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This research proposes a novel protocol for symmetric $N \to M$ telecloning, enabling the distribution of quantum state copies across multiple receivers using only sequential Bell state measurements. A key advancement is that even when teleportation fails at specific nodes, measurement outcomes allow remote inference of the original state with confidence scaling to the number of available copies. The study further demonstrates that pairwise entanglement is not strictly necessary for surpassing classical fidelity bounds in multipartite scenarios.
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Symmetric $N \to M$ telecloning and remote quantum state inference

arXiv3 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2608.18223v1 Announce Type: new Abstract: Teleporting unknown quantum states between distant nodes of a network is a significant feature of quantum communication. Few studies, however, have been conducted on $N \to M$ telecloning, in which $N$ copies of an unknown quantum state are optimally teleported to $M \geq N$ receivers. Previous work requires global POVMs on all copies and auxiliaries; here, we show that symmetric $N \to M$ telecloning can be probabilistically performed using only sequential (or parallel) Bell state measurements (BSMs), allowing the copies to be spatially separated. When successful, the fidelity of each receiver's reduced state saturates the bound imposed by the no-cloning theorem, with the probability of success being independent of $M$. In the case of an `unsuccessful' BSM, we show that the teleportation fidelity is likely to remain high, with the measurement outcome also providing information about the closest Pauli eigenbasis to the unknown state being telecloned. In this sense, each receiver can remotely infer the unknown quantum state with a level of confidence that scales with the number of copies, even if the fidelity of their own reduced state is sub-optimal. We additionally analyze the required resources to ensure the classical-communication fidelity bound is surpassed, both in terms of two-qubit inseparability and varying classes of multipartite entanglement. Surprisingly, we uncover that, at a given iteration of the protocol, pairwise entanglement is not always necessary to increase the teleportation fidelity and is never required to beat the classical bound for $N \geq 2$.

Abstract:Teleporting unknown quantum states between distant nodes of a network is a significant feature of quantum communication. Few studies, however, have been conducted on $N \to M$ telecloning, in which $N$ copies of an unknown quantum state are optimally teleported to $M \geq N$ receivers. Previous work requires global POVMs on all copies and auxiliaries; here, we show that symmetric $N \to M$ telecloning can be probabilistically performed using only sequential (or parallel) Bell state measurements (BSMs), allowing the copies to be spatially separated. When successful, the fidelity of each receiver's reduced state saturates the bound imposed by the no-cloning theorem, with the probability of success being independent of $M$. In the case of an `unsuccessful' BSM, we show that the teleportation fidelity is likely to remain high, with the measurement outcome also providing information about the closest Pauli eigenbasis to the unknown state being telecloned. In this sense, each receiver can remotely infer the unknown quantum state with a level of confidence that scales with the number of copies, even if the fidelity of their own reduced state is sub-optimal. We additionally analyze the required resources to ensure the classical-communication fidelity bound is surpassed, both in terms of two-qubit inseparability and varying classes of multipartite entanglement. Surprisingly, we uncover that, at a given iteration of the protocol, pairwise entanglement is not always necessary to increase the teleportation fidelity and is never required to beat the classical bound for $N \geq 2$.

arXiv:2608.18223 [quant-ph]

(or arXiv:2608.18223v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2608.18223 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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