Experimental Astronomy最新文献

Telescope cycle time estimation is one of the basic issues of observational astronomy. There are not many tools that help to calulate the cycle time for multiple telescopes with multiple instruments. This work presents a new tool for determing the observation time; it was applied at the Cerro Murphy Observatory (OCM) but can be used at any other observatory. The Machine Learning (ML) method was implied, resulting in a fully automatic software module that works without any user intervention. We propose a polynomial multiple regression method and demonstrate all steps to build a reliable ML model like data collecting, data cleaning, model training and error evaluation in relation to the implementation in the observatory software. The method was designed to work for different telescopes with several instruments. Accuracy analysis and the assessment of model errors were based on real data from telescopes, proving the usefulness of the presented method. Error evaluation shows that for 84.2 % of nights, the prediction error in operation time prediction does not exceed 2 %. Converted into a 10-hour observation night, 2 % corresponds to an error of no more than 12 minutes. The described model is already working at the OCM and optimizes the efficiency of the observations.

A Compton/Pair telescope, designed to provide spectral resolved images of cosmic photons from sub-MeV to GeV energies, records a wealth of data in a combination of tracking detector and calorimeter. Onboard event classification can be required to decide on which data to down-link with priority, given limited data-transfer bandwidth. Event classification is also the first and one of the most crucial steps in reconstructing data. Its outcome determines the further handling of the event, i.e., the type of reconstruction (Compton, pair) or, possibly, the decision to discard it. Errors at this stage result in misreconstruction and loss of source information. We present a classification algorithm driven by a Convolutional Neural Network. It provides classification of the type of electromagnetic interaction, based solely on low-level detector data. We introduce the task, describe the architecture and the dataset used, and present the performance of this method in the context of the proposed (e-)ASTROGAM and similar telescopes.

Reflectivity is a key topic in soft X-ray optics research and serves as the foundation for studying the performance of the optics for X-ray astronomical satellites. Since its establishment, the 100-m X-ray Test Facility (100XF) has been continuously developing various testing functionalities, including calibration of timing, imaging, and energy response. This paper provides a detailed description of the X-ray optics reflectivity test method based on the 100XF, which can be applied to various grazing incident X-ray optics, including Wolter-I and lobster-eye types, significantly expanding the application scope of the 100XF. A flat mirror sample (SiO(_{text{2 }}) coated on a Si wafer) is tested. Results of the variation of reflectivity with angle @ C-K(alpha ) (0.28 keV), Al-K(alpha )(1.49 keV), and Ti-K(alpha )(4.50 keV) are presented in the description. The reflectivity test method has also been applied to the coating reflectivity study of the enhanced X-ray Timing and Polarimetry Mission (eXTP) mirror. At the same time, a new method utilizing the continuum spectrum of bremsstrahlung was carried out to study the continuous variation of reflectivity with energy, greatly improving efficiency compared to traditional methods, and all the results show a good agreement with the theoretical values. The deviation between the test and theoretical values in the low-energy range (1.5-8.0 keV) is less than 10%.

The Chasing All Transients Constellation Hunters (CATCH) space mission is focused on exploring the dynamic universe via X-ray follow-up observations of various transients. The first pathfinder of the CATCH mission, CATCH-1, was launched on June 22, 2024, alongside the Space-based multiband astronomical Variable Objects Monitor (SVOM) mission. CATCH-1 is equipped with narrow-field optimized Micro Pore Optics (MPOs) featuring a large effective area and incorporates four Silicon Drift Detectors (SDDs) in its focal plane. This paper presents the system calibration results conducted before the satellite integration. Utilizing the data on the performance of the mirror and detectors obtained through the system calibration, combined with simulated data, the ground calibration database can be established. Measuring the relative positions of the mirror and detector system, which were adjusted during system calibration, allows for accurate installation of the entire satellite. Furthermore, the paper outlines the operational workflow of the ground network post-satellite launch.

Energetic particles of galactic and solar origin charge the metal free-falling test masses (TMs) of the interferometers for gravitational wave detection in space. The deposited charge couples with stray electric fields thus generating spurious Coulomb forces between the TMs and the electrode housing that limit the interferometer sensitivity. Long-term and short-term galactic cosmic-ray variations are strongly energy-dependent and the TM charging varies with particle energy distribution. We propose three different approaches involving Monte Carlo simulations and machine learning models in comparison to particle transport with the Parker equation to study the recurrent modulation of energy spectra of galactic particles ascribable to the passage of high-speed solar wind streams. The transit of interplanetary counterparts of coronal mass ejections modifies the effects of high-speed streams. This work aims at better understanding the energy-dependence of galactic cosmic-ray short-term variations for the Laser Interferometer Space Antenna (LISA), the first interferometer for gravitational wave detection in space, starting from lessons learned with LISA Pathfinder. The outcomes of our models will be used to assess the TM charging during the time LISA will remain in orbit around the Sun.

HERMES-Pathfinder is a space-borne mission based on a constellation of six nano-satellites flying in a low-Earth orbit. The 3U CubeSats, to be launched in early 2025, host miniaturized instruments with a hybrid Silicon Drift Detector/scintillator photodetector system, sensitive to both X-rays and gamma-rays. A seventh payload unit is installed onboard SpIRIT, an Australian-Italian nano-satellite developed by a consortium led by the University of Melbourne and launched in December 2023. The project aims at demonstrating the feasibility of Gamma-Ray Burst detection and localization using miniaturized instruments onboard nano-satellites. The HERMES flight model payloads were exposed to multiple well-known radioactive sources for spectroscopic calibration under controlled laboratory conditions. The analysis of the calibration data allows both to determine the detector parameters, necessary to map instrumental units to accurate energy measurements, and to assess the performance of the instruments. We report on these efforts and quantify features such as spectroscopic resolution and energy thresholds, at different temperatures and for all payloads of the constellation. Finally we review the performance of the HERMES payload as a photon counter, and discuss the strengths and the limitations of the architecture.

