndensitycontours,andinsidethe9arcminapertures,are
leastsquaresfit.Thecolourcorrectionswerecalculatedformod- listed in Table 3. The statistical errors are small and the mass
ifiedblackbodyspectraB (T)ν2 thatwerefittedtotheobserva- uncertaintyis dominatedby the uncertaintiesof the calibration
ν
tions after a preliminary estimation of the zero points. All ob- (∼10%),thedustopacity(up to a factorof two), andthe cloud
servations, including Planck and IRIS data, were colour cor- distance(typically∼30%correspondingto a∼50%uncertainty
rected before repeating the least squares fits. The corrections inthemass.
can be applied consistently only if the offsets of the Herschel
andPlanck/IRISmapsarealreadycorrectandthereforealsothis
3.3.Dustspectralindex
correctionneedstobedoneiteratively.However,thecolourcor-
rectionsareless than10%,anda sufficientaccuracyisreached The 100µm–500µm data were also fitted with modifiedblack-
alreadyontheseconditeration.Thesubsequentanalysiswascar- bodycurvesB (T)νβkeepingboththecolourtemperatureT and
ν
riedoutusingthesecolourcorrectedobservations. thespectralindexβasfreeparameters.Wemaskedoutthebor-
The statistical uncertainties of the offsets were estimated dersofthemaps(∼3′)andthenorthernendofthefieldPCC288
withthebootstrapmethodandarelistedinTable2.Theuncer- wherethecolumndensitymapandthemapofdustopacity(see
taintiesareoftheorderof1MJysr−1 butsmalleratthelongest Sect. 3.4 and Sect. 5.3) show a suspicious feature. The colour
wavelengths with the lowest surface brightness. The error es- temperatureandspectralindexmapsareshowninFig.4andrep-
timates are larger for the PACS channels apart from the field resentativeSEDsinFig.5.Themedianvaluesofβare2.21,2.21,
PCC550 where, as explainedabove, the quoted offsets are cal- and1.86forPCC288,PCC550,andPCC249,respectively.The
culatedusingaveragesurfacebrightnessvalues. samefitswithoutthe100µmdataareshowninAppendixB.2.
4 M.Juvelaetal.:GalacticcoldcoresII.HerschelstudyoftheextendeddustemissionaroundthefirstPlanckdetections
T(K) T(K) T(K)
15 17 15 17 17 19
PCC288 PCC550 PCC249
64d 00’
62d 40’
-71d 40’
0)
0
0
2J 62d 30’
(
δ -71d 50’
63d 30’
62d 20’
22h 54m 22h 52m 12h 26m 12h 24m 22h 25m 22h 20m
α(J2000) α(J2000) α(J2000)
Fig.2. DustcolourtemperaturemapsforthethreeSDPfields.Thecalculationsassumeafixedvalueofthespectralindex,β=2.0.
Themapresolutionis∼37′′andthecontoursaredrawnoneKelvinapart.
N(H)(cm-2) N(H)(cm-2) N(H)(cm-2)
21.6 21.9 22.2 22.5 21.0 21.3 21.6 21.9 21.3 21.6 21.9 22.2
PCC288 PCC550 PCC249
62d 40’ 64d 00’
-71d 40’
P1
0) P P1
0
0
2
(J 62d 30’
δ P2
-71d 50’ 63d 30’
P2
62d 20’
22h 54m 22h 52m 12h 26m 12h 24m 22h 25m 22h 20m
Fig.3. MapsofthehydrogencolumndensityN(H)derivedwiththecolourtemperaturemapsofFig.2.Themapshavearesolution
of∼37′′andthecontoursaredrawnatlevelswherelog N(H)equals21.5,21.8,and22.1.Thecirclesshowthe9arcminapertures
10
usedinJuvelaetal.(2010).
Table3.Themassestimatesoftheobservedfieldsorpartsofthe peratureandspectralindexmaps.Thewavelengthswerechosen
fieldsthataredefinedbyacolumndensitylimitorcorrespondto becausetheirrelativeintensitiesareimportantindeterminingthe
9arcminapertures(regionsP,P1,andP2). spectralindex.Themapoffsetswerefirstchangedbythevalues
listed in Table 2 and the surface brightness values were scaled
Field Region Mass(M⊙) correspondingtoa10%gainuncertainty.Thechangesatthetwo
PCC288 fullfield 1108 wavelengthswere made in opposite directionsin orderto have
log N >21.8 785 themaximumeffectinthederivedβvalues.Byapplyingthe∼1σ
10
log10N >22.1 242 shiftsbothinthegainandintheoffsetandatbothwavelengths
P 288 simultaneously,weshouldgetaconservativeestimateoftheun-
PCC550 fullfield 36.2
certainties. In Fig. 6, the resulting shifts of the observed (T,β)
log N >21.8 13.9
10 pairsareshownforthethreerandompixels.Thefullmapsofthe
P1 12.2
maximum and minimum β values are shown in the Appendix,
P2 11.3
Sect.B.1.
