Basic Survey Scheduling for the Wide Field Survey Telescope(WFST)

Aiming at improving the survey efficiency of the Wide Field Survey Telescope, we have developed a basic scheduling strategy that takes into account the telescope characteristics, observing conditions, and weather conditions at the Lenghu site. The sky area is divided into rectangular regions, referred to as “tiles,” with a size of2°. 577 × 2°. 634 slightly smaller than the focal area of the mosaic CCDs. These tiles are continuously filled in annulars parallel to the equator. The brightness of the sky background, which varies with the moon phase and distance from the moon, plays a significant role in determining the accessible survey fields. Approximately 50connected tiles are grouped into one block for observation. To optimize the survey schedule, we perform simulations by taking into account the length of exposures, data readout, telescope slewing, and all relevant observing conditions. We utilize the Greedy Algorithm for scheduling optimization. Additionally, we propose a dedicated dithering pattern to cover the gaps between CCDs and the four corners of the mosaic CCD array, which are located outside of the 3° field of view. This dithering pattern helps to achieve relatively uniform exposure maps for the final survey outputs.

Design and Cryogenic Performance of a Hexapod Platform for a Large Ground-based Wide Field Survey Telescope

The thermal gradient is an important factor that causes degradation to the image quality of telescopes. In order to ensure the accurate alignment of the primary focus unit and the primary mirror, the hexapod platform(as a corrector) is investigated in this paper. First, a ground-based telescope with 2.5 m aperture and 3.5 deg field of view is described. The telescope is under construction, and it is expected to be finished in 2023. Second, the hexapod platform with flexure hinges utilized to adjust the primary focus unit is proposed, which is applied as a corrector.Then, the inverse kinematics of the platform is established and an open-loop control system is built based on it.Finally, the cryogenic performance test for the hexapod platform is performed. The experimental results show that the resolution and repeatability of the translation for the hexapod platform can be achieved at the micrometer level.The resolution and repeatability of the rotation can be achieved at the arc-second level. Therefore, the cryogenic performance of the hexapod platform can meet the optical imaging requirements of the wide-field ground-based telescope. The kinematic analysis and cryogenic performance tests in the paper provide a technical reference for the precise alignment of the primary focus unit and the primary mirror, which can improve the imaging quality of the telescope.

Disturbance Observer-based Pointing Control of Leighton Chajnantor Telescope

Leighton Chajnantor Telescope(LCT), i.e., the former Caltech Submillimeter Observatory telescope, will be refurbished at the new site in Chajnantor Plateau, Chile in 2023. The environment of LCT will change significantly after its relocation, and the telescope will be exposed to large wind disturbances directly because its enclosure will be completely open during observation. The wind disturbance is expected to be a challenge for LCT's pointing control since the existing control method cannot reject this disturbance very well. Therefore, it is very necessary to develop a new pointing control method with good capability of disturbance rejection. In this research, a disturbance observer—based composite position controller(DOB-CPC) is designed, in which an H∞feedback controller is employed to compress the disturbance, and a feedforward linear quadratic regulator is employed to compensate the disturbance precisely based on the estimated disturbance signal. Moreover, a controller switching policy is adopted, which applies the proportional controller to the transient process to achieve a quick response and applies the DOB-CPC to the steady state to achieve a small position error. Numerical experiments are conducted to verify the good performance of the proposed pointing controller(i.e., DOB-CPC) for rejecting the disturbance acting on LCT.

Prospects of the Multi-channel Photometric Survey Telescope in the Cosmological Application of Type Ia Supernovae

The Multi-channel Photometric Survey Telescope(Mephisto)is a real-time,three-color photometric system designed to capture the color evolution of stars and transients accurately.This telescope system can be crucial in cosmological distance measurements of low-redshift(low-z,z■0.1)Type Ia supernovae(SNe Ia).To optimize the capabilities of this instrument,we perform a comprehensive simulation study before its official operation is scheduled to start.By considering the impact of atmospheric extinction,weather conditions,and the lunar phase at the observing site involving the instrumental features,we simulate light curves of SNe Ia obtained by Mephisto.The best strategy in the case of SN Ia cosmology is to take the image at an exposure time of 130 s with a cadence of 3 days.In this condition,Mephisto can obtain hundreds of high-quality SNe Ia to achieve a distance measurement better than 4.5%.Given the on-time spectral classification and monitoring of the Lijiang 2.4 m Telescope at the same observatory,Mephisto,in the whole operation,can significantly enrich the well-calibrated sample of supernovae at low-z and improve the calibration accuracy of high-z SNe Ia.

