Fast radio bursts (FRBs) are millisecond-duration radio transients from extragalactic sources. Some repeating FRBs exhibit variations in their Faraday rotation measure (RM) due to changes in their magneto-ionic environment. We report magneto-ionic variations of FRB 20220529, a repeating FRB from a disk galaxy at redshift 0.18. For the first 17 months of observations, the RM had a median of 17 radians per square meter (rad m ⁻² ) and a scatter of 101 rad m ⁻² . In December 2023, the RM jumped to 1977 ± 84 rad m ⁻² , then gradually returned to typical values within 2 weeks. This sudden RM variation indicates that a dense magnetized clump of plasma passed across the line of sight. We discuss potential explanations, including a coronal mass ejection from a companion star, high plasma turbulence, or binary orbital motion.

Thanks to the rapidly increasing time-domain facilities, we are entering a golden era of research on gamma-ray bursts (GRBs). In this Letter, we report our observations of GRB 240529A with the Burst Optical Observer and Transient Exploring System, the 1.5 m telescope at Observatorio de Sierra Nevada, the 2.5 m Wide Field Survey Telescope of China, the Large Binocular Telescope, and the Telescopio Nazionale Galileo. The prompt emission of GRB 240529A shows two comparable energetic episodes separated by a quiescence time of roughly 400 s. Combining all available data on the GRB Coordinates Network, we reveal the simultaneous apparent X-ray plateau and optical rebrightening around 10³–10⁴ s after the burst. Rather than the energy injection from the magnetar as widely invoked for similar GRBs, the multiwavelength emissions could be better explained as two shocks launched from the central engine separately. The optical peak time and our numerical modeling suggest that the initial bulk Lorentz factor of the later shock is roughly 50, which indicates that the later jet should be accretion driven and have a higher mass loading than a typical one. The quiescence time between the two prompt emission episodes may be caused by the transition between different accretion states of a central magnetar or black hole, or the fallback accretion process. A sample of similar bursts with multiple emission episodes in the prompt phase and sufficient follow-up could help to probe the underlying physics of GRB central engines.

Particle-in-cell simulations have unveiled that shock-accelerated electrons do not follow a pure power-law distribution, but have an additional low-energy “thermal” part, which owns a considerable portion of the total energy of the electrons. Investigating the effects of these thermal electrons on gamma-ray burst (GRB) afterglows may provide valuable insights into the particle acceleration mechanisms. We solve the continuity equation of electrons in energy space, from which multiwavelength afterglows are derived by incorporating processes including synchrotron radiation, synchrotron self-absorption, synchrotron self-Compton scattering, and γ–γ annihilation. First, there is an underlying positive correlation between the temporal and spectral indices due to the cooling of electrons. Moreover, thermal electrons result in simultaneous nonmonotonic variations of both the spectral and temporal indices at multiple wavelengths, which could be individually recorded by the 2.5 m Wide Field Survey Telescope and Vera Rubin Observatory Legacy Survey of Space and Time (LSST). The thermal electrons could also be diagnosed using afterglow spectra from synergistic observations in the optical (with LSST) and X-ray (with the Microchannel X-ray Telescope on board the Space Variable Objects Monitor) bands. Finally, we use Monte Carlo simulations to obtain the distribution of the peak flux ratio (R _X) between the soft and hard X-rays, and of the time delay (Δt) between the peak times of the soft X-ray and optical light curves. The thermal electrons significantly raise the upper limits of both R _X and Δt. Thus, the distribution of GRB afterglows with thermal electrons is more scattered in the R _X−Δt plane.

Gamma-ray bursts (GRBs) are luminous stellar explosions characterized by the ejection of relativistic jets. This work proposes a novel paradigm to study these GRB jets. By analyzing the timing information of prompt pulses and X-ray flares, in conjunction with the multiwavelength afterglow observations, we identify three distinct jets in the extraordinary GRB 060729, with initial bulk Lorentz factors ranging from approximately 20 to 80, smaller than typical values of >100. These three jets undergo two successive collisions, producing the observed pair of X-ray flares. Following these interactions, the system evolves into a fast, narrow jet and a slower, hollow jet that continues to propagate in the circumburst medium, evidenced by the notable twin bumps observed in the X-ray and optical afterglow of GRB 060729. Our findings demonstrate that the timing of the early emission enables us to measure the velocities of the GRB jets. The proposed paradigm enhances our understanding of jet dynamics and shock interactions and serves as a powerful tool for probing the physics of the central engine with the expanded sample in the current golden era of GRB research.

A series of sky surveys were launched in search of supernovae and generated a tremendous amount of data, which pushed astronomy into a new era of big data. However, it can be a disastrous burden to manually identify and report supernovae, because such data have huge quantity and sparse positives. While the traditional machine learning methods can be used to deal with such data, deep learning methods such as Convolutional Neural Networks demonstrate more powerful adaptability in this area. However, most data in the existing works are either simulated or without generality. How do the state-of-the-art object detection algorithms work on real supernova data is largely unknown, which greatly hinders the development of this field. Furthermore, the existing works of supernovae classification usually assume the input images are properly cropped with a single candidate located in the center, which is not true for our dataset. Besides, the performance of existing detection algorithms can still be improved for the supernovae detection task. To address these problems, we collected and organized all the known objectives of the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) and the Popular Supernova Project (PSP), resulting in two datasets, and then compared several detection algorithms on them. After that, the selected Fully Convolutional One-Stage (FCOS) method is used as the baseline and further improved with data augmentation, attention mechanism, and small object detection technique. Extensive experiments demonstrate the great performance enhancement of our detection algorithm with the new datasets.

The third Antarctic Survey Telescope array instrument at Dome A in Antarctica, the AST3-3 telescope, has been in commissioning from March 2021. We deployed AST3-3 at the Yaoan astronomical station in Yunnan Province for an automatic time-domain survey and follow-up observations with an optimised observation and protection system. The telescope system of AST3-3 is similar to that of AST3-1 and AST3-2, except that it is equipped with a 14 K × 10 K QHY411 CMOS camera. AST3-3 has a field of view of $1.{65}^{\circ }\times 1.{23}^{\circ }$ and is currently using the g band filter. During commissioning at Yaoan, AST3-3 aims to conduct an extragalactic transient survey, coupled with prompt follow-ups of opportunity targets. In this paper, we present the architecture of the AST3-3 automatic observation system. We demonstrate the data processing of observations by representatives SN 2022eyw and GRB 210420B.