PCC249 fullfield 3802
log N >21.8 1763
10
log N >22.1 627
10 3.4.Dustopacity
P1 252
P2 259 We calculated extinction maps at a 1.5′ resolution using stars
fromtheTwoMicronAllSkySurvey(2MASS,Skrutskieetal.
2006) and the NICER method (Lombardi& Alves 2001). The
InFig.6weshowtherelationsbetweenthederivedspectral values of A are obtained from NIR colour excess assuming
V
indicesandthecolourtemperatures.Forthreerandomlyselected anextinctionlawwithR =3.1.Thezeroleveloftheextinction
V
pixels,theblackcontoursshowwheretheχ2 valueofthe SED was setwith the Schlegeletal. (1998) extinctionmap.The ex-
fithasdoubledfromitsminimumvalue. tinctionestimatesenableusto estimate thesub-millimetredust
To getthe first idea of the possible effect of the calibration opacity relative to the visual extinction. The extinction is con-
uncertainty,wecomparedtwocaseswhereweadderrorstothe vertedto totalISM masswith the Bohlin etal. (1978) relation,
250µm and the 500µm maps and recalculate the colour tem- N(HI+H )∼1.87×1021A thatismultipliedby1.4m toac-
2 V H
M.Juvelaetal.:GalacticcoldcoresII.HerschelstudyoftheextendeddustemissionaroundthefirstPlanckdetections 5
4.0 4.0
PCC288 PCC550
3.5 3.5
3.0 3.0
2.5 2.5
β β
2.0 2.0
1.5 1.5
1.0 1.0
0.5 0.5
10 15 20 25 10 15 20 25
T(K) T(K)
Fig.6. Theobservedtemperaturedependenceofthespectralindexin thethreefields.Thevaluesareshownforindividualpixels
(greendots).Forthreeselectedpixels,theblackcontoursshowthelimitatwhichtheχ2 valueoftheSEDfithasdoubledfromits
minimumvalue.Forthesamepixelsthesmallersymbols(joinedwithsolidlines)showtheextremevaluesallowedbythecalibration
uncertainty(seetext).Theerrorregionsfortheseextremecasesaredrawnwithdashedanddash-dotlines.
countforthemassofhelium.Theconversionisdoneforeasier strength of the ISRF were scaled so that the surface brightness
comparisonwiththeliteraturebuttheconversionfactoritselfis levelsmatchtheobservationsofPCC288to∼30%.
appropriatemainlyfordiffusemediumandmayvaryacrossthe
fields.
Figure 7 shows the 250µm opacity maps derived from
Because the proper handling of regions near the internal
the SED fits done with β = 2.0. The median values in the
sourcesrequireshighspatialresolution,themodelwassampled
fields PCC288, PCC550, and PCC249 are 0.11, 0.064, and
onto a hierarchical grid with the smallest cell size correspond-
0.061cm2g−1. The opacities obtained with fixed value of β =
ing to the resolution of 10243 uniformgrid. The dust tempera-
2.0 and the free β are identical to within 20%. In the cen-
turedistributionsweresolvedwitha radiativetransferprogram
tral part of PCC288 the values rise close to κ(250µm) ∼0.22
thatisbasedonourMonteCarlocode(Juvela&Padoan2003)
while in the northern colder region of PCC249 (corresponding
but has been adapted for use with hierarchical grids (Lunttila
tothePlanckdetectionP1)thepeakvalueisevenhigher,above
et al., in preparation). The obtained surface brightness maps
∼0.3cm2g−1.ThevalueusedforthemassestimatesinSect.3.2
at 160µm, 250µm, 350µm, and 500µm were analysed to de-
was 0.23cm2g−1. This is clearly above the median values but
rivecolourtemperatureandspectralindexmaps.Noisewasnot
roughly consistent with the values associated with the highest
added to the synthetic observations and all wavelengths were
column densities. However, in the field PCC550 the values re-
given equal weight in the (T, β) fitting. The results are shown
main everywherebelow κ(250µm) =0.12cm2g−1. Our typical
inFig. 8wherethe threeinternalsourcesareclearlyvisible(in
opacity of 0.1cm2g−1 corresponds to τ(250µm)=2.3×10−25/H,
orderofincreasingluminosityfromWesttoEast).Thelefthand
slightly more than twice the value found in diffuse medium
frameshowsthedifferencebetweentheobservedcolourtemper-
(Boulangeretal.1996).
