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Aims. The X-ray luminous and radio-loud AGN SRGE J170245.3+130104 discovered at z $\sim$ 5.5 provides unique chances to probe the SMBH growth and evolution with powerful jets in the early Universe. Methods. We present 1.35 - 5.1 GHz Very Long Baseline Array (VLBA) results on the radio continuum emission and spectrum analysis for this quasar in a low flux density state. Results. This source is unresolved at three frequencies with the total flux densities of 8.35$\pm$0.09 mJy beam-1, 7.47$\pm$0.08 mJy beam-1, and 6.57$\pm$0.02 mJy beam-1 at 1.73 GHz, 2.26 GHz, and 4.87 GHz, respectively. Meanwhile, the brightness temperature is higher than 109 K. Conclusions. Compared with previous radio observations with arcsec-scale resolution, nearly all the radio emission from this source concentrates in the very central milli-arcsecond (mas) scale area. We confirm this source is a bright blazar at z > 5. This young AGN provide us the great chances to understand the first generation of strong jets in the early Universe., Comment: 5 pages, 2 figures, Accepted for publication in Astronomy & Astrophysics

Measuring the proper motion of the emission component in radio-quiet quasars (RQQs) could help to distinguish between the origins of the radio emission and to understand whether the jet production mechanism is the same in radio-loud quasars (RLQs) and RQQs. PG 1351+640 is one of the few RQQs suitable for proper motion studies: it has two compact components on milli-arcsecond scales, a flat-spectrum core and a steep-spectrum jet; both components are >2 mJy at 5 GHz and are well suited for Very Long Baseline Array (VLBA) observations. We compare recent VLBA observations with that made seventeen years ago and find no significant change in the core-jet separation between 2005 and 2015 (a proper motion of 0.003 mas yr-1). However, the core-jet separation increased significantly between 2015 and 2022, inferring a jet proper motion velocity of 0.063 mas yr-1, which corresponds to an apparent transverse velocity of 0.37c. The result suggests that the jet of the RQQ PG 1351+640 is mildly relativistic and oriented at a relatively small viewing angle., Comment: The article has been published by Oxford University Press: https://academic.oup.com/mnrasl/advance-article-abstract/doi/10.1093/mnrasl/slad051/7146829?utm_source=advanceaccess&utm_campaign=mnrasl&utm_medium=email

Disk winds and jets are ubiquitous in active galactic nuclei (AGN), and how these two components interact remains an open question. We study the radio properties of a radio-intermediate quasar III Zw 2. We detect two jet knots J1 and J2 on parsec scales, which move at a mildly apparent superluminal speed of $1.35\,c$. Two $\gamma$-ray flares were detected in III Zw 2 in 2009--2010, corresponding to the primary radio flare in late 2009 and the secondary radio flare in early 2010. The primary 2009 flare was found to be associated with the ejection of J2. The secondary 2010 flare occurred at a distance of $\sim$0.3 parsec from the central engine, probably resulting from the collision of the jet with the accretion disk wind. The variability characteristics of III Zw 2 (periodic radio flares, unstable periodicity, multiple quasi-periodic signals and possible harmonic relations between them) can be explained by the global instabilities of the accretion disk. These instabilities originating from the outer part of the warped disk propagate inwards and can lead to modulation of the accretion rate and consequent jet ejection. At the same time, the wobbling of the outer disk may also lead to oscillations of the boundary between the disk wind and the jet tunnel, resulting in changes in the jet-wind collision site. III Zw 2 is one of the few cases observed with jet-wind interactions, and the study in this paper is of general interest for gaining insight into the dynamic processes in the nuclear regions of AGN., Comment: accepted by ApJ

