Accelerating Noisy VQE Optimization with Gaussian Processes

Conference · Thu Sep 01 00:00:00 EDT 2022 · 2022 IEEE International Conference on Quantum Computing and Engineering (QCE)

DOI:https://doi.org/10.1109/qce53715.2022.00041· OSTI ID:1961346

Muller, Juliane ^[1]; Lavrijsen, Wim ^[1]; Iancu, Costin ^[1]; de Jong, Wibe ^[1]

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1. Lawrence Berkeley National Laboratory,Computing Sciences Area,Berkeley,CA,USA

Hybrid variational quantum algorithms, which combine a classical optimizer with evaluations on a quantum chip, are the most promising candidates to show quantum advantage on current noisy, intermediate-scale quantum (NISQ) devices. The classical optimizer is required to perform well in the presence of noise in the objective function evaluations, or else it becomes the weakest link in the algorithm. We introduce the use of Gaussian Processes (GP) as surrogate models to reduce the impact of noise and to provide high quality seeds to escape local minima, whether real or noise-induced. We build this as a framework on top of local optimizations, for which we choose Implicit Filtering (ImFil) in this study. ImFil is a state-of-the-art, gradient-free method, which in comparative studies has been shown to outperform on noisy VQE problems. The result is a new method: "GP+ImFil". We show that when noise is present, the GP+ImFil approach finds results closer to the true global minimum in fewer evaluations than standalone ImFil, and that it works particularly well for larger dimensional problems. Using GP to seed local searches in a multi-modal landscape shows mixed results: although it is capable of improving on ImFil standalone, it does not do so consistently and would only be preferred over other, more exhaustive, multistart methods if resources are constrained.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1961346
• Journal Information: 2022 IEEE International Conference on Quantum Computing and Engineering (QCE), Conference: 2022 IEEE International Conference on Quantum Computing and Engineering (QCE), Broomfield, CO (United States), 18-23 Sep 2022
• Country of Publication: United States
• Language: English