We present OmniUV, a multipurpose simulation toolkit for space and ground VLBI observations. It supports various kinds of VLBI stations, including Earth (ground) fixed, Earth orbit, Lunar fixed, Lunar orbit, Moon–Earth, and Earth–Sun Lagrange 1 and 2 points, etc. The main functionalities of this toolkit are: (1) trajectory calculation; (2) baseline uv calculation, by taking the availability of each station into account; (3) visibility simulation for the given uv distribution, source structure, and system noise; (4) image and beam reconstruction. Two scenarios, namely the space VLBI network and the wide-field array, are presented as the application of the toolkit at completely different scales. OmniUV is the acronym of “Omnipotent UV.” We hope it could work as a general framework, in which various kinds of stations could be easily incorporated and the functionalities could be further extended. The toolkit has been made publicly available.

High-redshift active galactic nuclei (AGN) provide key insights into early supermassive black hole growth and cosmic evolution. This study investigates the parsec-scale properties of 86 radio-loud quasars at z ≥ 3 using very long baseline interferometry (VLBI) observations. Our results show predominantly compact core and core-jet morphologies, with 35% having unresolved cores, 59% with core–jet structures, and only 6% with core–double jet morphology. Brightness temperatures are generally lower than expected for highly radiative sources. The jets’ proper motions are surprisingly slow compared to those of lower-redshift samples. We observe a high fraction of young and/or confined peak-spectrum sources, providing insights into early AGN evolution in dense environments during early cosmic epochs. The observed trends may reflect genuine evolutionary changes in AGN structure over cosmic time, or selection effects favoring more compact sources at higher redshifts. These results stress the complexity of high-redshift radio-loud AGN populations and emphasize the need for multi-wavelength, high-resolution observations to fully characterize their properties and evolution through cosmic history.

Context. Understanding the mechanisms that launch and shape powerful relativistic jets from supermassive black holes (SMBHs) in high-redshift active galactic nuclei (AGNs) is crucial for probing the co-evolution of SMBHs and galaxies over cosmic time. Aims. We focus on the high-redshift (z = 3.396) blazar OH 471 to explore the jet launching mechanism in the early Universe. Methods. Using multi-frequency radio monitoring observations and high-resolution Very Long Baseline Interferometry (VLBI) imaging over three decades, we studied the milliarcsecond structure and long-term variability of OH 471. Results. Our spectral modeling of the radio flux densities revealed a synchrotron self-absorbed spectrum, indicating strong magnetic fields within the compact core. By applying the flux freezing approximation, we estimated the magnetic flux carried by the jet. We found that it reaches or exceeds theoretical predictions for jets powered by black hole spin energy via the Blandford-Znajek mechanism. This implies that OH 471 is in a magnetically arrested disk (MAD) state, where the magnetic flux accumulated near the horizon regulates the accretion flow, allowing for an efficient extraction of black hole rotational energy. Conclusions. Our study demonstrates the dominance of MAD accretion in powering the prominent radio flares and relativistic jets observed in the radio-loud AGN named OH 471. Statistical studies of larger samples of high-redshift AGNs will shed light on the role of MAD accretion in launching and accelerating the earliest relativistic jets.

Long-period radio transients (LPTs) are a recently identified phenomenon that challenge our current understanding of compact objects and coherent radio emission mechanisms. These objects emit radio pulses similar to those of pulsars, but at much longer periods – on the order of minutes to hours. With duty cycles of only a few per cent, individual pulses have been observed to last between 10 and 1000 s. This places LPTs in a time-scale gap between the two main techniques used in transient radio searches: time-series analysis at millisecond to second time-scales, and image-plane searches sensitive to variability on the scale of days. As a result, LPTs remained undetected until recently, and only a handful are currently known. To increase the sample of known LPTs, we conducted a dedicated search using 200 h of archival data from the ASKAP Evolutionary Map of the Universe survey, covering 750 deg$^2$ of sky at the shortest possible imaging time-step of 10 s. This represents the first large-scale search using ASKAP data at second-scale resolution. Although no LPTs were detected, we identified flares from six stars, at least one had never been detected in the radio regime before. We placed a lower limit on the transient surface density of $2.21\times 10^{-6}$ deg$^{-2}$ at a 10-s time-scale, with a sensitivity of 16.9 mJy. Our findings evaluate the feasibility of detecting radio transients using 10-s imaging with ASKAP and provide insights into improving detection pipelines and observation strategies for LPTs.

快速射电暴是目前国际天文学新兴前沿热点，随着海量观测数据带来的处理和分析的挑战，亟需开展快速射电暴信号智能搜寻和甄别的研究. 为了加速快速射电暴搜寻研究，我们开发了一套基于机器学习的快速射电暴数据集，它可以训练机器学习算法以搜寻原始数据中的快速射电暴. 目前数据集有8020个快速射电暴、4010个背景噪声和4010个射频干扰仿真图像，这些图像是根据开放的快速射电暴观测结果构建的，并可根据需要扩展数量. 本研究旨在为最先进的人工智能算法提供开源数据集，以测试和比较快速射电暴识别算法. 该数据集为卷积神经网络(Convolutional Neural Network，简称CNN)和经典机器学习算法提供图像和numpy格式的文件. 数据集可以实现快速射电暴和非快速射电暴分类，或快速射电暴、射频干扰和背景噪声分类. 在本例中，我们使用有预训练模型的31种经典CNN算法. 在快速射电暴/非快速射电暴分类中，第一个历元训练中达到90%以上的准确率，在真实数据测试中达到99.8%的最大准确率.