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 ...

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 ...

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

Researchers demonstrated a quantum algorithmic speedup with the quantum approximate optimization algorithm, laying the groundwork for advancements in telecommunications, financial modeling, materials ...

Over the past decades, computer scientists have developed various computing tools that could help to solve challenges in quantum physics. These include large-scale deep neural networks that can be ...

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 ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...