Monika Schleier-Smith and Kent Irwin explain how their projects in quantum information science could help us better understand black holes and dark matter.

Researchers from SLAC and around the world increasingly use machine learning to handle Big Data produced in modern experiments and to study some of the most fundamental properties of the universe.

As members of the lab’s Computer Science Division, they develop the tools needed to handle ginormous data volumes produced by the next generation of scientific discovery machines.

The research team was able to watch energy from light flow through atomic ripples in a molecule. Such insights may provide new ways to develop a class of materials that improve efficiency and reduce the size of applications like solar cells and memory storage devices.