A quantum computer can solve optimization problems faster than classical supercomputers, a process known as “quantum advantage” and demonstrated by a USC researcher in a paper recently published in Physical Review Letters. The study shows how quantum annealing, a specialized form of quantum computing, outperforms the best current classical algorithms when searching for near-optimal solutions to complex problems. “The way quantum annealing works is by finding low-energy states in quantum systems, which correspond to optimal or near-optimal solutions to the problems being solved,” said Daniel Lidar, corresponding author of the study and professor of electrical and computer engineering, chemistry, and physics and astronomy at the USC Viterbi School of Engineering and the USC Dornsife College of Letters, Arts and Sciences. Scientists have been struggling to demonstrate quantum scaling advantage (where the quantum advantage grows as the problem size increases) through the use of a quantum annealer for years. Quantum annealing has long been theorized to offer computational advantages for optimization, but definitive evidence of scaling improvements over classical methods has been elusive.

Full report : Quantum computer outperforms supercomputers in approximate optimization tasks.