论文标题

Green功能的量子子空间扩展算法

Quantum subspace expansion algorithm for Green's functions

论文作者

Jamet, Francois, Agarwal, Abhishek, Rungger, Ivan

论文摘要

我们提出了一种算法,以计算Green在交互电子系统上的量子计算机上的功能,这是传统计算机上的一项艰巨任务。它使用基于Lanczos方法的持续分数表示,其中波函数被扩展为量子子空间内基态的线性组合。尽管在常规计算机上,计算的成本随着系统大小而呈指数增长,将方法限制在小型系统中,而代表量子计算机上的基础状态可以克服该指数缩放屏障。我们建议在量子电路中有效制备基础状态的两级多摩托猪跑时间演化,该量子利用了针对猪肉误差的子空间扩展的稳健性。使用量子模拟器,我们在具有无限协调的贝斯晶格上演示了Hubbard模型的算法,我们将其映射到动态平均场理论中的16 Qubit Anderson杂质模型。我们的算法可以准确地计算金属和莫特绝缘状态的绿色功能,其电路深度低几个数量级,低于提出的时间演化。两级多机时间演变将计算绿色功能计算所需的猪跑步骤的数量减少到大约四到六个。因此,我们预计该方法可以用于中等系统尺寸的近期量子计算机上,同时允许在未来的故障耐受量量子计算机上扩展到更大的电路深度和量子数。

We present an algorithm to compute Green's functions on quantum computers for interacting electron systems, which is a challenging task on conventional computers. It uses a continued fraction representation based on the Lanczos method, where the wave functions are expanded as linear combination of basis states within a quantum subspace. While on conventional computers the cost of the computation grows exponentially with system size, limiting the method to small systems, by representing the basis states on a quantum computer one may overcome this exponential scaling barrier. We propose a two-level multigrid Trotter time evolution for an efficient preparation of the basis states in a quantum circuit, which takes advantage of the robustness of the subspace expansion against Trotter errors. Using a quantum emulator we demonstrate the algorithm for the Hubbard model on a Bethe lattice with infinite coordination, which we map to a 16 qubit Anderson impurity model within the dynamical mean field theory. Our algorithm computes the Green's function accurately for both the metallic and Mott insulating regimes, with a circuit depth several orders of magnitude below what has been proposed using time evolution. The two-level multigrid time evolution reduces the number of Trotter steps required to compute the Green's function to about four to six. We therefore expect that the method can be used on near term quantum computers for moderate system sizes, while allowing for scalability to larger circuit depths and qubit numbers on future fault tolerant quantum computers.

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