量子计算WAHTOR算法优化策略实证分析比较研究

IF 2.9 Q3 CHEMISTRY, PHYSICAL
Leonardo Ratini, Chiara Capecci, Leonardo Guidoni
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引用次数: 1

摘要

摘要:利用分子哈密顿量通过轨道的一元变换的不变性,利用波函数-适应哈密顿量通过轨道旋转(WAHTOR)算法,可以显著缩短变分量子本征求解(VQE)方法中的变分电路深度。我们介绍了WAHTOR算法的非绝热版本,并通过估计原型基准测试系统中的量子处理单元(QPU)资源,比较了其在不同实现(两种绝热和两种非绝热)下的效率。在固定的VQE参数下计算哈密顿量的一阶和二阶导数不会带来明显的QPU过载,导致小分子的结果表明绝热牛顿-拉夫森方法是更方便的选择。相反,我们发现在Hubbard模型系统的情况下,信赖域非绝热优化更有效。因此,预设工作明确了经验变分分析的最佳优化策略,便于量子计算中更大变分波函数的优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization strategies in WAHTOR algorithm for quantum computing empirical ansatz: a comparative study
Abstract Exploiting the invariance of the molecular Hamiltonian by unitary transformation of the orbitals it is possible to significantly shorter the depth of the variational circuit in Variational Quantum Eigensolver (VQE) approach by using the Wavefunction-Adapted Hamiltonian Through Orbital Rotation (WAHTOR) algorithm.
In this work, we introduce a non-adiabatic version of the WAHTOR algorithm and compare its efficiency with different implementations (two adiabatic and two non-adiabatic) through estimating Quantum Processing Unit (QPU) resources in prototypical benchmarking systems. Calculating first and second order derivatives of the Hamiltonian at fixed VQE parameters does not introduce a significant QPU overload, leading to results on small molecules that indicate the adiabatic Newton-Raphson method as the more convenient choice. On the contrary, we find out that in the case of Hubbard model systems the trust region non-adiabatic optimization is more efficient.
The preset work therefore indicates clearly the best optimization strategies for empirical variational ansatzes, facilitating the optimization of larger variational wavefunctions for quantum computing.
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来源期刊
CiteScore
3.70
自引率
11.50%
发文量
46
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