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Zhaohui Shang

Publications and source records attributed to Zhaohui Shang.

At least 19 recordsLinked to original sources

$J$ and $H$ band sky brightness measurements from polar day to polar night at Dome A, Antarctica

The near-infrared (NIR) sky brightness is a fundamental parameter for evaluating the performance of ground-based infrared observatories. Dome~A on the Antarctic plateau offers exceptional atmospheric conditions, yet its NIR sky background has not been continuously monitored. We present the first continuous $J/H$-band measurements of the sky background at Dome~A from polar day to polar night, and characterize their median levels and temporal variability. The Antarctic Infrared Binocular Telescope (AIRBT), operating in the $J$ and $H$ bands, obtained continuous fixed-pointing observations from February to May 2024, which were used to measure the NIR sky background. The median sky brightness is $5.2/2.9$ and $15.3/13.4~\mathrm{mag~arcsec^{-2}}$ in $J/H$ bands during daytime and nighttime, respectively. The twilight--nighttime boundaries occur at solar elevations of $-9.3^\circ$ in $J$ and $-7.4^\circ$ in $H$. At the same solar elevation, the NIR sky background during the polar night is darker by about $0.1$ and $0.4~\mathrm{mag~arcsec^{-2}}$ in the $J$ and $H$ bands compared with the period of regular day--night alternation. During the polar-night period, the nighttime sky brightness in the $H$ band shows a more evident association with the sunspot number, while the corresponding trend in the $J$ band is weaker. These results reveal systematic differences in sky background between polar and non-polar environments and between polar night and regular day--night cycles. The measured sky brightness may be elevated, as the observations were conducted near solar maximum, highlighting the importance of long-term monitoring across the solar cycle.

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Atmospheric turbulence profiling with the Multistar Turbulence Monitor

Accurate characterization of atmospheric optical turbulence is essential for evaluating astronomical sites and optimizing adaptive optics systems. The Multistar Turbulence Monitor (MTM) infers the vertical distribution of the refractive-index structure constant Cn2(z) from differential image motion measured between multiple stellar pairs in short-exposure frames. We present a comprehensive investigation of the MTM method, combining theoretical analysis, instrument-performance assessment, numerical simulations, and on-sky observations obtained at the Daocheng Astronomical Site. Simulations based on a standard HV turbulence model demonstrate that the inversion pipeline robustly recovers both the integrated seeing and the vertical turbulence profile under realistic centroiding noise and varying pixel scales. The Markov Chain Monte Carlo (MCMC) inversion achieves stable results with thirteen discrete height nodes and provides reliable uncertainties. Three nights of MTM measurements at the Daocheng Astronomical Site show that MTM-derived seeing closely tracks simultaneous Differential Image Motion Monitor (DIMM) results, accurately reproducing both short-term fluctuations and nightly averages. These results confirm that MTM provides a simple, portable, and versatile solution for atmospheric turbulence profiling and routine seeing monitoring.

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Deep-learning-based prediction of Precipitable Water Vapor in the Chajnantor area

Astronomical observations at millimeter and submillimeter wavelengths heavily depend on the amount of Precipitable Water Vapor (PWV) in the atmosphere, directly affecting the sky transparency and degrading the quality of the signals received by radio telescopes. Predictions of PWV at different forecasting horizons is crucial to support telescope operations, engineering planning, and observational scheduling and efficiency of radio observatories installed in the Chajnantor area in northern Chile. We developed and validated a Long Short-Term Memory (LSTM) deep learning-based model to predict PWV at forecasting horizons of 12, 24, 36, and 48 hours using historical data from two 183 GHz radiometers and a weather station in the Chajnantor area. We find the LSTM method is able to predict PWV in the 12 and 24 hours forecasting horizons with Mean Absolute Percentage Error (MAPE) of 22% compared to 36% of the traditional Global Forecast System (GFS) method used by Atacama Pathfinder EXperiment (APEX) and the Root Mean Square Error (RMSE) in mm are reduced by 50%. We present a first application of deep learning techniques for preliminary predictions of PWV in the Chajnantor area. The prediction performance shows significant improvements to traditional methods in 12 and 24 hours time windows. We also propose upgrades to improve our method in short (< 1 hour) and long (> 36 hours) forecasting timescales for future work.

