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Quantum Information Processing

A framework for quantum controlled teleportation in multi-hop networks: noise analysis and IBMQ evaluation

Mahla Moridi Farimani, Yousef Mafi

Published Dec 17, 2025• 0 citations
Publisher

Abstract

Abstract Multi-hop quantum teleportation is a fundamental technique for enabling scalable, long-distance quantum communication, making it a key building block for future quantum networks. In this paper, we present a generalized multi-hop quantum controlled teleportation (MQCT) protocol that enables more flexible transfer across complex network architectures. We perform a detailed analysis of the protocol’s performance under realistic noise conditions, focusing on the impact of various noise sources on both the teleportation process and the underlying quantum channels. To assess its practical performance, we implemented the protocol on an IBM quantum (IBMQ) computer. The experimental results demonstrate the feasibility of the protocol in near-term quantum devices and provide valuable insights into its behavior under real-world quantum noise, paving the way for more reliable quantum communication systems.

DOI
10.1007/s11128-025-05017-9

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Quantum teleportation have a central role in quantum information science and allows transferring of an unknown quantum state through entanglement and classical communication. Unfortunately, the interaction with external and internal noise severely affects the quality of teleportation and poses limitations on practical applications of quantum communication networks. In this work, instead of conventional Bell teleportation, we introduce a Machine Learned adaptive protocol for optimizing multiple components of Quantum Teleportation in order to achieve higher fidelity in various noise environments. In order to demonstrate the performance of the proposed scheme, we study three different noise models, including bit-flip, amplitude damping, and depolarizing noise, both in case of single-qubit and two-qubit channels. As a result, we observe substantial improvement in the teleportation fidelity in comparison to the classical Bell-state teleportation protocol in certain noise conditions. Furthermore, the machine-learned protocol reveals a nontrivial strategy for compensation of decoherence and information losses. In addition, obtained results indicate the flexibility and reliability of the proposed framework for implementing various adaptive quantum communications while shedding light on possibilities of discovery of optimal quantum algorithms by means of automated approache
This work presents a simulation-based study of quantum teleportation for secure communication under ideal, noisy, and adversarial conditions using IBM’s Qiskit framework and the Qiskit Aer simulator. The study begins with the verification of Bell-state entanglement to establish quantum correlation, followed by the implementation of a standard three-qubit quantum teleportation protocol. The teleportation system is evaluated across four experimental scenarios: (i) ideal noiseless teleportation, (ii) depolarizing noise environments, (iii) basis disturbance attacks using unauthorized Hadamard operations, and (iv) entanglement injection attacks introducing an external qubit into the communication channel. Each scenario is analyzed using measurement statistics, probability distributions, and state behavior of the receiver qubit. The results demonstrate that quantum teleportation achieves high fidelity under ideal conditions, while environmental noise introduces statistical degradation in state reconstruction. Furthermore, adversarial interference significantly disrupts teleportation performance, with basis disturbance producing near-uniform probability distributions and entanglement injection altering receiver-side measurement statistics. This study highlights both the robustness and vulnerability of quantum communication protocols and emphasizes the importance of noise mitigation, entanglement security, and attack detection mechanisms in future quantum networking systems. The work is entirely simulation-based and implemented using Python and Qiskit.