Transcript Model SEDs of Massive YSOs

Radiative Transfer Models
of Dusty YSOs
Barbara Whitney (Space Science Institute),
Tom Robitaille & Kenny Wood (St. Andrews
University), Jon Bjorkman (U. Toledo), Remy
Indebetouw (U Va), Ed Churchwell (UW)
Outline
• Background and Motivation
– Large Volumes of mid-IR data now available from
Spitzer Space Telescope, ground-based
observatories and future space-based
• e.g., the GLIMPSE survey of the inner Galactic Plane
– Unanswered questions
•
•
•
•
2-D Models
3-D Models (high mass)
Model Grid & Fitter
Answers to questions? A few, maybe
Canonical View of Low-Mass Star
Formation
Dark cloud cores
• Free-fall times short, yet star
formation efficiency low
(Zuckerman & Evans 1974)
• Conditions for
support/collapse
– Magnetic fields/Ambipolar
diffusion (Shu 1977;
Mouschovias 1976; Nakano
1976)
– Supersonic turbulence/local
collapse (Mac Low & Klessen
2004)
Collapse -- Class 0
t < 104 yrs
SED: T~30 K
(Shu, Adams & Lizano 1987; Lada 1987)
Late Collapse -- Class I
t ~105 yrs
SED
slope, > 0, for
2 <  < 22 m
(Shu, Adams & Lizano 1987; Lada 1987)
Accretion Disk Stage -- Class II
t ~106-107 yrs
SED
slope, 0 > > -2
2 <  < 22 m
Debris or no Disk -- Class III
t > 107 yrs
SED
slope, < -2
2 <  < 22 m
Massive Star Formation -- Competing
theories
0.5 pc
5 pc
Analogous to low-mass
(McKee & Tan 2003)
Mergers in dense clusters
(Bonnell & Bate 2002)
Disk formation,
collimated outlfows
Disk disruption
less collimated flows
Questions
• What are the global properties of star
formation in the Galaxy? (GLIMPSE)
– Star formation rate and efficiency
– Timescales for evolution
• How do massive stars form?
– Do they form planets?
– Do low-mass stars in the vicinity of
massive stars form planets?
• What supports clouds against collapse?
Galactic Legacy Infrared Mid-Plane
Survey Extraordinaire
• One of five Spitzer Legacy
programs
– No proprietary period +
enhanced data products
• 4 wavelength bands: 3.6,
4.5, 5.8, 8 m
new project, MIPSGAL,
will get 24, 70, 160 !
(PI: Sean Carey)
• b=[-1,+1], |l|=10-65
GLIMPSE II: |l|<10 !
PI: Ed Churchwell
www.astro.wisc.edu/glimpse • Angular resolution <2”
GLIMPSE Data Products*
• GLIMPSE Point Source Catalog
– Highly reliable (>99.5%) -- 31 million sources
– Magnitude limits in 4 bands: 14.2, 14.1, 11.9, 9.5
• GLIMPSE Point Source Archive
– Less reliable but more complete -- 48 million
sources
– Magnitude limits: 14.5, 14.0, 13.0, 11.5
• Cleaned mosaic images
– 1.1x0.8 degrees (0.6” pixels)
– 3x2 degrees (1.2” pixels)
– Southern hemisphere available in Dec. (all Spitzer
“BCD” images and mosaiced AORs are available)
*Available at http://www.astro.wisc.edu/glimpse/glimpsedata.html
Example of cluster formation?
tens of pc
Class 0 Source?
324.72+0.34
1-2-4
J-H-K
320.23-0.29
Ch 1,2,4
2MASS
332.73-0.61
317.35+0.0
1-2-4
3x2 deg
Radiative Transfer Models
• Monte Carlo method
• 3-D spherical polar grid
• Calculates radiative equilibrium of dust
(Bjorkman & Wood 2001)
• Non-isotropic scattering + polarization
• Output: images + SEDs (+ polarization)
• Not included: PAHs, stochastic heating
of small grains, optically thick gas
emission
(Whitney et al. 2003a,b, 2004)
2-D YSO Model Geometry
• Rotationally-flattened infalling envelope
(Ulrich 1976)
• Flared disk
• Partially evacuated outflow cavity
AV through Envelope & Disk
Edge-on
Pole-on
Low-Mass
Protostar:
IRAS
04302+2247
L=0.5 Lsun
2-D RT models
NIR 3-color
(Padgett et al. 1999)
Spitzer IRAC predictions
J-H-K
[3.6]-]-[4.5]-[8.0]
[24]-[70]-[160]
Late
Class 0
Class I
(Whitney et al. 2003b)
IRAS 04368+2557
2MASS J-H-K
Spitzer IRAC [3.6]-[4.5]-[8.0]
Lowmass
Analog?
Massive protostars
Embedded Massive YSO
L*=40000
T*=4000
M
. *=17.5
M=10-4
Md=1
i
Av
0
6
60
53
90
3e4
Embedded Low-Mass YSO
L*=1.1
T*=4000
M
. *=1 -5
M=10
Md=0.05
i
Av
0
6
60
50
90
4e6
Massive Star+Disk
L*=40000
T*=30000
M*=17.5
Md=0.1
i
Av
0
0
60
0.1
90
3e3
Low-Mass Star + Disk
L*=40000
T*=4000
M*=17.5
Md=0.01
i
Av
0
0
60
0.1
90
3e5
Effect of Bipolar Cavity on Colors
Near-IR
IRAC
No cavity
cavity
• Models without cavities (e.g., 1-D) will
underestimate evolutionary stage!
