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Elemental Abundance Trends of the Metal-Poor Galactic Disks: Clues to Formation of the Galaxy Elemental Abundance Trends of the Elemental Abundance Trends of the Metal Metal-

• Poor Galactic Disks: Clues to

Poor Galactic Disks: Clues to Formation of the Galaxy Formation of the Galaxy

Gregory Ruchti (PhD thesis)

Department of Physics and Astronomy Johns Hopkins University advisors: Rosemary Wyse Jon Fulbright

Motivation Motivation

• Probe the evolution of the Milky Way Galaxy through

metal-poor (early?) disk stars

• Address questions such as:
• How and when did the Galactic disk start to form?
• How was it that a thin and a thick disk formed?
• What is the importance of mergers in disk formation and Galactic

evolution?

• How did the Galaxy evolve chemically?
• Combine power of large RAVE sample to provide

candidate metal-poor disk stars, with elemental abundances from follow-up high-resolution spectroscopy

• Information on recent and past SFH, IMF, more than overall [M/H]
• Different theories of disk(s) formation and evolution make different

predictions for elemental abundance patterns and low-metallicity tail (starburst vs satellite accretion etc)

• Probe the evolution of the Milky Way Galaxy through

metal-poor (early?) disk stars

• Address questions such as:
• How and when did the Galactic disk start to form?
• How was it that a thin and a thick disk formed?
• What is the importance of mergers in disk formation and Galactic

evolution?

• How did the Galaxy evolve chemically?
• Combine power of large RAVE sample to provide

candidate metal-poor disk stars, with elemental abundances from follow-up high-resolution spectroscopy

• Information on recent and past SFH, IMF, more than overall [M/H]
• Different theories of disk(s) formation and evolution make different

predictions for elemental abundance patterns and low-metallicity tail (starburst vs satellite accretion etc)

dSph vs. field-star abundances

complied by Koch

Different patterns reflect different SFH and chemical enrichment Halo kinematics

What about the metal-poor disk(s)? What about the metal-poor disk(s)?

• To date, published elemental

abundances for only about 25 thick disk stars with [Fe/H] < -1, and only ~10 with [Fe/H] < -1.5.

• Estimated old ages and high

[alpha/Fe] ratios consistent with rapid star formation and fixed IMF

• However, these stars are within a

few hundred parsecs of the Sun: a small volume where thick disk rare.

• Additionally, cannot investigate

possible radial and vertical metallicity or elemental abundance gradients in this small volume.

• A larger sample, probing a larger

volume, would greatly increase our understanding of the metal-poor thick disk.

• To date, published elemental

abundances for only about 25 thick disk stars with [Fe/H] < -1, and only ~10 with [Fe/H] < -1.5.

• Estimated old ages and high

[alpha/Fe] ratios consistent with rapid star formation and fixed IMF

• However, these stars are within a

few hundred parsecs of the Sun: a small volume where thick disk rare.

• Additionally, cannot investigate

possible radial and vertical metallicity or elemental abundance gradients in this small volume.

• A larger sample, probing a larger

volume, would greatly increase our understanding of the metal-poor thick disk.

e.g. Reddy & Lambert 2008 Thick disk: green, red and open ‘Hybrid’: black Halo: blue

Candidate Selection Candidate Selection

• From RAVE database identify metal-

poor stars with thin or thick disk kinematics as candidate sample

• Mostly giants.
• Use RAVE pipeline stellar parameters to

derive preliminary distances (fits to isochrones) and hence space motions

• Derive likely population assignment based on

space motions, radial velocities and RPMD.

• Candidate stars assigned to Galactic disk

population if thin- or thick-disk population probabilities are 10 times greater than that of being a halo star. Same method applied to distinguish thin and thick disks.

Echelle Observations Echelle Observations

• Obtained high resolution (R > 35,000) echelle spectra

(S/N > 100) for ~500 (! – good weather!) candidate metal- poor thick disk stars.

• Gives Fe, many other elements, and allows for improved

stellar parameters and population assignment.

• Echelle at Apache Point Observatory 3.5-m telescope.
• Resolving Power ~ 37,500; λ = [3500, 9800] Å
• 2-3 half-nights every quarter year.
• MIKE on Magellan Clay Telescope in Chile.
• Blue: Resolving Power ~ 42,000; λ = [3560, 5050] Å
• Red: Resolving Power ~ 33,000; λ = [4850, 9400] Å
• 2 nights in May 2007 and 2 nights in October 2008
• UCLES on Anglo-Australian Telescope in Australia.
• Resolving Power ~ 40,000; λ = [4460, 7270] Å
• 7 nights in June 2007, 5 nights in September 2008
• FEROS on 2.3-m Telescope at La Silla Observatory in Chile.
• Resolving Power ~ 47,000; λ = [3900, 10,000] Å
• 7 nights in February 2009

Elemental Abundances Elemental Abundances

• Measure equivalent widths using the Automatic

Routine for line Equivalent widths in stellar Spectra (ARES; Sousa et al. 2007).

• Compared to hand-measurements, ~3 mÅ differences
• Abundance analysis follows same methodology

as Fulbright 2000:

• One of the largest uniform samples of halo star

abundances in the literature.

• Differential halo-disk and disk-disk comparisons do

not suffer any significant systematic effects.

