Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy
By Lori Cameron
 

astronaut floating in space

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.

Read more about how scientists are working to build highly efficient machine-learning and image-analysis algorithms (login may be required for full text)


 

About Lori Cameron

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 l.cameron@computer.org. Follow her on LinkedIn.