The spatial-temporal evolution of coronal plasma parameters of the solar outer atmosphere at global scales, derived from solar full-disk imaging spectroscopic observation in the extreme-ultraviolet band, is critical for understanding and forecasting solar eruptions. We propose a multi-slits extreme ultraviolet imaging spectrograph for global coronal diagnostics with high cadence and present the preliminary instrument designs for the wavelength range from 18.3 to 19.8 nm. The instrument takes a comprehensive approach to obtain global coronal spatial and spectral information, improve the detected cadence and avoid overlapping. We first describe the relationship between optical properties and structural parameters, especially the relationship between the overlapping and the number of slits, and give a general multi-slits extreme-ultraviolet imaging spectrograph design process. The multilayer structure is optimized to enhance the effective areas in the observation band. Five distantly-separated slits are set to divide the entire solar field of view, which increase the cadence for raster scanning the solar disk by 5 times relative to a single slit. The spectral resolving power of the optical system with an aperture diameter of 150 mm are optimized to be greater than 1461. The spatial resolution along the slits direction and the scanning direction are about (4.4^{prime prime }) and (6.86^{prime prime }), respectively. The Al/Mo/B(_4)C multilayer structure is optimized and the peak effective area is about 1.60 cm(^2) at 19.3 nm with a full width at half maximum of about 1.3 nm. The cadence to finish full-disk raster scan is about 5 minutes. Finally, the instrument performance is evaluated by an end-to-end calculation of the system photon budget and a simulation of the observational image and spectra. Our investigation shows that this approach is promising for global coronal plasma diagnostics.

The High Energy Cosmic-Radiation Detection Facility (HERD) is dedicated to achieving several scientific objectives, including the search for dark matter, precise measurement of the cosmic ray spectrum, and gamma-ray sky survey observations. HERD’s innovative design incorporates a three-dimensional imaging calorimeter with five sensitive faces, significantly enhancing geometric acceptance. However, this design introduces a new challenge for reconstructing particles incident from all directions. This article aims to integrate rapidly advancing deep learning techniques into the reconstruction task. Utilizing simulation data, Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), and other deep learning networks are employed to reconstruct the energy of isotropic electrons. Model performance sees a significant boost through the application of end-layer visible energy correction and a “multi-class multi-prediction” approach, involving different models trained for distinct energy ranges. Moreover, recognizing differences between simulation and physical samples, the model is validated using the beam test data. The model predicts an energy resolution of better than 1% for simulation isotropic electrons ranging from 10 to 1000 GeV. In the case of beam data, the model achieves an energy resolution of 1.3% at 200 GeV, comparable to traditional methods. The results demonstrate the significant potential of deep learning in the reconstruction of three-dimensional calorimeters.

With the increasing aperture as well as the observation frequency of radio telescopes in the current period, the deformation caused by time-varying loads such as temperature and wind has been emphasized. Existing methods for measuring deformations often fall short in meeting the demands of full attitude coverage, quasi-real-time response, and high accuracy. This study introduces a novel geometric-optical measurement approach based on light-tracing. Diverging from traditional methods, this approach doesn’t directly measure the surface deformation of the main reflector. Instead, it creates a more easily measurable variable and establishes a mapping relationship between this variable and the main reflector deformation. In this innovative scheme, multiple laser modules are strategically positioned on the main reflector, treating the sub reflector as a spot projection surface. When the panel is displaced, the spot on the projection surface will follow and be displaced. In practice, the main reflector deformation can be solved by recording the position change of the light spots on the projection surface and utilizing the inverse reconstruction model. Besides, effective strategies are proposed to improve the robustness of the scheme. Next, the accuracy and real-time performance of the proposed method are verified through simulations and experiments. Results indicate that the proposed approach presents a fresh perspective to enhance the efficiency and precision of deformation measurements for large-aperture antennas.

X-ray mirror modules are the core components of X-ray astronomy research, which can focus X-rays from space and significantly improve detection sensitivity. This X-ray optical device are typically composed of nested multiple mirror shells and require maintaining a constant working temperature. Due to the thin-walled structure of the mirror shells and the fact that the inner surface reflects X-rays, direct contact temperature control is not feasible, making temperature control challenging. To evaluate the thermo-optical performance of the mirrors, based on the 100-m X-ray Test Facility (100XF) of the Institute of High Energy Physics (IHEP), a thermo-optical test device with high cleanliness was developed in this study. This system enables precise control of the mirror temperature and synchronous testing of X-ray performance, establishing the unique X-ray thermo-optical testing capability in China. The system consists of a high cleanliness level thermal sink, a liquid nitrogen circuit, multi-layer insulation, a temperature controller, and low-temperature probes. This system has demonstrated the capability to test the thermo-optical performance of X-ray mirror modules and has successfully conducted thermo-optical tests on the mirror module of the follow-up X-ray telescope (FXT) payload onboard the Einstein Probe (EP), achieving precise temperature control of the X-ray mirrors and testing its X-ray optical performance at different operating temperatures. The thermo-optical performance of the mirror module obtained from the thermal tests has been verified in-orbit. This paper provides a detailed description of the design, development, and validation of this system, as well as an overview of the results of the thermo-optical tests conducted on the FXT.