Entanglement-Assisted Communication Surpassing the Ultimate Classical Capacity

TL;DR

This paper demonstrates experimentally that entanglement-assisted communication can surpass classical capacity limits over noisy channels, achieving higher data rates and lower error rates than traditional methods.

Contribution

The authors experimentally implement entanglement-assisted communication surpassing classical capacity over lossy, noisy channels using a high-efficiency entanglement source and quantum receiver.

Findings

EACOMM exceeds classical capacity by up to 14.6% under the same power constraints.

EACOMM reduces bit-error rate by up to 69% compared to classical protocols.

Experimental validation of quantum advantage in noisy optical channels.

Abstract

Entanglement underpins a variety of quantum-enhanced communication, sensing, and computing capabilities. Entanglement-assisted communication (EACOMM) leverages entanglement pre-shared by communication parties to boost the rate of classical information transmission. Pioneering theory works showed that EACOMM can enable a communication rate well beyond the ultimate classical capacity of optical communications, but an experimental demonstration of any EACOMM advantage remains elusive. Here, we report the implementation of EACOMM surpassing the classical capacity over lossy and noisy bosonic channels. We construct a high-efficiency entanglement source and a phase-conjugate quantum receiver to reap the benefit of pre-shared entanglement, despite entanglement being broken by channel loss and noise. We show that EACOMM beats the Holevo-Schumacher-Westmoreland capacity of classical communication by up to 14.6%, when both protocols are subject to the same power constraint at the transmitter. As a practical performance benchmark, a classical communication protocol without entanglement assistance is implemented, showing that EACOMM can reduce the bit-error rate by up to 69% over the same bosonic channel. Our work opens a route to provable quantum advantages in a wide range of quantum information processing tasks.