Optimization with Noisy Intermediate-Scale Quantum devices (ONISQ)

The summary for the Optimization with Noisy Intermediate-Scale Quantum devices (ONISQ) grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the DARPA Defense Sciences Office, which is the U.S. government agency offering this grant.

Optimization with Noisy Intermediate-Scale Quantum devices (ONISQ): The Defense Sciences Office at the Defense Advanced Research Projects Agency (DARPA) is soliciting innovative research proposals in support of the Optimization with Noisy Intermediate-Scale Quantum devices (ONISQ) program. The goal of the ONISQ program is to establish that Quantum Information Processing (QIP) using Noisy Intermediate-Scale Quantum (NISQ) devices has a quantitative advantage for solving real-world combinatorial optimization problems as compared with the best known classical methods. In addition, the ONISQ program will develop a theoretical basis to explore the power of hybrid optimization approaches, including identifying families of problem instances in combinatorial optimization where QIP is likely to have the biggest impact. Proposed research should investigate innovative approaches that enable revolutionary advances in science, devices, and NISQ systems. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice. For the purposes of this BAA, QIP refers to quantum information processing using noisy, non-fault-tolerant devices. The advancement of fully fault-tolerant quantum computation is outside the scope of this BAA. Quantum annealing approaches are also explicitly excluded.