Quantum-inspired swarm optimisation applies principles of quantum mechanics to enhance swarm intelligence algorithms for complex systems. It extends classical particle swarm optimisation by ...

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 ...

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

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 ...

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 ...

Researchers have suggested to use a hybrid version of the so-called salp swarm algorithm (SSA) algorithm for maximum power point tracking in PV systems operating under highly fluctuating environmental ...