论文标题
反迭代量量子本质量有助于连续变量
Inverse iteration quantum eigensolvers assisted with a continuous variable
论文作者
论文摘要
用量子计算机解决本征态的能力是最终模拟物理系统的关键。在这里，我们提出了反迭代量子本质量，它利用量子计算的力量对经典的反功率迭代方法。一个关键的要素是将逆哈密顿逆因素构建为连贯的哈密顿进化的线性组合。我们首先考虑一种连续变量的量子模式（Qumode），用于实现像积分等线性组合，权重编码为Qumode资源状态。我们在有限的挤压下，用于各种物理系统（包括分子和量子多体模型），在有限挤压下使用数值模拟演示了量子算法。我们还讨论了一种混合量子古典算法，该算法直接总结了哈密顿进化的持续时间以进行比较。据揭示，连续变化的资源对于减少量子算法中哈密顿量的连贯演化时间是有价值的。
The capacity for solving eigenstates with a quantum computer is key for ultimately simulating physical systems. Here we propose inverse iteration quantum eigensolvers, which exploit the power of quantum computing for the classical inverse power iteration method. A key ingredient is constructing an inverse Hamiltonian as a linear combination of coherent Hamiltonian evolution. We first consider a continuous-variable quantum mode (qumode) for realizing such a linear combination as an integral, with weights being encoded into a qumode resource state. We demonstrate the quantum algorithm with numerical simulations under finite squeezing for various physical systems, including molecules and quantum many-body models. We also discuss a hybrid quantum-classical algorithm that directly sums up Hamiltonian evolution with different durations for comparison. It is revealed that continuous-variable resources are valuable for reducing the coherent evolution time of Hamiltonians in quantum algorithms.
