Tensor Train Optimization of Parameterized Quantum Circuits

被引：0
|
作者：
Paradezhenko, G. [1 ]
Pervishko, A. [1 ,2 ]
Yudin, D. [1 ,2 ]
机构：
[1] Skolkovo Inst Sci & Technol, Moscow 121205, Russia
[2] Far Eastern Fed Univ, Inst High Technol & Adv Mat, Lab Spin Orbitron, Vladivostok 690950, Russia
来源：
JETP LETTERS | 2023年 / 118卷 / 12期
关键词：
MATRIX PRODUCT STATES; RENORMALIZATION-GROUP; BARREN PLATEAUS; NETWORKS;
D O I：
10.1134/S0021364023603056
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
We examine a particular realization of derivative-free method as implemented on tensor train based optimization to the variational quantum eigensolver. As an example, we consider parameterized quantum circuits composed of a low-depth hardware-efficient ansatz and Hamiltonian variational ansatz for addressing the ground state of the transverse field Ising model. We further make a comparison with gradient-based optimization techniques and discuss on the advantage of using tensor train based optimization, especially in the presence of noise.
引用
收藏
页码：938 / 945
页数：8
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