Bent-tail radio galaxies (BTRGs) are characterized by bent radio lobes. This unique shape is mainly caused by the movement of the galaxy within a cluster, during which the radio jets are deflected by the intracluster medium. A combined method, which involves a deep learning-based radio source finder along with visual inspection, has been utilized to search for BTRGs from the Faint Images of the Radio Sky at Twenty cm survey images. Consequently, a catalog of 4876 BTRGs has been constructed, among which 3871 are newly discovered. Based on the classification scheme of the opening angle between the two jets of the galaxy, BTRGs are typically classified as either wide-angle-tail (WAT) sources or narrow-angle-tail (NAT) sources. Our catalog comprises 4424 WATs and 652 NATs. Among these, optical counterparts are identified for 4193 BTRGs. This catalog covers luminosities in the range of 1.91 × 10²⁰ ≤ L _{1.4 GHz} ≤ 1.45 × 10²⁸ W Hz⁻¹ and redshifts from z = 0.0023 to z = 3.43. Various physical properties of these BTRGs and their statistics are presented. Particularly, by the nearest neighbor method, we found that 1825 BTRGs in this catalog belong to galaxy clusters reported in literature.

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 the radio-intermediate quasar III Zw 2. We detect two jet knots, J1 and J2, on parsec scales that move at a mildly apparent superluminal speed of 1.35c. Two γ-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 ∼0.3 pc 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 quasiperiodic signals and the 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 inward 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. Object 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.

We present an independent catalog (FRIIRGcat) of 45,241 Fanaroff–Riley Type II (FR-II) radio galaxies compiled from the Very Large Array Faint Images of the Radio Sky at Twenty-centimeters (FIRST) survey and employed the deep learning method. Among them, optical and/or infrared counterparts are identified for 41,425 FR-IIs. This catalog spans luminosities 2.63 × 10²² ≤ L _rad ≤ 6.76 × 10²⁹ W Hz⁻¹ and redshifts up to z = 5.01. The spectroscopic classification indicates that there are 1431 low-excitation radio galaxies and 260 high-excitation radio galaxies. Among the spectroscopically identified sources, black hole masses are estimated for 4837 FR-IIs, which are in 10^7.5 ≲ M _BH ≲ 10^9.5 M _⊙. Interestingly, this catalog reveals a couple of giant radio galaxies (GRGs), which are already in the existing GRG catalog, confirming the efficiency of this FR-II catalog. Furthermore, 284 new GRGs are unveiled in this new FR-II sample; they have the largest projected sizes ranging from 701 to 1209 kpc and are located at redshifts 0.31 < z < 2.42. Finally, we explore the distribution of the jet position angle and it shows that the faint Images of the FIRST images are significantly affected by the systematic effect (the observing beams). The method presented in this work is expected to be applicable to the radio sky surveys that are currently being conducted because they have finely refined telescope arrays. On the other hand, we are expecting that further new methods will be dedicated to solving this problem.

Quasiperiodic micropulses (QMPs) are quasiperiodic microstructural features manifested in individual pulsar radio pulses, the study of which is crucial for understanding pulsar radiation mechanisms. Manual identification of QMPs in large-scale pulsar single-pulse datasets remains highly inefficient. To address this, we propose a dual-stage residual network (DSR) that achieves automated QMP detection in Five-hundred-meter Aperture Spherical radio Telescope observational data through joint analysis of single-pulse profiles and their amplitude distribution profiles, defined as the power spectra of the autocorrelation function derivatives of the microstructure residuals. The model was trained on PSR B1933+16 data from 2019 (10,486 single pulses) and evaluated on manually annotated PSR B1933+16 data from 2020 (9657 single pulses). DSR achieved 96.10% recall and 95.85% precision on the test set. This approach provides an automated pipeline for large-scale, reproducible QMP identification and establishes the foundation for in-depth investigation of their physical mechanisms.