论文标题

均匀顺序电路的时间演变

Time Evolution of Uniform Sequential Circuits

论文作者

Astrakhantsev, Nikita, Lin, Sheng-Hsuan, Pollmann, Frank, Smith, Adam

论文摘要

使用经典数值方法模拟通用量子多体系统的时间演变具有指数增长的成本,既可以随着进化时间或系统尺寸而增长。在这项工作中,我们提出了一个多条缩放的杂种量子量子算法,用于在热力学极限下演变的时间演变为一维均匀的系统。该算法使用分层均匀的顺序量子电路作为变异ansatz来表示无限的翻译不变量子状态。我们从数字上表明,该ANSATZ需要在仿真时间中多项式的多个参数才能获得给定精度。此外,在我们的变化进化算法中,保持了ANSATZ的这种有利的缩放。考虑到近期数字量子计算机设计混合动力优化的所有步骤。在经典计算机上对演变算法进行基准测试后,我们使用基于云的量子处理单元上有限数量的量子数来证明该均匀状态的可观察结果。使用更有效的张量收缩方案,该算法也可以作为经典数值算法提供改进。

Simulating time evolution of generic quantum many-body systems using classical numerical approaches has an exponentially growing cost either with evolution time or with the system size. In this work, we present a polynomially scaling hybrid quantum-classical algorithm for time evolving a one-dimensional uniform system in the thermodynamic limit. This algorithm uses a layered uniform sequential quantum circuit as a variational ansatz to represent infinite translation-invariant quantum states. We show numerically that this ansatz requires a number of parameters polynomial in the simulation time for a given accuracy. Furthermore, this favourable scaling of the ansatz is maintained during our variational evolution algorithm. All steps of the hybrid optimization are designed with near-term digital quantum computers in mind. After benchmarking the evolution algorithm on a classical computer, we demonstrate the measurement of observables of this uniform state using a finite number of qubits on a cloud-based quantum processing unit. With more efficient tensor contraction schemes, this algorithm may also offer improvements as a classical numerical algorithm.

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