论文标题
在量子退火中进行公平抽样
Achieving fair sampling in quantum annealing
论文作者
论文摘要
采样均等概率的哈密顿量的所有基态是采样算法的所需特征，但最近的研究表明，横向场量子退火样品的常见变体不公平地基态子空间。在本说明中，我们提出了扰动理论论证，表明可以通过采用反向退火启发的路径来纠正这种缺陷。我们确认，这一结论在模拟先前研究的小型实例以及量子退火硬件的较大实例中存在。
Sampling all ground states of a Hamiltonian with equal probability is a desired feature of a sampling algorithm, but recent studies indicate that common variants of transverse field quantum annealing sample the ground state subspace unfairly. In this note, we present perturbation theory arguments suggesting that this deficiency can be corrected by employing reverse annealing-inspired paths. We confirm that this conclusion holds in simulations of previously studied small instances with degeneracy, as well as larger instances on quantum annealing hardware.
