Since its inception in June 1983, RIACS has conducted basic and applied research in computer science for the nation's aeronautics and space-related missions and programs. In 2012, USRA partnered with NASA and Google to found the Quantum Artificial Intelligence Laboratory (QuAIL): the space agency’s hub to evaluate the near term impact of quantum technologies.
The mission of RIACS quantum computing team is to advance the industry and the body of knowledge in quantum information related sciences, and to continue to provide to its partners the most qualified technical support to address hard challenges in applied computer science.
The paper "Information scrambling in quantum circuits" (https://www.doi.org/10.1126/science.abg5029) involving USRA researcher Jeffrey Marshall and collaborators published in Science. In this paper, the authors experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor.
The paper "Classical symmetries and the Quantum Approximate Optimization Algorithm" (https://doi.org/10.1007/s11128-021-03298-4) by Ruslan Shaydulin, Stuart Hadfield, Tad Hogg, and Ilya Safro published in Quantum Information Processing. In this paper, the authors study the relationship between the Quantum Approximate Optimization Algorithm (QAOA) and the underlying symmetries of the objective function to be optimized.
USRA and Q2B team up again in 2021 to organize the Applied NISQ Computing Best Paper Award competition. Submission of arXiv papers posted in the calendar year are eligible (see submission instructions) - Prize includes up to $5,000 in quantum computing cloud credits and a full ticket and travel to Practical Quantum Computing Q2B conference!
Paper "Quantum-accelerated constraint programming" (https://doi.org/10.22331/q-2021-09-28-550) by Kyle E. C. Booth, Bryan O'Gorman, Jeffrey Marshall, Stuart Hadfield, and Eleanor Rieffel accepted to Quantum. In this paper, the authors show how quantum algorithms can accelerate constraint programming, at both the levels of inference and search.
The paper From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz by Stuart Hadfield, Zhihui Wang, Bryan O’Gorman, Eleanor G. Rieffel, Davide Venturelli and Rupak Biswas published in MDPI Algorithm, Volume 12, Issue 2, doi: 10.3390/a12020034 has been selected as best paper from MDPI for 2020. The paper has been very influential at QuAIL at USRA generating numerous derivative work.