The Jiao Tong University Spectroscopic Telescope Project

The Jiao Tong University Spectroscopic Telescope(JUST)is a 4.4-meter f/6.0 segmented-mirror telescope dedicated to spectroscopic observations.The JUST primary mirror is composed of 18 hexagonal segments,each with a diameter of 1.1 m.JUST provides two Nasmyth platforms for placing science instruments.One Nasmyth focus fits a field of view of 10′and the other has an extended field of view of 1.2°with correction optics.A tertiary mirror is used to switch between the two Nasmyth foci.JUST will be installed at a site at Lenghu in Qinghai Province,China,and will conduct spectroscopic observations with three types of instruments to explore the dark universe,trace the dynamic universe,and search for exoplanets:(1)a multi-fiber(2000 fibers)medium-resolution spectrometer(R=4000-5000)to spectroscopically map galaxies and large-scale structure;(2)an integral field unit(IFU)array of 500 optical fibers and/or a long-slit spectrograph dedicated to fast follow-ups of transient sources for multi-messenger astronomy;(3)a high-resolution spectrometer(R~100000)designed to identify Jupiter analogs and Earth-like planets,with the capability to characterize the atmospheres of hot exoplanets.

Are James Webb Space Telescope Observations Consistent with Warm Dark Matter?

We compare observed with predicted distributions of galaxy stellar masses M* and galaxy rest-frame ultra-violet luminosities per unit bandwidth LUV, in the redshift range z=2 to 13. The comparison is presented as a function of the comoving warm dark matter free-streaming cut-off wavenumber kfs. For this comparison the theory is a minimal extension of the Press-Schechter formalism with only two parameters: the star formation efficiency, and a proportionality factor between the star formation rate per galaxy and LUV. These two parameters are fixed to their values obtained prior to the James Webb Space Telescope (JWST) data. The purpose of this comparison is to identify if, and where, detailed astrophysical evolution is needed to account for the new JWST observations.

Integrated Test System for Large-aperture Telescopes Based on Astrophotonics Interconnections

This study aims to improve the integrated testing of large-aperture telescopes to clarify the fundamental principles of an integrated testing system based on astrophotonics.Our demonstration and analyses focused on element-position sensing and modulation based on spatial near-geometric beams,high-throughput step-difference measurements based on channel spectroscopy,distributed broadband-transmittance testing,and standard spectral tests based on near-field energy regulation.Comprehensive analyses and experiments were conducted to confirm the feasibility of the proposed system in the integrated testing process of large-aperture telescopes.The results demonstrated that the angular resolution of the light rays exceeded 5arcsec,which satisfies the requirements for component-position detection in future large-aperture telescopes.The measurement resolution of the wavefront tilt was better than 0.45μrad.Based on the channel spectral method—which combined a high signal-to-noise ratio and high sensitivity,along with continuous-spectral digital segmentation and narrowband-spectral physical segmentation—a resolution of 0.050μm and a range of 50μm were obtained.After calibration,the measurement resolution of the pupil deviation improved to exceed 4%accuracy,and the transmission measurements achieved a consistency of over 2%accuracy.Regarding fringe-broadband interferometry measurements,the system maintained high stability,ensuring its operation within the coherence length,and robustly detected the energy without unwrapping the phase.The use of a projector for calibrating broadband-spectrum measurements led to a reduction in contrast from 0.8142 to 0.6038,which further validates the system's applicability in the integrated testing process of large-aperture telescopes.This study greatly enhanced the observational capabilities of large-aperture telescopes while reducing the integrated system's volume,weight,and power consumption.

FAST:The Five-Hundred-Meter Aperture Spherical Radio Telescope

In the 90 years since its inception,radio astronomy has become the setting of almost all major astronomical discoveries and a hothouse for Nobel Prizes in Physics.As a result,countries all over the world have actively explored new engineering concepts to build large-aperture radio telescopes.Limited by their self-weight and wind load,100 m radio telescopes are regarded as the maximum limit of traditional radio telescopes.This perspective allowed the Arecibo 305 m telescope—built by Cornell University in the United States in 1963—to dominate the field for more than half a century.During this period,scholars have been exploring how to further expand their horizons in order to make a breakthrough in the problem of the universe.

