We present the beam pattern measurement of the Tianlai Cylinder Pathfinder Array. As it is a pure drift-scan instrument, we exploit the North-South motion of the Sun to demonstrate that the primary beam is factorizable. Leveraging this property, we decompose the primary beam into independent East-West (E-W) and North-South (N-S) components. Using the Sun as a calibration source, we obtain the E-W beam profiles at various elevations, applying normalization to eliminate the effects of solar activity. Subsequently, we simulate the observed signals using a sky map model to derive the best-fit N-S beam. The results of this work are consistent with previous expectations.
We present high-sensitivity Very Long Baseline Interferometry (VLBI) observations of four ultraluminous X-ray sources (ULXs): Holmberg II X-1, IC 342 X-1, NGC 6946 X-1, and NGC 925 X-1. No compact emission was detected on milliarcsecond scales, with rms noise levels reaching approximately 5--20 $\mu$Jy. The corresponding $5\sigma$ flux density upper limits reach $\sim 26\,\mu\mathrm{Jy}$, implying radio luminosity limits $L_{\rm R} \lesssim 2 \times 10^{33}\,\mathrm{erg\,s^{-1}}$. This disfavors any persistently bright hard-state-like compact core at our sensitivity level. The previously reported VLBI core in Holmberg II X-1 exhibits significant long-term variability, broadly consistent with an overall decline over the past decades. This behavior is consistent with emission from optically-thin ejecta undergoing adiabatic expansion. The VLBI non-detections may reflect intrinsically weak/intermittent compact emission, and/or low--surface--brightness structure that is resolved out by VLBI, and/or absorption/propagation effects such as free--free absorption in dense, ionized winds.
The solar interior is probed by the properties of the Sun's acoustic oscillations (p-modes) observed on the solar surface. The frequencies of these p-modes measured in the last three decades show long term variation similar to the 11 year cyclic behaviour exhibited by 10.7 cm radio flux, sunspot numbers and other solar activity indices. It is also now established that the cyclic behavior of some of the solar proxies are connected with geomagnetic activities and have implications for space weather. Hence, in recent years efforts have been made using machine-learning methods to forecast these solar proxies with a view to improve our understanding of space weather. Developing a comparable method for forecasting p-mode frequency shifts is therefore of interest for two reasons. Firstly, it will facilitate future investigations into its potential role in tracing energy drivers from the Sun's interior to the geospace response by improving models of solar interior dynamics to coronal and heliospheric plasma conditions. In other words, it will help establish a more robust and quantitative link between the Sun's interior and its exterior. Secondly, it may provide us with an independent indicator or an early indicator of ascending and descending phase of solar activity which might be useful for space weather forecasting. In this article, we develop and apply the standard time-series analysis and machine-learning based methods to characterise p-mode frequency shifts for the remaining solar cycle 25.
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this https URL and this https URL presented at the sys2025 workshop in Huntsville, AL (Nov 14-17. 2025)