Pi-QEM selects dominant low-weight Pauli strings for ML training in quantum error mitigation, reducing ground-state energy estimation error by up to 34.01% using a single observable in molecular simulations on noisy IBM backends.
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Pauli Weight Hamiltonian Term Selection for Optimized Machine Learning Based Quantum Error Mitigation
Pi-QEM selects dominant low-weight Pauli strings for ML training in quantum error mitigation, reducing ground-state energy estimation error by up to 34.01% using a single observable in molecular simulations on noisy IBM backends.