Witnessing entanglement in trapped-ion quantum error correction under realistic noise

• URL: http://arxiv.org/abs/2212.07479v3
• Date: Wed, 13 Dec 2023 16:48:40 GMT
• Title: Witnessing entanglement in trapped-ion quantum error correction under realistic noise
• Authors: Andrea Rodriguez-Blanco, Farid Shahandeh, and Alejandro Bermudez
• Abstract summary: Quantum Error Correction (QEC) exploits redundancy by encoding logical information into multiple physical qubits. We present a detailed microscopic error model to estimate the average gate infidelity of two-qubit light-shift gates used in trapped-ion platforms. We then apply this realistic error model to quantify the multipartite entanglement generated by circuits that act as QEC building blocks.
• Score: 41.94295877935867
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quantum Error Correction (QEC) exploits redundancy by encoding logical information into multiple physical qubits. In current implementations of QEC, sequences of non-perfect two-qubit entangling gates are used to codify the information redundantly into multipartite entangled states. Also, to extract the error syndrome, a series of two-qubit gates are used to build parity-check readout circuits. In the case of noisy gates, both steps cannot be performed perfectly, and an error model needs to be provided to assess the performance of QEC. We present a detailed microscopic error model to estimate the average gate infidelity of two-qubit light-shift gates used in trapped-ion platforms. We analytically derive leading-error contributions in terms of microscopic parameters and present effective error models that connect the error rates typically used in phenomenological accounts to the microscopic gate infidelities hereby derived. We then apply this realistic error model to quantify the multipartite entanglement generated by circuits that act as QEC building blocks. We do so by using entanglement witnesses, complementing in this way the recent studies by exploring the effects of a more realistic microscopic noise.

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