Deep Learning of Astronomical Spectroscopy

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Presentation transcript:

Deep Learning of Astronomical Spectroscopy J. Xavier Prochaska (UC Santa Cruz) Also starring: D. Parks, S. Dong, Z. Cai, V. Jankov

Who am I? J. Xavier Prochaska Professor of Astronomy & Astrophysics -- Spectroscopist (Former) Astronomer of UC Observatories First-class programmer (I think) Obsessed fan of Deep Learning Poised to dedicate the rest(?!) of my career to this adventure

Spectroscopy Astronomy Astrophysics Discovery, color, shape, location Velocity, composition, density, mass

Spectrum 2D Spectrum (Image) 1D Spectrum (array)

(Large) Spectral Datasets SDSS/BOSS (present) DESI (future) Spectra of ~1 million sources Spectra of ~20 million sources

Hydrogen Atom: “Lyman Alpha” By A_hidrogen_szinkepei.jpg: User:Szdoriderivative work: OrangeDog (talk • contribs) - A_hidrogen_szinkepei.jpg, CC BY 2.5, https://commons.wikimedia.org/w/index.php?curid=6273602

Damped Lya System (Galaxy)

CNN Classification + Spectral Analysis 400 pixel window Parks, X, Dong, Cai 2018

CNN Results Galaxy Surface Galaxy Redshift Density (position) Parks, X, Dong, Cai 2018

New Results CNN learned to ignore sky line Parks, X, Dong, Cai 2018

Peering into the Black Box.. Did the CNN learn the Lorentzian profile?!

SPectral Image Typing (SPIT) Jankov & X 2018

Future Work: U-net for Feature Detection Cai & X 2019

Future Work: GAN for outlier detection X & Huertas-Company 2019

Future Work: RNN for system detection Dong et al. 2019