论文标题
通过分子动力学杂交量子退火
Hybrid Quantum Annealing via Molecular Dynamics
论文作者
论文摘要
提出了一种新型的量子古典杂种方案，以有效解决大规模组合优化问题。关键概念是引入与横向场iSing模型的量子旋转相关的经典通量变量的哈密顿动力学。经典通量的分子动力学可以用作强大的预处理，以整理量子退火器的冷冻和矛盾的旋转。与标准的经典算法（禁忌搜索和模拟退火）相比，我们的平滑杂交的性能和准确性通过使用最大切割和ISING旋转玻璃玻璃问题来证明。
A novel quantum-classical hybrid scheme is proposed to efficiently solve large-scale combinatorial optimization problems. The key concept is to introduce a Hamiltonian dynamics of the classical flux variables associated with the quantum spins of the transverse-field Ising model. Molecular dynamics of the classical fluxes can be used as a powerful preconditioner to sort out the frozen and ambivalent spins for quantum annealers. The performance and accuracy of our smooth hybridization in comparison to the standard classical algorithms (the tabu search and the simulated annealing) are demonstrated by employing the MAX-CUT and Ising spin-glass problems.
