Decoding The Rosetta Stone of Galaxy Formation
The Milky Way with SDSS and Future Large Scale Surveys
Mario Juric
Institute for Advanced Study, Princeton
with Zeljko Ivezic, Nick Bond, Brani Sesar, Robert Lupton… and the SDSS Collaboration
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Big Picture :: Galaxy and Structure Formation on ≤ MW scales
• Mapping with SDSS
• Taking the measure of the Milky Way
• Realizing the dream of near-field cosmology
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
LCDM Structure Formation
I. Known knowns:
Structure formation on large scales
Hierarhical s. f.
Abundant substructure
…
II. Known unknowns:
Small scale structure formation
Baryon behavior
Disk formation
Disk survival
Nature of DM
…
The Galaxy:
Laboratory for II. -> I.
A complete cosmo+galform theory
must predict its properties
Bullock et al.
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Milky Way
• Thin disk
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Thick disk
(Pseudo)bulge
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Stellar halo
Exponential or
sech2 disk models
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Power laws or de
Vaucouleurs profiles for
the halo
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Components trace
the DM dominated potential
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They are a product of Milky Way formation and evolution
Dissecting the Milky Way with SDSS Program
1. Directly measure the distribution ©(~
r;~
v; [F e=H ]) of stellar
number density, kinematics, and metallicity in a representative volume of the Galaxy.
2. Use the distributions to learn about [Gg]alaxy formation, evolution, interactions
with environment, and the distribution of dark matter.
Sloan Digital Sky Survey
 Imaging and Spectroscopic Survey
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~8,000 deg2 to ~21.5 mag
5 bands (ugriz: UV-IR), 0.02 mag
< 0.1 arcsec absolute astrometry
~50M, mostly main sequence, stars
R=2000 spectrograph (390<λ/nm<600)
 RV to ~10 km/s
 Stellar parameters for for >280k stars
 SEGUE I/II
SDSS DR6 Imaging Sky Coverage
(Adelman-McCarthy et al. 2008, ApJS, 175, 297)
 An excellent tool for Galactic structure studies
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Accurate m’band photometry: distance and metallicity estimates
Accurate astrometry: proper motions
Large area and faint flux limit: representative volume
Numerous (MS) stars: reduced uncertainties
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
How we do it
~3M
~150M obsvs.
u, g, r
[Fe/H]
Teff
g, r, i
a, d
(circa 2002)
a, d
(circa 1955)
Mr
(absolute magnitude)
~50M
X, Y, Z
(position)
ma, md
(proper motion)
POSS (USNO-B catalog)
Mapping the Milky Way with SDSS
~30M
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Volume limited 3D distributions of r, [Fe/H], ml, mb
in 19 r-i color bins (spectral types ~F8-M5)
~8000 deg2
E.g: r-i=0.1-0.15 (late F)
20 kpc (density)
8 kpc (Fe/H, m)
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Dissecting the Data Cube
R
Z
Y
X
Y
Z
R
Mapping the Milky Way with SDSS
X
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Density Maps: D < 3kpc (Late K, M stars)
Right: X-Y maps of number
density distribution at Z=+/900 and +/-600 pc for
1 < r-i < 1.1 stars (~M dwarfs)
 “Face-on view” of the Galaxy
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Mapping the Milky Way with SDSS
Bottom: Density contours
around the axis of symmetry
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Density Maps: D > 3kpc (F, G, early K)
Mapping the Milky Way with SDSS
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Right: X-Y maps of number
density distribution at Z=5, 4,
12, 10 kpc for
.1 < r-i < .15 stars (~F/G SpT)
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Signatures of overdensities
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Edge-on View (R-Z density distribution)
Right: f(R, Z) density
distribution (“edge-on
view”)
 1 kpc (bottom right; M
dwarfs) to ~20kpc (top left;
F dwarfs) scales
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Map Analysis Summary:
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Mapping the Milky Way with SDSS
Smooth, axisymmetric,
background consistent
with exponentials (disk)
and power laws (halo)
Overlaid by localized
overdensities: clumps and
streams
Most major overdensities
at D > 3kpc
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Disk Model Fit
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M-dwarfs (D < 2 kpc)
excellently fit by two
exponentials
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Best fit:
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Mapping the Milky Way with SDSS
Z0 = 25 pc
H1=245 pc, H2=740 pc
L1=2.15 kpc, L2=3.3 kpc
f=13%
Reduced c2=1.6
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Uncertainties and
covariances easily seen in c2
plots (left)
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Same values obtained when
allowing the scales to vary in
adjacent color bins
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Halo Fits
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10kpc < D < 20kpc
Power law
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Clearly aspherical, oblate
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qH = 0.6
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Normalization: fH ≤ 0.5%,
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Poorer fit (reduced c2~3)
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Mapping the Milky Way with SDSS
nH = 2.8
Indicative of large scale
departures from simple
power law (dual halo)
Or clumpiness of the
halo (Bell et al. 2008)
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Why Should You Care?
