Phase transitions in big data
By using knowledge of phase transitions in physical systems, researchers can gain new insights into more efficient ways to answer questions about patterns and structures in sprawling datasets. SFI Professor Cris Moore recently organized a working group, held July 17–21 at SFI, that brought together experts from computer science, physics, and mathematics to explore connections between theoretical computer science and spin-glass theory, which is a framework for understanding phase transitions in complex materials.