This paper presents the photometric and spectroscopic analysis of a long-period totally eclipsing contact binary (HAT 307-0007476) for the first time. This system is a low mass ratio ($q\sim 0.114$) and medium contact binary ($f\sim 37.1~{{\ \rm per\ cent}}$). Two flare events were detected in multiple bands observations in December 2022. The interval between the two flare events is 4 d. The average duration of these two flares is about 2289 s. Both the two flares achieve the energy levels of superflares. The excess emission of the H$_\alpha$ line in the LAMOST spectra of this object was analysed, indicating its chromospheric activity. The O–C diagram showed a long-term orbital period increase, which is due to the mass transfer between the two component stars. We conclude that HAT 307-0007476 is currently in a stable region based on both Jspin/Jorb and the comparison between the instability parameters and its current values.

Ground-based astronomical observations face inherent challenges from weather changes, target visibility window constraints, and observational requirements. Enhancing the efficiency and effectiveness of telescope operations has long been a key objective for many observatories because of the high cost of observational resources. In this study, we formalize observation scheduling as a time-dependent combinatorial optimization problem. To achieve this, we implement a pointer network with temporal attention that is capable of planning observations while accounting for time-varying factors such as moonlight interference, target altitude, and air mass, which impact the exposure time and image quality. To support the training of the deep neural network, we propose a scoring mechanism to evaluate the effectiveness of the observations, which is optimized through a refined REINFORCE algorithm with a baseline. Furthermore, an exposure time calculator and an equipment kinematic model are incorporated to dynamically estimate the time costs during the decision-making process. The simulation results demonstrated that the trained model significantly outperformed both manual scheduling and a greedy algorithm in terms of theoretical reward scores and the total number of scheduled targets. Observation experiments conducted using a dual-telescope system at Muztaga observatory further validated the superiority of our approach, demonstrating a 45.8% enhancement in the total signal-to-noise ratio across all observed targets and a 24.1% increase in the number of completed tasks under the same observing conditions.

For fast rotating asteroids, observed lightcurves could be very different from real lightcurves due to long exposure time. We present an improved observed lightcurve model that accounts for long exposure time often encountered in observations of fast rotating asteroids. By integrating brightness over time, we derive more accurate observed lightcurve model, allowing for better shape and spin state inversion results. Our analysis demonstrates that the fast rotating model is more suitable for spin state inversion with longer exposure time, while Kaasalainen model suffices for shorter exposure time. For spin state and shape inversion, exposure time of approximately 0.4P and 0.2P represent critical thresholds respectively, beyond which the fast rotating model exhibits superior performance. Notably, scattering parameters have minimal impact on the shape inversion results. These findings contribute valuable insights to the determination of shape and spin states for fast rotating asteroids, shedding light on the challenges posed by long exposure time in such investigations.

To improve the observation efficiency of space debris surveys, a basic sky survey observation strategy was developed, with the aim of observing more space debris based on the Wide Field Optical Telescope Array run by Shandong University. The characteristics of the telescope and dynamic changes in the movement and position of space debris are considered in this strategy. An objective function was designed based on these factors. Using the pixelated sphere method to finely divide the celestial area, applying the summation filtering method, and using a greedy algorithm, the benefit of the objective function can be maximized, thus generating the optimal sky survey observation strategy. Through simulation and observation experiments, we demonstrate that the greedy algorithm observation strategy significantly improves the number of space debris instances and the number of arc segments with respect to the conventional observation strategy. This not only improves the automation level of space debris observation tasks, but also significantly enhances the execution efficiency of telescopes for debris observation. It is very helpful for cataloging space debris and generating collision warnings.

Theoretically, the Yarkovsky–O’Keefe–Radzievskii–Paddack (YORP) effect induced by thermal reemission from asteroid surfaces can either accelerate or decelerate their rotation. However, in the past decade or so, 12 asteroids confirmed to exhibit the YORP effect all show spinning-up behavior, raising questions about whether spinning-down asteroids exist and why they have not been definitively observed. Here, we present evidence that asteroid (433) Eros is undergoing spin deceleration, with an estimated YORP strength of υ = (−5.0 ± 4.6) × 10⁻¹⁰ rad day⁻² based on light curves spanning from 1953 to 2023. To account for possible systematic errors, we applied bootstrap resampling at the light-curve level. Besides, we also repeated the analysis on a subset of data with the most reliable light curves. While this reduced data set yields υ = (−3.0 ± 4.4) × 10⁻¹⁰ rad day⁻², the optimal υ remains negative, suggesting a consistent trend. The discrepancy of υ values highlights the significant role of systematic errors in YORP detection. We calculated the theoretical YORP strength υ _mod using both 1D and 3D heat conduction models and found it smaller than the observed value υ, perhaps due to surface heterogeneity. The well-studied Eros would be a perfect study object to make the YORP theory clearer.