Travis Metcalfe (NCAR) First results from the Asteroseismic Modeling Portal Collaborators: Michaël Bazot, Tim Bedding, Alfio Bonanno, Isa Brandão, Bill Chaplin, Jørgen Christensen-Dalsgaard, Orlagh Creevey, Maria Pia Di Mauro, Gülnur Dogan, Savita Mathur, Matthew Woitaszek, KASC WG1

Drinking from a Firehose

Ghost in the Machine Stellar evolution tracks from ASTEC, pulsation analysis with ADIPLS Parallel genetic algorithm optimizes globally, local analysis + SVD for errors Stellar age from match to large separation, correct surface effects empirically 0.75 < M < < Z < < Y < <  < 3.0 Metcalfe et al. (2009)

Fitting for stellar age Large frequency spacing decreases almost monotonically with age Binary decision tree to fit age from the observed large frequency spacing Calculates only radial modes until final step, scales surface effects Christensen-Dalsgaard (2004)

Incomplete modeling of surface convection zone leads to systematic errors Calibrated with difference between fit to “Model S” and BiSON radial modes Global fit to BiSON data, including scaled empirical correction for all modes Correcting for surface effects

Results from Sun-as-a-star data Fit to 36 frequencies with l = 0-2 and constraints on temperature, luminosity GA matches observed oscillation frequencies to better than about +2% Temperature and age within +0.1%, luminosity and radius within +0.4%

What is AMP? Web interface to specify observations with errors, or upload as a text file Specify parameter values to run one instance of the model, results archived Source code available for those with access to large cluster or supercomputer Woitaszek et al. (2009)

How does AMP work? 128-way parallel sets/week

 Cen A & B Data: de Meulenaer et al. (2010), Kjeldsen et al. (2005)

 Hyi &  Cet Data: Brandao et al. (2011), Teixeira et al. (2009)

Gemma & KOI-975 Data: Chaplin et al. (2010), Howell et al. (2011)

Overview & Future AMP works: objective global stellar modeling for theorists and observers. Reliable spectroscopy is essential, and conflicts are generally obvious. Dirt under the rug: some data sets do not yield satisfactory fits (  2 ~25). Why? Problems with the data (e.g. mode identification), deficiencies in the models (e.g. missing ingredients) or both. Future validation: remaining ground-based data, dozens of Kepler targets, a few CoRoT stars.