The Square Kilometre Array (SKA) project consists of delivering two largest radio telescope arrays being built by the SKA Observatory (SKAO), which is an intergovernmental organization bringing together nations from around the world with China being one of the major member countries. The computing resources needed to process, distribute, curate and use the vast amount of data that will be generated by the SKA telescopes are too large for the SKAO to manage on its own. To address this challenge, the SKAO is working with the international community to create a shared, distributed data, computing and networking capability called the SKA Regional Centre Alliance. In this model, the SKAO will be supported by a global network of SKA Regional Centres (SRCs) distributed around the world in its member countries to build an end-to-end science data system that will provide astronomers with high-quality science products. SRCs undertake deep processing, scientific analysis, and long-term storage of the SKA data, as well as user support. China has been actively participating in and promoting the construction of SRCs. This paper introduces the international cooperation and ongoing prototyping of the global SRC network, the construction plan of the China SRC and describes in detail the China SRC prototype. The paper also presents examples of scientific applications of SKA precursor and pathfinder telescopes completed using resources from the China SRC prototype. Finally, the future prospects of the China SRC are presented., Comment: T. An, et al. Status and progress of China SKA Regional Centre prototype. Sci. China-Phys. Mech. Astron. 65: 129501 (2022)

Large surveys using modern telescopes are producing images that are increasing exponentially in size and quality. Identifying objects in the generated images by visual recognition is time-consuming and labor-intensive, while classifying the extracted radio sources is even more challenging. To address these challenges, we develop a deep learning-based radio source detector, named \textsc{HeTu}, which is capable of rapidly identifying and classifying radio sources in an automated manner for both compact and extended radio sources. \textsc{HeTu} is based on a combination of a residual network (ResNet) and feature pyramid network (FPN). We classify radio sources into four classes based on their morphology. The training images are manually labeled and data augmentation methods are applied to solve the data imbalance between the different classes. \textsc{HeTu} automatically locates the radio sources in the images and assigns them to one of the four classes. The experiment on the testing dataset shows an average operation time of 5.4 millisecond per image and a precision of 99.4\% for compact point-like sources and 98.1\% for double-lobe sources. We applied \textsc{HeTu} to the images obtained from the GaLactic and the Galactic Extragalactic All-Object Murchison Wide-field Array (GLEAM) survey project. More than 96.9\% of the \textsc{HeTu}-detected compact sources are matched compared to the source finding software used in the GLEAM. We also detected and classified 2,298 extended sources (including Fanaroff-Riley type I and II sources, and core-jet sources) above $5\sigma$. The cross-matching rates of extended sources are higher than 97\%, showing excellent performance of \textsc{HeTu} in identifying extended radio sources. \textsc{HeTu} provides an efficient tool for radio source finding and classification and can be applied to other scientific fields., Comment: Accepted by Science Bulletin. Note that the final version of the paper in the journal is formatted slightly differently from the one in astro-ph because of the journal's layout

w-Projection is a wide-field imaging technique that is widely used in radio synthesis arrays. Processing the wide-field big data generated by the future Square Kilometre Array (SKA) will require significant updates to current methods to significantly reduce the time consumed on data processing. Data loading and gridding are found to be two major time-consuming tasks in w-projection. In this paper, we investigate two parallel methods of accelerating w-projection processing on multiple nodes: the hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) method based on multicore Central Processing Units (CPUs) and the hybrid MPI and Compute Unified Device Architecture (CUDA) method based on Graphics Processing Units (GPUs). Both methods are successfully employed and operated in various computational environments, confirming their robustness. The experimental results show that the total runtime of both MPI + OpenMP and MPI + CUDA methods is significantly shorter than that of single-thread processing. MPI + CUDA generally shows faster performance when running on multiple nodes than MPI + OpenMP, especially on large numbers of nodes. The single-precision GPU-based processing yields faster computation than the double-precision processing; while the single- and doubleprecision CPU-based processing shows consistent computational performance. The gridding time remarkably increases when the support size of the convolution kernel is larger than 8 and the image size is larger than 2,048 pixels. The present research offers useful guidance for developing SKA imaging pipelines., Comment: 9 pages. Published in Science Bulletin, 64, 586-594 (2019)