In this work we propose and discuss, through numerical simulations, the implementation of a multiple-photon resolving detector using a fibre ring, polarizing beam splitter, polarization rotator and single-photon detector. Following this, we show applications of such a device in photon number distribution and mesoscopic two-mode coherent state polarization estimations.

We present a numerical model based on multi-population rate equations for the simulation of quantum dot lasers with weak external optical feedback. The model accounts for the peculiar characteristics of the quantum dot material (inhomogeneous distribution of the QD size, presence of excited state and wetting layer _hellip) and can be used to calculate numerically the bifurcation diagram of the laser as function of several material and device parameters.

In 3D reconstruction applications, an important issue is the matching of point clouds corresponding to different perspectives of a particular object or scene, which is addressed by the use of variants of the Iterative Closest Point (ICP) algorithm. In this work, we introduce a cloud-partitioning strategy for improved registration and compare it to other relevant approaches by using both time and quality of pose correction. Quality is assessed from a rotation metric and also by the root mean square error (RMSE) computed over the points of the source cloud and the corresponding closest ones in the corrected target point cloud. A wide and plural set of experimentation scenarios was used to test the algorithm and assess its generalization, revealing that our cloud-partitioning approach can provide a very good match in both indoor and outdoor scenes, even when the data suffer from noisy measurements or when the data size of the source and target models differ significantly. Furthermore, in most of the scenarios analyzed, registration with the proposed technique was achieved in shorter time than those from the literature.