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Antarctic Infrared Binocular Telescope: Early Data Release of observations in the 1.4 μm water-vapor-absorption band

Ground-based observations around 1.4 $μ$m are normally limited by strong absorption of telluric water-vapor. However, Dome A, Antarctica has exceptionally dry conditions that offer a unique opportunity for observations in this band. We designed a new filter covering 1.34--1.48 $μ$m, namely $W'$, and installed it on the Antarctic Infrared Binocular Telescope (AIRBT) at Dome A in 2025. AIRBT comprises two identical 15 cm optical tube assemblies and two InGaAs cameras equipped with $J$ and $W'$ filters, respectively. With this Early Data Release (EDR), we aim to evaluate the performance of the $W'$ band at Dome A to observe objects with water-vapor features. This EDR covers $\thicksim 20 \ \mathrm{deg^2}$ in the Galactic plane using $\thicksim 20,000$ images in three nights. For 2 s exposures, the 5 $σ$ limiting magnitude histogram peaks at $J \thicksim 11.5$ mag (Vega) and $W' \thicksim 9.9$ mag, respectively. The $J-W'$ vs $J-H$ color-color diagram distinguishes ultracool candidates with water-vapor-absorption features from reddened early type stars. Furthermore, later-type stars tend to exhibit stronger water-vapor absorption. Some sources show larger $ΔW'$ than $ΔJ$ across the three nights, which we attribute to variations of their water-vapor-absorption depth. We conclude that it will be efficient to search for ultracool stars and estimate their spectral subtypes using $W'$ band imaging at Dome A, where the atmospheric transmission is high and stable.

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Antarctic Infrared Binocular Telescope. I. System Overview, Laboratory Testing, and On-Sky Performance Evaluation

Infrared time-domain surveys remain significantly underdeveloped compared with their optical counterparts. We have developed the Antarctic Infrared Binocular Telescope (AIRBT) to study the dynamic infrared sky at Dome A, Antarctica, taking advantage of the superb infrared observational conditions at this site. AIRBT consists of two identical 15 cm f/3 optical tube assemblies and two cost-effective indium gallium arsenide (InGaAs) cameras equipped with J and H filters, respectively. The cameras have 640 x 512 pixels with a size of 15 micrometers, providing a scale of 6.9 arcseconds per pixel and a field of view of 1.22 x 0.97 square degrees. We characterize the performance of the InGaAs cameras, including bias, readout noise, dark current, nonlinearity, and photon transfer curve. Our analysis highlights the distinct behaviors of InGaAs cameras compared with charge-coupled devices (CCDs). The bias and readout noise show temperature dependence, and the noise measured from the photon transfer curves has additional components that increase with exposure time. On-sky tests were conducted in October 2022 including system calibration, limiting depth, and photometric precision. For a single 3-second exposure, we achieved 5-sigma limiting magnitudes of 11.2 mag (Vega system) in J band and 9.7 mag in H band. The best photometric precision reached 20 millimagnitudes at the bright end, which could be further improved to sub-percent levels through image stacking. AIRBT was installed at Dome A in January 2023, and scientific observations began as soon as darkness set in.

