Benchmarking quantum computing applications,
powered by Orquestra®
Zapata AI has been selected to help quantify the long-term utility of quantum computers — and the resources required to unlock that utility.
Quantum computers promise to deliver an exponential advantage over classical computers. What’s less clear is where quantum computers will unlock the most value, and when exactly that advantage could arrive.
To better understand the future utility of quantum computers, the US Government’s Department of Defense (more specifically, the Defense Advanced Research Projects Agency, or DARPA) is interested in developing valuable quantum use cases and building application-oriented benchmark tests to assess future quantum hardware backends. DARPA is also interested in estimating the hardware resources required for different quantum applications. This work will give the Department of Defense a clearer picture of when quantum computers will deliver a practical advantage, and help the quantum computing community identify inefficiencies and bottlenecks that can be overcome to bring that advantage closer.
In 2022, Zapata AI received the Phase I award for the Quantum Benchmarking program from the US Government. As part of the award, Zapata AI has worked alongside partners in enterprise, academia, and technology to:
As a result of the work in Phase I, Zapata AI and its partners announced the delivery of the first 30 quantum computing challenge scenarios in May 2023. The team has since introduced BenchQ, an open-source tool for resource estimation and benchmarking for quantum computing applications. To build on this work, Zapata AI announced in November 2023 that it had received the award for Phase II of the Quantum Benchmarking program, as a participant in both Technical Area 1 (TA1) and Technical Area 2 (TA2)
All benchmarking work has been supported by Orquestra®, Zapata AI’s platform for building Industrial Generative AI applications. Orquestra’s hardware-agnostic format makes it the ideal platform for benchmarking the performance of different hardware backends for specific, large-scale applications.
– Lead Quantum Applications Research Scientist, IonQ