High-rate multiplexed entanglement source based on time-bin qubits for advanced quantum networks
Andrew Mueller, Samantha Davis, Boris Korzh, Raju Valivarthi, Andrew, D. Beyer, Rahaf Youssef, Neil Sinclair, Cristi\'an Pe\~na, Matthew D. Shaw,, and Maria Spiropulu

TL;DR
This paper presents a high-rate, multiplexed entanglement source using time-bin qubits, achieving record coincidence rates and high visibilities, advancing quantum network capabilities.
Contribution
The work introduces a 4.09 GHz repetition rate entangled photon source with frequency multiplexing into 8 channels, significantly improving entanglement distribution rates.
Findings
Achieved entanglement visibilities up to 99.4%
Total entanglement rates up to 3.55 million coincidences per second
Predicted potential for tenfold rate improvements
Abstract
Entanglement distribution based on time-bin qubits is an attractive option for emerging quantum networks. We demonstrate a 4.09 GHz repetition rate source of photon pairs entangled across early and late time bins separated by 80 ps. Simultaneous high rates and high visibilities are achieved through frequency multiplexing the spontaneous parametric down conversion output into 8 time-bin entangled pairs. We demonstrate entanglement visibilities as high as 99.4%, total entanglement rates up to 3.55e6 coincidences/s, and predict a straightforward path towards achieving up to an order of magnitude improvement in rates without compromising visibility. Finally, we resolve the density matrices of the entangled states for each multiplexed channel and express distillable entanglement rates in ebit/s, thereby quantifying the tradeoff between visibility and coincidence rates that contributes to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Information and Cryptography · Mechanical and Optical Resonators · Neural Networks and Reservoir Computing
