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.

Over the past few years, Kathleen Ratcliffe and Tien Fak Tan have worked together to help build the superconducting accelerator that will drive new scientific discoveries at SLAC’s X-ray laser.

From the invisible world of elementary particles to the mysteries of the cosmos, recipients of this prestigious award for early career scientists explore nature at every level.

At the Machine Shop, Pete Franco crafts beautiful, intricate and precise parts for the lab’s latest scientific tools.

FACET-II will pave the way for a future generation of particle colliders and powerful light sources, opening avenues in high-energy physics, medicine, and materials, biological and energy science.

Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.

It uses terahertz radiation to power a miniscule copper accelerator structure.

This leap in capability will allow scientists to investigate quantum and chemical systems more directly than ever before.

Marking the beginning of the LCLS-II era, the first phase of the major upgrade comes online.

Researchers have squeezed a high-energy electron beam into tight bundles using terahertz radiation, a promising advance in watching the ultrafast world of atoms unfold.

SLAC scientists and collaborators are developing 3D copper printing techniques to build accelerator components.