Reinforcement learning assisted non-reciprocal optomechanical gyroscope
arXiv:2503.08319 · doi:10.1103/PhysRevA.111.063504
Abstract
We propose a novel optomechanical gyroscope architecture based on a spinning cavity optomechanical resonator (COM) evanescently coupled to a tapered optical fiber without relying on costly quantum light sources. Our study reveals a striking dependence of the gyroscope's sensitivity on the propagation direction of the driving optical field, manifesting robust quantum non-reciprocal behavior. This non-reciprocity significantly enhances the precision of angular velocity estimation, offering a unique advantage over conventional gyroscopic systems. Furthermore, we demonstrate that the operational range of this non-reciprocal gyroscope is fundamentally governed by the frequency of the pumping optical field, enabling localized sensitivity to angular velocity. Leveraging the adaptive capabilities of reinforcement learning (RL), we optimize the gyroscope's sensitivity within a targeted angular velocity range, achieving unprecedented levels of precision. These results highlight the transformative potential of RL in advancing high-resolution, miniaturized optomechanical gyroscopes, opening new avenues for next-generation inertial sensing technologies.
12 pages, 5 figures
References in corpus (31)
- Cavity Optomechanics
- Quantum-coherent coupling of a mechanical oscillator to an optical cavity mode
- Quantum Fisher information matrix and multiparameter estimation
- Remote quantum entanglement between two micromechanical oscillators
- Entangled massive mechanical oscillators
- Nonreciprocal Photon Blockade
- Large Quantum Superpositions and Interference of Massive Nanometer-Sized Objects
- Reinforcement Learning in Different Phases of Quantum Control
- Direct observation of deterministic macroscopic entanglement
- Nonreciprocal Optomechanical Entanglement against Backscattering Losses
- Multimode circuit optomechanics near the quantum limit
- Reinforcement Learning with Neural Networks for Quantum Feedback
- Breaking Anti- Symmetry by Spinning a Resonator
- Optomechanical sensing of spontaneous wave-function collapse
- Estimation of Gaussian quantum states
- Quantum rotation sensing with dual Sagnac interferometers in an atom-optical waveguide
- Generalizable control for quantum parameter estimation through reinforcement learning
- Nonreciprocal enhancement of remote entanglement between nonidentical mechanical oscillators
- Coherent Transport of Quantum States by Deep Reinforcement Learning
- Deep Reinforcement Learning Control of Quantum Cartpoles
- QuanEstimation: An open-source toolkit for quantum parameter estimation
- Nonreciprocal Superradiant Phase Transitions and Multicriticality in a Cavity QED System
- Approximate Autonomous Quantum Error Correction with Reinforcement Learning
- The role of entanglement in calibrating optical quantum gyroscopes
- Faster State Preparation across Quantum Phase Transition Assisted by Reinforcement Learning
- Revealing Cosmic Rotation
- When heterodyning beats homodyning: an assessment with quadrature moments
- Generation and storage of spin squeezing via learning-assisted optimal control
- Single-Atom Verification of the Optimal Trade-Off between Speed and Cost in Shortcuts to Adiabaticity
- Optimal control of linear Gaussian quantum systems via quantum learning control
- Optimized mechanical quadrature squeezing beyond the 3-dB limit via a gradient-descent algorithm