Quantum Algorithm
Quantum algorithms aim to leverage the principles of quantum mechanics to solve computational problems intractable for classical computers. Current research focuses on developing and applying quantum algorithms for optimization problems (e.g., using QAOA and VQE), machine learning (including quantum neural networks and quantum-enhanced classical models), and linear algebra tasks, often employing hybrid quantum-classical approaches. These advancements hold significant potential for accelerating various scientific fields and practical applications, such as drug discovery, materials science, and financial modeling, although the extent of near-term practical impact remains an active area of investigation.
Papers
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