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST)

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST, also called the Guo Shou Jing Telescope) is a special reflecting Schmidt telescope. LAMOST’s special design allows both a large aperture (effective aperture of 3.6 m–4.9 m) and a wide field of view (FOV) (5°). It has an innovative active reflecting Schmidt configuration which continuously changes the mirror’s surface that adjusts during the observation process and combines thin deformable mirror active optics with segmented active optics. Its primary mirror (6.67m×6.05 m) and active Schmidt mirror (5.74m×4.40 m) are both segmented, and composed of 37 and 24 hexagonal sub-mirrors respectively. By using a parallel controllable fiber positioning technique, the focal surface of 1.75 m in diameter can accommodate 4000 optical fibers. Also, LAMOST has 16 spectrographs with 32 CCD cameras. LAMOST will be the telescope with the highest rate of spectral acquisition. As a national large scientific project, the LAMOST project was formally proposed in 1996, and approved by the Chinese government in 1997. The construction started in 2001, was completed in 2008 and passed the official acceptance in June 2009. The LAMOST pilot survey was started in October 2011 and the spectroscopic survey will launch in September 2012. Up to now, LAMOST has released more than 480 000 spectra of objects. LAMOST will make an important contribution to the study of the large-scale structure of the Universe, structure and evolution of the Galaxy, and cross-identification of multiwaveband properties in celestial objects.

Terrain-influenced wind flow of the Qitai radio telescope site

The wind environment of a site is one of the important factors affecting the observation performance of large aperture and high-performance radio telescopes.Exploring the relationship between the effects of different terrains on wind flow is important to optimize the wind environment of the site.The terrain of the Qitai radio telescope(QTT)site located in east Tianshan Mountains at an elevation of about 1800 m was used to study the wind flow in the adjacent zone of antenna based on numerical simulation.The area from 600m south to 600m north of the antenna is defined as the antenna adjacent zone,and three groups of boundaries with different terrains are set up upstream and downstream,respectively.Since the zone where the antenna is located is a slope terrain,in order to verify the influence of terrain on the wind flow and to clarify the relationship between the influence of boundary terrain on the wind flow,a control group of horizontal terrain is constructed.The simulation results show that the wind flow is mainly influenced by the terrain.The highest elevation of the upstream and downstream boundary terrains affects the basic wind speed.The upstream boundary terrain has a greater impact on wind flow than the downstream boundary terrain.In addition,the wind speed profile index obtained by numerical simulation is smaller than the actual index for the wind from south.Therefore,the wind speed at the upper level(about 100 m)obtained by inversion based on the measured wind speed at the bottom(about 10 m)is also smaller than the actual wind speed.

Direct Ion Beam Figuring Process and Rotational Measurement Method for Ultra-smooth Aspherical Surfaces of a 46.5 nm Telescope

This paper describes a fabrication process for the hyperboloidal concave mirror of a 46.5 nm telescope. The180 mm aperture hyperboloidal concave mirror and 70 mm aperture compensator are machined directly from chemical mechanical polishing of a spherical surface to a high-accuracy aspherical surface by ion beam figuring.The aspherical measurement method is the Dall null test. To minimize system errors in the measurement process,the rotational measurement method with six rotations is used in the null test. The results of the analysis for the ME(first solve the machined surface profile, then solve the system errors) and EM(first solve the system errors, then solve the machined surface profile) methods of calculation in the measurement are given. The ME method is a more accurate rotational test method, and the six rotations are appropriate for rotational measurements. After the figuring process, the hyperboloidal concave mirror surface profile reached 8.27 nm rms and the compensator surface profile is approximately 4 nm rms. The roughness of the hyperboloidal concave mirror is smooth to0.160 nm rms.

Back Frame Section Size Optimization of Large Aperture Telescope

The back frame structure of a large radio telescope is an important component supporting the reflecting surface,which is directly related to the surface precision.Its optimal design is of key significance for ensuring the surface precision and reducing structural weight.Two methods are constructed to optimize the cross-section size of the telescope back frame in this paper,the criterion method and the first-order optimization method.The criterion method is based on the Lagrangian multiplier method and Kuhn-Tucker condition.This method first establishes the mathematical model by taking the inner and outer radiuses of the back frame beams as the design variables,the structural weight as the constraint condition,and the structural compliance as the objective function,then derives the optimization criterion.The first-order optimization method takes the inner and outer radiuses of the beams as the design variables,the back frame RMS as the objective function,and the structural weight as the constraint condition.Comparison of RMS,structural stress uniformity and optimization efficiency shows that both algorithms can effectively reduce structural deformation and improve RMS,but the criterion method has relatively better result than the first-order method.

