Bayesian optimization of Fisher Information in nonlinear multiresonant quantum photonics gyroscopes

We propose an on-chip gyroscope based on nonlinear multiresonant optics in a thin film chi (2) resonator that combines high sensitivity, compact form factor, and low power consumption simultaneously. We theoretically analyze a novel holistic metric - Fisher Information capacity of a multiresonant nonlinear photonic cavity - to fully characterize the sensitivity of our gyroscope under fundamental quantum noise conditions. Leveraging Bayesian optimization techniques, we directly maximize the nonlinear multiresonant Fisher Information. Our holistic optimization approach orchestrates a harmonious convergence of multiple physical phenomena - including noise squeezing, nonlinear wave mixing, nonlinear critical coupling, and noninertial signals - all encapsulated within a single sensor-resonator, thereby significantly augmenting sensitivity. We show that similar to 470x improvement is possible over the shot-noise limited linear gyroscope with the same footprint, intrinsic quality factors, and power budget.