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Advanced Quantum Technologies

Parameterized Quantum Circuits for Learning Cooperative Quantum Teleportation

Yan‐Y. Feng, Jian Zhou, Dan‐B. Zhang, Jin‐J. Shi

Published Jul 10, 2022• 7 citations
Publisher

Abstract

Abstract Quantum teleportation is an elemental process in quantum communication and many variants have been widely investigated theoretically and experimentally. Motivated by cooperation in classical communications, cooperative quantum teleportation (CQT) are developed with features of the cooperation referring to allocation of resources and operations among participants. Parameterized quantum circuit (PQC) are employed to learn the CQT protocols on account of different training scenarios with controls of gate parameters among shared entangled states, measurement, and recovery operations. Numerical results show the CQT protocols can be discovered with unit fidelity regardless of ideal or nonideal channels by training the PQCs with hybrid quantum‐classical (HQC) optimization under full cooperations of the participants. Further, the influence of quantum channel noise on the teleportation performance is explored by parameterizing the entangled states with noise and entanglement parameters under adjustable recovery operations. Simulation results indicate the trained PQC can improve the system performance, which implies the potential denoising capability of the HQC algorithms. The suggested CQT protocols satisfy the underlying properties of universality, randomness, locality and cooperation, and discussions indicate the designed quantum circuits can be optimized in view of quantum and circuit costs by appropriate optimization algorithms for achieving higher state fidelity in the future work.

DOI
10.1002/qute.202200040

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Abstract Quantum teleportation is an elemental process in quantum communication and many variants have been widely investigated theoretically and experimentally. Motivated by cooperation in classical communications, cooperative quantum teleportation (CQT) are developed with features of the cooperation referring to allocation of resources and operations among participants. Parameterized quantum circuit (PQC) are employed to learn the CQT protocols on account of different training scenarios with controls of gate parameters among shared entangled states, measurement, and recovery operations. Numerical results show the CQT protocols can be discovered with unit fidelity regardless of ideal or nonideal channels by training the PQCs with hybrid quantum‐classical (HQC) optimization under full cooperations of the participants. Further, the influence of quantum channel noise on the teleportation performance is explored by parameterizing the entangled states with noise and entanglement parameters under adjustable recovery operations. Simulation results indicate the trained PQC can improve the system performance, which implies the potential denoising capability of the HQC algorithms. The suggested CQT protocols satisfy the underlying properties of universality, randomness, locality and cooperation, and discussions indicate the designed quantum circuits can be optimized in view of quantum and circuit costs by appropriate optimization algorithms for achieving higher state fidelity in the future work.
Quantum teleportation is a quantum communication protocol that has been extensively studied both theoretically and experimentally. The proposed approach of using the LOCCNet framework to learn quantum teleportation protocols is investigated in this study. In the proposed protocols consider various training scenarios, including controlling gate parameters between shared entangled states, and recovery operations. To optimize the training, the parameterized quantum circuits (PQC) with training parameters is used in the LOCCNet framework, and the results show that a high-fidelity quantum teleportation protocol can be achieved even under non-ideal channels. Moreover, simulations are conducted to evaluate the effect of quantum channel noise on teleportation performance by varying the noise of entangled states and entanglement parameters under adjustable operations. The findings suggest that the trained PQC can improve system performance and potentially offer denoising capabilities. Compared with the existing LOCCNet protocol, the newly designed LOCCNet protocol has better noise immunity and can improve the fidelity and transmission success rate in specific scenarios.
Quantum teleportation (QT) is the principal method of transferring quantum states from one place to another without actually revealing which quantum state is being transferred. This protocol makes use of entangled states shared between the sending and receiving stations, and two bits of classical information. However, in real communication systems which are used to carry the entangled state, a typical noise results in the degradation of the fidelity of teleported states. The protocol of controlled quantum teleportation (CQT) represents an extension to the standard quantum teleportation (SQT) with includes the third entity, so called “controller“, and is based on sharing of a tripartite entangled quantum state. The role of controller is to permit the fidelity of teleported state to be higher than it can be done using only classical resources. As a typical noise has detrimental effect on the performance of quantum teleportation protocols, In this work, a study of different noisy channels, which can exhibit the Markovian or non-Markovian dynamics is presented. Each noisy channel is characterized by the teleportation fidelity and by the control power.
Abstract Quantum teleportation as the key strategy for quantum communication requires pure maximally shared entangled states among quantum nodes. In practice, quantum decoherence drastically degrades the shared entanglement during entanglement distribution, which is a serious challenge for the development of quantum networks. However, most of the decoherence control strategies proposed thus far are either resource-intensive or time-consuming. To overcome this obstacle, we enable noise-resistant teleportation through a noisy channel with a limited number of qubits and without applying time-consuming weak measurements. We apply a quantum gate control unit consisting of a controlled NOT gate and a rotation gate after the original teleportation protocol is accomplished. Furthermore, we demonstrate that a teleportation fidelity of unity is attainable when environment-assisted measurement is added to the proposed teleportation protocol via quantum gates. Moreover, we present an entanglement distribution process by employing the designed quantum gate control unit followed by the deterministic standard teleportation protocol to improve teleportation fidelity by establishing improved shared entanglement. Our performance analysis indicates that the proposed teleportation schemes offer a competitive fidelity and success probability compared with the conventional schemes and a recent weak measurement-based teleportation protocol.
Distributed quantum information processing protocols such as quantum entanglement distillation and quantum state discrimination rely on local operations and classical communications (LOCC). Existing LOCC-based protocols typically assume the availability of ideal, noiseless, communication channels. In this paper, we study the case in which classical communication takes place over noisy channels, and we propose to address the design of LOCC protocols in this setting via the use of quantum machine learning tools. We specifically focus on the important tasks of quantum entanglement distillation and quantum state discrimination, and implement local processing through parameterized quantum circuits (PQCs) that are optimized to maximize the average fidelity and average success probability in the respective tasks, while accounting for communication errors. The introduced approach, Noise Aware-LOCCNet (NA-LOCCNet), is shown to have significant advantages over existing protocols designed for noiseless communications.
We propose a novel framework for teleportation-mediated non-local gate synthesis by integrating evolutionary learning with a quantum variational autoencoder (QVAE). The conventional approaches to quantum teleportation often rely on static entanglement resources and fixed measurement bases, which limit adaptability and efficiency. The proposed method addresses these limitations through a symmetry-preserving QVAE that dynamically compresses quantum states while preserving teleportation-critical features, combined with an evolutionary optimizer to refine protocol performance. The QVAE employs a parameterized quantum circuit with SU(3)-symmetric layers to encode two-qubit states into a compressed latent representation, then reconstructs them via a Bell-basis measurement decoder. The evolutionary component optimizes a multi-objective fitness function balancing teleportation fidelity and entanglement efficiency, adapting parameters in real-time through Gaussian mutations and annealing. Moreover, the system integrates seamlessly with existing teleportation protocols by replacing traditional Bell-state generation with adaptive state preparation and post-teleportation error correction. Implemented on a superconducting quantum processor with classical co-processing, our framework achieves high fidelity (above 0.99) while reducing classical communication overhead by 50%. The hybrid architecture operates at a 10 kHz update rate, ensuring compatibility with current quantum networking standards without additional hardware requirements. This work demonstrates the potential of evolutionary quantum autoencoders to enhance teleportation-based gate synthesis, offering a scalable and adaptive solution for future quantum communication systems.
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