论文标题

驱动中尺度导体中的粒子电流统计数据

Particle current statistics in driven mesoscale conductors

论文作者

Brenes, Marlon, Guarnieri, Giacomo, Purkayastha, Archak, Eisert, Jens, Segal, Dvira, Landi, Gabriel

论文摘要

我们提出了一种高度可观的方法来计算驱动导体中电荷传输的统计数据。该框架可以在非零温度,与末端的强耦合以及存在非晶状光 - 物质相互作用的情况下应用,远离平衡。该方法结合了所谓的介绍铅形式主义与全面计数统计数据。它产生了广义的量子主方程,该方程决定了电荷交换的概率分布函数的当前波动的动力学和高阶矩。对于通用时间依赖性的二次汉密尔顿人,我们提供了在系统参数,储层或系统储层相互作用的非扰动状态下计算噪声的封闭形式表达式。该方法访问了电流及其噪声的完整动力学,使我们能够以非平衡配置计算电荷转移的方差。动力学表明,在驱动系统中,应在涵盖哪个时期内谨慎地在操作上定义平均噪声。

We propose a highly-scalable method to compute the statistics of charge transfer in driven conductors. The framework can be applied in situations of non-zero temperature, strong coupling to terminals and in the presence of non-periodic light-matter interactions, away from equilibrium. The approach combines the so-called mesoscopic leads formalism with full counting statistics. It results in a generalised quantum master equation that dictates the dynamics of current fluctuations and higher order moments of the probability distribution function of charge exchange. For generic time-dependent quadratic Hamiltonians, we provide closed-form expressions for computing noise in the non-perturbative regime of the parameters of the system, reservoir or system-reservoir interactions. Having access to the full dynamics of the current and its noise, the method allows us to compute the variance of charge transfer over time in non-equilibrium configurations. The dynamics reveal that in driven systems, the average noise should be defined operationally with care over which period of time is covered.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源