Federal Grant Award Summary

The Pennsylvania State University received a $300,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences (CFDA 47.049) effective July 1, 2026, through June 30, 2029. The award funds research to develop a systematic framework that accelerates reinforcement learning (RL) for complex systems governed by ordinary and differential-algebraic equations. The core innovation involves a novel procedure termed moment-closed differential algebra that transforms nonlinear physics-based models into linear mappings by embedding trajectories into time-dependent Schrödinger equations while preserving system constraints. The research reformulates policy iteration as a bilinear quantum control problem to enable efficient updates, reducing the dominant computational costs of model-based reinforcement learning to quantum operations such as Hamiltonian simulation and amplitude estimation.

The project deliverables include new quantum-accelerated algorithms that integrate machine learning with quantum hardware to accelerate training for artificial intelligence systems controlling complex infrastructure such as power grids and advanced robotics. Beyond core research products, the award supports broader impacts through workforce development initiatives, including new courses integrating quantum and machine learning concepts, student research opportunities, and public outreach events. The research directly advances national priorities in artificial intelligence and quantum science by enabling the design of safe and resilient technologies while demonstrating potential exponential speedups through favorable dimension scaling in quantum-classical hybrid approaches.