A novel framework for Shot number minimization in Quantum Variational Algorithms

• URL: http://arxiv.org/abs/2307.04035v1
• Date: Sat, 8 Jul 2023 19:14:01 GMT
• Title: A novel framework for Shot number minimization in Quantum Variational Algorithms
• Authors: Seyed Sajad Kahani and Amin Nobakhti
• Abstract summary: Variational Quantum Algorithms (VQAs) have gained significant attention as a potential solution for various quantum computing applications. implementing these algorithms on quantum devices often necessitates a substantial number of measurements. This paper presents a generalized framework for optimization algorithms aiming to reduce the number of shot evaluations in VQAs.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Variational Quantum Algorithms (VQAs) have gained significant attention as a potential solution for various quantum computing applications in the near term. However, implementing these algorithms on quantum devices often necessitates a substantial number of measurements, resulting in time-consuming and resource-intensive processes. This paper presents a generalized framework for optimization algorithms aiming to reduce the number of shot evaluations in VQAs. The proposed framework combines an estimator and an optimizer. We investigate two specific case studies within this framework. In the first case, we pair a sample mean estimator with a simulated annealing optimizer, while in the second case, we combine a recursive estimator with a gradient descent optimizer. In both instances, we demonstrate that our proposed approach yields notable performance enhancements compared to conventional methods.

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