Hamiltonian dynamics on digital quantum computers without discretization error

IF 6.6 1区 物理与天体物理 Q1 PHYSICS, APPLIED
Etienne Granet, Henrik Dreyer
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Abstract

We introduce an algorithm to compute expectation values of time-evolved observables on digital quantum computers that requires only bounded average circuit depth to reach arbitrary precision, i.e. produces an unbiased estimator with finite average depth. This finite depth comes with an attenuation of the measured expectation value by a known amplitude, requiring more shots per circuit. The average gate count per circuit for simulation time t is \({\mathcal{O}}({t}^{2}{\mu }^{2})\) with μ the sum of the Hamiltonian coefficients, without dependence on precision, providing a significant improvement over previous algorithms. With shot noise, the average runtime is \({\mathcal{O}}({t}^{2}{\mu }^{2}{\epsilon }^{-2})\) to reach precision ϵ. The only dependence in the sum of the coefficients makes it particularly adapted to non-sparse Hamiltonians. The algorithm generalizes to time-dependent Hamiltonians, appearing for example in adiabatic state preparation. These properties make it particularly suitable for present-day relatively noisy hardware that supports only circuits with moderate depth.

Abstract Image

数字量子计算机上的哈密顿动力学无离散化误差
我们介绍了一种在数字量子计算机上计算时间演化观测值期望值的算法,这种算法只需要有界的平均电路深度就能达到任意精度,即产生具有有限平均深度的无偏估计值。这种有限深度会使测量到的期望值出现已知幅度的衰减,因此每个电路需要更多的测量次数。在模拟时间 t 内,每个电路的平均门数为({\mathcal{O}}({t}^{2}{\mu }^{2}),其中 μ 为哈密顿系数之和,与精度无关,与之前的算法相比有显著改进。在有射击噪声的情况下,达到ϵ精度的平均运行时间为({\mathcal{O}}({t}^{2}{\mu }^{2}{epsilon }^{-2})\)。系数之和的唯一依赖性使其特别适用于非稀疏哈密顿。该算法还适用于时间依赖的哈密顿,例如在绝热态制备中出现的哈密顿。这些特性使它特别适用于当今相对嘈杂、仅支持中等深度电路的硬件。
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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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