Fundamental parameters, integrated RGB mass loss and dust production in the Galactic globular cluster 47 Tucanae

5.5 MB·English

by  Iain McDonald

Draftversion January7,2011
PreprinttypesetusingLATEXstyleemulateapjv.11/10/09
FUNDAMENTAL PARAMETERS, INTEGRATED RGB MASS LOSS AND DUST PRODUCTION IN THE
GALACTIC GLOBULAR CLUSTER 47 TUCANAE
I. McDonald1, M. L. Boyer2, J. Th. van Loon3, A. A. Zijlstra1, J. L. Hora4, B. Babler5, M. Block6, K. Gordon2,
M. Meade5, M. Meixner2, K. Misselt6, T. Robitaille4, M. Sewi lo2, B. Shiao2, B. Whitney2
Draft version January 7, 2011
ABSTRACT
Fundamental parameters and time-evolution of mass loss are investigated for post-main-sequence
1
starsin the Galactic globularcluster 47Tucanae (NGC 104). This is accomplishedby fitting spectral
1
energydistributions(SEDs)toexistingopticalandinfraredphotometryandspectroscopy,toproduce
0
2 atrueHertzsprung–Russelldiagram. We confirmthecluster’sdistanceasd=4611+−221030 pcandageas
12 1 Gyr. Horizontal branch models appear to confirm that no more RGB mass loss occurs in 47
n ±
Tuc than in the more-metal-poor ω Centauri, though difficulties arise due to inconsistencies between
a
the models. Using our SEDs, we identify those stars which exhibit infrared excess, finding excess
J
only among the brightest giants: dusty mass loss begins at a luminosity of 1000 L⊙, becoming
5 ∼
ubiquitous above L = 2000 L⊙. Recent claims of dust production around lower-luminosity giants

cannot be reproduced, despite using the same archival Spitzer imagery.
]
R Subject headings: stars: mass-loss— circumstellar matter — infrared: stars — stars: winds, outflows
S — globular clusters: individual (NGC 104) — stars: AGB and post-AGB
.
h
p 1. INTRODUCTION varies as a function of initial mass and metallicity
- (Fusi Pecci & Bellazzini1997;Lamers & Cassinelli1999;
o Circumstellardustproduction,andthevariationofits
Catelan 2000); whether dust can form efficiently around
r occurrence with a star’s fundamental parameters, must
st be understood if we are to gain insight into both Galac- RGB stars; at what evolutionary stage dust production
begins; and whether radiation pressure on oxygen-rich
a tic ecology and the history of the chemical enrichment
[ of the Universe. The dusty winds of asymptotic giant dustgrainsis sufficientto driveawind, especiallyatlow
metallicity (e.g. Lewis 1989), or whether chromospheric
branch(AGB)starsdominatetheproductionofinterstel-
1 (magneto-acoustic) driving or pulsation may also be
lardustatallredshiftsatwhichAGBstarsareobserved,
v important (Hartmann & MacGregor1980; Dupree et al.
and have therefore determined the chemical enrichment
5
1984; Woitke 2006; McDonald & van Loon 2007).
9 ofPopulationIstars,includingtheSunandSolarSystem
Globular clusters provide an excellent laboratory in
0 (Gehrz1989;Sedlmayr1994;Zinner2003;Valiante et al.
which we can examine these questions. They typically
1 2009). TheintegratedmasslossofRGBstarsdetermines
host a single or dominant population of stars at identi-
. theenvelopemassofastarleavingtheRGBtip. Itconse-
1 cal ages and metallicities, with sufficient number to be
quently determines its position on the horizontalbranch
0 statistically useful. Comparisons within globular clus-
(HB) and appears to be the major factor causing the
1 tersthereforeprobevariationswithevolution,whilecom-
‘second parameter’ (after metallicity) required to define
1 parisonsbetween globular clusters probe variationswith
HB morphology (e.g. Rood 1973; Catelan 2000). Mass
: metallicity and age. To provide a proper comparison,
v lossontheasymptoticgiantbrancheventuallyejectsthe
i star’sentirehydrogenenvelope,creatingapost-AGBstar it is vital to compare fundamental parameters of stars.
X These can be determined by comparing spectral energy
and (perhaps) a planetary nebula (PN).
r A number of factors hamper the quantitative exam- distributions(SEDs)tosyntheticspectrafromstellarat-
a mosphere models. This approach has the advantage of
ination of dust production. These including difficul-
allowing one to identify infrared excess, characteristic of
ties in determining outflow velocities in faint, metal-
dust production, in the SED.
poor stars; the difficulty in determining grain density
In this study, we examine the fundamental pa-
(or porosity), grain size and grain shape; the diffi-
rameters of stars in the globular cluster 47 Tu-
culty in identifying the mineralogy of grains being pro-
canae (NGC 104), one of the most-massive (6–
duced; even the difficulty in determining whether in-
frared excess is present at all. Open questions in- 9 105 M⊙; Scott & Rose 1975; Meylan & Mayor
×
clude how instantaneous and integrated RGB mass loss 1985; Mandushev et al. 1991) and nearest ( 4500 pc;
≈
Harris 1996; Percival et al. 2002; McLaughlin et al.
