Bayesian optimization of Fisher Information in nonlinear multiresonant quantum photonics gyroscopes

Area of Science:

• Photonics
• Quantum Optics
• Sensor Technology

Background:

• Traditional gyroscopes face limitations in sensitivity, size, and power consumption.
• On-chip photonic devices offer potential for miniaturization and enhanced performance.

Purpose of the Study:

• To propose and theoretically analyze a novel on-chip gyroscope.
• To achieve high sensitivity, compact form factor, and low power consumption simultaneously.

Main Methods:

• Utilizing nonlinear multiresonant optics in a thin film χ⁽²⁾ resonator.
• Analyzing sensitivity using a novel holistic metric: Fisher Information capacity.
• Employing Bayesian optimization to maximize nonlinear multiresonant Fisher Information.

Main Results:

• Demonstrated a holistic optimization approach integrating multiple physical phenomena.
• Achieved significant sensitivity augmentation through noise squeezing, nonlinear wave mixing, and critical coupling.
• Showcased potential for $$ improvement over shot-noise limited linear gyroscopes.

Conclusions:

• The proposed on-chip gyroscope offers a promising solution for advanced inertial sensing.
• The novel holistic metric and optimization approach are key to enhanced gyroscope sensitivity.
• This technology enables compact, low-power, high-sensitivity inertial measurement units.