Researchers have developed a quantum particle swarm optimization algorithm for maximum power point tracking that reportedly generates 3.33% more power in higher temperature tests and 0.89% more power ...

Optimization algorithms seek the best possible solutions to complex problems by iteratively refining candidate solutions. Swarm intelligence techniques draw inspiration from collective behaviours in ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

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 ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...