论文标题
量子驾驶汽车分子动力学:近期量子计算机上的一种成本效益的分子模拟方法
Quantum Car-Parrinello Molecular Dynamics: A Cost-Efficient Molecular Simulation Method on Near-Term Quantum Computers
论文作者
论文摘要
在本文中,我们提出了一种成本降低的方法,用于在近期量子计算机,量子CAR-PARRINELLO分子动力学(QCPMD)上进行有限温度分子动力学。近期量子计算机最有前途的应用之一是量子化学。可以预期,通过分子动力学对分子的模拟也可以通过应用有希望的近期量子算法(VQE)的有希望的近期量子算法来有效地执行。但是,该方法可能需要大量的计算成本来实现足够的准确性,否则,统计噪声会严重影响结果。为了解决这些问题,我们发明了一种有效的分子时间演化方法,该方法受汽车方法启发。在我们的方法中,表征量子状态的参数基于运动方程而不是被优化。此外,通过考虑Langevin动力学,我们可以利用内在的统计噪声。作为QCPMD的应用,我们提出了一种有效的分子振动频率分析方法,在该方法中,我们可以使用QCPMD计算的分子动力学结果。数值实验表明,我们的方法可以精确模拟平衡状态下的langevin动力学,我们可以成功预测给定分子的特征频率。此外,在数值模拟中,与使用VQE的分子动力学相比,我们的方法实现了大幅度的成本降低。我们的方法在不使用广泛使用的VQE方法的情况下实现了有效的计算。从这个意义上讲,我们在近期量子计算机上打开了分子动力学的新可能性。我们期望我们的结果激发了对分子模拟的有效近期量子算法的进一步发明。
In this paper, we propose a cost-reduced method for finite-temperature molecular dynamics on a near-term quantum computer, Quantum Car-Parrinello molecular dynamics (QCPMD). One of the most promising applications of near-term quantum computers is quantum chemistry. It has been expected that simulations of molecules via molecular dynamics can be also efficiently performed on near-term quantum computers by applying a promising near-term quantum algorithm of the variational quantum eigensolver (VQE). However, this method may demand considerable computational costs to achieve a sufficient accuracy, and otherwise, statistical noise can significantly affect the results. To resolve these problems, we invent an efficient method for molecular time evolution inspired by Car-Parrinello method. In our method, parameters characterizing the quantum state evolve based on equations of motion instead of being optimized. Furthermore, by considering Langevin dynamics, we can make use of the intrinsic statistical noise. As an application of QCPMD, we propose an efficient method for vibrational frequency analysis of molecules in which we can use the results of the molecular dynamics calculated by QCPMD. Numerical experiments show that our method can precisely simulate the Langevin dynamics at the equilibrium state, and we can successfully predict a given molecule's eigen frequencies. Furthermore, in the numerical simulation, our method achieves a substantial cost reduction compared with molecular dynamics using the VQE. Our method achieves an efficient computation without using widely employed method of the VQE. In this sense, we open up a new possibility of molecular dynamics on near-term quantum computers. We expect our results inspire further invention of efficient near-term quantum algorithms for simulation of molecules.