Distributed Control Software for the Active Surface System of Tian-ma Radio Telescope

The Tian-ma Radio Telescope(TMRT) applies an Active Surface System(ASFS), which corrects for large-scale deformations due to gravity and thermal on the primary reflector. The centralized and automated management of the ASFS using software has become a challenge, for which we have developed the TMRT Active Surface System Control Software(TASCS). This paper describes the design and implementation of TASCS for device control,status monitoring, human-computer interaction, and data management functionalities. TASCS adopts the opensource Tango Controls framework and distributes middleware technology to realize real-time automated adjustment of the primary reflector through remote centralized control of a large number of actuators. At present, it has been successfully deployed on the TMRT and has played an important role in Event Horizon Telescope observations.

Two annular CsI(Tl) detector arrays for the charged particle telescopes

In this study,we constructed two annular detector arrays comprising 24 wedge-shaped CsI(Tl) crystals,and tested them using anαsource and radioactive beams of ^(14-16) Con a CD_2 target.We compared the properties of a CsI(Tl) crystal encapsulated with various reflectors,revealing that using the 80-μm-thick ESR film to pack the CsI(Tl) crystal yielded the largest light output with the smallest non-uniformity in light output (ΔLO).For the 24 CsI(Tl) detectors with the 80-μm-thick ESR films,the average energy resolution improved as the average light output increased;however,it deteriorated as theΔLO value increased.To form two annular Si-CsI(Tl) telescopes for identifying the light-charged particles,theΔLO value and energy resolution of each CsI(Tl) detector were maintained under 20%and 7.7%,respectively.These telescopes were tested for the first time in a direct nuclear reaction experiment using ^(14-16) C+d.The results demonstrated that the Z=1 and Z=2 charged particles were adequately discriminated by the telescopes using the standardΔE-E method.

Optical system research of multi-object fiber spectroscopic survey telescope

In the first part of this paper,four different Cassegrain optical systems with their correctors are designed and studied for multi-object fiber slit spectroscopic survey.The aperture in 6.5 m and field of view 3°are taken for these optical systems.Assuming observation wavelength range is 0.365-0.95μm,the maximum zenith distance for observing is 60°,the maximum diameter of these lenses is 1.66 m,the altitude of the telescope site is 2500 m,two correctors are composed of 4-piece lenses and the other two are 5-piece lenses.The results obtained are:f-ratio about 3.7,the image quality for all four systems with EE80D≤0.60″,the linear diameter of the focal surface is about 1.2 m and 11 000 fibers can be set on it.Considering the limit of size of fused silica and optical glass,the maximum diameter for lens is about 1.7 m.Such a 6.5 m telescope is about the largest one if using the above correctors.Considering the multiobject spectroscopic survey is greatly important,we also studied some telescope optical systems having their aperture near or larger than 10 m used for the multi-object fiber spectroscopic survey.Such ideas are introduced in the last section of this paper.

Photometric Monitoring of Blazar 3C 66A with the Yunnan University Astronomical Observatory 1 m Telescope

3C 66A is one of our first batches of photometric monitoring objects with the 1 m optical telescope at Yunnan University Astronomical Observatory.In the present work,the observational campaign was performed from 2021 November 1 to 2022 February 27 in the Johnson-Morgan system V and R bands.The average magnitudes in each band were■=15.52±0.18 mag and■=15.07±0.17 mag.The overall variability amplitudes wereΔV=■,Amp=70.27%andΔR=■,Amp=68.56%,respectively.Most of the intraday variabilities(IDVs)occurred in 2021 December and 2022 February.The minimal rise/decay timescale was about 6 minutes(5.82±2.74 minutes and 6.18±2.81 minutes on 2022 February 11,6.99±3.70 minutes and 6.17±2.91 minutes on 2022 February 12).Durations of these rapid variabilities were from 11.99 to 179.67 minutes.The discrete correlation function analyses between V and R bands showed significantly correlated variability.Color index analysis of ID Vs showed that the spectrums do not change with variabilities.