1JodrellBankCentreforAstrophysics,AlanTuringBuilding, 2006; Salaris et al. 2007) Galactic globular clusters,
Manchester, M139PL,UK;[email protected] with a metallicity of [Fe/H] –0.7 (Harris 1996;
2STScI,3700SanMartinDrive,Baltimore,MD21218, USA Carretta & Gratton1997;McWil≈liam & Bernstein2008;
3Lennard-JonesLaboratories,KeeleUniversity,ST55BG,UK Worley et al. 2010) and interstellar reddening of E(B
4Harvard-Smithsonian Center for Astrophysics, 60 Garden −
V)=0.04mag(Harris1996). Throughoutthispaper,we
Street, MS65,Cambridge,MA02138-1516, USA
5Department of Astronomy, University of Wisconsin, Madi- willrefertotwosimilarstudies: McDonald et al.(2009),
son,475NorthCharterStreet,Madison,WI53706-1582, USA which covers the cluster ω Centauri (NGC 5139; here-
6Steward Observatory, University of Arizona, 933 North after Paper I); and Boyer et al. (2009), which covers the
CherryAvenue,Tuscon,AZ85721,USA
2 McDonald et al.
-71.6 photometric data used in the SEDs come from a vari-
ety of different sources covering different fields of view.
These data are summarised in Figure 1 and Table 1.
-71.8 Stetson (optical) They include data taken with the Spitzer Space Tele-
scope’s (Werner et al.2004)fourInfraredArrayCamera
Salaris (near-IR)
g) (IRAC; Fazio et al. 2004) bands, at 3.6, 4.5, 5.8 and 8
de -72 Origlia µm from the Surveying the Agents of Galaxy Evolution
on ( SAGE + MCPS (Spitzer IRAC) in the Small Magellanic Cloud (SAGE-SMC) program
ati (Gordon et al. 2009). At the distance of 47 Tuc, the
n
cli-72.2 1.66–1.98′′ full-width at half-maximum (FWHM) of the
e
D Barmby point spread function (PSF) of IRAC provides a resolu-
(Spitzer MIPS)
tion of 0.036–0.043 pc, with a dynamic range sufficient
-72.4
to detect the cluster’s HB stars. Further IRAC data of
the cluster core were presented in Origlia et al. (2007)
SAGE (no MCPS)
-72.6 (Spitzer PID20298; PI: R. Rood). Here, we use the re-
8 7.5 7 6.5 6 5.5 5 4.5 analysed data from Boyer et al. (2010). For this second
Right Ascension (deg) IRACdataset,weusedthe“deep”photometrywhen[3.6]
Fig. 1.—Spatialcoverageofthesurveysusedinthispaper. See > 11 mag, and the “shallow” photometry otherwise.
textfordetailsofeachsurvey. Thecrossmarkstheclustercentre. Longer-wavelength 24-µm data was sourced from the
Multiband Imaging Photometer for Spitzer (MIPS;
cluster NGC 362 (hereafter Paper II).
Rieke et al.2004)datafromBarmby et al.(2009),asthe
Dust production in 47 Tuc is of particular interest
SAGE-SMC MIPS data do not cover the cluster.
due to the study of Origlia et al. (2007). This study
Near-IR JHKs-band photometry for the entire clus-
has claimed observational evidence of dust production
ter was taken from the 2-µm All Sky Survey (2MASS;
along the entire RGB, in contrast to the observations of
Skrutskie et al. 2006). The 2MASS image near the clus-
other clusters (e.g. ω Cen; Paper I). If this claim can be
ter core is heavily blended, and the recorded photo-
confirmed, it significantly increases the number of stars
metric fluxes are artificially raised by blending of both
we know of that are returning dust to the interstellar
partially-resolvedand unresolved stars. To solve this is-
medium. This would be particularly important at high
sue, we preferentially used the JHKs-band photometry
(z 6) redshift, where AGB stars remain the dominant
∼ fromSalaris et al.(2007) over2MASS. These data cover
dust producers, but cannot account for a galaxy’s en- a 4.′9 4.′9 region around the cluster core. These data
tiredustbudget(Valiante et al.2009). Suchclaimsmust are of×substantially better resolution (< 0′.′9) and con-
therefore be taken seriously and examined carefully. An
sequentlysufferless fromsourceconfusionandblending.
analysis of the Origlia et al. claim was undertaken by
The“deep”Salarisphotometrywasusedinpreferenceto
Boyer et al. (2010), who raise concern that apparently-
the “shallow” when Ks > 12.5 mag. Some stars, in the
red stellar colours may be a result of stellar blending in
southernhalfoftheclustercore,werenotcoveredbythe
the densely populated cluster core (∼50000 M⊙ pc−3 Salaris data: many of these therefore have abnormally
— Gebhardt & Fischer 1995) and data artifacts due to
high 2MASS fluxes, and therefore scatter to higher lu-
saturation of the brightest stars. Origlia et al. (2010)
minosities. Here they can be confused with AGB stars,
defended their original hypothesis, suggesting that this
though they typically lie slightly above the AGB branch
dust is too warm to present considerable reddening of
(their locus lies on the dividing line between regions (1)
the [3.6]–[8]colour,but does present considerable excess
and (2) in the HRD shown later).
in Ks–[8]. One of our aims herein must therefore be to The mid-IR Spitzer photometry is complemented by
examine this issue in more depth.
optical data from the Magellanic Clouds Photometric
This paper follows a similar approachto Paper I. Sec-
Survey (MCPS; Zaritsky et al. 2002), which contains
tion 2 details the photometric data we use, its sources
JohnsonUBV-bandandGunni-bandphotometryofthe
and its reduction; determination of stellar parameters
region. Onceagain,thisonlycoversthesouth-eastofthe
forthe cluster’sstarsby fitting theirspectralenergydis-
cluster. To cover the remainder of the cluster, we used
tributions (SEDs); and the creation of a Hertzsprung–
the Johnson UBV-band and Cousins IC-band photom-
Russell diagram (HRD). Section 3 covers the fitting of
etry of Salaris et al. (2007), and the Johnson UBVIJ-
stellar isochrones to the HRD. In Section 4, we derive
band7 photometry of Stetson (2000).
mid-infrared (mid-IR) excesses for our stars, based on
our SEDs, and use these to determine which stars are 2.2. Creation of a master catalogue
dustyandcomparethemtothoseinOriglia et al.(2007).
