Astronomy Colloquium

Image
Image
Edge-On Spiral Galaxy
September 26, 2019
4:00PM - 5:00PM
Location
E0040 Scott Laboratory

Date Range
Add to Calendar 2019-09-26 16:00:00 2019-09-26 17:00:00 Astronomy Colloquium

Into the Starlight: Learning the Milky Way

Yuan-Sen Ting - Institute for Advanced Study

Understanding physical processes responsible for the formation and evolution of galaxies, like the Milky Way, is a fundamental but unsolved problem in astrophysics. Most stars are long-lived, using the stars as “fossil records” (what is known as Galactic archaeology) can offer unparalleled insight into the assembly of galaxies. In recent years, the landscape of Galactic archaeology is rapidly changing, thanks to ongoing large-scale surveys (astrometry, photometry, spectroscopy, and asteroseismology), which provide a few orders of magnitude more stars than before. In this talk, I will discuss new “phenomenological” opportunities enabled by large surveys. I will also discuss how machine-learning tools could leverage the big data about the Milky Way by maximally harnessing information from low-resolution spectra and photometric fluxes of stars. Finally, I will present new opportunities that will soon be enabled by LSST and DESI.

Coffee and Donuts will be served at 3:30pm in 4054 McPherson Lab.

E0040 Scott Laboratory Department of Astronomy astronomy@osu.edu America/New_York public
Description

Into the Starlight: Learning the Milky Way

Yuan-Sen Ting - Institute for Advanced Study

Understanding physical processes responsible for the formation and evolution of galaxies, like the Milky Way, is a fundamental but unsolved problem in astrophysics. Most stars are long-lived, using the stars as “fossil records” (what is known as Galactic archaeology) can offer unparalleled insight into the assembly of galaxies. In recent years, the landscape of Galactic archaeology is rapidly changing, thanks to ongoing large-scale surveys (astrometry, photometry, spectroscopy, and asteroseismology), which provide a few orders of magnitude more stars than before. In this talk, I will discuss new “phenomenological” opportunities enabled by large surveys. I will also discuss how machine-learning tools could leverage the big data about the Milky Way by maximally harnessing information from low-resolution spectra and photometric fluxes of stars. Finally, I will present new opportunities that will soon be enabled by LSST and DESI.

Coffee and Donuts will be served at 3:30pm in 4054 McPherson Lab.