Researchers across the lab are developing AI tools to harness data and particle beams in real time and make molecular movies, speeding up the discovery process in the era of big data.

The high-energy upgrade will keep the U.S. at the forefront of X-ray science and technology, allowing researchers to advance fields such as sustainability, human health and quantum information.

David Cesar, Julia Gonski and W.L. Kimmy Wu will each receive $2.75 million issued over five years for their research in X-ray and ultrafast science, new physics and primordial gravitational waves.

What could smaller particle accelerators look like in the future? SLAC scientists are working on innovations that could give more researchers access to accelerator science.

Sebek’s extraordinary career at SSRL includes helping build the facility’s original electron injector back in the 1980s and working on almost all of its electrical systems since.

The long – but not too long – cavity would ping-pong X-ray pulses inside of a particle accelerator facility to help capture nature’s fastest movements.

The algorithm pairs machine-learning techniques with classical beam physics equations to avoid massive data crunching.

Knowing a magnet’s past will allow scientists to customize particle beams more precisely in the future. As accelerators stretch for higher levels of performance, understanding subtle effects, such as those introduced by magnetic history, is becoming more critical.

Edelen draws on machine learning to fine tune particle accelerators, while Kurinsky develops dark matter detectors informed by quantum information science.