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Rapidly Achieving Chemical Accuracy with Quantum Computing Enforced Language Model (2405.09164v1)

Published 15 May 2024 in quant-ph

Abstract: Finding accurate ground state energy of a many-body system has been a major challenge in quantum chemistry. The integration of classic and quantum computers has shed new light on resolving this outstanding problem. Here we propose QiankunNet-VQE, a transformer based LLMs enforced with quantum computing to learn and generate quantum states. It has been implemented using up to 12 qubits and attaining an accuracy level competitive with state-of-the-art classical methods. By leveraging both quantum and classical resources, this scheme overcomes the limitations of variational quantum eigensolver(VQE) without the need for cumbersome error mitigation. Moreover, QiankunNet-VQE provides a different route to achieve a practical quantum advantage for solving many-electron Schr\"odinger equation without requiring extremely precise preparation and measurement of the ground-state wavefunction on quantum computer.

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