Example Output of BenchQ that Compares Qubit Requirements and Run Time for Ion Trap versus Superconducting Architectures.
Credit: Zapata AI

One of the products that has resulted from the DARPA Quantum Benchmarking program that we reported on earlier this month is BenchQ, a tool developed by Zapata AI along with partners at Aalto University, IonQ, the University of Technology Sydney, and the University of Texas at Dallas. A key purpose of the tool is to provide a user with an estimate of the quantum processor resources required to solve high-utility problems. As an example, Zapata has used the tool to provide estimates of the number of qubits and run time needed to calculate the ground state energy of various molecules. The tool assumes a processor with a fault tolerant computing architecture. It can be used by hardware designers to help them set hardware design goals to optimize their hardware architecture for most efficient processing of various problems. It can also be used by algorithm designers to give them a sense of what capabilities of a future quantum processor are needed in order to successfully run their programs.

As part of the DARPA program, the team developed 30 application scenarios to run on BenchQ and will be developing additional scenarios as part of their continuing research. Additional information about BenchQ can be found on a blog article posted on the Zapata website here and the code can be accessed on the GitHub site for BenchQ here.

December 14, 2023