绝热量子优化设计：旅行商问题的一个案例研究
Designing Adiabatic Quantum Optimization: A Case Study for the Traveling Salesman Problem
摘要：
随着量子技术的进步，更复杂的量子退火装置变得可用。虽然它们为解决优化问题提供了新的可能性，但它们的真正潜力仍然是一个悬而未决的问题。由于绝热算法的优化设计在其评估中起着重要的作用，我们说明了在基于旅行商问题（TSP）的量子退火硬件上实现优化问题时要考虑的方面和挑战。我们证明了，如果量子动力学没有仔细定制的问题，局部极小值之间的隧道可以指数抑制。此外，我们表明，不平等的约束，特别是，模拟量子退火机的实施提出了一个主要的障碍。我们最后认为，可编程数字量子退火器可以克服许多这些障碍，并可以-一旦足够大的量子计算机存在-提供一个有趣的路线，使用量子退火的一大类问题。
英文摘要：
With progress in quantum technology more sophisticated quantum annealing devices are becoming available. While they offer new possibilities for solving optimization problems, their true potential is still an open question. As the optimal design of adiabatic algorithms plays an important role in their assessment, we illustrate the aspects and challenges to consider when implementing optimization problems on quantum annealing hardware based on the example of the traveling salesman problem (TSP). We demonstrate that tunneling between local minima can be exponentially suppressed if the quantum dynamics are not carefully tailored to the problem. Furthermore we show that inequality constraints, in particular, present a major hurdle for the implementation on analog quantum annealers. We finally argue that programmable digital quantum annealers can overcome many of these obstacles and can - once large enough quantum computers exist - provide an interesting route to using quantum annealing on a large class of problems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