A Secure and Cost-Effective Training Framework Atop Serverless Computing for Object Detection in Blasting

The data analysis of blasting sites has always been the research goal of relevant researchers.The rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of blasting.Serverless Computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine learning.In this paper,we design a distributedmachine learning training application based on the AWS Lambda platform.Based on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively realized.It also encrypts the data set,effectively reducing the risk of data leakage.We rent a cloud server and a Lambda,and then we conduct experiments to evaluate our applications.Our results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.

Learning Discriminatory Information for Object Detection on Urine Sediment Image

In clinical practice,the microscopic examination of urine sediment is considered an important in vitro examination with many broad applications.Measuring the amount of each type of urine sediment allows for screening,diagnosis and evaluation of kidney and urinary tract disease,providing insight into the specific type and severity.However,manual urine sediment examination is labor-intensive,time-consuming,and subjective.Traditional machine learning based object detection methods require hand-crafted features for localization and classification,which have poor generalization capabilities and are difficult to quickly and accurately detect the number of urine sediments.Deep learning based object detection methods have the potential to address the challenges mentioned above,but these methods require access to large urine sediment image datasets.Unfortunately,only a limited number of publicly available urine sediment datasets are currently available.To alleviate the lack of urine sediment datasets in medical image analysis,we propose a new dataset named UriSed2K,which contains 2465 high-quality images annotated with expert guidance.Two main challenges are associated with our dataset:a large number of small objects and the occlusion between these small objects.Our manuscript focuses on applying deep learning object detection methods to the urine sediment dataset and addressing the challenges presented by this dataset.Specifically,our goal is to improve the accuracy and efficiency of the detection algorithm and,in doing so,provide medical professionals with an automatic detector that saves time and effort.We propose an improved lightweight one-stage object detection algorithm called Discriminatory-YOLO.The proposed algorithm comprises a local context attention module and a global background suppression module,which aid the detector in distinguishing urine sediment features in the image.The local context attention module captures context information beyond the object region,while the global background suppression module emphasizes objects in uninformative backgrounds.We comprehensively evaluate our method on the UriSed2K dataset,which includes seven categories of urine sediments,such as erythrocytes(red blood cells),leukocytes(white blood cells),epithelial cells,crystals,mycetes,broken erythrocytes,and broken leukocytes,achieving the best average precision(AP)of 95.3%while taking only 10 ms per image.The source code and dataset are available at https://github.com/binghuiwu98/discriminatoryyolov5.

Enhancing Dense Small Object Detection in UAV Images Based on Hybrid Transformer

Transformer-based models have facilitated significant advances in object detection.However,their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unmanned aerial vehicle(UAV)imagery.Addressing these limitations,we propose a hybrid transformer-based detector,H-DETR,and enhance it for dense small objects,leading to an accurate and efficient model.Firstly,we introduce a hybrid transformer encoder,which integrates a convolutional neural network-based cross-scale fusion module with the original encoder to handle multi-scale feature sequences more efficiently.Furthermore,we propose two novel strategies to enhance detection performance without incurring additional inference computation.Query filter is designed to cope with the dense clustering inherent in drone-captured images by counteracting similar queries with a training-aware non-maximum suppression.Adversarial denoising learning is a novel enhancement method inspired by adversarial learning,which improves the detection of numerous small targets by counteracting the effects of artificial spatial and semantic noise.Extensive experiments on the VisDrone and UAVDT datasets substantiate the effectiveness of our approach,achieving a significant improvement in accuracy with a reduction in computational complexity.Our method achieves 31.9%and 21.1%AP on the VisDrone and UAVDT datasets,respectively,and has a faster inference speed,making it a competitive model in UAV image object detection.

Local saliency consistency-based label inference for weakly supervised salient object detection using scribble annotations

Recently,weak supervision has received growing attention in the field of salient object detection due to the convenience of labelling.However,there is a large performance gap between weakly supervised and fully supervised salient object detectors because the scribble annotation can only provide very limited foreground/background information.Therefore,an intuitive idea is to infer annotations that cover more complete object and background regions for training.To this end,a label inference strategy is proposed based on the assumption that pixels with similar colours and close positions should have consistent labels.Specifically,k-means clustering algorithm was first performed on both colours and coordinates of original annotations,and then assigned the same labels to points having similar colours with colour cluster centres and near coordinate cluster centres.Next,the same annotations for pixels with similar colours within each kernel neighbourhood was set further.Extensive experiments on six benchmarks demonstrate that our method can significantly improve the performance and achieve the state-of-the-art results.