Quantum Computation

Quantum computation aims to leverage quantum mechanical phenomena for computational advantages over classical approaches, primarily focusing on solving currently intractable problems. Current research emphasizes developing and refining quantum algorithms for machine learning tasks, including variational methods, quantum neural networks, and kernel-based approaches, often implemented on near-term quantum devices like quantum annealers and gate-based systems. These efforts are driven by the potential to improve the efficiency and capabilities of machine learning, materials science simulations, and optimization problems, although significant challenges in hardware scalability and noise mitigation remain.