Search Results (230)

Hydrogen technologies are increasingly important for energy storage and decarbonization of industrial and transport sectors. Hydrogen compression is accompanied by thermal effects that influence energy efficiency and thermal loading of compression systems. This study numerically investigates the influence of compression chamber wall thickness on heat transfer and wall temperature evolution during hydrogen compression in a liquid piston compressor. An axisymmetric multiphysics model was used to simulate a single compression stroke at initial pressures of 3–20 MPa, stroke durations of 0.5–20 s, and chamber wall thicknesses of 2.5–10 mm. The simulations show that wall temperature rise increases with compression stroke duration and initial pressure, while increasing wall thickness reduces the per-stroke temperature increase due to higher thermal inertia. The results also indicate non-uniform wall heating, with the highest temperatures occurring in the upper region of the compression chamber. Full article

The continuous growth of the population of Resident Space Objects (RSOs) poses increasing challenges for Space Situational Awareness (SSA), particularly in terms of detection capability and collision risk mitigation. Ground-based radar systems represent a primary class of remote sensing instruments for RSO observation; however, their deployment is often constrained by cost and infrastructure requirements. In this context, the reuse of existing large radio astronomy facilities as radar receivers offers an innovative and potentially cost-effective alternative. This paper presents a fully model-based feasibility study of S-band bi-static radar observations of RSOs using the Sardinia Radio Telescope (SRT) as a high-sensitivity ground-based receiver. The analysis is entirely analytical and is conducted in the absence of experimental radar measurements. A bi-static radar equation framework is adopted to evaluate received signal power and the resulting signal-to-noise ratio (SNR) as functions of target size, range, and observation geometry. The model explicitly incorporates thermal noise, integration time and target dynamics, radio-frequency interference (RFI), atmospheric and environmental clutter contributions, and the realistic antenna radiation pattern of the SRT through a Gaussian beam approximation. Detection thresholds, maximum observable ranges, and performance envelopes are derived for representative RSO dimensions, and the impact of off-boresight reception on detectability is quantified. The results define the operational conditions under which RSOs may be detected in an S-band bi-static configuration and demonstrate the potential of the SRT as a non-conventional ground-based instrument for space object observation, supporting future developments in SSA and space debris monitoring strategies. Full article

We present a circular complementary split ring resonator (CCSRR) flexible antenna operating in the 1.4 GHz radio-astronomy quiet frequency band. The antenna is designed for microwave non-invasive brain temperature sensing of an infant’s head to aid in the therapeutic hypothermia treatment of hypoxic–ischemic encephalopathy (HIE) and traumatic brain injury (TBI). The proposed metamaterial-inspired antenna is designed on a flexible Kapton substrate with a biocompatible Polydimethylsiloxane (PDMS) protective superstrate layer. For brain temperature measurement, the flexible antenna is placed directly on the scalp to collect thermal noise power from the underlying tissue layers. The received thermal power is to be delivered to a sensitive microwave radiometer. The CCSRR antenna exhibits sharp frequency selectivity at 1.4 GHz with inherent filtering capability, strong field confinement, and excellent suppression of out-of-tissue (external) electromagnetic interference and thermal noise contributions. To closely match the realistic scenario, the CCSRR antenna, initially designed in a planar multi-layer configuration, is investigated in various bending configurations (cylindrical and spherical) with a curvature radius of 55 mm. The results indicate stable performance under bending. Good agreement between simulated and on-body measured results is observed in the desired frequency band. Full article

We present a study of the linear polarization properties of radio sources within the 10 deg². Wide Chandra Deep Field South (W-CDFS) in S-band (2–4 GHz). Our W-CDFS image has an angular resolution of 15 arcsec and a 1$\sigma$ RMS in Stokes I of ≈50 $\mathsf{\mu }$Jy/beam. We detect 1920 distinct source components in Stokes I and 175 in linear polarization. We examine the polarized source counts, Faraday Rotation measures, and fractional polarization of the sources in the survey. We show that sources with a total intensity above ≈10 mJy have a mean fractional polarization value of ≈3% from modeling the polarized counts. We also calculate an estimate for the limit on the fractional polarization level of sources with a total intensity below 1 mJy (mostly star-forming galaxies) of ≲3% using stacking. The mean Faraday Rotation we measure is consistent with that due to the Milky Way. We also show that fractional polarization is correlated with in-band spectral index, consistent with a lower mean fractional polarization for the flat-spectrum population. In addition to characterizing the S-band polarization properties of sources in the W-CDFS, this study will be used to validate the shallower, but higher angular resolution S-band polarimetric information that the VLA Sky Survey will provide for the whole sky above Declination −40 degrees over the next few years. Full article

