Machine Learning System Improves Accelerator Diagnostics

A machine learning system is helping operators resolve routine faults at the Continuous Electron Beam Accelerator Facility (CEBAF). The system monitors the accelerator cavities, where faults can trip off the CEBAF. The system identified which cavities were tripping off about 85% of the time and identified the type of fault about 78% of the time.

New machine learning tool diagnoses electron beams in an efficient, non-invasive way

For the past few years, researchers at the Department of Energy’s SLAC National Accelerator Laboratory have been developing “virtual diagnostics” that use machine learning to obtain crucial information about electron beam quality in an efficient, non-invasive way. Now, a new virtual diagnostic approach incorporates additional information about the beam that allows the method to work in situations where conventional diagnostics have failed.

Fermilab delivers final superconducting particle accelerator component for world’s most powerful laser

Fermilab gives a sendoff to the final superconducting component for the LCLS-II particle accelerator at SLAC National Accelerator Laboratory in California. LCLS-II will be the world’s brightest and fastest X-ray laser. A partnership of particle accelerator technology, materials science, cryogenics and energy science, LCLS-II exemplifies cross-disciplinary collaboration across DOE national laboratories.

U.S. Department of Energy Announces $18 Million to Advance Particle Accelerator Technologies and Workforce Training

he U.S. Department of Energy (DOE) today announced $18 million in new funding to advance particle accelerator technology, a critical tool for discovery sciences and optimizing the way we treat medical patients, manufacture electronics and clean energy technologies, and defend the nation against security threats.

Cheaper, greener particle accelerators will speed innovation

A team of scientists at the Center for Bright Beams (CBB) – a National Science Foundation Science and Technology Center led by Cornell University – are working on the next generation of superconducting materials that will greatly reduce the costs associated with operating large particle accelerators and lessen their environmental impact.

Research Fellow Turns to Accelerator Power for Wastewater Cleanup

In honor of Hermann Grunder, the founding director of Jefferson Lab, and his contributions to accelerator science, the lab recently established the Hermann Grunder Postdoctoral Fellowship in Accelerator Science. Now, the first Hermann Grunder fellow, John Vennekate, has started work. He said he hopes to follow in the footsteps of his fellowship’s namesake to continue blazing a new trail for practical applications of superconducting accelerators.

After 20 years, physicists find a way to keep track of lost accelerator particles

Physicists at Oak Ridge National Laboratory have developed a measurement technique to better understand beam loss—stray particles that travel outside the confinement fields of a particle accelerator. Mitigating beam loss is paramount to realizing more powerful accelerators at smaller scales and lower costs.

Remote-Working Team to Tame Electron Beams

A major injector upgrade at the U.S. Department of Energy’s Thomas Jefferson National Accelerator Facility was well underway early last year when the pandemic hit, throwing scientists and their long-anticipated project for a loop. Literally overnight, they had to leave their desks, control room and colleagues behind and rapidly learn how to work together from the confines of their own homes.

Machine Learning Improves Particle Accelerator Diagnostics

Operators of Jefferson Lab’s primary particle accelerator are getting a new tool to help them quickly address issues that can prevent it from running smoothly. The machine learning system has passed its first two-week test, correctly identifying glitchy accelerator components and the type of glitches they’re experiencing in near-real-time. An analysis of the results of the first field test of the custom-built machine learning system was recently published in the journal Physical Review Accelerators and Beams.

American Vacuum Society Honors Jefferson Lab Accelerator Scientist

Some of the most advanced work to enable research at the U.S. Department of Energy’s Thomas Jefferson National Accelerator Facility is focused on ensuring that nothing gets in the way of the electron beam produced for nuclear physics experiments. Now, one Jefferson Lab staff scientist is being honored for her work on producing ultra-high to extreme-high vacuum environments to do just that.

Fermilab achieves 14.5-tesla field for accelerator magnet, setting new world record

Fermilab scientists have broken their own world record for an accelerator magnet. In June, their demonstrator steering dipole magnet achieved a 14.5-tesla field, surpassing the field strength of their 14.1-tesla magnet, which set a record in 2019. This magnet test shows that scientists and engineers can meet the demanding requirements for the future particle collider under discussion in the particle physics community.

Three Fermilab scientists receive DOE Early Career Research Awards

The Department of Energy’s Office of Science has selected three Fermilab scientists to receive the 2020 DOE Early Career Research Award, now in its 11th year. The prestigious award is designed to bolster the nation’s scientific workforce by providing support to exceptional researchers during the crucial early years, when many scientists do their most formative work.

In International Physics Collaborations, Working Remotely Is Nothing New

Marjorie Shapiro, an experimental particle physicist and faculty senior scientist at Berkeley Lab, has been accustomed to working remotely and observing extreme social distancing from some colleagues for years, given that the scientific experiment she supports is 5,800 miles away.