Efficient variational quantum eigensolver methodologies on quantum processors
Abstract
Adaptive and tetris-adaptive variational quantum eigensolver methods combined with entanglement forging and error mitigation techniques demonstrate effective ground state calculations for BeH2 on noisy quantum hardware.
We compare the performance of different methodologies for finding the ground state of the molecule BeH2. We implement adaptive, tetris-adaptive variational quantum eigensolver (VQE), and entanglement forging to reduce computational resource requirements. We run VQE experiments on IBM quantum processing units and use error mitigation, including twirled readout error extinction (TREX) and zero-noise extrapolation (ZNE) to reduce noise. Our results affirm the usefulness of VQE on noisy quantum hardware and pave the way for the usage of VQE related methods for large molecules.
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