University System of Maryland

Ionq, Inc.

Yuan Su

Yunseong Nam

Jason Madjdi Amini

Kai Hudek

Dmitri Maslov

Michael Lurie Goldman

Jonathan Albert Mizrahi

Andrew Childs

Neil Julien Ross

The disclosure describes the implementation of automated techniques for optimizing quantum circuits of the size and type expected in quantum computations that outperform classical computers. The disclosure shows how to handle continuous gate parameters and report a collection of fast algorithms capable of optimizing large-scale-scale quantum circuits. For the suite of benchmarks considered, the techniques described obtain substantial reductions in gate counts. In particular, the techniques in this disclosure provide better optimization in significantly less time than previous approaches, while making minimal structural changes so as to preserve the basic layout of the underlying quantum algorithms. The results provided by these techniques help bridge the gap between computations that can be run on existing quantum computing hardware and more advanced computations that are more challenging to implement in quantum computing hardware but are the ones that are expected to outperform what can be achieved with classical computers.

Automated optimization of large-scale quantum circuits with continuous parameters

Growing community of inventors

Hyattsville, MD, United States of America

Yuan Su