Two GEM Fellows reflect on their summer internships at SLAC and share their thoughts on representation and mentorship.

The facility, LCLS-II, will soon sharpen our view of how nature works on ultrasmall, ultrafast scales, impacting everything from quantum devices to clean energy.

SLAC’s Matt Garrett and Susan Simpkins talk about tech transfer that brings innovations from the national lab to the people, including advances for medical...

Teaching machine learning the basics of accelerator physics is particularly useful in situations where actual data don’t exist.

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

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...

Wan-Lin Hu’s job is to improve the way people and artificial intelligence collaborate to run SLAC’s complex machines.

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...