SYRACUSE, N.Y. - BosonQ Psi Federal LLC (BQP), of Syracuse, N.Y., has received a SpaceWERX Small Business Innovation Research (SBIR) award to develop a quantum-inspired artificial intelligence application designed to improve space domain awareness. The company did not disclose the value of the award. The project will focus on developing and validating a Physics-Constrained Quantum-Assisted Machine Learning (PC-QAML) software application intended to improve the identification and classification of unknown objects and behaviors in Earth’s orbital environment. Space domain awareness organizations monitor thousands of objects in orbit, including operational satellites, debris, and other objects that may require additional analysis. BosonQ Psi Federal says its technology is designed to address challenges associated with uncorrelated tracks, which are detections that cannot immediately be matched to known objects. Related: Researchers eye quantum, photonic, and bio/organic integrated circuits for next-gen transistor technology Physics meets quantum The company says its PC-QAML approach combines physics-based modeling with quantum-inspired computational techniques to reduce the computational requirements of artificial intelligence models while maintaining accuracy. The technology is designed for deployment on edge computing platforms where processing capability, power consumption, and communications availability may be constrained. According to BosonQ Psi Federal, its approach reduces the size of AI models from approximately 14 million parameters to about 2,000 parameters while maintaining greater than 99% classification accuracy. The company also reports up to a tenfold reduction in inference latency and approximately 90% lower power consumption compared with conventional machine learning approaches. The company says the technology has previously been demonstrated on an NVIDIA Jetson Nano edge computing platform at the Space Domain Awareness TAP Lab, where it was evaluated for orbital separation detection during the 2025 SDA Mini-Accelerator. BosonQ Psi Federal identifies PC-QAML as a candidate technology for future uncorrelated track classification and Threat Simulation Catalog integration. BosonQ Psi Federal develops software