atureandthemassweightedaverageofthetruetemperature.In
the regionshown,the dusttemperatureis overestimatedbybe-
4. RadiativetransfermodelofPCC288 tween∼0.25Kinthemostdiffuseareasand∼8Kattheposition
of the strongest source. The median error is ∼0.8K. An error
To find out the level at which temperature variationsalong the
in the temperatureis associated with an oppositechangein the
line-of-sight may bias the observed values of the spectral in-
spectral index.In a fit with a fixed value of β = 2, the median
dex and the dust temperature, we made a simple model of the
error would be only 0.4K. At a temperature of T = 15K, this
PCC288 region. The model was not intended as a fit to the
wouldcorrespondtoalessthan15%underestimationofcolumn
PCC288 observations but is only used to estimate the general
density.If β is keptas a free parameter,the 0.8K bias leads to
observationalbiasesinasettingsimilartothisfield.Themodel
a ∼30%errorin columndensitywhenthe estimate is basedon
wasbasedonthecolumndensitymapshowninFig.3andrepre-
κat160µm.Thisdecreasestoonly∼10%whentheestimateis
sentsaboxwithasizeof5.4pc(ford=800pc).Theline-of-sight
based on 500µm. However, close to the sources the errors re-
density profile was gaussian with a FWHM that was 0.4pc to-
mainlarge,atleastafactoroftwo.
wards the densest part of the cloud and increased up to 1.6pc
in regions of low column density. The numbersroughly corre-
spondtothescalesofthecentralclumpandthewholefieldbut
arebasicallyadhocvalues.Inparticular,thedensitydistribution InFig.8,themedianvalueoftheobservedspectralindexis
of the model is quite smooth with a maximum density of only β=1.92 which is only slightly smaller than the actual value of
3.7×104cm−3. Because also the wavelength dependenceof the the dust model, β=2.0. The values are more biased in areas of
spectralindexcouldbiastheobservedβvalues(seeMalinenet high column density and the observed β is consistently below
al.2011),themodellingwasdonewithamodifiedversionofthe 1.9inthesouth.Atthepositionofthesourcesβisreducedfur-
normal Milky Way dust model (Draine 2003) where β was set thertoaminimumvalueof1.56.Theobservationsprovidegood
to a constantvalueof 2.0 forall wavelengthsλ > 100µm.The estimatesofthe spectralindexonlyinthe morediffuseregions
cloud is illuminated from the outside by an isotropic interstel- butalsoatacertaindistancefromthesourceswheretheinternal
lar radiation field (ISRF; Mathis 1983). Three blackbody radi- heatingapparentlyhelpstokeepthetemperatureconstantalong
ationsourceswitha temperatureof2000K andluminositiesof theline-of-sight.Althoughthe columndensityishighestin the
10,20,and50L⊙ wereaddedtorepresentinternalheating.We centralclump,thebiasishigherinthesouth,furtherawayfrom
showtheresultsforamodelwherethecolumndensitiesandthe theheatingsources.
6 M.Juvelaetal.:GalacticcoldcoresII.HerschelstudyoftheextendeddustemissionaroundthefirstPlanckdetections
κ(cm2/g) κ(cm2/g) κ(cm2/g)
0.1 0.2 0.3 0.1 0.2 0.1 0.2 0.3
PCC288 PCC550 PCC249
62d 40’
-71d 40’ 64d 00’
0)
0
0
2J 62d 30’
(
δ -71d 50’ 63d 30’
62d 20’
22h 54m 22h 52m 12h 26m 12h 24m 22h 25m 22h 20m 22h 15m
α(J2000) α(J2000) α(J2000)
Fig.7. Mapsof thedustopacityderivedfromthe comparisonof the NIRextinctionmapsand SED fitswith a fixed valueofthe
spectralindex,β=2.0.Thevaluesaregivenfor250µmandrelativetothetotalISMmass.Thecontoursaredrawnstartingwiththe
valueof0.05cm2g−1andwithastepof0.02cm2g−1(PCC550)or0.03cm2g−1(PCC288andPCC249).
5. Discussion 5.2.Cloudmassesanddustopacity
5.1.Colourtemperatures InJuvelaetal.(2010)themasseswereestimatedonlyforcom-
pactobjects,withafixedcircularapertureandwithbackground
The calculation of the colour temperature maps for the full subtraction.Themasseswerequotedalsofora 9arcmindiam-
Herschel fields confirmed the Planck detections of cold dust eter aperture and these can now be compared with the values
emission. Evenin the field PCC249, with active star formation of Table 3 that were obtained without backgroundsubtraction.
and a high average colour temperature, the Planck detections In PCC288, the estimate has increasedby a factor of two from
correspondtoregionswherethecolourtemperatures,T ∼15K, 140M⊙to288M⊙.InthecaseofPCC550thebackgroundlevel
are ∼2 degreesbelow the values of the surroundingareas. The issmallandthechangeismuchsmaller.Thepreviousvaluesof
Planck detections are based on the cold dust signature that re- 9.2M⊙ and 8.1M⊙ for P1 and P2, respectively, have been re-
mains when the warm component traced by the 100µm IRIS placedby12.2M⊙and11.3M⊙.InPCC249theintensitylevels
maps has been subtracted (Montier et al. 2010). This does not areagainhighandalsothecontrastbetweentheemissioninthe
require a low colour temperature for the total emission. The selectedaperturesandthesurroundingreferenceareasissmall.
separation of the warm and the possible cold component is As a result, the masses obtained without background subtrac-
more uncertain in warm regions where the warm component tionaremuchlarger.Thepreviousestimatesof90M⊙(areaP1)
is strong and must be subtracted with higher relative accuracy. and 93M⊙ (area P2) have increased to 252M⊙ and 259M⊙.
