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BBN Developing Photonic Chip Quantum Sensors under DARPA’s INSPIRED

RTX BBN Technologies is advancing the development of compact photonic quantum sensors under DARPA’s INSPIRED program. The sensors leverage quantum states of squeezed light to achieve over ten times the precision of current systems, with potential applications in LiDAR, biosensing, network monitoring, and navigation. These devices aim to overcome the shot noise limit, a fundamental barrier in conventional sensors, to provide higher accuracy for both defense and commercial uses.

The project focuses on designing and prototyping a photonic chip-scale detector capable of measuring photon properties with unprecedented sensitivity. This detector uses squeezed light to reduce quantum fluctuations, enhancing the ability to detect weak signals across frequencies from 100 MHz to 10 GHz. The BBN-led effort brings together expertise from Xanadu Quantum, the University of Maryland, and Raytheon’s Advanced Technology division, with contributions spanning quantum measurement, integrated photonics, and rapid prototyping.

Fabrication challenges include transferring squeezed-light capabilities from large lab setups to millimeter-scale chips suitable for field deployment. The program also explores integration into compact systems for a variety of applications, from autonomous navigation to communication and sensing. Work is ongoing across facilities in Massachusetts, Maryland, California, and Canada.

Key Points

Technology: Photonic chip quantum sensors using squeezed light.

Applications: LiDAR, fiber-based sensing, navigation, communications.

Frequency Range: 100 MHz to 10 GHz.

Team Members: RTX BBN Technologies, Xanadu Quantum, University of Maryland, Raytheon Advanced Technology.

Locations: Cambridge, MA; San Diego, CA; College Park, MD; Toronto, Canada.

“Improving accuracy, sensitivity, and resolution in fielded sensors enhances decision-making across numerous sectors, from mapping to autonomous systems,” said Dr. Mo Soltani, principal investigator at BBN.

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