Feedback stabilization of a nanoparticle at the intensity minimum of an optical double-well potential
Vojt\v{e}ch Mlyn\'a\v{r} (1), Salamb\^o Dago (2), Jakob Rieser (2), Mario A. Ciampini (2), Markus Aspelmeyer (2, 3), Nikolai Kiesel (2), Andreas Kugi (1, 4), Andreas Deutschmann-Olek (1) ((1) Automation, Control Institute, TU Wien, Vienna, Austria, (2) University of Vienna

TL;DR
This paper presents an adaptive feedback control method using LQG controllers to stabilize a nanoparticle at the intensity minimum of an optical double-well potential, reducing residual motion and temperature, with implications for quantum experiments.
Contribution
It introduces a simple, efficient LQG control strategy for nanoparticle stabilization at optical intensity minima, addressing experimental imperfections and enabling quantum regime applications.
Findings
Successfully stabilizes nanoparticle at intensity minimum
Reduces nanoparticle's residual variance and temperature
Demonstrates feasibility for quantum state preparation
Abstract
In this work, we develop and analyze adaptive feedback control strategies to stabilize and confine a nanoparticle at the unstable intensity minimum of an optical double-well potential. The resulting stochastic optimal control problem for a noise-driven mechanical particle in a nonlinear optical potential must account for unavoidable experimental imperfections such as measurement nonlinearities and slow drifts of the optical setup. To address these issues, we simplify the model in the vicinity of the unstable equilibrium and employ indirect adaptive control techniques to dynamically follow changes in the potential landscape. Our approach leads to a simple and efficient Linear Quadratic Gaussian (LQG) controller that can be implemented on fast and cost-effective FPGAs, ensuring accessibility and reproducibility. We demonstrate that this strategy successfully tracks the intensity minimum…
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