Chen et al. (2001; SDSS turnoff stars, ~280 deg2)
12
Juric et al. (2008; ~6500 deg2)
 Significant disagreements
in prior measurements
10
8
Siegel et al. (2002; ~15deg2)
 Significant disagreements
about the percentage of
mass contained in the thick
disk
 IMPORTANT, as these fits
are EXTRAPOLATED to the
rest of the Galaxy when
building dynamical models
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Value of Wide Area I: Breaking the Degeneracy
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NGP line of sight only:
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H1=260pc
H2=1000pc
f=4%
Mapping the Milky Way with SDSS
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H1=245pc
H2=750pc
f=13%
Two substantially
different fits describe
the NGP line of sight
equally well
A number of prior
studies are NGP-only
Wide area survey is
necessary to break the
degeneracy
In our case, the fit
always converged to
the same minimum (or
did not converge at all)
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Value of Wide Area II: Seeing/Avoiding the Substructure
 Vermin of the Galaxy
 If unrecognized, overdensities will influence the fits
 The only way to identify them is with a wide area survey
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Distribution of Metallicity in the Milky Way
Ivezic et al. (2008)
No radial metallicity gradient
Features in density space ↔ features in metallicity space
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Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Vertical Variation of Metallicity Distribution Function (MDF)
1)
Clear disk/halo
separation
•
2)
Mapping the Milky Way with SDSS
Halo: Gaussian MDF
Vertical metallicity
gradient in the disk
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Disk MDF
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Detection of metallicity
gradient
¹ D (Z ) = ¹ 1 + ¢ ¹ exp(¡ jZ j=H ¹ ) dex
H ¹ = 1:0kpc; ¹ 1 = ¡ 0:78; ¢ ¹ = 0:35
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Disk metallicity
distribution:
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Mapping the Milky Way with SDSS
Approximately fitted with a
gaussian with Z-dependent
mean,
F([Fe/H]) ~ G(mD, s=0.16)
Best fit by an asymmetric
distribution with a slight
low-metallicity tail
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Asymmetric Disk MDF
Disk
Disk
Halo
Halo
Halo
Halo
Disk
Disk
©disk ([F e=H ]) / G(¹ D ; ¾= 0:11) + 1:7 £ G(¹ D ¡ 0:1; ¾= 0:21)
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Adding Kinematics: Proper motions towards the NGP
Easy to interpret: vf= mb×D is the rotational velocity
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Halo/Disk Components, Disk Rotational Velocity Lag
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Top panels: small dots are
individual stars, large
symbols are the median
values
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Top left: disk stars show
clear rotational velocity
lag
Top right: halo stars
vf ~ 220 km/s, no
significant rotation
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Disk Halo
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Halo
Disk
Mapping the Milky Way with SDSS
Halo
Disk
Bottom left: disk velocity
lag not linear
Bottom right: halo
velocity dispersion
increase consistent with
being due to photometric
errors only
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Rotational velocity distribution functions
0.8 < Z/kpc < 1.2
2 < Z/kpc < 3
Mapping the Milky Way with SDSS
1.5 < Z/kpc < 2
5 < Z/kpc < 7
1.
Disk: Asymmetric
rotational
velocity
distribution with
Z-gradient
2.
Halo: Unimodal,
Gaussian velocity
distribution of
fixed dispersion
and mean
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Revisiting the Thin/Thick Disk Dichotomy
Vertical density distribution exhibits a break
 Metallicity distribution exhibits a metal-weak tail
 Rotational velocity distribution exhibits a lowvelocity tail
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Is there evidence for a model of the density,
metallicity, and velocity distributions as a
superposition of two distinct populations?
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Metal-rich, kinematically cold, thin disk
Metal-poor, kinematically warm, thick disk?
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Metallicity-rotational Velocity Correlation
Ivezic et al. (2008)
Left: Expected rotational velocitymetallicity correlation at 1kpc < Z < 1.2kpc
 Right: Observed metallicity-rotational
velocity correlation
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Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Thick Disk Formation: Major merger, heating, or accreted?
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We find no evidence for the thick disk being a clearly
distinct component
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Abundance dichotomy
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May pose a problem for formation by a single major merger
We cannot differentiate between the other two possibilities
Caveat: Model admittedly simple. Will be revisited in the context
of dynamical models of the Galaxy (work in progress)
Usually used to argue for “catastrophic” thin/thick disk formation
Not so: see Schonrich & Binney (arXiv: 0809.3006v1)
Thin disk/thick disk… The Disk.
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Disk Formation with Radial Migration
Roškar et al (2008) simulation: gas accretion only, SNe feedback, no mergers.
Analysis: Loebman et al. (arXiv: 0810.5158v1).
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Next Decade: Decoding the Rosetta Stone of Galaxy Formation
Disclaimer: “This part contains statements which may be deemed to be "Forward-Looking Statements"
within the meaning of Section 27A of the Securities Act of 1933… Statements that are not historical
facts, including statements about our beliefs and expectations, are forward-looking statements. These
statements are based on current plans, estimates and projections, and therefore you should not place
undue reliance on them.”
