Efficient and high-fidelity entanglement in cavity QED without high cooperativity
Sumit Goswami, Cheng-Hsuan Chien, Neil Sinclair, Brandon Grinkemeyer, Shayne Bennetts, Ying-Cheng Chen, Hsiang-Hua Jen

TL;DR
This paper introduces a modified state-carving protocol for cavity QED that achieves near-perfect entanglement efficiency using only one photon, enabling scalable quantum computing and communication.
Contribution
A simple modification to the state-carving protocol that allows efficient, high-fidelity entanglement with unit probability using only one photon interaction.
Findings
Achieves fidelity of 0.999 at cooperativity of 34
Overcomes 50% efficiency limit of previous protocols
Facilitates large-scale quantum network applications
Abstract
The so-called state-carving protocol generates high-fidelity entangled states at an atom-cavity interface without requiring high cavity cooperativity. However, this protocol is limited to 50\% efficiency, which restricts its applicability. We propose a simple modification to the state-carving protocol to achieve efficient entanglement generation, with unit probability in principle. Unlike previous two-photon schemes, ours employs only one photon which interacts with the atoms twice - avoiding separate photon detections which causes irrecoverable probability loss. We present a detailed description and performance evaluation of our protocol under non-ideal conditions. High fidelity of 0.999 can be achieved with cavity cooperativity of only 34. Efficient state-carving paves the way for large-scale entanglement generation at cavity-interfaces for modular quantum computing, quantum repeaters…
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.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Information and Cryptography · Optical Network Technologies · Neural Networks and Reservoir Computing
