Efficient variational quantum eigensolver methodologies on quantum processors

• URL: http://arxiv.org/abs/2407.16107v1
• Date: Tue, 23 Jul 2024 00:38:34 GMT
• Title: Efficient variational quantum eigensolver methodologies on quantum processors
• Authors: Tushar Pandey, Jason Saroni, Abdullah Kazi, Kartik Sharma,
• Abstract summary: We implement adaptive, tetris-adaptive variational quantum eigensolver (VQE) and entanglement forging to reduce computational resource requirements. 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.
• Score: 4.192048933715544
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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