We present an efficient fluorescence detector in the visible region of the spectrum with a photon detection dynamic range over 10 (6) photons/s made of a temperature-stabilized Si-based multi-pixel photon counter at temperature down to 5 degrees C. We show that effective cooling of the device by means of a compact thermo-electric cooler brings several advantages, such as high gain, low dark noise rate, and thus high signal-to-noise ratio in the efficient fluorescence detection at 398.9 nm from the (1)S(0) ? (1)P(1) transition of the ytterbium atoms in an effusive atomic beam. We present also a comparison of the fluorescence detection efficiencies between the device and a side-on photo-multiplier tube with known gain positioned at the symmetric location from the ytterbium atomic beam.
This paper addresses the problem of monocular depth estimation, which plays a key role to understand a given scene. Owing to the success of the generative model using deep neural networks, the performance of depth estimation from a single image has been significantly improved. However, most previous approaches still fail to accurately estimate the depth boundary and thus lead to the result of the blurry restoration. In this paper, a novel and simple method is proposed by exploiting the latent space of the depth-to-depth network, which contains useful encoded features for guiding the process of depth generation. This network, so-called guided network, simply consists of convolution layers and their corresponding deconvolution ones, and is also easily trained by only using single depth images. For efficiently learning the relationship between a color value and its related depth value in a given image, we propose to train the color-to-depth network via loss defined along with features from the latent space of our guided network (i.e., depth-to-depth network). One important advantage of the proposed method is to greatly enhance local details even under complicated background regions. Moreover, the proposed method works very fast (at 125 fps with GPU). Experimental results on various benchmark datasets show the efficiency and robustness of the proposed approach compared to state-of-the-art methods.
We report on the generation of narrow-bandwidth and frequency-modulated cascaded emission of two photons from a collimated Yb atomic beam. Efficient population transfer from the ground state (6s 2 1 S 0 ) to upper state (6s7s 1 S 0 ), of which direct transition at 291.1 nm is dipole forbidden, is achieved through a resonant two-photon excitation enhanced by the electromagnetically induced transparency mediated by the intermediate state (6s6p 1 P 1 ). Then cascaded emission of two photons with a bandwidth of 54 MHz at 611.3 nm (idler) and 555.8 nm (signal) occurs in sequence from the upper state via the spin triplet state (6s 2 3 P 1 ). Numerical calculations of the density matrix equations taking into account the residual Doppler effect and strong driving fields successfully explain the experimental results for the idler and signal beam intensities depending on the various parameters of the driving fields. Synchronized optical switching and frequency-modulation characteristics of the idler and signal beams are also reported.
This study proposes a new software platform, called ROS2-TMS, for an informationally structured environment. An informationally structured environment is vital for developing intelligent service robots by embedding various sensors in the environment to enhance the sensing capability and intelligence of robots. Thus far, we have been developing a software platform, named ROS-TMS, for an informationally structured environment, which connects various sensors and robots using ROS architecture. In recent years, ROS2, a next-generation version of ROS, has been released. ROS2 has many advantages, such as enhanced security, QoS control, and support for various platforms. ROS2-TMS, a new version of ROS-TMS, is developed not only by porting existing modules in ROS-TMS, such as the control system for a communication robot, but also by adding useful functions utilizing new features in ROS2. For instance, we added a voice user interface to control robots and various devices in the environment, such as lights or a bed. In addition, we implemented a new task scheduler that provides a cancelation function to stop running tasks and improve the security of the platform.
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