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arXiv 2203.13271quant-ph
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用离子阱张量网络量子本征解算器探测量子物质的相位

Probing phases of quantum matter with an ion-trap tensor-network quantum eigensolver

Michael Meth, Viacheslav Kuzmin, Rick van Bijnen, Lukas Postler, Roman Stricker, Rainer Blatt, Martin Ringbauer, Thomas Monz, Pietro Silvi, Philipp Schindler

摘要:

张量网络(TN)态是局域量子哈密顿量的基态的有效参量表示,广泛应用于数值模拟。在这里,我们将TN量子态直接编码到量子模拟器中,这可能比纯粹的数值模拟具有指数优势。特别地,我们通过制备扩展的Su-Schrieffer-Heeger模型的基态,在离子阱量子计算机上用变分量子本征求解器实现了量子编码TN量子态的优化.通过估计生成状态的拓扑不变量,验证其拓扑序来表征生成状态。我们的TN编码作为捕获离子电路仅采用单站点寻址光脉冲-平台上自然可用的本地操作。我们通过选择不同的磁子级,以及分离的过渡频率来编码偶数和奇数量子比特,以减少最近邻串扰。

英文摘要:

Tensor-Network (TN) states are efficient parametric representations of ground states of local quantum Hamiltonians extensively used in numerical simulations. Here we encode a TN ansatz state directly into a quantum simulator, which can potentially offer an exponential advantage over purely numerical simulation. In particular, we demonstrate the optimization of a quantum-encoded TN ansatz state using a variational quantum eigensolver on an ion-trap quantum computer by preparing the ground states of the extended Su-Schrieffer-Heeger model. The generated states are characterized by estimating the topological invariants, verifying their topological order. Our TN encoding as a trapped ion circuit employs only single-site addressing optical pulses - the native operations naturally available on the platform. We reduce nearest-neighbor crosstalk by selecting different magnetic sublevels with well-separated transition frequencies to encode even and odd qubits.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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