论文标题
用于分子振动光谱的量子启发的经典算法
Quantum-inspired classical algorithm for molecular vibronic spectra
论文作者
论文摘要
最近，我们看到了使用采样问题（例如随机电路采样和高斯玻色子采样）对量子优势的首次合理主张。明显的下一步是将潜在的量子优势引导到解决实际应用，而不是原理实验实验。最近，已经提出了一种量子模拟器，特别是高斯玻色子采样器，可以有效地产生分子振动光谱，这是分子的重要特性，也是分析化学成分和研究分子结构的重要工具。计算分子振动光谱一直是一项艰巨的任务，并且其最著名的经典算法量表在系统大小中组合。因此，它是量子设备提供计算优势的任务的候选者。在这项工作中，我们提出了一种量子启发的经典算法，用于用于谐波电位的分子振动光谱。我们首先表明，可以使用经典算法与运行玻色子采样器一样准确地有效地解决了与Fock-State Boson采样相对应的分子振动光谱问题。特别是，我们将Gurvits的算法推广到Fock-State Boson采样光谱的近似傅立叶成分，并使用Parseval的关系证明，只要傅立叶成分的误差很小，可以抑制光谱的误差。我们还表明，即使没有Gurvits-type算法，也可以完全解决高斯玻色子采样的分子振动光谱问题，该问题与化学中的实际分子振动光谱问题相对应。因此，我们证明这些问题不是量子优势的候选者。然后，我们提供了一个更通用的分子振动光谱问题，该问题在化学上也充满了动力，我们可能能够利用玻色子采样器。
We have recently seen the first plausible claims for quantum advantage using sampling problems such as random circuit sampling and Gaussian boson sampling. The obvious next step is to channel the potential quantum advantage to solving practical applications rather than proof-of-principle experiments. Recently, a quantum simulator, specifically a Gaussian boson sampler, has been proposed to generate molecular vibronic spectra efficiently, which is an essential property of molecules and an important tool for analyzing chemical components and studying molecular structures. Computing molecular vibronic spectra has been a challenging task, and its best-known classical algorithm scales combinatorially in the system size. Thus, it is a candidate of tasks for which quantum devices provide computational advantages. In this work, we propose a quantum-inspired classical algorithm for molecular vibronic spectra for harmonic potential. We first show that the molecular vibronic spectra problem corresponding to Fock-state boson sampling can be efficiently solved using a classical algorithm as accurately as running a boson sampler. In particular, we generalize Gurvits's algorithm to approximate Fourier components of the spectra of Fock-state boson sampling and prove using Parseval's relation that the error of the spectra can be suppressed as long as that of the Fourier components are small. We also show that the molecular vibronic spectra problems of Gaussian boson sampling, which corresponds to the actual molecular vibronic spectra problem in chemistry, can be exactly solved even without Gurvits-type algorithms. Consequently, we demonstrate that those problems are not candidates of quantum advantage. We then provide a more general molecular vibronic spectra problem, which is also chemically well-motivated, for which we might be able to take advantage of a boson sampler.
