论文标题
用离子陷阱张量 - 网络量子量子量子量子探测量子物质量子量子量子量子
Probing phases of quantum matter with an ion-trap tensor-network quantum eigensolver
论文作者
论文摘要
张量 - 网络（TN）状态是在数值模拟中广泛使用的局部量子哈密顿量的基态的有效参数表示。在这里，我们将TN ANSATZ状态直接编码到量子模拟器中，该模拟器可能会提供与纯数值模拟相比的指数优势。特别是，我们通过准备扩展的Su-Schrieffer-Heeger模型的基接地状态，在离子陷阱量子计算机上使用变异量子量量计优化量子编码的TN ANSATZ状态。生成的状态的特征是估计拓扑不变的，并验证其拓扑顺序。我们作为被困的离子电路的TN编码仅采用单点地址来解决光脉冲 - 平台上自然可用的本机操作。我们通过选择具有分离良好的过渡频率的不同磁性差异来降低最近的邻居串扰，以均匀编码和奇数。
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.
