利用对困离子量子计算机的测量增强电子对近似性

IF 6.6 1区 物理与天体物理 Q1 PHYSICS, APPLIED
Luning Zhao, Qingfeng Wang, Joshua J. Goings, Kyujin Shin, Woomin Kyoung, Seunghyo Noh, Young Min Rhee, Kyungmin Kim
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引用次数: 0

摘要

电子对近似为量子计算机上的化学模拟提供了一种高效的变分量子求解器(VQE)方法。由于纠缠门的数量与系统大小成二次方比例,且测量开销恒定,轨道优化的单元对耦合簇双(oo-upCCD)公式在准确性和效率之间取得了平衡。然而,电子对近似使得该方法无法达到定量精度。为了改进它,我们探索了对 oo-upCCD 的二阶扰动(PT2)修正理论。PT2 考虑了 oo-upCCD 中缺失的断对贡献,同时保留了其效率。对于分子键伸展和化学反应,该方法显著提高了预测能量的准确性,将 oo-upCCD 的误差减少了 90%。在 IonQ 的量子计算机上,我们发现 PT2 能量修正具有很强的抗噪能力。仅在 VQE 能量上应用简单的误差缓解后,预测的 VQE-PT2 反应能量与无噪声模拟器非常一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Enhancing the electron pair approximation with measurements on trapped-ion quantum computers

Enhancing the electron pair approximation with measurements on trapped-ion quantum computers

The electron pair approximation offers an efficient variational quantum eigensolver (VQE) approach for chemistry simulations on quantum computers. With the number of entangling gates scaling quadratically with system size and a constant measurement overhead, the orbital optimized unitary pair coupled cluster double (oo-upCCD) ansatz strikes a balance between accuracy and efficiency. However, the electron pair approximation prevents the method from achieving quantitative accuracy. To improve it, we explore the theory of second order perturbation (PT2) correction to oo-upCCD. PT2 accounts for the missing broken-pair contributions in oo-upCCD, while retaining its efficiencies. For molecular bond stretching and chemical reactions, the method significantly improves the predicted energy accuracy, reducing oo-upCCD’s error by up to 90%. On IonQ’s quantum computers, we find that the PT2 energy correction is highly noise-resilient. The predicted VQE-PT2 reaction energies are in excellent agreement with noise-free simulators after applying simple error mitigations solely on the VQE energies.

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来源期刊
npj Quantum Information
npj Quantum Information Computer Science-Computer Science (miscellaneous)
CiteScore
13.70
自引率
3.90%
发文量
130
审稿时长
29 weeks
期刊介绍: The scope of npj Quantum Information spans across all relevant disciplines, fields, approaches and levels and so considers outstanding work ranging from fundamental research to applications and technologies.
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