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Probing the cosmological 21~cm global signal from the Antarctic ice sheet

The redshifted 21 cm line, arising from neutral hydrogen, offers a unique probe into the intergalactic medium and the first stars and galaxies formed in the early universe. However, detecting this signal is a challenging task because of artificial radio-frequency interference (RFI) and systematic errors such as ground effects. The interior of the Antarctic continent provides an excellent location to make such observations, with minimal RFI and relatively stable foreground signals. Moreover, a flat plateau in central Antarctica, with an ice cap over 2000 m deep, will show less ground reflection of radio waves, reducing the signal complexity in the area around the probing antenna. It may be advantageous to perform cosmological 21 cm experiments in Antarctica, and a 21 cm Antarctic global spectrum experiment can potentially be deployed on the Antarctic ice cap. We have performed preliminary instrumental design, system calibration, and implementation of such an instrument optimized for extreme cold and capable of long-term autonomous operation. This system shows the ability to effectively detect the 21~cm signal, confirming Antarctica as an excellent observational site for radio cosmology.

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The Mini-SiTian Array: A Pathfinder for the SiTian Project

The Mini-SiTian Array serves as a pathfinder for the SiTian project, which aims to survey the entire sky in $gri$ bands every 30 minutes, reaching a limiting magnitude of 21. This special issue features 11 papers covering the design, operation, data reduction, and early scientific results from two years of Mini-SiTian observations. The insights gained from these pathfinder experiments represent a significant milestone toward the full realization of the SiTian project.

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GRRIS: a real-time intra-site observation scheduling scheme for distributed survey telescope arrays

The distributed telescope array offers promise for conducting large-sky-area, high-frequency time domain surveys. Multiple telescopes can be deployed at each observation site, so intra-site observation task scheduling is crucial for enhancing observation efficiency and quality. Efficient use of observable time and rapid response to special situations are critical to maximize scientific discovery in time domain surveys. Besides, the competing scientific priorities, time-varying observation conditions, and capabilities of observation equipment, lead to a vast search space of the scheduling. So with the increasing number of telescopes and observation fields, balancing computational time with solution quality in observation scheduling poses a significant challenge. Informed by the seminal contributions of earlier studies on a multilevel scheduling model and global scheduler for time domain telescope array, this study is devoted to further exploring the site scheduler. Formulating the observation scheduling of multiple telescopes at the site as a cooperative decision-making problem, this paper proposes GRRIS, a real-time intra-site observation scheduling scheme for telescope array using graph and reinforcement learning. It employs a graph neural network to learn node features that can embed the spatial structure of the observation scheduling. An algorithm based on multi-agent reinforcement learning is designed to efficiently learn the optimum allocation policy of telescope agents to field nodes. Through numerical simulations with real-world scenarios, GRRIS can achieve up to a 22% solution improvement over the most competitive scheme. It offers better scalability and sub-second decision speed, meeting the needs of observation scheduling control for future distributed telescope arrays.

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Machine learning-based seeing estimation and prediction using multi-layer meteorological data at Dome A, Antarctica

Atmospheric seeing is one of the most important parameters for evaluating and monitoring an astronomical site. Moreover, being able to predict the seeing in advance can guide observing decisions and significantly improve the efficiency of telescopes. However, it is not always easy to obtain long-term and continuous seeing measurements from a standard instrument such as differential image motion monitor (DIMM), especially for those unattended observatories with challenging environments such as Dome A, Antarctica. In this paper, we present a novel machine learning-based framework for estimating and predicting seeing at a height of 8 m at Dome A, Antarctica, using only the data from a multi-layer automated weather station (AWS). In comparison with DIMM data, our estimate has a root mean square error (RMSE) of 0.18 arcsec, and the RMSE of predictions 20 minutes in the future is 0.12 arcsec for the seeing range from 0 to 2.2 arcsec. Compared with the persistence, where the forecast is the same as the last data point, our framework reduces the RMSE by 37 percent. Our method predicts the seeing within a second of computing time, making it suitable for real-time telescope scheduling.

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Data Release of the AST3-2 Automatic Survey from Dome A, Antarctica

AST3-2 is the second of the three Antarctic Survey Telescopes, aimed at wide-field time-domain optical astronomy. It is located at Dome A, Antarctica, which is by many measures the best optical astronomy site on the Earth's surface. Here we present the data from the AST3-2 automatic survey in 2016 and the photometry results. The median 5$σ$ limiting magnitude in $i$-band is 17.8 mag and the light curve precision is 4 mmag for bright stars. The data release includes photometry for over 7~million stars, from which over 3,500 variable stars were detected, with 70 of them newly discovered. We classify these new variables into different types by combining their light curve features with stellar properties from surveys such as StarHorse.

