Optimal Feedback Cooling of a Charged Levitated Nanoparticle with Adaptive Control

journal article in Web of Science

English

We use an optimal control protocol to cool one mode of the center-of-mass motion of an optically levitated nanoparticle. The feedback technique relies on exerting a Coulomb force on a charged particle with a pair of electrodes and follows the control law of a linear quadratic regulator, whose gains are optimized by a machine learning algorithm in under 5 s. With a simpler and more robust setup than optical feedback schemes, we achieve a minimum center-of-mass temperature of 5 mK at 3×10-7 mbar and transients 10-600 times faster than cold damping. This cooling technique can be easily extended to 3D cooling and is particularly relevant for studies demanding high repetition rates and force sensing experiments with levitated objects.

Charged particles; Cooling; Learning algorithms; Machine learning; Nanoparticles

Conangla, G.P.; Ricci, F.; Cuairan, M.T.; Schell, A.W.; Meyer, N.; Quidant, R.

3. 6. 2019

1079-7114

Physical Review Letters

122

22

United States of America

223602-1

223602-6

6

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.122.223602