Tutorial: calibration refinement in quantum annealing

Frontiers in Computer Science

Computer Science

Pau Farré¹  Kelly Boothby¹  Jack Raymond¹  Kevin Chern¹  Andrew D. King² 

[1] D-Wave, Burnaby, BC, Canada;null;

关键词: quantum computing;    quantum annealing;    D-Wave;    calibration;    quadratic unconstrained binary optimization;    Ising;   

DOI  :  10.3389/fcomp.2023.1238988

 received in 2023-06-12, accepted in 2023-08-17,  发布年份 2023

来源: Frontiers

【 摘 要 】

Quantum annealing has emerged as a powerful platform for simulating and optimizing classical and quantum Ising models. Quantum annealers, like other quantum and/or analog computing devices, are susceptible to non-idealities including crosstalk, device variation, and environmental noise. Compensating for these effects through calibration refinement or “shimming” can significantly improve performance but often relies on ad-hoc methods that exploit symmetries in both the problem being solved and the quantum annealer itself. In this tutorial, we attempt to demystify these methods. We introduce methods for finding exploitable symmetries in Ising models and discuss how to use these symmetries to suppress unwanted bias. We work through several examples of increasing complexity and provide complete Python code. We include automated methods for two important tasks: finding copies of small subgraphs in the qubit connectivity graph and automatically finding symmetries of an Ising model via generalized graph automorphism. We conclude the tutorial by surveying additional methods, providing practical implementation tips, and discussing limitations and remedies of the calibration procedure. Code is available at: https://github.com/dwavesystems/shimming-tutorial.

【 授权许可】

Unknown   
Copyright © 2023 Chern, Boothby, Raymond, Farré and King.