Say you’re an aspiring physicist, probing the quantum world to gain insight into the fundamental nature of reality.
There are two ways to go about your scientific odyssey, but both involve very expensive machinery. One way is to smash a bunch of atoms together, revealing their subatomic guts; another is to toss them under a ray of light, illuminating a nanoscopic trajectory across space.
A group of theoretical physicists at Northeastern are setting out to do the latter, with millions in new funding. They are part of a multi-institutional team that received a $2.7 million grant from the Department of Energy for a project aimed at developing a set of machine-learning tools and associated software that will help researchers better interpret quantum images produced by one of the world’s largest and most powerful particle accelerators, the billion-dollar Stanford Linear Accelerator.
The funding for the project will be split more or less equally between Northeastern University, Howard University—the lead institution involved—and the Stanford Linear Accelerator Center (SLAC).
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