The U.S. Defense Advanced Projects Research Agency (DARPA) has provided an $8.6 million award over four years to a team including the Universities Space Research Assocation (USRA), Rigetti Computing, and NASA’s Quantum Artificial Intelligence Laboratory (QuAIL). The research will focus on advancing quantum hardware/software to help solve optimization problems such as scheduling and asset allocation. The grant is a part of the DARPA’s Optimization with Noisy Intermediate-Scale Quantum program (ONISQ) program which has a goal of establishing that quantum information processing using NISQ devices has a quantitative advantage for solving real-world-combinatorial optimization problems. These types of problems have a lot of applications within the U.S. military.
A key element of this research will be to leverage the Quantum Approximate Optimization Algorithm (QAOA) which uses a hybrid classical-quantum approach for solving these types of optimization problems. The Rigetti hardware has certain features, such as the colocation of the classical and the quantum computers, which provides performance advantages for these types of algorithms. Rigetti is also developing multi-core versions of their quantum computer which will exceed 100 qubits and we expect those machines to be used eventually in this program.
In general, the Rigetti team will be supplying the hardware while the NASA/USRA team will be concentrating on the algorithms. The NASA/USRA team will also work on benchmarking the algorithms against the high performance classical solutions so they can determine when a quantum advantage is achieved. There will also be certain areas where the teams will jointly study hardware/software tradeoffs to improve overall performance of the algorithms.
We asked the people at Rigetti if the team working on this program would be eligible for the $1 Million Quantum Advantage prize announced in September 2018 if it is successful. Apparently, the Rigetti employees and partners are excluded from winning the prize so it would still be available to other end users.
March 27, 2020