Federal Grant Award Summary

The University of Arizona received a $600,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070) for the period July 1, 2026 through June 30, 2029. The award funds research into enhanced quantum reservoir computing through non-Markovian environments, investigating whether a single atom interacting with light inside a waveguide can perform complex machine learning computations normally requiring large processor networks. The research team will develop a quantum reservoir computing framework utilizing a two-level atom strongly coupled to a mirror-terminated waveguide, with adjustable non-Markovian memory effects to increase computational complexity and efficiency. Deliverables include new complexity metrics for quantifying reservoir performance, theoretical and experimental validation of the computing approach, and documentation of transitions between memoryless and strongly non-Markovian system regimes.

Beyond research outputs, the award supports significant workforce development initiatives including a quantum boot camp for high school and undergraduate students, integration of research findings into university coursework in quantum optics and machine learning, K-12 outreach activities in collaboration with local organizations, and open-access dissemination of software tools and publications. The project addresses fundamental challenges in energy-efficient computing for edge applications where power and size constraints are critical, with potential applications in real-time processing systems requiring minimal hardware footprint.