Software tools for quantum control: Improving quantum computer performance through noise and error suppression

• DOI: 10.48550/arxiv.2001.04060
• Publication Date: 2020-01-01
• Authors: Harrison Ball; Michael J. Biercuk; André Carvalho; Jiayin Chen; Michael Hush; Leonardo Andreta ...; Li Li; Per Liebermann; Harry J. Slatyer; Claire Edmunds; Virginia Frey; Cornelius Hempel; Alistair Milne
• Keywords: Quantum Physics; 0103 physical sciences; FOS: Physical sciences; Quantum Physics (quant-ph); 01 natural sciences

Manipulating quantum computing hardware in the presence of imperfect devices and control systems is a central challenge realizing useful computers. Susceptibility to noise limits performance capabilities noisy intermediate-scale (NISQ) devices, as well any future technologies. Fortunately enables efficient execution logic operations algorithms with built-in robustness errors, without need for complex logical encoding. In this manuscript we introduce software tools application integration research, serving needs R&D teams, algorithm developers, end users. We provide an overview set python-based classical creating deploying optimized solutions at various layers stack. describe architecture leveraging both high-performance distributed cloud computation local custom into systems, explain how key functionality integrable other packages programming languages. Our presentation includes detailed mathematical product features including flexible optimization toolkit, filter functions analyzing susceptibility high-dimensional Hilbert spaces, new approaches characterization. Pseudocode presented order elucidate common workflows these tasks, benchmarking reported numerically intensive highlighting benefits selected cloud-compute architecture. Finally, present series case studies demonstrating using real experimental settings trapped-ion superconducting computer hardware.