BEAST HackDay Intro (27 Nov 2017)

Transcript

1. The BEAST Karl D. Gordon Space Telescope Sci. Inst. Baltimore, MD, USA BEAST hack day 27 Nov 2017 STScI
2. The BEAST Bayesian Extinction And Stellar Tool • SED fitter for individual stars at a known distance • Include stellar and dust physics • Use Probabalistic/Bayesian techniques • Accurate noise model for crowded data • Must be fast – need to fit many stars – PHAT has >100 million stars
3. Model of single star in a galaxy • The physical description of a stellar SED – 7 parameters give stellar and interstellar dust properties • Stellar evolutionary tracks – Birth mass, age, & metallicity – Mapping to radius, T(eff), & log(g) – Stellar atmospheres (surface flux) → T(eff) & log(g) • Dust Extinction curves – A(V) = Dust column; R(V) ~ average grain size – f A = mixing between dust w/ 2175 Å bump (Fitzpatrick 1999 ) and SMC Bar 2175 Å bumpless dust (Gordon et al. 2003 ) • The distance
4. BEAST Strengths • Parameterized dust extinction model – Encompasses the known behavior – MW, LMC, SMC, & M31 • Noise model includes covariance – Correlation in noise between observed bands – From crowding/confusion and absolute calibration • Based on Bayesian techniques – Allows for the inclusion of prior information – Allows for hierarchical models (ensemble modeling)
5. Visual BEAST SED Construction
6. New Mixture Model encompassing all known Local Group Extinction Curves Gordon et al. (2015) and Gordon & Tchernyshyov (in prep.)
7. Covariance! Covariance Matrix & Bias in Fitting Calculating Covariance & Bias from ASTs
8. Priors = Other Knowledge = Assumptions
9. Impact of Crowding/Confusion
10. Visualization of Covariance Matrix & Bias from ASTs (from dedicated ASTs tests with 125 realizations per model)
11. Visualization of 6-band covariance matrices (~2000 models x 20 realizations per model)
12. BEAST Results PHAT Star in M31
13. Recovery of Simulated Star
17. MegaBEAST • Multi-level model • Hierarchical Bayesian model • Ensemble model • Works by modeling the outputs of the BEAST – Mathematically equivalent to modeling the observed fluxes! – But only needs to model the BEAST fit parameters • Age, mass, metallicity • A(V), R(V), f A • Account for completeness and star/dust geometry, star formation history, ...
20. Decomposed A(V) maps for Brick 21 Foreground M 31
21. BEAST/MegaBEAST Effort • Technique paper – Gordon et al. (2016, ApJ, 826, 104) • Active team – Gordon, Arab, Boyer, Choi, Durbin, Fouesneau, Johnson, Kapala, Kahn, Sandstrom, Weisz, Williams, Yanchulova Merica-Jones • BEAST hack week (20-24 Feb 2017, UCSD) – Code development, testing code, documentation, etc. – Using astropy affiliated package template – Extensions for AGB and YSOs in dicussion • BEAST is fairly mature – public on github at the end of Feb 2017 – Setup for distributed development of code, documentation, etc. • MegaBEAST in development
22. Thanks!