The PCC249 sources are very bright with peak surface bright- Differencesare,ofcourse,notsurprisingbecausethenewmea-
ness reaching in both PACS and the 250µm SPIRE band sev- surementsare for the whole mass along the line-of-sightwhile
eral thousand MJysr−1. The Planck observations were able to theoldonescorrespondtothecolumndensityexcesswithinthe
locatethetwonearbycoldregionsdespitethefactthat,accord- aperture.
ingtoHerschel,theyaresmallandthusbeamdiluted:thePlanck
InPCC249,thenewvaluesareinbetteragreementwithmass
beamshaveasignificantcontributionalsofromthewarmersur-
estimates frommolecularline observations.Wang et al. (2009)
roundingregions. obtainedfrom13CO(2–1)observationsavalueof1700M⊙ for
Intheanalysisperformedwithafixedspectralindexvalueof aregionthatcorrespondstoourarea P1.Theestimatewascal-
β=2.0,theminimumcolourtemperatureswere13.8K,13.1K, culatedforaclouddistanceof1.67kpcwhich,withthedistance
15.6K,and14.8KforPCC288,PCC550,andthenorthernand ofd = 800pcassumed here,translatesto ∼390M⊙. The value
the southernareasin PCC249,respectively.Theseare a couple derived from Herschel data is still lower but already ∼65% of
ofdegreeshigherthanthevaluesreportedinJuvelaetal.(2010) this number. On the other hand, the situation has not changed
wheretemperatureswerecalculatedafterthe subtractionofthe much for PCC550 where the masses obtained from molecular
local background. In spite of the different nature of the fields, line studies (Vilas-Boas et al. 1994; see Juvela et al. 2010) are
the minimum temperatures are rather similar. Of course, even also higher than our values. In PCC550-P2 the molecular line
the backgroundsubtracted observationsdo not give a true pic- datagaveamassof16.5M⊙ andthe∼50%discrepancyisstill
ture of the coldest temperaturesthat inside the cores are likely notveryserious. However,for the coreP1 (coreMu5in Vilas-
to be below 10K (e.g., Crapsi et al. 2007; Harju et al. 2008). Boas et al. 1994) the CO analysis lead to a value of ∼ 33M⊙
With radiative transfer modelling of the dust continuumobser- that is three times our estimate. The uncertainty of κ can ex-
vations one could derive an upper limit for the central temper- plain most of this discrepancy. The values derived in Sect. 3.4
aturebutoncethetemperatureisreducedcloseto6K,thecold were all below κ(250µm) = 0.15cm2g−1 with a median value
dustwillbedifficulttodetectevenwithHerschelobservations. of0.073cm2g−1.Withκ(250µm) = 0.085cm2g−1 themasses-
In our simple model of the field PCC288, the minimum phys- timate of P1 would be in perfect agreementwith the value ob-
ical dust temperature was only ∼2K lower than the minimum tained from the line observations.The radiative transfer model
colour temperature.It is very likely that in the real clumps the ofPCC288hintedthatthecolumndensityestimatesmaybebi-
centraldensitiesrisehigherthaninourradiativetransfermodel ased.InthecaseofPCC550thefinalanswertothisquestionmay
andthereforealsoreachlowerphysicaltemperatures. be providedby the detailed radiative transfer modelling that is
M.Juvelaetal.:GalacticcoldcoresII.HerschelstudyoftheextendeddustemissionaroundthefirstPlanckdetections 7
currentlyunderway(Ysardetal.,inpreparation).Onecanalso 5.3.Spectralindices
questiontheaccuracyoftheCO massestimates.Thefractional
abundances are not accurately known, the observations of the Wefittedtheobserved(T,β)valuesofFig.4withtwoanalytical
cold regionsmay be affected by some degreeof molecular de- formulas,β= A(T/20K)−α andβ=(δ+ωT)−1.Theparameters
pletion(e.g.,PCC550),and,conversely,theopticaldepthsofthe of the relations are listed in Table 4. The obtained T(β) rela-
employed13COlinescanbecomehighenoughsothatradiative tionsaresteeperthanreportedinDupacetal.(2003)whofitted
transfereffectscanbiastheresults(e.g.,self-absorptionaffecting PRONAOSobservationsusingthelatterformula.Ourrelationis
theobserved13CO/C18Olineratios).Consideringallthesources closertotheresultsfromtheArcheopsexperiment(De´sertetal.
