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通过绝热解耦子系统演化的投影量子本征求解器:一种在有噪声量子计算机中实现分子能量学的资源高效方法。

Projective quantum eigensolver via adiabatically decoupled subsystem evolution: A resource efficient approach to molecular energetics in noisy quantum computers.

作者信息

Patra Chayan, Halder Sonaldeep, Maitra Rahul

机构信息

Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.

Centre of Excellence in Quantum Information, Computing, Science and Technology, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.

出版信息

J Chem Phys. 2024 Jun 7;160(21). doi: 10.1063/5.0210854.

Abstract

Quantum computers hold immense potential in the field of chemistry, ushering new frontiers to solve complex many-body problems that are beyond the reach of classical computers. However, noise in the current quantum hardware limits their applicability to large chemical systems. This work encompasses the development of a projective formalism that aims to compute ground-state energies of molecular systems accurately using noisy intermediate scale quantum (NISQ) hardware in a resource-efficient manner. Our approach is reliant upon the formulation of a bipartitely decoupled parameterized ansatz within the disentangled unitary coupled cluster framework based on the principles of nonlinear dynamics and synergetics. Such decoupling emulates total parameter optimization in a lower dimensional manifold, while a mutual synergistic relationship among the parameters is exploited to ensure characteristic accuracy via a non-iterative energy correction. Without any pre-circuit measurements, our method leads to a highly compact fixed-depth ansatz with shallower circuits and fewer expectation value evaluations. Through analytical and numerical demonstrations, we establish the method's superior performance under noise while concurrently ensuring requisite accuracy in future fault-tolerant systems. This approach enables rapid exploration of emerging chemical spaces by the efficient utilization of near-term quantum hardware resources.

摘要

量子计算机在化学领域具有巨大潜力,为解决经典计算机无法企及的复杂多体问题开辟了新的前沿领域。然而,当前量子硬件中的噪声限制了它们在大型化学系统中的适用性。这项工作包括开发一种投影形式主义,旨在以资源高效的方式使用有噪声的中等规模量子(NISQ)硬件精确计算分子系统的基态能量。我们的方法依赖于在基于非线性动力学和协同论原理的解缠幺正耦合簇框架内制定二分去耦参数化假设。这种去耦在较低维流形中模拟总参数优化,同时利用参数之间的相互协同关系通过非迭代能量校正确保特征精度。无需任何预电路测量,我们的方法可得到具有更浅电路和更少期望值评估的高度紧凑的固定深度假设。通过分析和数值演示,我们证明了该方法在噪声环境下的卓越性能,同时确保了未来容错系统所需的精度。这种方法通过有效利用近期量子硬件资源,能够快速探索新兴的化学空间。

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