These data were combined using dao-
The mass-lossratesanddust compositionsofthese stars
match/daomaster (Stetson 1993) and objects
are analysed in an accompanying work (Paper IV).
detected in only one filter (assumed to be bad data)
2. DATAREDUCTION were dropped. The final source list contains photometry
for 104153 stars located within 30′ of the cluster core
2.1. The input data (00h24m05.2s –72◦04′51′′ — Harris 1996).
Fromthis source list, a subset of sources were selected
which had enough photometry to determine their tem-
As 47 Tuc covers a large area on the sky (its tidal ra-
dius is 43′; Harris 1996), a uniform set of photometric 7 We refer to the Johnson I band as IJ throughout to avoid
data is not available for every star in the cluster. The confusionwiththeotherI-banddatainthiswork.
Fundamental parameters and dust production in 47 Tuc 3
TABLE 1
Inputphotometricdataandtheir coverageof the cluster.
Wavelength Source Coverage
UBVi MCPS;Zaritskyetal.(2002) Westofcluster,avoidscore
UBVIC Stetson(2000) ∼20′×20′ aroundcore
UBVIJJHKs Salarisetal.(2007) Northerntwo-thirdsofcore
JHKs 2MASS;Skrutskieetal.(2006) Entirecluster
3.6–8µm1 SAGE-SMC;(Gordonetal.,inprep.) South-westofcluster,notincludingcore
3.6–8µm Origliaetal.(2007)2 Clustercore&immediatewest&east
24µm3 Barmbyetal.(2009) Clustercore&immediatesouth-west
1Spitzer IRACat3.6,4.5,5.8and8µm;Fazioetal.(2004).
2Weusethere-analyseddataofBoyeretal.(2010).
3Spitzer MIPS;Riekeetal.(2004).
it does better account for the 10-µm interstellar absorp-
TABLE 2
Adopted centralwavelengthsandzeropoints for the tion peak. This can affect the mass-loss rates we derive,
photometric filtersused. though is unlikely to be significant for the small extinc-
tion toward the cluster.
Filter Centralwavelength Zeropoint
Obtaining the correctfilter transmissionsis important
(nm) (Jy)
when obtaining accurate stellar parameters. Differences
U 350 1659
can occur in the transmission efficiency of the filter it-
B 442 4130
self,theCCD,thetelescopeand(particularly)theatmo-
V 550 3810
i 786 2427 sphere. Wecantestwhetherourfiltertransmissionsand
IC 810 2520 stellaratmospheremodels arecorrectbyplottingthe ra-
IJ 880 2635 tio of the observed flux to the flux of our stellar model
J 1240 1602 foreachstar(Figure2),whichisverysensitivetoerrors.
H 1650 1010 Incorrect zero points for a particular magnitude system
Ks 2160 630 manifest themselves as global offsets from unity. Incor-
[3.6] 3600 280.9 rect filter transmissions lead to a very strong tempera-
[4.5] 4500 179.7 ture dependance in the above ratio. We list the adopted
[5.8] 5800 115.0
zero points in Table 2, which gives the approximate cor-
[8] 8000 64.13
responding wavelengths for each filter for reference.
[24] 24000 7.14
Errorsinonebandwillpropagatethemselvesinreverse
peratures and luminosities by fitting their SEDs. We onto neighbouring bands, making identifying sources of
selected stars with at least four photometric bands with error difficult. Such issues exist for the very hottest
flux measurements, the bluest of which must be in the and coolest (most-luminous) stars (>6500 K and <3900
optical(I-bandorshorterwavelength)andthereddestof K, respectively). At low temperatures, dynamic atmo-
whichmustbeintheIR(Ks-bandorlongerwavelength). spheric processes and incomplete molecular opacities in
This reduced the source list to 47727 stars with usable our model atmospheres introduce variations from the
photometry. model. Conversely,athightemperatures,ourmodelsare
limitedto6500Kanddonotcovertheveryhotteststars.
2.3. The data reduction process StarsoffsetinFigure2inallbandsmayalsobeGalactic
foregroundorbackgroundSMCfieldstars. Thesearenot
well modelled as their metallicities and surface gravities
are substantially different from those of the cluster.
SEDs were created following the method used in Pa-
SeveralothersystematicsarevisibleinFigure2. These
pers I and II. Briefly, this involves comparing broad-
include:
band photometry to artificially-dereddened model spec-
tra whichhavebeen convolvedto the photometricfilters
Quantisationerrorsamongthelowest-luminositystars,
ofthe observations. Here,we againuse the marcs mod- •
which manifest themselves as fan-shaped spreads visi-
elsofPaperI(see alsoGustafsson et al.1975,2008). In-
bleintheU and8-µmfilters,butarenegligibleamong
terpolating between these models determines the stellar
the hottest stars.
temperature,andthemultiplicationofthemodelfluxre-
quired to match the observedflux determines the stellar Poorconvergenceof models around6250K. This only
luminosity. We initially assume that the distance and • affectsthe hotterstarswhichhavenomid-IRphotom-
reddening to 47 Tuc are 4500 pc and E(B V) = 0.04 etry, for which we cannot therefore determine mid-IR
−
mag, respectively. We later show by isochrone fitting excess.
that these values are indeed appropriate ( 3).