of uncertainty, the mass estimates obtained from the lines and 2008)wheretheobservationsfitarelationβ= AT−αwithanex-
fromdustcontinuumareingoodagreement. ponentvalueofα=0.66±0.054.TheerrorestimatesinTable4
do not reflect the true uncertainty but only the accuracy of the
The median values of the dust absorption cross sections
curvefitting.Onesourceofuncertaintyistheaccuracytowhich
κ(250µm)obtainedfromthecomparisonwithNIRextinctionare
the very small grain contribution could be subtracted from the
0.13,0.073,and0.055cm2g−1 forthefieldsPCC288,PCC550,
100µmdata.However,thetemperatureandspectralindexmaps
andPCC249,respectively.Thepeakvaluesare higherbymore
derivedwithoutthe100µmbandarerelativelysimilartothere-
than a factor of two and, in PCC550 and PCC249, are associ-
sultsshowninFig.4(seeAppendixB.2).Wewillnextexamine
ated with regions of higher column density. This behaviour is
thereliabilityofthedetectionofthespectralindexvariationsin
expected and could be explained by an increase in grain sizes.
thepresenceofothererrorsources.
In PCC288, there is some indication that the dust opacity has
Calibration errors affect the (T, β) values mostly in a sys-
increasedinthecentralclump,closetothecolumndensitymax-
tematicfashion.InFig. 6, we indicatedforthreerepresentative
imum.TheincreasetowardstheNorthcornerisverylikelyonly
pixelstheshiftsthatwouldresultfroma10%changeinthegain
anartifact.Theresultscouldchangenoticeablyevenwithinthe
calibration combined with a change in the offset that is equal
limitssetbytheaccuracyofthezeropointsofthesurfacebright-
totheuncertaintieslistedinTable2.Thecalibrationerrorstend
nessscale.Nevertheless,theresultssuggestspatialvariationsat
to move all points along a trajectory similar to that caused by
least by a factor of two. Most of our κ(250mum)values are in
the range0.05–0.2cm2g−1. Scaled with ν2, this correspondsto randomnoisewithoutmuchaffectingthedetectionofaninverse
κ(850µm)=0.004–0.017cm2g−1.TheA valueswerecalculated T −β relation. In the field PCC550, the spectral indexreaches
V
assuminganextinctionlawwithR =3.1.Thisisappropriatefor values β ∼2.35 at the locations of the two cores. In the high-
V
β version (calibration errors causing higher 250µm and lower
mostareasbutnotnecessarilyforthedensestcores.Byadopting
R =5.5,theextinctionvalueswoulddecreaseby∼16%.Taking 500µm surface brightness) the centre of the PCC550 filament
V
would reach β ∼ 2.7 while the background would remain at
intoaccountapossibledecreaseintheratioN(H)/A thecalcu-
V
β ∼2.4.Oppositechangesinthecalibrationwoulddecreasethe
lated dust opacities could increase further by more than 30%
(see Evans et al. 2009, Draine 2003, and the online tables1). spectralindexvaluesinthefilamenttoavalue∼2,still0.2–0.3
unitsabovethebackground.Thisshowsthattheincreaseofdust
This would further strengthen the case for an increasing sub-
opacitywithinthePCC550filamentisrobustagainstcalibration
millimetredustopacityinthecoldanddensecores.
errorsalthoughtheuncertaintyintheabsolutevalueofβishigh,
The opacities can be compared with values found in
closeto∼0.4.Theeffectsofadifferentcalibrationaresimilarin
other studies. Using COBE measurements, Boulanger et al.
the other two fields, changingthe absolute levelof β withouta
(1996) derived an effective dust cross section for high lat-
clearchangeinthemorphology.
itude diffuse medium. At 850µm, the obtained values are
κ(850µm)=0.005cm2g−1 inagreementwiththelowendofour WeusedMonteCarlosimulationstoquantifythenoisebias
andtheevidenceforanegativeβ−T correlation.Weaddednoise
measurements.InthedarkcloudIC5146,Krameretal.(2003)
found the values to vary from κ /κ ∼ 1.3 × 10−5 in warm tothesurfacebrightnessmeasurementandrepeatedthefitofthe
regions (20-30K) to ∼ 5 × 10−8550in Vcolder regions with T ∼ β(T) = AT−α relation.Thestatistical uncertainty of the surface
brightnessmeasurements,σ ,wasestimatedfromthedifference
12K. With the conversion used in Sect. 3.4, these correspond S
to∼0.003cm2g−1and0.011cm2g−1,ingeneralagreementwith betweentheobservedmapsandtheSEDfitswithafreeβparam-
eter. Theseareconservativeestimatesbecausetheresidualsare
our range of values. However, there are also dense and cold
affected also by calibration errors. The calibration uncertainty
cloudswhere similar increase of dust opacity has notbeen ob-
σ was assumed to consist of a 10% uncertainty in the gain
served. Nutter et al. (2008) reportedobservationsof a filament C
calibration and the zero point uncertainties listed in Table 2.
in Taurusand concludedthat these can be modelledaccurately
To see how sensitive the extracted values are on the statistical
without any spatial variations of dust properties. Juvela et al.