This paper addresses the knowledge gap on the beginning of the history of contact with extraterrestrial intelligent beings in international astronautics. In the mid-1950s, the world’s space law practitioner, Andrew G. Haley, proposed the concept of Metalaw, the law governing interactions between all beings in the Universe, as he represented the American Rocket Society in the International Astronautical Congress, the single largest gathering of space-faring nations. Haley, with experience in radio communications law dating back to the 1930s, played a pivotal role in pushing for the international allocation of radio frequencies in space. Haley was, too, an agile mediator with the Soviet Union and its bloc, acting across various organizations and forums. This article, in contextualizing Haley’s introduction of Metalaw, shows how the onset of the Space Age coincided with the emergence of a contact scenario involving extraterrestrial intelligence enabled by the corresponding techno-scientific capabilities of the time. It demonstrates how extraterrestrial intelligence discursively addressed outer space regulation as a bone of contention between the two geopolitically divided parts, a regulation upon which the US’s global satellite system would depend. The analysis in this article recounts the birth of the Metalaw concept at the intersection of outer space imaginary, law, international organizations, science and technology, diplomacy, the Space Race, the Cold War, and radio astronomy’s Search for Extraterrestrial Intelligence. Full article

This paper presents the design and implementation of the Power Stage GAIA (PSG), a high-current digital bias board developed by the Italian National Institute for Astrophysics (INAF) to extend the capabilities of the GAIA bias system. The PSG was developed within the Advanced European THz Receiver Array (AETHRA) project to support next-generation cryogenic receivers for millimeter-wave astronomy. Specifically, the AETHRA Work Package 1 (WP1) W-band downconverter integrates Monolithic Microwave Integrated Circuits (MMICs) requiring currents significantly exceeding the 50 mA limit of standard bias boards. To address these requirements, the PSG introduces a modular extension providing ten independent channels, each capable of delivering up to 500 mA with a programmable output range of 0–5 V. A key feature of the design is the adoption of a fully linear architecture based on LT1970 power amplifiers and INA225 precision sensors managed via an I²C digital interface. This approach ensures the high current capability required by modern power amplifiers while strictly avoiding the spectral noise and Radio Frequency Interference (RFI) typical of switching power supplies. Experimental validation confirms the system’s robustness and precision: the board demonstrated linear operation up to 460 mA and exceptional long-term stability, with a measured RMS voltage deviation below 50 µV. These results establish the PSG as a scalable, low-noise solution suitable for biasing high-power MMICs in future cryogenic receiver arrays. Full article

The Sardinia Radio Telescope (SRT) is an Italian antenna utilized for scientific research in the field of radio astronomy across a broad frequency range from 300 MHz to 116 GHz. Among the various cryogenic receivers installed on SRT, the dual-polarized C-Low receiver operates within the frequency range of 4.2–5.6 GHz, which is the lower portion of the well-known C-band, and is installed at the Gregorian focus of the telescope. This article presents a general description of the design of the receiver, highlighting its signal acquisition chain, which conditions weak signals from the sky for transmission to the digital back-end, responsible for data processing. An analysis of the radio-frequency interference environment affecting scientific observations is also presented, together with the adopted mitigation strategies. Finally, we report the results of the characterization tests performed with the C-Low receiver at SRT, focusing on the pointing accuracy model, gain-curve calibration, focus-curve calibration, and beam-shape analysis. The results of these characterization tests demonstrate the performance and accuracy of the C-Low receiver, providing a reference for future observations and instrumentation improvements. Full article

Perseus A (3C 84), a powerful radio source located at the centre of the giant elliptical galaxy NGC 1275—classified as a Seyfert type II AGN and the dominant member of the X-ray bright Abell 426 cluster–exhibits radio emission variability over a wide range of timescales, from decades to hours. This study investigates intraday variability (IDV) in the 6.5 GHz radio emission of 3C 84 using the RT-32 radio telescope in Zolochiv, Ukraine. A novel low-amplitude azimuthal scanning method enabled quasi-simultaneous measurements of antenna and system temperatures, allowing for separation of intrinsic source variations from propagation effects. During an observation session in August 2021, a burst with a peak intensity of 13.5 Jy above the background was detected, likely corresponding to a Fast Radio Burst (FRB). Additionally, quasi-periodic low-amplitude variations with timescales from 0.3 to 6 h were observed. These fluctuations correlate strongly with local atmospheric changes, such as dew formation on the telescope structure, and, to a lesser extent, with ionospheric acoustic–gravity waves. The findings highlight the importance of accounting for propagation conditions when interpreting short-timescale radio variability in AGNs and suggest the need for multi-station, multi-frequency monitoring campaigns to distinguish between intrinsic and environmental modulation of AGN flux densities. Full article

