While physicists and engineers are working on building the computers of tomorrow — quantum computers, that is — Yu Tong is pushing the field forward from a different angle. As a mathematician and a theorist, he works not with subatomic particles and lasers, but with pencil and paper, designing algorithms for quantum computers.
“You have to use your quantum computers to do something and for that, you need algorithms,” said the new assistant professor of Mathematics and Electrical and Computer Engineering. “We need a new set of tools because the ideas behind quantum algorithms are usually very different than those for classical computers.”
In addition to developing algorithms, Tong also draws on math and theory to look for ways to use quantum computers. While small quantum computers can already solve a few specific types of problems, larger quantum computers will be capable of solving a much wider range. What type of problems? Researchers have only begun to answer that question.
“We don’t yet know what quantum computers are going to be able to do,” Tong said. He drew an analogy with today’s computers: “Back in the early days, no one thought they would be useful for Chat GPT.”
Quantum computers are more powerful than today’s supercomputers because they operate using the laws of quantum physics — the non-intuitive rules that govern how atomic and subatomic particles behave. One of these rules is superposition, which refers to particles existing in more than one place, or more than one state, at the same time. The way particles in superposition interfere with each other can be harnessed to create computational power vastly more efficient than the 1’s and 0’s of classical computing.
For certain applications, quantum computers are exponentially more efficient. For example, certain simulations on a quantum computer can be doubled in scale with only twice the energy, while doubling that simulation on today’s computers would take considerably more energy. That’s the reason today’s supercomputers fill entire rooms.
“That’s why I got into this field,” Tong said. “For so many of the problems we previously struggled with, there is a straightforward path to solving them with quantum computers.”
Tong uses mathematical proofs to explore what quantum computers are able to do in theory. “Right now, the hardware of quantum computers is not very reliable, but on the theory side, we have very good models of what a reasonable quantum computer can do,” he said, “and those models will enable us to analyze whether a problem is solvable or not on this computer.”
As a member of the Duke Quantum Center, Tong is looking forward to collaborating with experimentalists who can help keep his ideas grounded in reality. “As theorists, we tend to forget about the experimental side, because the things you can do in experiments are very limited compared to the things you can think about,” he said. “Sometimes we abuse this freedom and go too far into things people cannot do right now. Having experimentalists nearby forces us to think, ‘Can we do interesting things with hardware people can build right now?’”
The collaborative atmosphere at the Duke Quantum Center was a significant draw to Tong. “I feel there is much more conversation between experimentalists and theorists at the Duke Quantum Center than is typical in other places where there is a mix of both,” he said. “I think that’s a very interesting, very stimulating environment.”
Experimentalists at the Duke Quantum Center say the feeling is mutual. “We’re very interested in working with Yu Tong, who thinks about algorithms and applications,” said Christopher Monroe, the Duke Quantum Center’s director and the Gilhuly Family Presidential Distinguished Professor of Electrical and Computing Engineering and Physics. “People haven’t had these machines for very long, and we don’t know exactly how they can be applied. Yu is able to think about that in an abstract way. There aren’t that many people like that out there.”
Tong, who came to Duke from the Institute for Quantum Information and Matter at Caltech, is also developing guiding principles for designing quantum algorithms. These guidelines emphasize operations that early iterations of quantum computers will excel at, while minimizing operations unlikely to work as well, at least in the early days.
“We want to figure out what to use those computers for,” he said, “and how to use them in the most efficient manner.”
Tong’s work requires inspiration, which he says often hits while he’s out walking or discussing problems with colleagues.
“Doing theory works like mining,” he said, “sometimes you hit a gemstone; sometimes you just get dirt.”
Department of Mathematics