Non-equilibrium quadratic measurement-feedback squeezing in a micromechanical resonator

TL;DR

This paper demonstrates a nonlinear measurement-feedback protocol in a micromechanical resonator that achieves significant noise reduction by utilizing quadratic observables and avoids parametric divergence, advancing control of non-equilibrium dynamics.

Contribution

It introduces a novel nonlinear measurement-feedback scheme using quadratic observables to suppress noise and prevent divergence in micromechanical systems.

Findings

Achieved -5.1 dB noise reduction through measurement-feedback control.

Avoided parametric divergence by employing a nonlinear feedback protocol.

Unveiled entropy production rates indicating effective cooling in the system.

Abstract

Measurement and feedback control of stochastic dynamics has been actively studied for not only stabilizing the system but also for generating additional entropy flows originating in the information flow in the feedback controller. In particular, a micromechanical system offers a great platform to investigate such non-equilibrium dynamics under measurement-feedback control owing to its precise controllability of small fluctuations. Although various types of measurement-feedback protocols have been demonstrated with linear observables (e.g., displacement and velocity), extending them to the nonlinear regime, i.e., utilizing nonlinear observables in both measurement and control, retains non-trivial phenomena in its non-equilibrium dynamics. Here, we demonstrate measurement-feedback control of a micromechanical resonator by driving the second-order nonlinearity (i.e., parametric squeezing) and directly measuring quadratic observables, which are given by the Schwinger representation of pseudo angular momentum (referred as Schwinger angular momentum). In contrast to that the parametric divergence occurs when the second-order nonlinearity is blindly driven, our measurement-feedback protocol enables us to avoid such a divergence and to achieve a strong noise reduction at the level of $-5.1\pm 0.2$ dB. This strong noise reduction originates in the effective cooling included in our measurement-feedback protocol, which is unveiled by investigating entropy production rates in a coarse-grained model. Our results open up the possibility of not only improving noise-limited sensitivity performance but also investigating entropy production in information thermodynamic machines with nonlinear measurement and feedback.