Diane Feuillet New Mexico State University Jon Holtzman Jo Bovy Leo Girardi The APOGEE Team Thick disk Old Kinematically hot Metal poor Alpha rich Thin disk Younger Kinematically ID: 525990
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Determining Ages of APOGEE Giants with Known Distances
Diane Feuillet New Mexico State UniversityJon Holtzman, Jo Bovy, Leo GirardiThe APOGEE TeamSlide2Slide3
Thick disk:
OldKinematically hotMetal poorAlpha richThin disk:YoungerKinematically coldMetal richAlpha poorMetallicity gradientsAge-metallicity relationNidever
+ 2014Galactic Chemical Evolution
Frinchaboy
+ 2013Slide4
Apache Point Observatory Galactic Evolution Experiment
Explore Galactic evolution through detailed chemical abundancesR~23,000, 1.51-1.70μ spectrograph130,000 red giants, ~400,000 in APOGEE-2Slide5
Abundances Across the Disk
Hayden+ 2015Slide6
Abundances Across the Disk
Hayden+ 2015Direct comparisons of different radial bins is difficultSFR, inflow, mixing, etcSlide7
Absolute Ages of Stars
Not Easy!EmpiricalGyrochronologyChromospheric activityModel-dependentIsochrone model matchingAsteroseismologyRecently, CN abundancesAge adds important third dimension to traditional [Fe/H] vs [α/Fe] spaceSlide8
Ages and Abundances
Haywood+ 2013Age adds crucial evolutionary information and population identificationSlide9
Ages and Abundances
?
?
?
Haywood+ 2013Slide10
Ages of Red Giants
Age can be determined from massSeismic masses are good, uncertainty ~15%CN massesL, Teff, log g massUncertainty depends on log g, ~0.11 dex or 30%PARSEC
Bressan+ 2012
Feuillet+ 2016
0.38
dex
uncertainty in ageSlide11
Ages of Red Giants
Use Bayesian isochrone matching with all parametersMV adds age resolution to giant branchPARSECFeuillet+ 2016Slide12
Test Sample
Isochrone points with APOGEE-like uncertainties imposedBayesianAssume flat SFH in ageChabrier IMFTake mean of age PDF[Fe/H], Teff, MV, log g
σ
= 0.1807
Feuillet+
2016Slide13
Local Sample
700 local giants within 400 pc Observed with 1m+APOGEEReduced and analyzed with APOGEE software
Hipparcos distances
Apache Point Observatory
Feuillet+
2016Slide14
Local Sample
324 RC stars identifiedFeuillet+ 2016Slide15
Local Sample
Reasonable age distributionSuggests age-alpha relationObserved
Expected
Feuillet+ 2016Slide16
Hierarchical Modeling
Find a more informed prior for the SFHUse the full age PDF to constrain a model SFHα-dependent Gaussian SFHFeuillet+ 2016Slide17
Hierarchical Modeling
Feuillet+ 2016Slide18
Age Trends
Strong relation between α abundance and mean age of Gaussian modelAge-metallicity relation consistent with other workVelocity dispersion consistent with GCSFeuillet+ 2016Slide19
Age Trends
Strong relation between α abundance and mean age of Gaussian modelAge-metallicity relation consistent with other workVelocity dispersion consistent with GCS
Feuillet+
2016Slide20
Age Trends
Strong relation between α abundance and mean age of Gaussian modelAge-metallicity relation consistent with other workVelocity dispersion consistent with GCSFeuillet+ 2016Slide21
Age Trends
Strong relation between α abundance and mean age of Gaussian modelAge-metallicity relation consistent with other workVelocity dispersion consistent with GCS
Power law indices
U V W Total
Feuillet+ 2016 0.30 0.39 0.44 0.36
GCS (Holmberg+ 2009) 0.39 0.40 0.53 0.40
Feuillet+
2016Slide22
Future Work
Need large samples with distance measurementsApply to APOGEE RC sampleTest monoabundance subsamplesExpand hierarchical modeling methodWith Gaia distancesAPOGEEAPOGEE-2GALAHGaia-ESO Slide23
Future Work
Need large samples with distance measurementsApply to APOGEE RC sampleTest monoabundance subsamplesExpand hierarchical modeling methodWith Gaia distancesAPOGEEAPOGEE-2GALAHGaia-ESO QUESTIONS?