Entangling two levitated particles in free space via trap modulation and Bayesian feedback

TL;DR

This paper presents an optimal control method using trap modulation and Bayesian feedback to generate steady-state quantum entanglement between two levitated nanoparticles in free space, even with low measurement efficiency.

Contribution

It introduces a novel scheme combining trap modulation, Coulomb coupling, and Bayesian feedback to achieve unconditional entanglement of levitated particles.

Findings

Achieves unconditional entanglement in steady state.

Enables quantum squeezing in normal modes of particles.

Operates effectively at low measurement efficiencies.

Abstract

We propose an optimal control scheme for generating quantum entanglement between two optically-levitated nanoparticles in free space. Specifically, we consider that the mechanical motion frequencies of the two levitated particles are modulated by adjusting the amplitude of the trapping beam. The two particles are coupled through Coulomb interaction, and the particles' positions are continuously monitored via homodyne detection on the back-scattered light from both particles. By employing an optimal Bayesian feedback scheme, we achieve unconditional entanglement between the two particles in steady states. More precisely, a Kalman filter is used to estimate the states of the two particles and subsequently a linear quadratic regulator is applied to derive the optimal feedback forces exerted on the particles. Physically, periodic modulation enables significant quantum squeezing in both the common mode and the differential mode of the two particles. The Coulomb coupling between the particles introduces a difference in the squeezing of the two normal modes, thereby facilitating the entanglement of the two levitated particles. Our scheme allows for the realization of both conditional and unconditional entanglement at relatively low measurement efficiencies and with low requirements for Coulomb coupling strength, significantly enhancing the feasibility of implementation.