Demonstration of a CAFQA-bootstrapped Variational Quantum Eigensolver on a Trapped-Ion Quantum Computer

• URL: http://arxiv.org/abs/2408.06482v1
• Date: Mon, 12 Aug 2024 20:30:37 GMT
• Title: Demonstration of a CAFQA-bootstrapped Variational Quantum Eigensolver on a Trapped-Ion Quantum Computer
• Authors: Qingfeng Wang, Liudmila Zhukas, Qiang Miao, Aniket S. Dalvi, Peter J. Love, Christopher Monroe, Frederic T. Chong, Gokul Subramanian Ravi,
• Abstract summary: We develop a novel hardware-software interface framework to support independent software environments for both the circuit and hardware end. This framework can be applied to a variety of academic quantum devices beyond the trapped-ion quantum computer platform.
• Score: 3.1248137848871647
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: To enhance the variational quantum eigensolver (VQE), the CAFQA method can utilize classical computational capabilities to identify a better initial state than the Hartree-Fock method. Previous research has demonstrated that the initial state provided by CAFQA recovers more correlation energy than that of the Hartree-Fock method and results in faster convergence. In the present study, we advance the investigation of CAFQA by demonstrating its advantages on a high-fidelity trapped-ion quantum computer located at the Duke Quantum Center -- this is the first experimental demonstration of CAFQA-bootstrapped VQE on a TI device and on any academic quantum device. In our VQE experiment, we use LiH and BeH$_2$ as test cases to show that CAFQA achieves faster convergence and obtains lower energy values within the specified computational budget limits. To ensure the seamless execution of VQE on this academic device, we develop a novel hardware-software interface framework that supports independent software environments for both the circuit and hardware end. This mechanism facilitates the automation of VQE-type job executions as well as mitigates the impact of random hardware interruptions. This framework is versatile and can be applied to a variety of academic quantum devices beyond the trapped-ion quantum computer platform, with support for integration with customized packages.

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