论文标题

石墨烯的空缺:绝热量子优化的应用

Vacancies in graphene: an application of adiabatic quantum optimization

论文作者

Carnevali, Virginia, Siloi, Ilaria, Di Felice, Rosa, Fornari, Marco

论文摘要

量子退火器的复杂性已经增长,以至于现在有可能涉及几千吨的量子计算。在本文中,\ textColor {black} {{均打算显示量子退火以解决物理相关性问题的可行性,我们使用了一个简单的模型,与当前量子退火器的能力兼容,以研究}石墨烯空位缺陷的相对稳定性。通过映射将碳接收互换主导到二次无约束的二进制优化问题上的关键相互作用,我们的方法利用了\ textColor {black} {{black} {基态以及量子的激发态,}量子退火器与其相对形成的所有可能的多重缺陷一起提取所有可能的缺陷。这种方法重现已知的结果,并为量子退火应用于物理化学兴趣问题提供了垫脚石。

Quantum annealers have grown in complexity to the point that quantum computations involving few thousands of qubits are now possible. In this paper, \textcolor{black}{with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, to study} the relative stability of graphene vacancy defects. By mapping the crucial interactions that dominate carbon-vacancy interchange onto a quadratic unconstrained binary optimization problem, our approach exploits \textcolor{black}{the ground state as well the excited states found by} the quantum annealer to extract all the possible arrangements of multiple defects on the graphene sheet together with their relative formation energies. This approach reproduces known results and provides a stepping stone towards applications of quantum annealing to problems of physical-chemical interest.

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