Spectral analysis of spin noise in an optically spin-polarized stochastic Bloch equation driven by noisy magnetic fields

We provide a closed-form autocorrelation function and power spectral density (PSD) of the solution, along a prescribed probing direction, to a noisy version of an optically pumped Bloch equation wherein each component of the external magnetic field is subject to (possibly correlated) white noise. We conclude that, up to first order in the white noise covariance amplitudes, noise in the bias B-field direction does not affect the autocorrelation function. Moreover, the noise terms for the remaining two axes make different contributions to the magnetic noise-driven spin PSD; in particular, the contribution corresponding to noises perpendicular to the probing direction dominates at high frequencies. Some results concerning the second (and higher) order terms are given, and an effective Larmor frequency shift caused by anisotropic transversal B-field noises, towards the DC direction, is revealed. The analytic results are supported by Monte Carlo simulations employing the Euler-Maruyama method.Comment: 16 pages, 7 figure

Quantum illumination receiver using double homodyne detection

A quantum receiver is an essential element of quantum illumination (QI) which outperforms its classical counterpart, called classical-illumination (CI). However, there are only few proposals for realizable quantum receiver, which exploits nonlinear effects leading to increasing the complexity of receiver setups. To compensate this, in this article, we design a quantum receiver with linear optical elements for Gaussian QI. Rather than exploiting nonlinear effect, our receiver consists of a 50:50 beam splitter and homodyne detection. Using double homodyne detection after the 50:50 beam splitter, we analyze the performance of the QI in different regimes of target reflectivity, source power, and noise level. We show that our receiver has better signal-to-noise ratio and more robust against noise than the existing simple-structured receivers.Comment: 9 pages, 6 figure

Optical repumping of triplet PP-states enhances magneto-optical trapping of ytterbium atoms

Radiative decay from the excited $^1P_1$ state to metastable $^3P_2$ and $^3P_0$ states is expected to limit attainable trapped atomic population in a magneto-optic trap of ytterbium (Yb) atoms. In experiments we have carried out with optical repumping of $^3P_{0,2}$ states to $^3P_1$, we observe enhancement of trapped atoms yield in the excited $^1P_1$ state. The individual decay rate to each metastable state is measured and the results show an excellent agreement with the theoretical values.Comment: 5 pages, 5 figure

Integrated Pose Estimation Using 2D Lidar and INS Based on Hybrid Scan Matching

Point cloud data is essential measurement information that has facilitated an extended functionality horizon for urban mobility. While 3D lidar and image-depth sensors are superior in implementing mapping and localization, sense and avoidance, and cognitive exploration in an unknown area, applying 2D lidar is inevitable for systems with limited resources of weight and computational power, for instance, in an aerial mobility system. In this paper, we propose a new pose estimation scheme that reflects the characteristics of extracted feature point information from 2D lidar on the NDT framework for exploiting an improved point cloud registration. In the case of the 2D lidar point cloud, vertices and corners can be viewed as representative feature points. Based on this feature point information, a point-to-point relationship is functionalized and reflected on a voxelized map matching process to deploy more efficient and promising matching performance. In order to present the navigation performance of the mobile object to which the proposed algorithm is applied, the matching result is combined with the inertial navigation through an integration filter. Then, the proposed algorithm was verified through a simulation study using a high-fidelity flight simulator and an indoor experiment. For performance validation, both results were compared and analyzed with the previous techniques. In conclusion, it was demonstrated that improved accuracy and computational efficiency could be achieved through the proposed algorithms

Design and Verification of Observability-Driven Autonomous Vehicle Exploration Using LiDAR SLAM

This paper explores the research topic of enhancing the reliability of unmanned mobile exploration using LiDAR SLAM. Specifically, it proposes a technique to analyze waypoints where 3D LiDAR SLAM can be smoothly performed in potential exploration areas and points where there is a risk of divergence in navigation estimation. The goal is to improve exploration performance by presenting a method that secures these candidate regions. The analysis employs a 3D geometric observability matrix and its condition number to discriminate waypoints. Subsequently, the discriminated values are applied to path planning, resulting in the derivation of a final destination path connecting waypoints with a satisfactory SLAM position and attitude estimation performance. To validate the proposed technique, performance analysis was initially conducted using the Gazebo simulator. Additionally, experiments were performed with an autonomous unmanned vehicle in a real-world environment