论文标题
基于递归变分系列方法计算分子和材料特性的近期量子算法
Near-term quantum algorithm for computing molecular and materials properties based on recursive variational series methods
论文作者
论文摘要
确定分子和材料的特性是量子计算的主要应用之一。该领域的一个主要问题是：我们如何使用不完善的近期量子计算机来解决实际价值问题？我们提出了一种量子算法，以使用近期量子设备估计分子的性质。该方法是一种递归变分系列估计方法，在该方法中，我们在Chebyshev多项式方面扩展了感兴趣的操作员，并使用变分量子算法在扩展中评估每个术语。我们通过计算能量域中的单粒子绿色功能和时间域中的自相关函数来测试我们的方法。
Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is: how might we use imperfect near-term quantum computers to solve problems of practical value? We propose a quantum algorithm to estimate the properties of molecules using near-term quantum devices. The method is a recursive variational series estimation method, where we expand an operator of interest in terms of Chebyshev polynomials and evaluate each term in the expansion using a variational quantum algorithm. We test our method by computing the one-particle Green's function in the energy domain and the autocorrelation function in the time domain.
