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Efficient universal quantum channel simulation in IBM’s cloud quantum computer

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An Erratum to this article was published on 17 October 2018

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Abstract

The study of quantum channels is an important field and promises a wide range of applications, because any physical process can be represented as a quantum channel that transforms an initial state into a final state. Inspired by the method of performing non-unitary operators by the linear combination of unitary operations, we proposed a quantum algorithm for the simulation of the universal single-qubit channel, described by a convex combination of “quasi-extreme” channels corresponding to four Kraus operators, and is scalable to arbitrary higher dimension. We demonstrated the whole algorithm experimentally using the universal IBM cloud-based quantum computer and studied the properties of different qubit quantum channels. We illustrated the quantum capacity of the general qubit quantum channels, which quantifies the amount of quantum information that can be protected. The behavior of quantum capacity in different channels revealed which types of noise processes can support information transmission, and which types are too destructive to protect information. There was a general agreement between the theoretical predictions and the experiments, which strongly supports our method. By realizing the arbitrary qubit channel, this work provides a universally- accepted way to explore various properties of quantum channels and novel prospect for quantum communication.

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Change history

  • 17 October 2018

    In this work, Shi-Jie Wei and Tao Xin contributed equally to this work. This annotation for the contribution was omitted in the original publication of this paper [1]. It can be confirmed in the previous arXiv version [2]. Hence, The sentence “Shi-Jie Wei and Tao Xin contributed equally to this work.” should be added.

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Wei, SJ., Xin, T. & Long, GL. Efficient universal quantum channel simulation in IBM’s cloud quantum computer. Sci. China Phys. Mech. Astron. 61, 70311 (2018). https://doi.org/10.1007/s11433-017-9181-9

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