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Hybrid Reinforcement Learning Enables Quantum Architecture Search And Optimizes Molecular Ground-State Energy
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Hybrid Reinforcement Learning Enables Quantum Architecture Search And Optimizes Molecular Ground-State Energy
A new artificial intelligence system autonomously designs quantum circuits for calculating molecular energies, achieving greater accuracy and compactness than existing methods by simultaneously optimising both the circuit’s structure and its internal settings.
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