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arxiv: 2311.01105 · v2 · pith:OEIYDOZGnew · submitted 2023-11-02 · 🪐 quant-ph

ADAPT-QSCI: Adaptive Construction of an Input State for Quantum-Selected Configuration Interaction

classification 🪐 quant-ph
keywords statequantuminputqsciadapt-qsciadaptiveconstructionmethod
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We present a quantum-classical hybrid algorithm for calculating the ground state and its energy of the quantum many-body Hamiltonian by proposing an adaptive construction of a quantum state for the quantum-selected configuration interaction (QSCI) method. QSCI allows us to select important electronic configurations in the system to perform CI calculation (subspace diagonalization of the Hamiltonian) by sampling measurement for a proper input quantum state on a quantum computer, but how we prepare a desirable input state has remained a challenge. We propose an adaptive construction of the input state for QSCI in which we run QSCI repeatedly to grow the input state iteratively. We numerically illustrate that our method, dubbed ADAPT-QSCI, can yield accurate ground-state energies for small molecules, including a noisy situation for eight qubits where error rates of two-qubit gates and the measurement are both as large as 1%. ADAPT-QSCI serves as a promising method to take advantage of current noisy quantum devices and pushes forward its application to quantum chemistry.

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    XGBoost models trained on ≤16-qubit data predict eigensolver hyperparameters and reduce error by 0.12% on 28-qubit systems.