§
We have revised the process used in Papers I and II Increased scatter in the HB stars around 50 L⊙. This
to better accountfor interstellarreddening. This follows • is due to unknown processes (though could indicate
thesameprocedureasinMcDonald et al.(2010),namely an abundance spread) and does not affect any giant
that we use the absorptionprofiles ofMcClure (2009) to branch dust producers.
obtain Aλ/AKs, assuming that AV = 3.2E(B V) and
−
that A /A = 7.75. While the change in process does Small ( 1%) remaining systematic under- or over-
V Ks
• ∼
not significantly affect the stellar parameters we derive, estimates of flux in several filters. The colour-based
4 McDonald et al.
5000
U B V Ig Ic
1000
100
10
c
p
k Ij J H Ks
5
4.
at
) O•
L
y (
sit
o
n
mi
u
L 5000
[3.6] [4.5] [5.8] [8] [24]
1000
100
10
0.5 1 1.5 0.5 1 1.5
[Observed / modelled] flux
7000
6000
5000
4000
3000 U B V Ig Ic
K)
e (
ur
at
er
p
m
e
T
Ij J H Ks
7000
6000
5000
4000
3000 [3.6] [4.5] [5.8] [8] [24]
0.5 1 1.5 0.5 1 1.5
[Observed / modelled] flux
Fig. 2.— Differences between observed and SED-fitted model fluxes as a function of luminosity (top panels) and temperature (bottom
panels,whereonlystarswithL>5L⊙ areshown).
Fundamental parameters and dust production in 47 Tuc 5
Stellar parametersasdeTtAeBrmLEine3d by SEDfitting. Afull 11001200 12515 111001680000 12515
1000 1040
electronictableis availableonline. 990 1020
1000
980 980
Sequence RA(deg) Dec(deg) Temperature Luminosity 970 960
940
Number (J2000) (J2000) (K) (L⊙) 960 920
1 4.641571 –72.328035 6147 258.4 950 900
3930 3920 3910 3900 40003950390038503800
2 4.685675 –72.365643 4449 56.53
330 340
3 4.706252 –72.387843 5399 1.625 335
9352 9352
4 4.722603 –72.374671 4500 1.228 325 330
···5 4.72··5·042 –72.3··6·6471 5·3·0·8 1.·0·5·7 5 kpc5 kpc 320 333122505
4.4. 315 310
ddeetteeccttiioonncorfitIeRrioenxcweessusine (s§u4c)harceascehso,sbenuttothmeaaxmimpilsie- ) at ) at O•O•3104280 4260 4240 33000545004400430042004100
tmuadge(o&f1t0h%es)eexeffceescstessiwsemaurcehlosomkianlglerfotrh.an the >0.1 sity (Lsity (L 190 4929 222234000 4929
oo 210
We therefore do not expect these systematics to affect minmin 185 129000
our detection of circumstellar dust. uu 180
LL 170
Problemscausedby unresolvedblending in the cluster 160
180 150
corearevisibleinseveralbands. Asnotedintheprevious
4580 4560 4540 4700 4600 4500 4400
section, this is a particular concern in the 2MASS data, 185 220
where there is considerably more scatter in the fitted 8937 210 8937
180 200
parameters and observed:expected flux ratios.
190
Table 3 contains the list of stellar parameters deter- 175 180
mined for the stars. 170 170
160
165 150
4360 4340 4320 4300 4500 4400 4300 4200
2.4. Accuracy of the fits TTeemmppeerraattuurree ((KK))
2.4.1. Analysis of departures from the models 63 65
64
62 19514 63 19514
61 62
As noted in 2.3, the goodness-of-fit of our SED mod- 60 6601
59 59
els depends str§ongly on the zero points and filter trans- 58 58
57
missions used. While Figure 2 shows that the models 57 56
agree well with the observations between temperatures 54005350530052505200 55005400530052005100
of 3900 and 6500 K, stars lying outside of this range 63 61
are subject to some error. To assess the magnitude of 62 28472 28472
cc 61 60
this error, a representative selection of stars was taken kpkp 60
and the data from the most-affected filters (U, B and 5 5 59 59
oaIJntu)rtweheerrasentergleelmar3o9vt0ee0md–.p6e5Tr0ah0tisuKrhe,aswdoiftahtnhteeegmlsitgpaierbrslaetinu(<rteh5seKcht)eamneffgpieencrgt- L) at 4.L) at 4.O•O• 557853005250520051505100 585250 5200 5150 5100
slightly more for stars outside this range. The coolest y (y ( 46 47
stars have temperature uncertainties caused by poorly- ositosit 45 15423 46 15423
matchingmodelsofordertensofdegrees,butthesestars minmin 45
are also strongly variable. Any ‘instantaneous’ measure LuLu 44 44
oftemperaturesuchasthis willthereforenotnecessarily
43 43
berepresentativeofthemeanstellartemperaturetothis
4850 4800 4750 4900 4800 4700 4600
degree of accuracy.