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Milky Way Halo
Belokurov et al (2007)
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Dark Side is Really Dark
Simon & Geha (2007)
More, potentially closer, ultrahigh M/L dwarfs left to be
uncovered, providing targets for
DM annihilation searches.
A project for DES.
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Future: Disk is Where the Action Is
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Disks are the least well understood results of structure
formation
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Disk formation
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Disk survival
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Old disks?
Reformed after z=1?
Disk structure
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When?
Where?
How?
Disk dark matter?
This is where this program is going
We will soon be able to observationally constrain all of
these questions
Surprisingly little being done to actually do it (compared
to the efforts devoted to the halo)
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Mass Distribution of the Milky Way Disk
Measuring the vertical force field Kz(R,φ)
 Constraining the mass scale length of the disk
 Constraining the DM distribution (e.g. Dehnen & Binney 1998, BT 2007)
The Sun
SEGUE Imaging Footprint
D~2kpc
Galactic Plane (edge-on view)
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Juric et al. (2008)
Abundant Disk Substructure
 Monoceros stream (Newberg et al. 2002; not shown here, more later)
 Two additional disk substructures
 R=6.5kpc, Z=1.5kpc: ~20% over the background
 “Thick disk asymmetry” of Larsen & Humphreys (1996)
 R=9.5kpc, Z=0.8kpc: ~50% over the background
 Faint kinematic/metallicity signature (Bond et al., in prep)
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Juric et al. (2008)
Abundant Disk Substructure
 Need further follow-up (wider survey) to trace its full extent
 20-40 such streams in the disk (crude extrapolation)
 These are merger remnants + results of secular evolution: simulations
should be able to predict their properties
 Need a statistical description to compare with simulations
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Evidence of Mergers: Monoceros Stream
Kazantzidis et al. (2007) simulations
Juric et al. (2008) “observations”
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Monoceros Stream: Evidence of Accretion
Disk only
Mapping the Milky Way with SDSS
Disk w. Mon.
Ivezic et al. (2008)
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Monoceros stream
(Newberg et al. 2002)
clearly distinct in
metallicity space
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Metal poor compared to
the disk, but metal rich
compared to the halo
([Fe/H] = -0.95 dex)
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Strong evidence for
external origin (merger
remnant, as opposed to
disk flaring or excitation)
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
North-South Asymmetries: “Disk Buckling?”
Morrison, Rockosi, Juric, ...
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Why Now?
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SDSS: “I’m not dead!”
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Kinematics
SEGUE I/II, APOGEE (2011 onwards)
Upcoming:
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SDSS-III (now): 2,000 deg2 of additional imaging
Pan-STARRS PS1 (2009): 30,000 deg2 to r=23, deeper w. coadds
SkyMapper (2009): 20,000 deg2 to r=21.6, deeper w. coadds
DES (2011?): 5,000 deg2 to r=25.6
GAIA (2013): 40,000 deg2 to r=20, mas proper motions
LSST (2015): 20,000 deg2 to r=24, to r=27 with coadds
RAVE (2010?): 1M radial velocities
In the next 5 years, the Galaxy will be mapped in unprecedented detail. The
major challenge for the future is converting that data into useful information.
 Boon for Galactic structure studies
 We need a framework for systematic and quantitative comparison with
simulations
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Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
The Galaxy with Pan-STARRS and LSST
RR Lyrae limit
MS stars limit
Pan-STARRS 3p Survey at z=2.1kpc above the plane
Bullock & Jonhston (2005), Ivezic et al. and the LSST collab. (2007)
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
SDSS III / APOGEE :: Unveiling the History of the Milky Way
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H-band spectra of ~100,000 red giants selected from 2MASS
R~20,000, typical S/N~100
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Radial velocities to ~ 0.5 km s-1
Individual abundances of ~10 chemical elements, including O, C, N, Fe, Si
Increase number of high-res, high-S/N spectra by factor of 100!
Bright time observations, 2011-2014, with new, 300-fiber, cryogenic
spectrograph
Detailed chemical and kinematic mapping of all Galactic stellar
populations, including the inner Galaxy (high AV regions)
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Chemical evolution and enrichment
Merger remnants in phase space
Chemical fingerprinting
=> “Growing” the Milky Way’s merger tree
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH
Instead of a Summary: The Galaxy Within a Decade (an optimist’s view)
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Knowledge of dynamical state and formation history of a
galaxy:
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The mass of the DM halo (GAIA, HVSs)
Census of (visible) DM subhaloes (Pan-STARRS, DES, LSST)
Dark matter distribution (SDSS III, GAIA, LSST)
Dynamical model (SDSS III, Pan-STARRS, GAIA, LSST)
Disk formation, in situ vs. accretion (SDSS III, GAIA, LSST)
Tracing merger remnants (SDSS III, GAIA, Pan-STARRS, LSST)
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All of these, esp. the insights on disk build-up, generalize
to other galaxies
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Necessary for complete, beginning-to-end, understanding
of structure formation in the universe.
Mapping the Milky Way with SDSS
Mario Juric <mjuric@ias.edu>, Tuesday, January 6th, 2009.
Ohio State, Columbus, OH