Bayesian optimization of Fisher Information in nonlinear multiresonant quantum photonics gyroscopes
Mengdi Sun, Vassilios Kovanis, Marko Lončar, Zin Lin
Abstract
Abstract We propose an on‐chip gyroscope based on nonlinear multiresonant optics in a thin film χ (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 improvement is possible over the shot‐noise limited linear gyroscope with the same footprint, intrinsic quality factors, and power budget.