5.5 6
Aformalestimateoftheerrormaybecalculatedusing
40122 40122
‘simulated’ observations using the Monte-Carlo method, 5.5
whereby the flux in each band is set to be the observed 5
value plus-or-minus an error sampled from a Gaussian 5
probability distribution with σ identical to the reported
4.5 4.5
photometric error. This suffers two problems: (1) it
6300 6250 6200 6150 65006400630062006100
would take prohibitively long to perform this test for
every star and (2) it only takes into account the photo- TTeemmppeerraattuurree ((KK))
metric error,not the modelling error. We have therefore
Fig.3.— Monte-Carlo fitting results, showing (left) photomet-
selected a small sample of stars from across the HRD,
ricerrorsonlyand(right)errorsderivedfromdeparturesfromthe
andperformedMonte-Carlosimulationstodeterminethe model. Red bars show the 1-D standard deviations of the distri-
errorsintheirparameters. Wedothistwice: thefirstac- butions. Labelsdenotesequencenumbersoftheobjects(Table3),
countsforonlythephotometricerror,asdescribedabove; chosentoberepresentativeoftheirrespectivepartsoftheHRD.
6 McDonald et al.
TABLE 4
Starschosen forMonte-Carlo simulations.
Sequence RA(deg) Dec(deg) Temperature1 Luminosity1 Coverage Notes
Number (J2000) (J2000) (K) (L⊙)
12515 5.9604583 –72.0725000 3916±4 ±25 982±11 ±35 B−[24] UpperRGB/AGB
9352 5.9282500 –72.1920278 4265±5 ±55 316±3 ±7.2 B−Ks CentralRGB/AGB
4929 5.7577500 –72.1565278 4567±6 ±59 184±1.4 ±16 B−[8] LowerAGB
8937 5.9237083 –72.0840556 4329±10±65 175±3 ±11 B−[24] RGB
19514 6.0277917 –72.0754167 5283±30±80 60.0±0.7 ±1.7 B−Ks HB(core)
28472 6.1138333 –72.0774722 5191±27±18 59.8±1.0 ±0.5 B−Ks HB(notcore)
15423 5.9881250 –71.9649722 4782±10±36 45.0±0.4 ±0.6 B−Ks RGBclump
40122 6.5137500 –72.2503611 6250±13±56 5.05±0.06±0.18 B−[4.5] MSTO
1Firsterrorencompassesphotometricerrors,seconderrorencompasses modellingerrors.
the secondreplacesthe Gaussianσ withthe deviationof atures also agreewithin errors,averaging47 K (1.3%)
the observations from the model. cooler in our SED fits (st. dev. 311 K).
The starswithwhich weperformthis test arelistedin
Table4andtheresultsareshowninFigure3. Itisfirstly Koch & McWilliam(2008) —eightcentralRGB stars
•
clear that the temperature and luminosity we derive are (4200–4500 K), individual temperatures differ at the
interdependent: spreadalongtheRGBtrackappearsde- 2σ level. As a whole, the stars average 25 K (0.6%)
termined primarily by errors in the optical data, while warmer in our SED fits, smaller than the standard
spread perpendicular to the RGB track appears deter- deviation of the differences between the two papers
mined primarily by errorsin the IR data. It is also clear (31 K).
thatthephotometricerrorsareconsiderablylessthanthe
Worley et al. (2010) — five of the spectra used in
total error as estimated by differences between the ob- •
McDonald & van Loon (2007), individual tempera-
servationsandstellar atmosphere models. As we note in
tures differ at the 4σ level, averaging 231 K (6.1%)
4.1, this is probably due to under-reported errors due
§ cooler in our SED fits (st. dev. 108 K).
to image artifacts and blending from sources within a
few arcseconds. In the right-handpanels of Figure 3, we The exceptionally low standard deviation of the
note that those stars with no data longwardof Ks-band Koch & McWilliam(2008)temperaturesprovidesagood
havesignificantlymorescatterperpendiculartothegiant check of the accuracy of both our measurements and
branch: Spitzer dataarethereforecrucialindetermining theirs. It is worth noting that the discrepancy between
accurate stellar parameters, even for warm stars. our results and those of Carretta et al. (2004) lies in the
Varyingastar’sfundamentalparameterscanalsohave accuracy of our photometry, not their spectroscopic de-
an effect on the values we achieve. Likely variations for terminations. A systematic offset between our SED fit-
bona fide 47 Tuc cluster members are somewhat smaller ting and conventional spectroscopic techniques is likely
than the corresponding errors in temperature or lumi- limited to <30 K (<0.7%)in temperature and <2.8%in
nosity caused by inaccuracies in the model, which are luminosity.
of order 1–2% for temperature and 2–9% in luminosity.
By varying [Fe/H] between solar and –1.4 we produced 2.5. The Hertzsprung–Russell diagram
differences of similar magnitude, varying the mass from
Havingdeterminedthestellarparametersfortheabove
0.6–1.0 M⊙ produced differences of order 0.3% in lumi- objects, the data were then compiled into an HRD, pre-
nosity, and varying E(B V) between 0 and 0.12 mag
− sented in Figure 4.
produced luminosity changes of <5%. The largest un-
The HRD shows a number of features, mostly iden-
certainty, at least in terms of luminosity, appears to be
tifying our target stars as post-main-sequence stars in
in the distance to the cluster.
