Adaptive variational preparation of the Fermi-Hubbard eigenstates
Adaptive variational preparation of the Fermi-Hubbard eigenstates
复制标题
费米-哈伯德本征态的自适应变分制备
作者：
Gaurav Gyawali;M. Lawler
在量子化学和凝聚态物理中对强相互作用电子系统的基态进行近似，有望成为量子计算机最早的应用之一。在本文中，我们通过使用可解释的自适应变分量子本征解算器（VQE）（称为ADAPT-VQE）[1]，为多达6个站点（12个量子比特）的小网格准备了费米-哈伯德模型的高精度基态。与非自适应VQE相比，该算法通过在每一步添加由单体或两体费米子算子构建的最佳门来构建系统特定的模型。我们表明，这种自适应方法优于非自适应对应较少的变参数，短门深度，并缩放与系统的大小。我们还演示了自适应变分方法的应用，通过准备激发态和绿色函数，使用建议的ADAPT-SSVQE算法。变分方法的较低深度、渐近收敛、噪声容限[2-4]和高度可控的系统特异性分析使得自适应变分方法特别适合NISQ设备。
Approximating the ground states of strongly interacting electron systems in quantum chemistry and condensed matter physics is expected to be one of the earliest applications of quantum computers. In this paper, we prepare highly accurate ground states of the Fermi-Hubbard model for small grids up to 6 sites (12 qubits) by using an interpretable, adaptive variational quantum eigen-solver(VQE) called ADAPT-VQE [1]. In contrast with non-adaptive VQE, this algorithm builds a system-specific ansatz by adding an optimal gate built from one-body or two-body fermionic operators at each step. We show this adaptive method outperforms the non-adaptive counterpart in terms of fewer variational parameters, short gate depth, and scaling with the system size. The fidelity and energy of the prepared state appear to improve asympotically with ansatz depth.We also demonstrate the application of adaptive variational methods by preparing excited states and Green functions using a proposed ADAPT-SSVQE algorithm. Lower depth, asymptotic convergence, noise tolerance of a variational approach[2–4] and a highly controllable, system specific ansatz make the adaptive variational methods particularly well-suited for NISQ devices.
影响因子：
6.4
作者：
Preskill, John
通讯作者：
Preskill, John