�糵����

Whether you’re conducting a symphony or you’re conducting an experiment in particle accelerator physics, creating perfect resonance is always a thing of beauty.

When Minghao Song (Ph.D. PHYS ’22) conducted his Ph.D. thesis at SLAC National Accelerator Laboratory in Menlo Park, California, his work studying autoresonant excitation of accelerator electron beams and his development and application of machine-learning methods in storage ring design and online optimizations earned him the .

What is autoresonant excitation? It’s a method that allows physicists to control the amplitude of a nonlinear oscillator—a system that moves back and forth, repeatedly returning to its initial state. By sweeping the frequency of the driver (the oscillating object), physicists are able to match the drive frequency with the particles’ natural oscillation frequency, resulting in larger beam amplitudes.

“My study included a derived theory of how to successfully drive the accelerator electron beams to large amplitudes with autoresonant excitation,” says Song, explaining that the electron beam’s oscillation is more sustainable using this method, which results in more precise information. “We can get thousands—or even tens of thousands—of numbers of turns of the beam oscillation. The precision of measuring nonlinear beam dynamics will be much more accurate compared to the traditional method using kicker magnets.”

While Song has already made a name for himself in his young career in the field of accelerator physics, it’s the interdisciplinary nature of the field that excites him most. He takes the opportunity of testing and improving his own abilities in related areas as a personal challenge.

“It involves accelerator physics, magnetic engineering, mechanical design—experts from all kinds of fields,” says Song. “Doing research in the accelerator field can really broaden your horizons and improve your personal capabilities. It’s really a great field to do research.”

His start in accelerator physics came while he was a master’s student and continued in 2017 when he began his Ph.D. in physics at Illinois Tech.

“There are many research opportunities in the Department of Physics,” says Song. “My Ph.D. adviser—[Emeritus Professor of Physics] Linda Spentzouris—gave me the opportunity to do research with her and recommended me to [SLAC National Accelerator Laboratory Senior Scientist] Xiaobiao Huang to do my Ph.D. thesis work under his guidance.”

The sheer size and abilities of the particle accelerator in Menlo Park sparked Song’s curiosity and continues to drive his interest in particle physics to this day.

“I was really fascinated by the sophisticated and big particle accelerator!” says Song. “I’m also curious how it could accelerate electron particles close to the speed of light and produce a very bright photon beam. I keep this curiosity and fascination.”

Now a research associate at Brookhaven National Laboratory in New York, he’s building on his Ph.D. work, aiming to make upgrades to the National Synchrotron Light Source II (NSLS-II).

“One goal is to deliver a reliable storage ring lattice for the NSLS-II upgrade in the future,” says Song, noting how a more reliable storage ring lattice would achieve a lower beam emittance, long straights for insertion devices, sufficient free space, optimal nonlinear beam dynamics and robustness to magnet errors. “Another goal is to develop useful methods that are based on the machine learning technique and to optimize accelerator performance.”