47 Tuc. Also visible on the HRD is a background se-
quence of stars belonging to the SMC (13). This merges
2.4.2. Comparison with other works
with the main sequence (MS) of 47 Tuc at roughly the
In order to determine the accuracy of our SED luminosity where the SMC’s HB and red clump would
fits, we compare our temperatures with a number of be. Regions (9) and (14) contain foreground and back-
spectroscopically-derivedtemperatures. We do notcom- ground objects of indeterminate distance. Typically, we
paretheluminosities,asthefittingproceduremeansthat would expect region (9) to contain stars in the Galactic
the luminosity is directly determined fromthe model af- disc (47 Tuc lies at Galactic co-ordinates l = 305.90◦,
ter the temperature fit has been made. The resulting b = 44.89◦ — Harris 1996) and region (14) to contain
−
discrepancies are listed below: backgroundgalaxies(Boyer et al.2008; PaperI). In this
particularsample,however,region(14)mayalsocontain
Carretta et al.(2004)—nineearly-RGBstars( 5100 some SMC young stellar objects (YSOs) and cool main
• ≈
K),temperaturesagreewithin errors: onaveragethey sequence objects. We do not expect many YSOs, how-
are 21 K (0.4%) warmer in our SED fits than their ever, as our region of interest lies away from the bulk
spectroscopictemperatures,cf.108Kforthestandard of the galaxy’s star-forming regions. The main sequence
deviation of the temperature differences. starsatthistemperaturearemostlybelowthesensitivity
threshold of our data.
McDonald & van Loon (2007) — nine upper Verticalartifactsarealsovisibleonthediagram. These
•
RGB/AGB stars (<4000 K, >1100 L⊙), temper- occur every 250 K and correspond to the temperature
Fundamental parameters and dust production in 47 Tuc 7
10000
1000 (1) Post-AGB candidates
(2) Evolved AGB candidates
(3) Upper RGB/AGB
pc (4) Early-AGB (5) Central RGB
k
4.5 100
at (13) SMC
) O• (6) E-HB (7) HB (8) RGB Bump
L
y ( ( E10a)r ly
sit (9) Field stars RGB (9) Field stars
no 10
mi (14) Galaxies
u
L (11) MSTO
1
(12) MS
0.1
7000 6500 6000 5500 5000 4500 4000 3500 3000
Temperature (K)
10000
1000
c
p
k
4.5 100
at
) O•
L
y (
sit
no 10
mi
u
L
1
0.1
7000 6500 6000 5500 5000 4500 4000 3500 3000
Temperature (K)
Fig.4.— HRD of stars in the direction of 47 Tuc, showing evolutionary and spatial components. The top panel contains all stars, the
bottom panel contains only stars more than 2′ from the cluster core, which have photometric data in the optical, near-IR and mid-IR.
Abbreviationsarediscussedinthetext.
8 McDonald et al.
grid of our model spectra. They are generally caused by
poor-qualityoptical photometry in low-luminosity stars. 1000
Especially important are discrepancies between the ob- c
p
served U- and B-band photometry and those predicted 5 k
by the marcs model spectra, hence the increasedpreva- 4.
lenceofartifactsathighertemperatureswheremoreflux at 100
isemittedinU andB. Asourmodelsonlyextendto6500 ) O•
L
K,wemustassumethatstarswithtemperaturesderived y (
tobe&6500Khaveprogressivelymore-uncertainparam- osit 10
eters. We have therefore limited our study to stars with n
mi
T 7000 K, of which there are 46398. u
≤ L
Several important evolutionary points (numbered in
Figure4)canbenotedatthis point,whichweuseinthe 1

next section to fit stellar isochrone models. These are:
the main-sequence turnoff (MSTO; 11 in Figure 4), the
start of the RGB (10), the RGB bump (8), the upper 1000
c
RGB (5), the RGB tip (top of (2)), the base of the HB kp
(bottomof(7))andthestartoftheAGB(bottomof(4)). 4.5
Areviewoftheseevolutionaryprocesses,withparticular at 100
emphasisonglobularclusters,canbefoundinMcDonald ) O•
L
(2009). y (
CircumstellardustreprocessesopticallightintotheIR, sit 10
causinganapparentcoolingofthestar’seffectivetemper- no
ature. ThismovesthestartotherightontheHRD,mov- mi
u
ing into region (2). Throughout their time on the RGB, L
starslosemassthroughstellarwinds. Forthemajorityof 1
the time, these appear to be dustless winds driven from
the chromosphere (McDonald & van Loon 2007; Paper 6500 6000 5500 5000 4500 4000 3500
I),butiftheIRexcessesreportedbyOriglia et al.(2007) Temperature (K)
aretrue,wemayseesomelow-luminositystarsinthisre-
Fig.5.—Toppanel: PadovaisochronesgeneratedusingtheCMD
gion by virtue of their circumstellar dust. This issue is
utility,overlaidonadensity-mappedHRD.Bottompanel: Padova
confused, however, by the presence of field stars, and of isochrones generated using the YZVAR utility. Arrows show the
stars with poorly-determined photometry. locations of the RGB bumps of the isochrones. Details of the
Our HRD contains a well-denoted and well-separated isochrones’parameterscanbefoundin§3.1.
early-AGB. By its very nature, however, the AGB helium fraction and α-element enhancement. The accu-
asymptoticallyapproachestheRGB,andthetwobecome racy of this determination depends both on the system-
indistinguishable above 300 L⊙. More-rapid evolution atic errorspresent in our data ( 2.4), and the validity of
on the AGB means that∼there are 4–5 times more stars the assumptions we make. To§minimise systematic er-
per unit luminosity on the RGB than AGB. rors,wehaveusedthe‘cleaned’subsetofstarspresented
HeliumfusionontheupperAGBalsobecomesincreas- inthe bottompanelofFigure4,tothe exclusionofstars
inglyvolatile: itsviolencecanincreaseastar’sluminosity withpoorphotometryandthoseintheimmediatecluster
dramatically(uptoafactorofseveral)forashortperiod core.
of time (102 103 years), termed a thermal pulse (TP; In this study, we compare our HRD to two sets of
∼
e.g. Zijlstra 1995; Wachter et al. 2008). Such stars may isochrones, both of which were used in Paper I. These
scatterabovethemaingiantbranchintheHRD,intore- are namely the Padova isochrones (Marigo et al. 2008;
gion (1), but this area is confused by normal AGB stars Bertelli et al. 2008)8 and the Dartmouth isochrones
with poor photometry. (Dotter et al. 2008)9.