Massive Stars: The need for 2-D, 3-D
models
(van der Tak et al. 2000)
>100 m: no
<100 m: yes
3-D models
• Motivation
– UCHII regions: Previous 1-D models of
mid-IR spectra can’t fit full SED: give too
deep 10 m absorption for a given FIR flux,
and too steeply rising SED in NIR/MIR
(Faison et al. 1998, van der Tak et al.
2000)
Model Ingredients
• O star in a molecular cloud (massive
stars heat up large volumes)
• Use fractal ISM structure, D=2.6
(Elmegreen 1997)
• Average radial density profile is varied
from r0 to r-2.5
• Smooth-to-clumpy ratio is varied from
3% to 100%
(Indebetouw et al. 2005)
3-D clumpy models
NIR
IRAC
MIPS
Indebetouw et al. (2005)
Clumpy model SEDs
Average
Smooth (1-D) model
200 sightlines from 1 source (grey lines)
Fits to Data: G5.89-0.39
Mid-IR data: Faison et al. (1998)
Best clumpy model
Grey lines show other sight lines
Best smooth model
G5.89 Model parameters
Tstar
41000 K
L
2.54x105
Rin
0.0001 pc
Rout
2.5 pc
Menv
50000
Av_ave
131
Smooth/Clumpy
10%
Radial density
ave~r0
Fractal dimension
2.6
Color-color plots
200 sightlines from 1 clumpy model
Smooth model
All the UCHII Observations
Mid-IR data: Faison et al. (1998)
Grey lines: G5.89 best model
3-D Model summary
• UCHII regions may be O-B stars still
embedded in their natal molecular
clouds but not surrounded by infalling
envelopes.
• Bolometric flux of clumpy models varies
by a factor of 2 lower and higher than
the true luminosity depending of viewing
angle
(Indebetouw et al. 2005)
2-D/3-D Model grid + Data fitter
• Large Grid of YSO Models (20,000)
x 10 inclinations = 200,000 SEDs!
6 weeks of cpu time on about 50 processors
• Linear Regression Fitter to find best model to
fit an observed SED
– Models are convolved with any broadband filter of
interest
– First tries to find good fit from a grid of stellar
atmosphere files
– Simultaneously fits foreground AV
– Can process the GLIMPSE survey in about a
week
(Robitaille et al. 2005)
Grid Creation
• Sample stellar mass and age (logarithmically)
• calculate T* and R* from evolutionary tracks (Bernasconi & Maeder
1996; Siess et al. 2000)
Grid Parameters
198,680 SEDs
Relating Observed Class to Model
“Stage”
Class
I
Spectral
Index (220 m)
>0
II
-2 - 0
III
Stage Envelope
Infall rate
(Msun/yr/
M*1/2)
I
>2x10-6
Disk
mass
(M*)
II
<2x10-6
>1x10-7
III
0
<1x10-7
<-2
Synthetic cluster Color-color plots -IRAC
Reddening line
stars
• D=4 kpc (RCW
49)
• GLIMPSE
low/high
sensitivity limits
• “Stage I”
• Stage II
• Stage III
• all
Class vs Stage
• Classification
spectral index
was defined
over
wavelength
range of 222 m (Lada
1987).
• What
happens for
2-I?
Motivation for Fitter
• Fit as many datapoints as available
simultaneously
• Unbiased (except for grid choices) -- shows all
fits to a given dataset
– Estimates uncertainties
• Estimates foreground AV
(Robitaille et al. 2005)
Fitter results on a single source
GLIMPSE Empty Field
• 99.6% of
sources fit with
stellar
atmospheres
• 0.4% evolved
stars, bad data
or YSOs?
RCW 49
Class I source
RCW 49
• 96.6% of
sources fit with
stellar
atmospheres
• 3% well-fit with
YSO models
IC348 Mass
histogram
• “Known” IMF
(using prior
information
on stellar
parameters)
• Data from
Lada et al.
(2005)
IC348 Mass
histogram
• Based on
Model Fitter
Only
RCW 49 Synthetic Mass histogram
• Sampled
masses from
grid using
Salpeter IMF
(flatter slope
below 0.5 Msun)
• Sampled ages
using Taurus
ratios (Kenyon
& Hartmann
1995)
• Apply GLIMPSE
sensitivy limits
RCW 49
Fitted
Mass
histogram
• Use model
fitter to
determine
masses
Applications of Grid & Fitter
• Study Global properties of star
formation in Galaxy
– Star formation rate, lifetimes of
evolutionary states, IMF
– A high star formation efficiency argues for
turbulent cloud support (vs. magnetic)
• Search for disks around massive stars
– Adds further credence to accretion model
for high-mass star formation
– Disks form planets
…applications
• Study low-mass star formation in vicinity of
high-mass
– May be more common mode of star formation
(Hester & Desch 2004)
– Disk lifetimes, sizes
• 3-D extinction map
• Galactic structure
– 80% of stars are K giants
– Fitter can distinguish gravity (I.e., giants/MS)
Future Work
• Radiative Transfer
– Add PAHs, stochastic heating of small grains
• Grid and fitter will be publicly available in
2006
• RT codes available at
http://gemelli.spacescience.org/~bwhitney/codes