noisealone,wecarriedoutonesetofsimulationswhereσ was
(2009) estimated for a Corona Australis molecular cloud fila- S
addedto the observedmaps. However,we mainlycomparethe
menta κ value thatwas almostconsistentwith valuesfoundin
originalobservationswithreferencesimulationswithaflatβ(T)
diffuseclouds.Thisinspiteofthefactthattheregionhadmore
than20mofvisualextinctionandhadaminimumcolourtemper- relation. These are based on the SED fits that were made with
β = 2.0.Inthefirstsetofsimulationsσ andσ wereaddedto
ature of ∼11K although,on the other hand,the sub-millimetre S C
the inputmaps. In the secondset of simulationsone quarterof
measurements may have suffered from some spatial filtering.
eachsurfacebrightnessmapwasadditionallyscaledwitharan-
Theresultsshouldbetested,possiblywiththehelpofHerschel
domfactorcorrespondingtoa10%relativeerror.Thissimulates
observations,toconfirmwhetherthedustbehaviouristhisdiffer-
mapping artifacts, σ , whose effect is fundamentally different
entinapparentlysimilarcloudsorwhethertheresultscouldbe M
from both σ (affecting each pixel independently)and σ (af-
explainedbythedifficultyofreachinganaccuracyofmeasure- S C
fectingallpixelssimultaneously).Whileσ canshiftallthe(T,
mentsthatis neededfora reliabledeterminationofdustopaci- C
β) points along almost a fixed trajectory, without a noticeable
ties.
change in the best fitting β(T) relation, the mapping artifacts
willincreasethedispersionofthe(T,β)valuesalongthenoise-
1 http://www.astro.princeton.edu/draine/dust/dust.html inducedβ(T) curve. Thiscould be misinterpretedas a stronger
8 M.Juvelaetal.:GalacticcoldcoresII.HerschelstudyoftheextendeddustemissionaroundthefirstPlanckdetections
Table4.Parametersoftheβ(T)fits. spectralindexincreasesfrom∼2.2attheboundariesto∼2.5in
thecentralclumpbeforedecreasingto∼1.5atthelocationofthe
β(T)=A(T/20K)−α β(T)=(δ+ωT)−1 strongestwarmsourceatthecentreofthemap.InPCC249the
Target A α δ ω warm sourcesaresimilarly associated with spectralindexmin-
PCC288 1.89(0.02) 0.62(0.03) 0.18(0.02) 0.018(0.001) ima,β ∼1.0nearPCC249-P1and∼1.3nearPCC249-P2,while
PCC550 1.90(0.02) 0.44(0.02) 0.26(0.02) 0.014(0.001) thevaluesinthecentralmapotherwisearebetween1.8and2.2.
PCC249 1.77(0.01) 0.97(0.02) 0.02(0.01) 0.027(0.001) It is clear that warm sources are associated with significantly
lowerβ.Theevidenceforhighβvalues(>>2)towardsthecold-
est clumps is somewhat weaker because it comes from larger
evidenceofaninverserelationbetweenβandT. Thecompari- scalesthatmightbe affectedbymappingartifacts. However,in
sonbetweenthe SED fits andthesurfacebrightnessmapssug- PCC288andPCC550,T andβareclearlyanticorrelatedalsoin
gestedthepresenceofsomesuchartifacts(seeAppendixB).In theregionswithT <15K.InPCC249thesituationissimilarat
PCC249,thesewerebelow∼5%apartfromthenorthernendof large scales but not in the cores PCC249-P1 and PCC249-P2.
the160µmmapwhere,withinanarealessthan5%ofthewhole Theseareveryneartostrongradiationsourceswhichmayhave
map, the residual rises between 10% and 20%. In PCC288 the affectedthespectralindexestimates.
artifactsremainbelow 10%whenthe northerncornerhas been We conclude that there is strong evidence of spatial varia-
maskedout.ThesameappliestoPCC550exceptforthe160µm tions in the apparent dust spectral index and the magnitude of
mapwherethedifferencetotheSEDfitisabove10%overabout these changes is likely to be at least ∆ ∼ 0.2 and can be up
one third of the map and reaches values 20–30% over an area to ∆ ∼ 1 towards warm, internally heated sources. The simple
less than 10% of the full map. By introducing a 10% error in modelofthePCC288fieldshowedthattheseapparentvariations
the quarter of the mapped area and in all the frequencybands, do not necessarily indicate an equalchange in the dust proper-
wearecertaintoobtainaconservativeestimateofthemapping ties.Inthemodel,thespectralindexofthegrainscouldbe0.2–
artifacts,especiallyinPCC288andPCC249. 0.3 units higher than what is observed (Sect. 4). This applies
Figure 9 shows the distribution of the parameters α in this toregionsofhighcolumndensityandwithoutinternalheating.