Stars on the TP-AGB are also unstable to pulsation The CMD interface for the Padova isochrones
via the κ-mechanism (Ulmschneider 1998), where har- (Marigo et al. 2008) does not allow the user to change
monicoscillationsarestochasticallyexcited. Thiscauses either the helium content or α-enrichment of the
semi-regular variability at first, then more-regular and isochrones. The YZVAR interface (Bertelli et al. 2008),
increasingly-violent pulsation until the AGB tip, where however,allows both the helium content and a Reimers-
the stellar atmosphere disperses. This variability will law mass-loss rate (Reimers 1975) to be varied by the
cause some horizontal and vertical scatter of these stars user, though also does not allow the α-enrichment to be
in the HRD, as we typically only use one epoch of pho- varied. In this regard, we have simply adopted a fixed
tometry for every filter. metal content, [Z/H], and assumed that metals scale as
solar values. The Dartmouth models allow the variation
3. ISOCHRONEFITTING of both helium and α-enrichment in fixed steps.
3.1. Introduction Alteringtheaboveparametershasthefollowingeffects:
By fitting stellar isochrones to our data, we can re- Increasing the helium content of the isochrones steep-
determinethebasicparametersfortheclusterasawhole, •
namely its distance, reddening and age. To do this, we 8 http://stev.oapd.inaf.it/cgi-bin/cmd
must make assumptions about the cluster’s metallicity, 9 http://stellar.dartmouth.edu/∼models/webtools.html
Fundamental parameters and dust production in 47 Tuc 9
Metallicity: [Z/H] = [Fe/H] = –0.7;
•
1000 Heliumfraction: Y =24% Y⊙(Dorman et al.1989);
c • ≈
p
k α-enrichment: [α/Fe] +0.2 dex (Dartmouth
5 • ≈
4. isochrones only);
) at O•100 • Distance: d = 4.5 kpc;
y (L • Reddening: E(B−V) = 0.04 mag; AV = 0.124 mag;
nosit 10 ARg=e:3t.1=; 12.5 1.2 Gyr.
mi • ±1.4
u
L Isochrones using these parameters are shown in Figures
1 5 and 6. It is clear from these figures that the best-
fitting isochrone is that of the Dartmouth models, but
at the adopted value of [α/Fe] = 0. This provides a
1000 remarkably-good fit to the data. The only exception to
c
p this is on the upper RGB, above the red clump, where
k
5 the [α/Fe] = +0.2 model fits better (see also later, in
at 4. 100 Figure 9). An increase in α-element abundances follow-
) O• ing first dredge-upis notexpected, as the stars have not
L begun helium burning. It could, however, be explained
osity ( 10 iufpe,xatnradmifisxuinchg monixtihnegRalGteBrsotchceurssurafraocuencdhefimrsitstdryre(deg.ge-.
n
mi D’Antona & Ventura 2007; Karakas et al. 2010, and ref-
Lu erences therein). This effect is shown in more detail in
1 3.2.5. Note that the Padova isochrones, which qualita-
§
tively fit the upper giant branches and MSTO, are also
6500 6000 5500 5000 4500 4000 3500 for [α/Fe] = 0.
Temperature (K)
3.2. Cluster parameters
Fig.6.—AsFigure5fortheDartmouthisochrones. Toppanel:
isochrones at [α/Fe] = 0. Bottom panel: isochrones at [α/Fe] = 3.2.1. Metallicity and abundances
+0.2. Themetallicityandabundanceof47Tuc’sstarsisbet-
enstheslopeoftheRGB,thoughtheRGBtipstaysin ter determined from spectroscopic studies of individual
roughly the same place. It also causes an increase in starsthanfromourHRD(see 2.4.2forsuchstudies). As
§
the luminosity difference between the MSTO and the noted,however,thebest-fittingisochronerequires[α/Fe]
start of the RGB. = 0. To fit the Padova isochrones by changing the α-
enhancement (which roughly corresponds to moving the
Increasingtheα-enrichmentacceleratesMSTO,mean- isochrone horizontally in the HRD) requires [α/Fe] < 0.
•
ingthispointcorrespondstolowerluminosities. Italso For the purposes of isochrone fitting, we have proceeded
shifts the entire isochrone to cooler temperatures and under the assumption that there is no α-element enrich-
increases the luminosity of the RGB bump. ment compared to solar values.
