Programmable Synthetic Magnetism and Chiral Edge States in Nano-Optomechanical Quantum Hall Networks

TL;DR

This paper demonstrates the creation of reconfigurable, topologically protected chiral edge states in nano-optomechanical networks using synthetic magnetic fields, enabling unidirectional phononic transport and potential applications in nanoscale information processing.

Contribution

It introduces a method to induce and control synthetic magnetic fields in optomechanical networks, realizing quantum-Hall-like edge states with full reconfigurability.

Findings

Observation of chiral edge states in optomechanical networks.

Reconfigurable magnetic fluxes control localized states.

Detection of unidirectional phononic transport.

Abstract

Artificial magnetic fields break time-reversal symmetry in engineered materials--also known as metamaterials, enabling robust, topological transport of neutral excitations, much like electronic conduction edge channels in the integer quantum Hall effect. We experimentally demonstrate the emergence of quantum-Hall-like chiral edge states in optomechanical resonator networks. Synthetic magnetic fields for phononic excitations are induced through laser drives, while cavity optomechanical control allows full reconfigurability of the effective metamaterial response of the networks, including programming of magnetic fluxes in multiple resonator plaquettes. By tuning the interplay between network connectivity and magnetic fields, we demonstrate both flux-sensitive and flux-insensitive localized mechanical states. Scaling up the system creates spectral features that are precursors to Hofstadter butterfly spectra. Site-resolved spectroscopy reveals edge-bulk separation, with stationary phononic distributions signaling chiral edge modes. We directly probe those edge modes in transport measurements to demonstrate a unidirectional acoustic channel. This work unlocks new ways of controlling topological phononic phases at the nanoscale with applications in noise management and information processing.