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Efficient modeling of superconducting quantum circuits with tensor networks

机译:用张量网络高效建模超导量子电路

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We use a tensor network method to compute the low-energy excitations of a large-scale fluxonium qubit up to a desired accuracy. We employ this numerical technique to estimate the pure-dephasing coherence time of the fluxonium qubit due to charge noise and coherent quantum phase slips from first principles, finding an agreement with previously obtained experimental results. By developing an accurate single-mode theory that captures the details of the fluxonium device, we benchmark the results obtained with the tensor network for circuits spanning a Hilbert space as large as 15180. Our algorithm is directly applicable to the wide variety of circuit-QED systems and may be a useful tool for scaling up superconducting quantum technologies.
机译:我们使用张量网络方法来计算大规模浮夸Qubit的低能量激发,其最高可达所需的精度。 我们采用该数值技术来估计由于第一原理的电荷噪声和相干量子相单位引起的浮雕QUB对Qubit的纯脱相干时间,找到与先前获得的实验结果的协议。 通过开发精确的单模理论,捕获浮雕装置的细节,我们基准与浪潮网络获得的结果,用于跨越15180的Hilbert空间的电路。我们的算法直接适用于各种电路QED 系统,并且可以是用于缩放超导量子技术的有用工具。

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