High-fidelity quantum teleportation through noisy channels via weak measurement and environment-assisted measurement
Results in Physics, ISSN: 2211-3797, Vol: 55, Page: 107164
2023
- 4Citations
- 3Captures
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Article Description
A perfect teleportation protocol requires pure maximally shared entangled states. While in reality the shared entanglement is drastically degraded due to the inevitable interaction with the noisy environment. Here, we propose a teleportation protocol to teleport an unknown qubit through amplitude damping channels with a fidelity up to one with a single copy of the entangled state. Our proposed teleportation protocol, while illustrated using the Bell and W entangled states as examples, can be utilized with any type of entangled states. In our protocol, we utilize environment-assisted measurement (EAM) during the entanglement distribution, and further modify the original teleportation protocol to apply weak measurement in the last step of teleportation. We find a balance between teleportation fidelity and success probability by varying the strength of the weak measurement. Furthermore, we investigate the protection of third-party assisted teleportation protocols, where all the qubits of the entangled state pass through the amplitude damping channel. In particular, for the third-party assisted teleportation with the W state, the decoherence of the shared entanglement can be totally suppressed by using EAM, hence no weak measurement is required to achieve an average teleportation fidelity of unity. The numerical simulation results reveal that our proposed teleportation protocol outperforms both the weak measurement based probabilistic teleportation protocol and the original teleportation protocols without protection.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2211379723009579; http://dx.doi.org/10.1016/j.rinp.2023.107164; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85176119346&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2211379723009579; https://dx.doi.org/10.1016/j.rinp.2023.107164
Elsevier BV
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