A Tensor Product Space for Studying the Interaction of Bipartite States of Light with Nanostructures

arxiv(2024)

引用 0|浏览3
暂无评分
摘要
Pairs of entangled photons are important for applications in quantum nanophotonics, where their theoretical description must accommodate their bipartite character. Such character is shared at the other end of the intensity range by, for example, the two degenerate instances of the pump field involved in second-harmonic generation. Describing the interaction of nanophotonic structures with bipartite states of light is, regardless of their intensity, a challenge with important technological applications. Here, we develop a theoretical framework for studying the interaction of material structures with bipartite states of light. The basic element is the symmetrized tensor product space of two copies of an electromagnetic Hilbert space. One of the benefits inherited from the single Hilbert space is that consequences of material symmetries are readily deduced. We derive selection rules for second-order non-linear processes in objects with rotational and/or mirror symmetries. We numerically verify several selection rules by combining quantum-chemical calculations with a Maxwell solver to simulate second-harmonic generation in two different MoS_2 clusters. The computationally convenient scattering matrix method is also extended to the tensor product space when the response of the object to one part of the state is independent of the other. For such a case, we obtain the relation between the scattering matrix in the single Hilbert space and the scattering matrix for bipartite states. Such a separable case is relevant for the entanglement evolution of biphoton states interacting with nanostructures. We discuss some possibilities for accommodating the computations of non-linear effects in the framework, for example, through a non-separable scattering operator, where the response of the object to one part of the state depends on the other part.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要