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A Multilevel Scheduling Framework for Distributed Time-domain Large-area Sky Survey Telescope Array

Telescope arrays are receiving increasing attention due to their promise of higher resource utilization, greater sky survey area, and higher frequency of full space-time monitoring than single telescopes. Compared with the ordinary coordinated operation of several telescopes, the new astronomical observation mode has an order of magnitude difference in the number of telescopes. It requires efficient coordinated observation by large-domain telescopes distributed at different sites. Coherent modeling of various abstract environmental constraints is essential for responding to multiple complex science goals. Also, due to competing science priorities and field visibility, how the telescope arrays are scheduled for observations can significantly affect observation efficiency. This paper proposes a multilevel scheduling model oriented toward the problem of telescope-array scheduling for time-domain surveys. A flexible framework is developed with basic functionality encapsulated in software components implemented on hierarchical architectures. An optimization metric is proposed to self-consistently weight contributions from time-varying observation conditions to maintain uniform coverage and efficient time utilization from a global perspective. The performance of the scheduler is evaluated through simulated instances. The experimental results show that our scheduling framework performs correctly and provides acceptable solutions considering the percentage of time allocation efficiency and sky coverage uniformity in a feasible amount of time. Using a generic version of the telescope-array scheduling framework, we also demonstrate its scalability and its potential to be applied to other astronomical applications.

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Cloud Cover and Aurora Contamination at Dome A in 2017 from KLCAM

Dome A in Antarctica has many characteristics that make it an excellent site for astronomical observations, from the optical to the terahertz. Quantitative site testing is still needed to confirm the site's properties. In this paper, we present a statistical analysis of cloud cover and aurora contamination from the Kunlun Cloud and Aurora Monitor (KLCAM). KLCAM is an automatic, unattended all-sky camera aiming for long-term monitoring of the usable observing time and optical sky background at Dome~A. It was installed at Dome~A in January 2017, worked through the austral winter, and collected over 47,000 images over 490 days. A semi-quantitative visual data analysis of cloud cover and auroral contamination was carried out by five individuals. The analysis shows that the night sky was free of cloud for 83 per cent of the time, which ranks Dome~A highly in a comparison with other observatory sites. Although aurorae were detected somewhere on an image for nearly 45 per cent of the time, the strongest auroral emission lines can be filtered out with customized filters.

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Astronomy from Dome A in Antarctica

Dome A in Antarctica has been demonstrated to be the best site on earth for optical, infrared, and terahertz astronomical observations by more and more evidence, such as excellent free-atmosphere seeing, extremely low perceptible water vapor, low sky background, and continuous dark time, etc. In this review paper, we present a complete picture of the development of astronomy at Dome A from the very beginning, review recent progress in time-domain astronomy, demonstrate exciting results of the site testing, and address the challenges in instrumentation. Currently proposed projects are briefly discussed.

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NBFTP: A Dedicated Data Transfer System for Remote Astronomical Observation at Dome A

Dome A, Antarctica has been thought to be one of the best astronomical sites on the earth since decades ago. From it was first visited by astronomers in 2008, dozens of facilities for astronomical observation and site testing were deployed. Due to its special geographical location, the data and message exchange between Dome A and the domestic control center could only depend on Iridium. Because the link bandwidth of Iridium is extremely limited, meanwhile the network traffic cost is quite expensive and the network is rather unstable, the commonly used data transfer tools, such as rsync and scp, are not suitable in this case. In this paper, we design and implement a data transfer tool called NBFTP (narrow bandwidth file transfer protocol) for the astronomical observation of Dome A. NBFTP uses a uniform interface to arrange all types of data and matches specific transmission schemes for different data types according to rules. Break-point resuming and extensibility functions are also implemented. Our experimental results show that NBFTP consumes 60% less network traffic than rsync when detecting the data pending to be transferred. And when transferring small files of 1KB, the network traffic consumption of NBFTP is 40% less than rsync. However, as the file size increases, the network traffic consumption of NBFTP tends to approach rsync, but it is still smaller than rsync.

