Nonlinear response of a nano-structure including two square quantum dots (QDs) of identical material but dissimilar sizes is discussed by considering possible quantum interferences. Density matrix approach is developed to extract physical characteristics of the system by considering Hamiltonians including couplings of the excitons to thermal bath and the possible intra-dot relaxations as well as the near field optical energy transfers (of Yukawa-type potentials) between the probable eight quantum states in subwavelength range. Realization of nonlinear behavior is studied systematically by putting the structure inside a unidirectional ring cavity and driving it by pair of dichromatic fields, that one provides a weak probe, while the other offers a strong driving component. It is shown that the absorption/dispersion properties of the probe field might be controlled by tuning the quantum interference via changing the structural features as well as the externally controlled parameters. Thus adjusting the optical bistability (OB) threshold, hysteresis cycle size or even transition from OB to multi-stability might be possible easily. Moreover, machine learning approach is proposed to evaluate how predictable are the responses of the suggested structure in various preliminary circumstances. Results clearly reflect high potential of the suggested structure for applications such as all-optical switches or memories.

通过考虑可能的量子干涉，讨论了包含两个相同材料但尺寸不同的方形量子点 (QD) 的纳米结构的非线性响应。密度矩阵方法被开发来通过考虑哈密顿量来提取系统的物理特征，包括激子与热浴的耦合和可能的点内弛豫以及可能的八个之间的近场光学能量转移（汤川型势）亚波长范围内的量子态。通过将该结构置于单向环形腔内并通过一对二色场驱动它，一个提供弱探针，另一个提供强驱动组件，系统地研究了非线性行为的实现。结果表明，可以通过改变结构特征以及外部控制参数来调节量子干涉来控制探测场的吸收/色散特性。因此，可以轻松调整光学双稳态 (OB) 阈值、滞后周期大小，甚至从 OB 到多稳态的过渡。此外，提出了机器学习方法来评估建议结构在各种初步情况下的响应的可预测性。结果清楚地反映了所建议的结构在全光开关或存储器等应用中的巨大潜力。