Monte Carlo study, each resulting from the simulation of 500 The effect is opposite to the observed correlation between the
sets of synthetic surface brightness maps. For each set of fre- columndensityand β andfurthersupportsthe idea ofhigherβ
quency maps, the colour temperatures and the spectral indices values for the dust grains in the cold cores. This behaviour is
wereestimatedpixelbypixel,andtheanalyticalβ(T)formulas expected on the basis of laboratory measurements and can be
werefittedtotheresults.ThedistributionS1correspondstothe explained by the properties of the grain materials at low tem-
observedmaps with added noise, σ . The distributions R1 and perature(Mennellaetal. 1998;Boudetetal. 2005; Me´nyetal.
S
R2 correspond to simulations with a constant value of β = 2, 2007).Ontheotherhand,thelowvaluesofβthatwereobserved
R1 containing σ and σ and R2 additionally the mapping er- towardsthewarmsourcesinPCC288canbefullyexplainedby
S C
rorsσ . Theverticallinesshowtheparametervaluesobtained line-of-sighttemperaturevariations.Itwillbedifficulttodeter-
M
directlyfromtheobservations. mine whether also the intrinsic spectral index of the grains is
Becauseofthenoise-inducedanticorrelationbetweenT and lowerinsuchregions(seealsoMalinenetal.,2011).
β,theαvaluesarepositiveevenwhentheinputdatacorrespond Theexactrelationbetweentheobservedandrealβdepends
to a constant value of β = 2.0. For the same reason, the dis- on the properties of the object in question (density structure,
tributionsS1areshiftedrelativetotheobservedvaluesandare strength of the external radiation field, nature of the internal
narrow only because the effect is almost identicalin all Monte sourcesetc.)andtheresultsofourradiativetransfermodelcan-
Carlo realizations. In the fields PCC288 and PCC249, the ob- notbegeneralizedveryfar.We havestarteddetailedmodelling
servedα valuesare higherthanmost valuesin the R1 distribu- oftheobservationsofPCC550.Theresultsofthatstudywillgive
tion. If mapping artifacts can be ignored, this indicates a real usabetterideaonhowtheobservedspectralindexvariations,if
anticorrelation between temperature and the observed spectral real,arerelatedtotheactualdustproperties.Thismayalsoshed
index.Thehypothesisα > 0getsprobabilities97%and99%in new light on the reliability of the mass estimates derived from
the case of PCC288 and PCC249, respectively. However, with Herschelobservations(Ysardetal.,inpreparation).
thesimulatedmappingartifactsthereferencedistributionsR2is Thepossiblepresenceofmappingartifactswasfoundtobe
much wider and the correspondingprobabilitiesare reducedto themainproblemintheevaluationoftheobservationalT–βre-
69%and66%.Thedetectionsarenolongerstatisticallysignifi- lation. In new observations larger map sizes and increased re-
cantbutthenumbersdependcriticallyontheactuallevelofσ . dundancywouldhelptoreducesuchartifactsandmakeiteasier
M
Webelievethatthenoisevaluesusedinthesimulationwerecon- to evaluate their impact. The situation may be improved with
servativeandthetruthliessomewherebetweenthecasesR1and betterdatareductionmethodsand,inthefuture,onecouldalso
R2.Therefore,theMonteCarlostudygivessome,althoughweak usePlanckdatatocheckforlowresolutionartifactsinthelong
evidenceforanon-flatβ(T)relation.InthecaseofPCC550,the wavelength Herschel data. When combined with far-infrared
valuesofαwerehigherinthesimulationsthaninobservations. data,thePlanckobservationsthemselvesareverysuitableforthe
Thisispossibleif themappingartifactsconspiredtoproducea studyofthespectralindexvariationsandwillbeusedtoexamine
lowαvalueormayindicateoverestimationoftheerrors. thesituationalsoincoldcoresandclumps(PlanckCollaboration
The Monte Carlo study showed that the global analysis of 2011a,2011b).
(T, β) points does not give a conclusive proof of spectral in-
dex variations. That analysis is not sensitive to very localized
6. Conclusions
β variations while it may be significantly affected by artifacts
thataremorelikelytoexistclosetomapedgesandfarfromour We have studied Herschel surface brightness measurements of
dense sources. In Fig. 4, many of the spectral index variations three areas where the Planck satellite data indicated the pres-
areclearlycorrelatedwithactualcloudstructuresand,therefore, ence of significant amounts of cold dust. By analysing surface
are unlikely to be caused by mappingartifacts. In PCC288 the brightnessmapsatwavelengthsbetween100µmand500µmwe
M.Juvelaetal.:GalacticcoldcoresII.HerschelstudyoftheextendeddustemissionaroundthefirstPlanckdetections 9
mapthedustcolourtemperature,dustopacity,anddustspectral thePACSbeam.Nevertheless,theresidualscouldbeassociated
indexvariationsoverthefields.Theresultsleadtothefollowing withanimperfectdeconvolutionofthedetectortimeconstants.
conclusions:
– ThecolourtemperaturemapsconfirmthePlanckdetections B.1.Mapsofthespectralindexuncertainty
ofcolddust.Theanalysisofthetotalintensityleadstomin-
The derivedspectralindexvaluesare affectedby observational
imumcolourtemperatureof13–15Kinthethreefields.