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Night-time measurements of astronomical seeing at Dome A in Antarctica

Seeing, the angular size of stellar images blurred by atmospheric turbulence, is a critical parameter used to assess the quality of astronomical sites. Median values at the best mid-latitude sites are generally in the range of 0.6--0.8\,arcsec. Sites on the Antarctic plateau are characterized by comparatively-weak turbulence in the free-atmosphere above a strong but thin boundary layer. The median seeing at Dome C is estimated to be 0.23--0.36 arcsec above a boundary layer that has a typical height of 30\,m. At Dome A and F, the only previous seeing measurements were made during daytime. Here we report the first direct measurements of night-time seeing at Dome A, using a Differential Image Motion Monitor. Located at a height of just 8\,m, it recorded seeing as low as 0.13\,arcsec, and provided seeing statistics that are comparable to those for a 20\,m height at Dome C. It indicates that the boundary layer was below 8\,m 31\% of the time. At such times the median seeing was 0.31\,arcsec, consistent with free-atmosphere seeing. The seeing and boundary layer thickness are found to be strongly correlated with the near-surface temperature gradient. The correlation confirms a median thickness of approximately 14\,m for the boundary layer at Dome A, as found from a sonic radar. The thinner boundary layer makes it less challenging to locate a telescope above it, thereby giving greater access to the free-atmosphere.

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The SiTian project

SiTian is an ambitious ground-based all-sky optical monitoring project, developed by the Chinese Academy of Sciences. The concept is an integrated network of dozens of 1-m-class telescopes deployed partly in China and partly at various other sites around the world. The main science goals are the detection, identification and monitoring of optical transients (such as gravitational wave events, fast radio bursts, supernovae) on the largely unknown timescales of less than 1 day; SiTian will also provide a treasure trove of data for studies of AGN, quasars, variable stars, planets, asteroids, and microlensing events. To achieve those goals, SiTian will scan at least 10,000 square deg of sky every 30 min, down to a detection limit of $V \approx 21$ mag. The scans will produce simultaneous light-curves in 3 optical bands. In addition, SiTian will include at least three 4-m telescopes specifically allocated for follow-up spectroscopy of the most interesting targets. We plan to complete the installation of 72 telescopes by 2030 and start full scientific operations in 2032.

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Automation of the AST3 optical sky survey from Dome~A, Antarctica

The 0.5\,m Antarctic Survey Telescopes (AST3) were designed for time-domain optical/infrared astronomy. They are located in Dome~A, Antarctica, where they can take advantage of the continuous dark time during winter. Since the site is unattended in winter, everything for the operation, from observing to data reduction, had to be fully automated. Here, we present a brief overview of the AST3 project and some of its unique characteristics due to its location in Antarctica. We summarise the various components of the survey, including the customized hardware and software, that make complete automation possible.

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Multi-star Turbulence Monitor: A new technique to measure optical turbulence profiles

The strength and vertical distribution of atmospheric turbulence is a key factor determining the performance of optical and infrared telescopes, with and without adaptive optics. Yet, this remains challenging to measure. We describe a new technique using a sequence of short-exposure images of a star field, obtained with a small telescope. Differential motion between all pairs of star images is used to compute the structure functions of longitudinal and transverse wavefront tilt for a range of angular separations. These are compared with theoretical predictions of simple turbulence models by means of a Markov-Chain Monte-Carlo optimization. The method is able to estimate the turbulence profile in the lower atmosphere, the total and free-atmosphere seeing, and the outer scale. We present results of Monte-Carlo simulations used to verify the technique, and show some examples using data from the second AST3 telescope at Dome A in Antarctica.

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