Increasing the metallicity of the isochrones will shift
3.2.2. Reddening
•
themtocoolertemperatures,asstrongerphotospheric
lines make the atmosphere more opaque. The de-reddening of the cluster we apply can be al-
tered using the relations listed in Paper I. This gives an
Increasing the fitted distance of the cluster will shift approximate solution for different values of E(B V)
• −
theisochronestowardhigherluminositieswithrespect withoutthe needto re-analysethe entire dataset. Based
to the stars. againontheDartmouth[α/Fe]isochrones,wefindagree-
ment with the accepted value of E(B V) 0.04 mag
Ifthe cluster’sreddeningis higher,we willhavethere- (Harris 1996). − ≈
•
fore underestimated the de-reddening correction: fur-
ther correction then requires the stars to move to 3.2.3. Age and distance
higher temperatures and luminosities with respect to
Oncethe metallicity,abundancesandreddeningofthe
the isochrones. This does not affect all stars equally,
starshavebeenset,the agecanprimarilybe determined
and hotter stars will require larger corrections than
from the temperature of the MSTO. This is vertically
cooler stars, with the result that the HRD becomes
scaled to match the luminosity of the MSTO/RGB base
horizontally stretched and vertically skewed (see Pa-
at 5500 K. The parameters of age and distance are thus
per I for the way this is treated).
anti-correlated.
The cluster’s age affects the isochrones in a number AsshowninFigure7,isochronesfor12 1Gyrfitthe
• of ways,with the largestalterations being in the posi- datawell. Anincomplete stellarcatalogue±ofobjects be-
tioning of the MSTO and base of the RGB. low 1 L⊙ means that the models will fit progressively
∼
less well below this luminosity. Isochrones are plotted
We initially assumed the following parameters: fordistancesof4783,4611and4456pc for11,12and13
10 McDonald et al.
5
200
4
c
p
4.5 k 3 pc 150
at 5 k
y (L) O• 2 ) at 4.O• 1 9000 [α/Fe] = 0 +0.2
osit y (L 80
min osit 70
Lu 1 min 60 0 +0.2
0.9 u
0.8 L
50
0.7
0.95 M 0.95 M
6400 6200 6000 5800 5600 5400 5200 5000 40 0.08.59 0M MO•O•0.08.59 0M MO•O•
O• O•
Temperature (K)
5600 5400 5200 5000 4800 4600 4400
Fig. 7.—As Figure6, showing Dartmouth isochrones at [α/Fe] Temperature (K)
= 0, covering the MSTO. Isochrones are placed at 11, 12 and 13
Gyr. Fig.9.—TheupperRGB,HBandAGBof47Tuc(small,black
dots). These are overlain with Dartmouth RGB isochrones (blue
dashedlines)at[α/Fe]=0(left)and+0.2(right),andwithsimilar
HBmodels(large,coloureddots). Inorderofincreasingluminosity,
10000
theHBtracks areforstellarmassesof0.85,0.90and0.95M⊙.
s
ar 1000 200
st
of
er 150
b
m c
u 100 p
Cumulative n 10 y (L) at 4.5 kO• 1 890000
sit 70
o
n
mi 60
1 u
100 1000 L
50
Luminosity (L ) at 4.5 kpc
O• 0.75 M
O•
40 0.65 MO• 0.70 MO•
Fig. 8.— The luminosity function for 47 Tuc (solid, red line),
along with theoretical Pisa isochrones. Lower, short-dashed line 5600 5400 5200 5000 4800 4600 4400
(blue): AGB andHB starsonly. Upper,long-dashed line(green): Temperature (K)
AGB/HB+RGBstars.
Fig.10.—AsFig.9,butwithPisaHBmodelsat(left-to-right)
Gyr, respectively. Adding in the 2.8% systematic lumi-
0.65,0.70and0.75M⊙.
nosity uncertainty in luminosity ( 2.4.2), this equates to
§
a distance of 4611 +−221030 pc. thedata. Thedeparturebetween60and100L⊙ isprob-
Bothsets(CMD&YZVAR)ofPadovaisochronesyield ablydue tocontaminationfromfieldstarsandscatterin
similar constraints on age. The distances implied for theHRDfrompoorphotometry. Thefactthatwedonot
theseisochronesareapproximately4%(180pc)lessthan find as many HB stars at 50 L⊙ as the models predict
≈
for the Dartmouth isochrones. suggestthat either we do not have a complete sample of
all HB stars, or that some of the HB stars have already
3.2.4. Luminosity function been ejected from the cluster due to mass segregation
(cf. HB lifetime 190 Myr; core relaxation time 91
Figure8showstheobservedandtheoreticalluminosity
≈ ≈
Myr; Harris 1996). This is not readily visible in radial
functions of 47 Tuc. The observed luminosity function
density plots of our sources due to the differing depths
is derived from all stars below 6000 K and 4200 L⊙ (to
of the original surveys we used.
include the dusty long-period variable star 47 Tuc V1,
butexcludeknownfieldstars)whichdonotfallinregion
3.2.5. HB mass via isochrone fitting
13(SMC)oftheHRD.Thetheoreticalisochroneusesthe
Pisa stellar evolution models for a 0.90 M⊙ RGB and a The amount of mass lost on the RGB can be deter-
0.65 M⊙ AGB star. The isochrones have been scaled to minedby measuringthe difference betweenthe RGB-tip
one star for every80000 yearsofevolution. It should be stars’initialmassesandthemassofstarsontheHB.The
noted that the AGB models terminate at 1550 L⊙: we age of the stars means we can neglect mass loss during
haveextrapolatedtheminFigure8toestimatethatthere the comparatively short ( 1.8 Myr; Silva Aguirre et al.
∼
are some 8 2 AGB stars above the theoretical RGB tip 2010) evolutionary period between the RGB-tip and
±
at 2780 L⊙. zero-ageHB. Initial massesfor isochronesat 12 1 Gyr
±
Overall,the luminosity function provides a good fit to are: