The VRO: How Astronomy’s Biggest Dataset Will Change Your Universe
- Prof. Eric Morganson
The VRO: How Astronomys Biggest Dataset Will Change Your Universe - - PowerPoint PPT Presentation
The VRO: How Astronomys Biggest Dataset Will Change Your Universe Prof. Eric Morganson National Center for Supercomputing Applications University of Illinois July 20, 2020 The Name Thing Formerly: telescope and data were LSST (the Large
Formerly: telescope and data were LSST (the Large Synoptic Survey Telescope) Telescope: Vera Rubin Observatory Data: LSST (Legacy Survey of Space and Time)
Vera Rubin measured galaxy masses and discovered strong evidence for dark matter
How optical astronomy works How the Vera Rubin Observatory changes the game What we will learn How you can see the data
Map by Pan-STARRS, a telescope with a 1.8 meter mirror
SDSS, a 2.5 meter telescope (cheap) Subaru, an 8.1 meter telescope (expensive)
Left: The ALMA Radio Array Top Right: The Chandra X-Ray Telescope Bottom Right: An optical Spectrum
degree
○ 12 Years Most 8-10 m telescopes image the red circle
○ 5 nights Most 8-10 m telescopes image the red circle
○ Starting 2023
○ 100x deeper than previous surveys
○ Gets color information ○ Get light curve
Large mirror: expensive Large field of view: more precise engineering Large Mirror with Large Field of View: super expensive Gigantic CCD camera: super expensive and maybe impossible before 2010
○ 6200 LBS
○ 267 iPhones
○ 1 MacBook Pro
○ 20 MacBook Pros
○ 60 K MacBook Pros
astronomical data currently taken
Left: simulated galaxy mergers create “streams” Right: actual streams around the Milky Way
Left: star falling into black hole in a “Tidal Disruption Event” Right: Two Neutron stars spinning into a black hole
yearly (starting 2024)
○ Dark Energy Survey
○
des.ncsa.illinois.edu/easyweb
○ Image ○ Brightness ○ Location
○ Every observation of an object ○ Every new supernova* ○ Every observation of an asteroid
○ Download ○ Email ○ Tweet/text/??? *LSST will find 1,000 new supernova per night
large datasets
non-astronomy projects
dominated by LSST data
https://www.zooniverse.org/