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arXiv:0912.2512

Communication via Quantum Neural Network

A. Al Segher, NASSER METWALLY

Published Dec 13, 2009• 1 citation
arXivHTMLPDF

Abstract

In this study, the partially entangled neural networks is used to transfer information between two neurons, where the original teleportation protocol is employed this for this purpose. The effect of the network strength on the fidelity of the transported information is investigated. We show that as the strength of the network increases, the accuracy of the transformed information increases. As a practical application, we consider the spread of swine flu virus between two equivalent tranches of the community. In this treatment two factors are considered, one for humanity and the other for influence factor. The likelihood of infection between different age group is investigated, where we show that the strength of the neural network and the degree of infection plays an important role on transferring infection between different age group. From theoretical point of view, we show that it is possible to control the spread of the virus by controlling the network parameter. Also, by using local rotation, one can decrease the rate of infection between the young.

DOI
10.48550/arxiv.0912.2512

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In this study, the partially entangled neural networks is used to transfer information between two neurons, where the original teleportation protocol is employed this for this purpose. The effect of the network strength on the fidelity of the transported information is investigated. We show that as the strength of the network increases, the accuracy of the transformed information increases. As a practical application, we consider the spread of swine flu virus between two equivalent tranches of the community. In this treatment two factors are considered, one for humanity and the other for influence factor. The likelihood of infection between different age group is investigated, where we show that the strength of the neural network and the degree of infection plays an important role on transferring infection between different age group. From theoretical point of view, we show that it is possible to control the spread of the virus by controlling the network parameter. Also, by using local rotation, one can decrease the rate of infection between the young.
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Recent advances in quantum communication have enabled long-distance secure information transfer through quantum channels, giving rise to quantum networks with unique physical and statistical properties. However, as in classical networks, the propagation of viruses in these systems could have severe consequences. Here, we investigate the critical problem of virus spreading in quantum networks. We develop quantitative tools, particularly a modified nonlinear dynamical system model, for performing epidemiological analyses on quantum networks. Our results show that quantum networks tend to be more resilient to viral infections, exhibiting higher epidemic thresholds than classical networks with identical graph topologies. This apparent robustness, however, arises primarily from the sparser connectivity inherent to the quantum networks. When the comparison is made at a fixed average connectivity, classical and quantum networks display comparable epidemic thresholds. These findings provide key insights into the security and reliability of future large-scale quantum communication systems. Our work bridges the fields of quantum information science, network theory, and epidemiology, paving the way for future studies of quantum epidemiological dynamics.
A bidirectional quantum teleportation protocol is introduced over a quantum network consisting of more than four members sharing a coherent entangled state, where it is implemented in a perfect or noisy environment. The results show that the amplitude of the coherent state and the decoherence parameter play important roles in maximizing or minimizing this probability. At fixed values of the amplitude and decoherence parameters, the success of probability increases as the number of users increases. The fidelity of the teleported coherent state depends on the type of encoded information, whether entangled/partial or classical information, namely, it depends on the weight parameter. The stable behavior of the fidelity is displayed when users teleport classical information.
In this paper, a high fidelity scheme of quantum teleportation based on quantum neural network (QNN) is proposed. The QNN is composed of multi-bit control-not gates. The quantum teleportation of a qubit state via two-qubit entangled channels is investigated by solving the master equation in Lindblad operators with a noisy environment. To ensure the security of quantum teleportation, the indirect training of QNN is employed. Only 10% of teleported information is extracted for the training of QNN parameters. Then the outputs are corrected by the other QNN at Bob's side. We build a random series of numbers ranged in [0, π] as inputs and simulate the properties of our teleportation scheme. The results show that the fidelity of quantum teleportation system is significantly improved to approach 1 by the error-correction of QNN. It illustrates that the distortion can be eliminated perfectly and the high fidelity of quantum teleportation could be implemented.
A quantum network (QN) is constructed via maximum entangled coherent states. The possibility of using this network to achieve quantum communication between multi-participants is investigated. We showed that the probability of the successful teleportation of an unknown state depends on the size of the used network. As the number of participants increases, the success probability does not depend on the intensity of the field. Implementing a quantum teleportation protocol via a noisy QN is discussed. The unknown state can be teleported perfectly with small values of the field intensity and larger values of the noise strength. The success probability of this suggested protocol increases abruptly for larger values of the noise strength and gradually for small values. For small-size QNs, the fidelity of the teleported state decreases smoothly, whereas it decreases abruptly for larger-sized networks.