Machine learning-based analysis has become essential to efficiently handle the increasing massive data from modern astronomical instruments in recent years. Churchwell et al. (2006, 2007) identified infrared ring structures, which are believed to relate to the formation of massive stars, with the human eye. Recently, Ueda et al. (2020) showed that Convolutional Neural Networks (CNN) can detect objects with indistinct boundaries such as infrared rings with comparable accuracy as the human eye. However, such a classification-based object detector requires a long processing time, making it impractical to apply to existing all-sky 12 μm and 22 μm data captured by WISE. We introduced the Single Shot MultiBox Detector (SSD, Liu W. et al. 2016), which directly outputs the locations and confidences of targets, to significantly reduce the time for identification. We applied an SSD model to the rings toward the 6 deg2 region in the Galactic plane which is the same region used in Ueda et al. (2020), and confirmed that the time for identification was reduced by about 1/80 with maintaining almost the same accuracy. Since detecting small rings is still difficult by even this model, an input image should be cropped
into small images, which increases the number of applications of the model. There is still room for reducing the
processing time. In the future, we will try to solve this problem and detect the rings faster.
Photogrammetry technique is widely used for the initial alignment of main-reflector panels of millimeter/ submillimeter-wave telescopes by analyzing a great number of photos of the reflector at the rest state taken from different angles and distances. In this study, we investigated a possibility that the photogrammetry can be applied for real-time surface measurements which is important to realize active surface controls that improve reflector surface accuracy during scientific observations. The technique is important especially for realizing larger aperture and higher frequency telescopes. We developed a simulator to investigate the accuracy of the surface measurements with photos taken with fixed cameras mounted on the stays of the sub-reflector. As a result, we found that the accuracy of surface measurement is roughly inversely proportional to square-root of the number of fixed cameras, and the calculation time roughly proportional to the product of the numbers of cameras and measurement points. For the case of Nobeyama 45-m telescope, the accuracy of 1 mm (rms) was achieved for 164 surface points by 10 cameras with a calculation time of ∼2 sec by a developed python code using a single-core Xeon processor. In order to improve the accuracy with a minimum number of cameras, more various camera positions (e.g., surrounding the vertex hole of the main reflector and surrounding the main reflector) should be investigated, and their combination should be optimized. Applying high-performing technologies such as multiprocessors and/or GPUs, faster calculation is to be considered.
Owing to recent performance improvement and lower pricing of computers, built-in computers are equipped in virtually all measurement/control hardware, and small computers (e.g., Raspberry-Pi) can be obtained inexpensively to monitor the environment and/or hardware status. Those devices are able to communicate via network. The system having flexibility adaptable with the rapidly changing trend of hardware is desired in order to provide powerful functions quickly for the telescope control. Software developed for robot operations could be used for this purpose that controlling distributed and network-linked hardware. The Robot Operating System (ROS) is an open source software platform and one of the most used frameworks for robot operations. It has a number of libraries and tools to help us create robot applications. Under this background, we are developing NECST (NEw Control System for Telescope) using ROS framework. In NECST, each atomic operation (such as device operation and arithmetic operation) is divided into a node which is an elemental object in ROS. Nodes are grouped and packaged by their functionalities for convenience. The control systems of telescope and receiver are built by combining those packages. Since there are about ∼100 nodes even in the telescope control part, we also developed utilities to manage nodes that visualizes sent/received data in real time. Currently, NECST is installed and operated mainly for receiver control and antenna control of 1.85-m mm-submm wave telescope.
We report the current status of the 1.85-m mm-submm telescope installed at the Nobeyama Radio Observatory (altitude 1400 m) and the future plan. The scientific goal is to reveal the physical/chemical properties of molecular clouds in the Galaxy by obtaining large-scale distributions of molecular gas with an angular resolution of several arcminutes. A semi-automatic observation system created mainly in Python on Linux-PCs enables effective operations. A large-scale CO J =2–1 survey of the molecular clouds (e.g., Orion-A/B, Cygnus-X/OB7, Taurus- California-Perseus complex, and Galactic Plane), and a pilot survey of emission lines from minor molecular species toward Orion clouds have been conducted so far. The telescope also is providing the opportunities for technical demonstrations of new devices and ideas. For example, the practical realizations of PLM (Path Length Modulator) and waveguide-based sideband separating filter, installation of the newly designed waveguide-based circular polarizer and OMT (Orthomode Transducer), and so on. As the next step, we are now planning to relocate the telescope to San Pedro de Atacama in Chile (altitude 2500 m), and are developing very wideband receiver covering 210–375 GHz (corresponding to Bands 6–7 of ALMA) and full-automatic observation system. The new telescope system will provide large-scale data in the spatial and frequency domain of molecular clouds of Galactic plane and Large/Small Magellanic Clouds at the southern hemisphere. The data will be precious for the comparison with those of extra-galactic ones that will be obtained with ALMA as the Bands 6/7 are the most efficient frequency bands for the surveys in extra-galaxies for ALMA.
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