论文标题
电导中的疾病信息:量子反问题
Disorder information from conductance: a quantum inverse problem
论文作者
论文摘要
一旦完全指定其所有散射中心,就可以简单地计算量子设备的电导。但是,要以相反的方式进行此操作,即,从设备电导率中找到有关散射器组成的信息,这是一项难以捉摸的任务。在疾病的存在下,这尤其更具挑战性。在这里,我们提出了一个程序,其中可以从两端偶然量子设备的看似嘈杂的光谱电导率中提取有价值的组成信息。特别是,我们提出了一种反转方法,该方法可以通过分析能量依赖性电导指纹来识别随机分布的杂质的性质和浓度。使用紧密结合和密度函数理论模拟的石墨烯纳米纤维作为一个很好的例子显示了结果,表明这种反演技术是一般,鲁棒的,可以从标准电导率测量中提取无序中学设备的结构和组成信息。
It is straightforward to calculate the conductance of a quantum device once all its scattering centers are fully specified. However, to do this in reverse, i.e., to find information about the composition of scatterers in a device from its conductance, is an elusive task. This is particularly more challenging in the presence of disorder. Here we propose a procedure in which valuable compositional information can be extracted from the seemingly noisy spectral conductance of a two-terminal disordered quantum device. In particular, we put forward an inversion methodology that can identify the nature and respective concentration of randomly-distributed impurities by analyzing energy-dependent conductance fingerprints. Results are shown for graphene nanoribbons as a case in point using both tight-binding and density functional theory simulations, indicating that this inversion technique is general, robust and can be employed to extract structural and compositional information of disordered mesoscopic devices from standard conductance measurements.