Randomized Benchmarking of Local Zeroth-Order Optimizers for Variational Quantum Systems
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Abstract (arXiv)
In the field of quantum information, classical optimizers play an important role. From experimentalists optimizing their physical devices to theorists exploring variational quantum algorithms, many aspects of quantum information require the use of a classical optimizer. For this reason, there are many papers that benchmark the effectiveness of different optimizers for specific quantum optimization tasks and choices of parameterized algorithms. However, for researchers exploring new algorithms or physical devices, the insights from these studies don't necessarily translate. To address this concern, we compare the performance of classical optimizers across a series of partially-randomized tasks to more broadly sample the space of quantum optimization problems. We focus on local zeroth-order optimizers due to their generally favorable performance and query-efficiency on quantum systems. We discuss insights from these experiments that can help motivate future works to improve these optimizers for use on quantum systems.
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References · 6
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2020Variational Quantum Algorithmscited by 692
- 2023On quantum backpropagation, information reuse, and cheating measurement collapsecited by 32
- 2022Do Quantum Circuit Born Machines Generalize?cited by 19
- 2020Natural Evolutionary Strategies for Variational Quantum Computationcited by 15
- 2021Adaptive shot allocation for fast convergence in variational quantum algorithmscited by 12
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