• Line list includes many interesting species:
• Fe I and Fe II for stellar parameter estimation
• Major alpha elements (Mg, Si, Ca, Ti, O)
• Major neutron capture elements (eg. Ba, Eu, Y, Zr)
• Odd-Z light elements (eg. Na, Al, K)
• Fe-group elements (eg. V, Cr, Ni, Zn)

Elemental Abundances Elemental Abundances

• Stellar parameters also derived during analysis:
• Effective temperature set using excitation temperature

method based on Fe I lines.

• Surface gravity, log(g), set by minimizing difference

between calculated abundance of iron from Fe I lines and Fe II lines.

• Microturbulent velocity selected to minimize slope of Fe I

iron abundance versus reduced width of each Fe I line.

• A short-fall of this method is for log(g) < 1.0,

ionization equilibrium fails.

• For these log(g) values are typically lower than expected.
• Typical errors: σTeff~200K, σlog(g)~0.3, σ[Fe/H]~0.1,

σ[alpha/Fe]~0.1

Check with Elizabeth re status of pipeline!!

Echelle [Fe/H] Histogram

Echelle [Fe/H]

• 1
• 2
• 3

Distances Distances

Under development

• Distances are estimated using echelle stellar

parameters:

• Fit to grid of Padova isochrones defined in metallicity

with two selected ages: 12 Gyr and 4 Gyr.

• Used Teff, log(g), [Fe/H] (all echelle-based), and 2MASS

J-Ks as fit parameters.

• To account for lifetimes in different evolutionary

phases we applied the theoretical Luminosity Functions as a priori probabilities to our fits: most important for the low log g RGB.

• How reliable are the isochrones?
• Final distances estimated from the mean of the

distances derived from the two ages.

• Typical errors are ~ 20-30%

• Padova isochrones with Z = 0.001012 ([Fe/H] = -1.5,

[alpha/Fe] = 0.3) -- Black = 12 Gyr; Red Dashed = 4 Gyr

• Errors in Log(g) ~ 0.3 dex,

Errors in Teff ~ 200 K 106 stars analysed so far to obtain elemental abundances

Log Teff (echelle) Log g (echelle) ~2dex spread in [Fe/H]

Population Assignments Population Assignments

Under development

Applied 5 ( 3 + 2) Membership Criteria with different distance dependencies: 1. Full space motion criterion

• Similar to initial selection of sample to observe
• Compute 3-D space motions and compare to standard

velocity distributions:

• Thin disk: 〈VΘ〉 = -15 km/s, (σΠ,σΘ,σZ) = (39,20,20)
• Thick disk: 〈VΘ〉 = -51 km/s, (σΠ,σΘ,σZ) = (63,39,39)
• Also possibility of higher lag for metal-poor thick disk
• Halo: 〈VΘ〉 = -220 km/s, (σΠ,σΘ,σZ) = (141,106,94)
• Candidate stars assigned to Galactic disk population if

thin- or thick-disk population probabilities are 10 times greater than that of being a halo star. Same method applied between thin and thick disks.

2. Component dispersion limit criterion

• Another assignment probability given by how much each

velocity component differs from its standard mean velocity.

• If |Vi - 〈Vi〉| ≥ 2.5 x σVi , then the star is assigned to the next

population.

3. RPMD criterion

• Find which population in reduced proper motion space is

closest to each star

• A weighted average of these three criteria is

computed

• Set up monte carlo of 1000 points using normal distribution

for each input parameter

• Calculate mean and spread for each assignment using the

monte carlo points -- spread used as the weight

• Gives an initial estimate of the final population assignment.

• The final two criteria are used as conditional bounds --

since they can tell us if halo over disk, but not the other way around. 4. Galactocentric radial velocity criterion

• Similar technique to the 3-D space motion criterion
• If population assignment gives halo over thick disk, then final

population assignment is halo. Similarly considered between thick and thin disks.

5. 3D Positional criterion

• Uses scale-heights of the disks to obtain probability.
• Same condition applies for this criterion as the radial velocity criterion.

Population assignment of any one star always probabilistic, need large samples to characterise distributions.

Toomre Diagram

Black : Thin Disk Yellow: Thin/Thick Red: Thick Disk Green:Thick/Halo Blue: Halo 106 candidate metal-poor thick disk stars analyzed.

Alpha Abundances Alpha Abundances

• To Date, 106 candidate metal-poor

thick disk stars analyzed.

• Black = Thin Disk
• Green = Thin /Thick
• Red = Thick Disk
• Yellow = Thick Disk / Halo
• Blue = Halo
• Confirmed the existence of metal-poor

stars in the thick disk, with [Fe/H] < - 1.5.

• These stars have high [α/Fe] ratios,

implying they formed early in the star formation process, when enrichment dominated by Type II SNe.

• does not support late accretion from

satellite galaxies.

• Consistency between [α/Fe] values for

halo stars and metal-poor thick disk stars

• implies that massive-star IMF is

invariant.

Thin Thick Halo

Radial and Vertical Gradients Radial and Vertical Gradients

Thin Thick Halo [Alpha/Fe] defined as the weighted average of abundance from Mg, Si, Ca, and Ti with error in abundance and number of lines measured used as the weights.

Black = Thin Disk Green = Thin /Thick Red = Thick Disk Yellow = Thick Disk / Halo Blue = Halo

Velocity Relations