Quantum computers promise to outperform today’s traditional computers in many areas of science, including chemistry, physics, and cryptography, but proving they will be superior has been challenging. The most well-known problem in which quantum computers are expected to have the edge, a trait physicists call “quantum advantage,” involves factoring large numbers, a hard math problem that lies at the root of securing digital information.

In 1994, Caltech alumnus Peter Shor (BS ‘81), then at Bell Labs, developed a quantum algorithm that would easily factor a large number in just seconds, whereas this type of problem could take a classical computer millions of years. Ultimately, when quantum computers are ready and working—a goal that researchers say may still be a decade or more away—these machines will be able to quickly factor large numbers behind cryptography schemes.

But, besides Shor’s algorithm, researchers have had a hard time coming up with problems where quantum computers will have a proven advantage. Now, reporting in a recent Nature Physics study titled “Local minima in quantum systems,” a Caltech-led team of researchers has identified a common physics problem that these futuristic machines would excel at solving. The problem has to do with simulating how materials cool down to their lowest-energy states.