Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy
By Lori Cameron
Share this on:
The Sloan Digital Sky Survey is the largest astronomical survey, producing 200 gigabytes of data every night. While it has already acquired nearly a million field images of more than 200 million galaxies, future surveys will amass even greater data volumes. The Large Synoptic Survey Telescope, currently in development, promises to capture a whopping 30,000 gigabytes of data every night (30 terabytes), requiring efficient and accurate analysis of never-before-seen cosmological events. The challenge of big data is teaching computers to capture galaxy images while determining the properties of those galaxies with high precision.
Lori Cameron is a Senior Writer for the IEEE Computer Society and currently writes regular features for Computer magazine, Computing Edge, and the Computing Now and Magazine Roundup websites. Contact her at email@example.com. Follow her on LinkedIn.