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YSO/PMS disk types, time-scales
and evolution
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Luke Thomas Maud – ESAC Trainee 2009
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Bruno Merin – Herschel Science centre
(Supervisor)
Hervé Bouy – Herschel Science centre
(Research Fellow)
Outline
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Formation Scenario
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The Sample
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Spectra
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Categorization
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Mass and Age Estimates
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Results
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Conclusion and Possible Interpretation
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The Future
YSO Formation
Younginside:
stellar objects
Using IR we can probe clouds and ‘see’ YSOs
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form in molecular
clouds, opaque to
optical light
Clouds collapse, cores
form..
Angular momentum
conservation generates
a spinning disk as
material falls inwards..
As the disks evolve they
disperse/evaporate and
the central star joins
the main sequence...
It is possible that a
planetary system is
created.
Formation – Spectral Energy
Distributions
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Since the late 80s investigations have been
undertaken to evaluate the evolution of YSOs
Adams, Lada and Shu 1987 developed the
‘classical’ classification system for YSOs
Using Spectral Energy Distributions (SEDs) one
can see how the flux of the emission varies
Thus how the YSO evolves
This however is the ‘general’ model and
classes are based upon a slope from 2 to 24
um wavelengths
The Sample
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This project is a continuation of previous papers
investigating the 5 close star forming regions
from the Cores to Disks (c2d) Spitzer legacy
program (Evans et al 2009)
IC 348 Perseus
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The initial sample had photometry for 1024 YSO
candidates with estimated ages of 1 -10 Myrs
Encompassing the timescales of disk dissipation
previously observed for low mass stars and
probing slightly different environments
Rho Ophiuchus
NGC 1333 Perseus
Serpens Core
The Sample
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However after analysis, the C2D YSOs had
unexplainable age attributes
The problem is due to the degeneracy involved
in SED fitting
We created a new sample of objects that had
full spectroscopic data, this means the Spectral
types of the stars could be constrained
We include only stars that are Class II and III
from (Greene et al. 1994)
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II -1.6 ≤ α < -0.3, III α < -1.6
We now have a fully usable sample of 819 YSOs
Spectra Energy Distributions – (Spectra)
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For all the targets in the sample we create SEDs
Thus we plot the wavelength of photometric data
vs. the flux at that wavelength
Classification
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In comparison to the basic Class II and III we
see a more diverse range of SEDs:
Classification
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So we define limits of classification with reference to the
median CTTS and the fitted photospheres
Mass and Age Estimates
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We get temperatures from the spectral types
and luminosities from the fitted photospheres
These are passed to HR diagrams for plotting
against PMS tracks computed be Baraffe et al
(1998) and Siess et al (2000)
Sanity check that we are not doing anything ‘silly’ as
the objects fit on the HR diagram.
Mass and Age Estimates
•
These 664 targets have excellent SED fits and have mass
constraints
from the
HR4fitting:
 and
Weage
group
the objects
into
groups now
Resulting SEDs: Good (81%)
•
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Under Luminous – Sources below the tracks –
Need to be further away
Over-Luminous – Sources above the tracks – Need
to be closer
Over-Lum
(5%)
Under-Lum
(5%) Strange
(9%)
Strange
– Objects
with non-fitting
and ‘weird’
SEDs – Would require extra analysis
Final – Objects used in the main results – 664
Results
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The resultant mass and age spread is
sensible, and within expected values for
Low mass star forming regions:
We appear to represent stellar masses down to ~0.03Mo
and up to ~ 3.5 Mo
Results
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We divide the final group in Mass ranges of:
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Separating the stars’ physical properties
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M < 0.5 Mo, 0.5 < M < 1.5 Mo and M > 1.5Mo
Fully convective, radiative core/convective envelope
and convective core/radiative envelope respectively
And Age ranges of:
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1 – 5 Myrs, 5 – 10 Myrs and 10 – 20 Myrs
To cover the general disk dispersal time scales
and evolution
We produce 9 pie charts rich with information
Speculation
Conclusions - Interpretation
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As
appears
that
disks
lower mass stars
TheitSpitzer
data
allows
thearound
new categorization
of the
last
longer stages of disks around YSOs via SEDs
evolutionary
and
clearly
‘transitionals’
 more
timedetects
for instabilities
and coagulation of particles
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Largest
statistical
sample
bigger than any previous and
potential
home for
rocky3-5x
planets?
covers a larger range of ages and environments
The most massive stars’ disks disperse fast
Initial stages all appear the same (fisher test) – NEW
 timescales preferential for large ‘Jupiter’ planets that
RESULT!
form over short times in rich disks (we need disk mass)
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More massive stars remove there disks faster, none
Latest
statistics
(Udry
et al. 2007) suggest low
are present
after 10
Myrs
mass stars have low mass multiple planet systems
Primordial
are
still evident
at ages
above
while highclass
massdisks
show
single
migrated
Jupiter
10 Myrs for stars with M < 1.5Mo
mass ones (obviously still limited in technology)
Mass plays a role in evolution – Has been suggested
but this is evidence!
Future
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The age constrains are the
current best with simple HR
fitting, however do not
account for accretion
luminosity and a more
robust method is required

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Herschel will provide this
coverage and add a new
perspective allowing
comparisons of disk and
stellar mass. One of the key
parameters of the disk itself
Our method is applicable
to the Gould belt clouds
currently underway
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(under-luminous if not
accreting = older)
To calculate disk mass we
require observations
extending into the sub-mm
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High resolution
spectroscopy would help
identify transitional disks
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With a much large sample
Binaries are ‘empty’ vs.
planet harbouring disks
Alma and JWST will shed
extra light on the data
with increased
sensitivity/resolution

Imaging will allow disk radii
to be constrained
Thank You for your attention
Any Questions Please
A Problem? - Scaling
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Note the ranges probed by the photometry
(MIPS1)
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F/A type at ~ 21AU
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Solar type at ~ 7 AU
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Low-mass at ~ 3 AU
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The previous assumptions assume the disks scale
with mass and are all comparable – however they
may not scale directly (1:1)
Thus for are low mass sources in the pie charts
classified using a different range in the SEDs??
Scaling
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NO, due to the nature of SED with the logarithmic
scale we see only a small shift of data points
This would therefore supports that stars and disk
may scale together as one may expect (more
mass, more gravity, more disk)
Additional Classification
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To move allow another perspective independent of the
larger fluctuation of age in HR fitting; we also present a
model based upon the scheme of Cieza et al (2007)
Cieza use l turnoff and α excess – which describe the
distance of the inner disk to the central star and the
degree of opacity or thickness of the disk
These are grouped for the same masses as the pie charts
Additional Results
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The ranges of the 3 mass groups appear to be comparable
Suggests the actual evolutionary sequence maybe the similar
independent upon mass
Note the tight range of Primordial disk, with Transitional
disks above α = 0 and Settled moving right and down
Again the aforementioned ‘scaling’ problem is dismissed as
one would expect the turn-off ranges to be altered, but
clearly they are similar