noise,errorsinthezeropointoftheadoptedsurfacebrightness
– The results show an increase in the dust opacity towards
scale,anderrorsinthegaincalibration.FigureB.4showsmaps
colder and denser cloud regions. The range of values for
thatcanbeusedtoassesstheimportanceofgaincalibrationand
the dust absorption cross section was estimated to be
zero point errors. As discussed in Sect. 3.3, we modified the
κ(250µm) ∼ 0.05–0.2cm2g−1, in agreement with previous
250µm and 500µm surface brightnessmapsby addingor sub-
studies.
tractingthezeropointuncertaintiesfromTable2andbyscaling
– Themedianvaluesoftheobservedspectralindiceswerebe-
themapsbyanamountcorrespondingtoa10%gainuncertainty.
tween1.9and2.2.Wewitnessedaninverserelationbetween
Thechangesatthetwo wavelengthsweremadein oppositedi-
thecolourtemperatureandthespectralindex.AMonteCarlo
rections in order to have the maximum effect in the β value.
studyindicatedbutdidnotconclusivelyproveatemperature
By applying 1σ shifts in the gain and in the offset and at both
dependenceof β beyondwhatcouldbe producedby obser-
wavelengthscriticalfor the determinationof the spectralindex
vationalerrors.However,becausethechangesarewellcor-
we should get conservative limits for the spectral indices. The
relatedwithcolumndensity,webelievethevariationstobe
mapsofminimumandmaximumspectralindicesareshownin
real.Verylowvaluesdowntoβ∼1.0wereobservedtowards
Fig.B.4.
warm sources but these are likely to be caused mainly by
temperaturevariationsratherthanchangesinthegrainchar-
acteristics. B.2.Temperatureandspectralindexmapswithout100µm
– Withthehelpofasimpleradiativetransfermodel,weexam- data
inedtherelationbetweentheobservedandintrinsicspectral
Thesubtractionofthe VSG emission fromthe 100µm datare-
indices.Theresultsshowthattheintrinsicβvalueofthedust
lied on the ratio of the VSG and BG grainsin the De´sert et al.
grains is underestimatedin regionsof high column density
(1990)dustmodel.Thisalsoaffectsthe160µmdatabutonlyas
and,therefore,the observationsmayalso underestimatethe
anuncertaintyofthezeropointoftheintensityscale.Tocheckto
realvariationofthespectralindex.Ontheotherhand,theflat
whatextentthecolourtemperatureandthespectralindexmaps
spectrum nearinternalheatingsourcescan be explainedby
are influenced by the 100µm data, we recomputed the param-
the line-of-sighttemperaturevariationswithoutany change
eters using the 160µm–500µm data only. The resulting maps
inthedustproperties.
of the colour temperature and the spectral index are shown in
Fig.B.5.
AppendixA: Frequencymaps The maps are morphologically similar to those shown in
Fig.4.ThelargestdifferencesareinPCC550where,withoutthe
FiguresA.1–A.3showthe100µm,160µm,250µm,and350µm
100µmdata,thespectralindexmapcloselyfollowstheshapeof
surfacebrightnessmapsforthethreeSDP fields.Themapsfor
thedensefilament.TheappearanceofSWpartofthatmapagain
500µm are not included but their appearance, apart from the
suggests the presence of some artifact, the β values decreasing
lower intensity and lower spatial resolution,is almostidentical
close to one. Compared to Fig. 4, PCC249 exhibits somewhat
withthe350µmmaps.
lowervaluesofβandahigherrangeoftemperatures.
Acknowledgements. MJandJMacknowledge thesupport oftheAcademy of
AppendixB: Residualmapsat160µm–500µm
Finland Grant No.127015. JMacknowledges the support fromVa¨isa¨la¨ foun-
Thequalityofthe B (T)νβ fitsandthemapsthemselvescanbe dation.Thispublication makesuseofdataproductsfromtheTwoMicronAll
ν Sky Survey, which is a joint project of the University of Massachusetts and
evaluatedbyexaminingtheresidualmapsatthefivewavelengths theInfraredProcessingandAnalysisCenter/CaliforniaInstituteofTechnology,
usedintheSEDfit.ThesemapsareshowninFigs.B.1–B.3. fundedbytheNationalAeronauticsandSpaceAdministrationandtheNational
In PCC288 the average residuals are −4.0, 16.9, 6.7, −6.3, ScienceFoundation.
and 1.4MJysr−1 in the five bands in the order of increasing
wavelength.Thecorrespondingvaluesare−0.35,2.4,2.4,−1.9,
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Fig.1. Three-colour figures of the three SDP fields. The red,
green, and blue colours correspond to the 250µm, 160µm,
and 100µm intensities (PCC288 and PCC249) or the 350µm,
250µm, and 160µm intensities (PCC550). Only the area cov-
ered by both the PACS and SPIRE instruments is shown. See
AppendixAforimagesoftheindividualbands.