Bayesian optimization of Fisher Information in nonlinear multiresonant quantum photonics gyroscopes.

Autor: Sun, Mengdi, Kovanis, Vassilios, Lončar, Marko, Lin, Zin
Předmět:
Zdroj: Nanophotonics (21928606); May2024, Vol. 13 Issue 13, p2401-2416, 16p
Abstrakt: 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 ∼ 470 × improvement is possible over the shot-noise limited linear gyroscope with the same footprint, intrinsic quality factors, and power budget. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index