Ultra-Low Noise Inertial Sensor Operating at Exceptional Point

IFOS proposes an innovative approach to demonstrate enhanced inertial sensing with ultra-low-noise performance. In conventional ring laser gyros, precision increases with cavity size and measurement time. However, by exploiting Exceptional Points (EP) in coupled resonators, an enhanced gyro sensitivity can be achieved without having to increase size or measurement time, thereby extending the time for standalone spacecraft navigation. This new performance-enhancing principle therefore offers the promise, for the first time, of a chip-scale gyroscope photonic integrated circuit (PIC) platform with precision inertial navigation potential with all the benefits of integration, resulting in a monolithic sensor that is robust and resistant to shock. In Phase I, IFOS and Stanford University will analyze expected performance and limitations of a laser gyroscope that operates at an EP. In Phase II, we will design, fabricate, and characterize an EP gyro to produce a prototype of a chip-scale gyroscope with inertial navigation noise and drift performance. IFOS is working with aerospace primes for accerlated infusion. Beyond spacecraft GNC, the increased precision of the EP-enhanced gyro also opens new science possibilities such as measurements of fundamental physical constants, improving the sensitivity-bandwidth product for gravity wave detection, and tests of general relativity.The IFOS innovation is applicable to commercial aerospace and maritime navigation, intelligent transportation, medical robotics, and subsurface energy prospecting.

NASA applications include CubeSats/SmallSats, ISS payloads, and flagship missions. Beyond spacecraft GNC, the increased precision of the EP-enhanced gyro also opens new science possibilities such as measurements of fundamental physical constants, improving the sensitivity-bandwidth product for gravity wave detection, and tests of general relativity.

The IFOS innovation is applicable to commercial aerospace and maritime navigation, intelligent transportation, medical robotics, and subsurface energy prospecting.

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