Wind disturbance is one of the key factors affecting the high-precision pointing of large-aperture radio telescopes. Therefore, it is indispensable to monitor the wind environment of the site. This enables the acquisition of wind environment data, facilitating targeted wind-resistant design to maintain the observational performance of the radio telescope. A 60 m high wind tower is located within the QTT (QiTai Radio Telescope, 110 m) site. This study investigates the wind environment characteristics based on the wind data for the entire year of 2021. The analysis of anomalous data from the wind tower indicates that these are mainly caused by local freezing rain and snow conditions. The temporal variations and vertical distribution characteristics of the wind environment were analyzed. On an annual basis, winds predominantly originate from north–south, while those from east–west are relatively less frequent; 90% of the winds are less than 4 m/s; the maximum recorded wind speed is 22.29 m/s; the prevailing winds are from the SSE (south-southeast) direction. On a monthly basis, the distributions of wind direction and speed exhibit a distinct seasonal cycle, with wind speeds being relatively lower in winter. On a diurnal basis, the wind direction undergoes a reversal, with northerly winds prevailing during the day and southerly winds at night; the diurnal wind speed distribution shows that nocturnal wind speeds are relatively stable and lower. Daily wind speed statistics indicate that there were 79 days on which 90% of wind speeds throughout the day were less than or equal to 2 m/s. Compared to sites of other telescopes of a similar class, the wind environment at the QTT site is relatively favorable. Full article

The proliferation of terrestrial and space-based communication systems introduces significant radio frequency interference (RFI), which severely compromises data acquisition for radio telescopes, necessitating robust and dynamic scheduling solutions. This study addresses this challenge by implementing a Deep Recurrent Reinforcement Learning (DRL) framework for the control and dynamic scheduling of the X-Y pedestal-mounted KMITL radio telescope, explicitly trained for RFI avoidance. The methodology involved developing a custom simulation environment with a domain-specific Convolutional Neural Network (CNN) feature extractor and a Long Short-Term Memory (LSTM) network to model temporal dynamics and long-horizon planning. Comparative evaluation demonstrated that the recurrent DRL agent achieved a mean effective survey coverage of 475 deg²/h, representing a 72.7% superiority over the non-recurrent baseline, and maintained exceptional stability with only 1.0% degradation in median coverage during real-world deployment. The DRL framework offers a highly reliable and adaptive solution for telescope scheduling that is capable of maintaining survey efficiency while proactively managing dynamic RFI sources. Full article

The exponential growth of candidate data from large-scale radio pulsar surveys has created a pressing need for efficient and accurate classification methods. This paper presents a novel hybrid pulsar candidate recognition algorithm that integrates diagnostic plot images and structured numerical features using a multi-scale DenseNet framework. The proposed model combines convolutional neural networks (CNNs) for extracting spatial patterns from pulsar diagnostic plots and feedforward neural networks (FNNs) for processing scalar features such as SNR, DM, and pulse width. By fusing these multimodal representations, the model achieves superior classification performance, particularly in class-imbalanced settings standard to pulsar survey data. Evaluated on a synthesized dataset constructed from FAST and HTRU survey characteristics, the model demonstrates robust performance, achieving an F1-score of 0.904 and AUC-ROC of 0.978. Extensive ablation and cross-validation analyses confirm the contribution of each data modality and the model’s generalizability. Furthermore, the system maintains low inference latency (4.2 ms per candidate) and a compact architecture (~2.3 million parameters), indicating potential for real-time deployment once validated on real observational datasets. The proposed approach offers a scalable and interpretable multimodal framework for automated pulsar classification and provides a foundation for future validation and potential integration into observatories such as FAST and the Square Kilometre Array (SKA). Full article

Obtaining an antenna’s back-up structure (BUS) temperature field is an essential prerequisite for analyzing its thermal deformation. Thermodynamic simulation can obtain the structure’s thermal distribution, but it has low computational accuracy. There is a problem with cumbersome wiring and difficult maintenance of the temperature measurement system. This study developed an improved RIME-XGBoost model to realize the temperature prediction of the BUS of the Nanshan 26-m Radio Telescope (NSRT). The proposed model successfully predicts the NSRT’s BUS temperature distribution based solely on environmental sensing (ambient temperature, angle of solar radiation, antenna’s orientation, etc.). The relative prediction accuracy between the predicted and actual BUS temperature is 97.15%, and the predictive error is less than 0.897 K (root mean square error, RMSE). This research result provides an alternative method for the real-time reconstruction of the structure’s thermal distribution in large-aperture radio telescopes. Full article

A radio source with a period of 75.88 s, suspected of being an ultra-long period pulsar, was discovered in 2020 with the MeerKAT radio telescope. Here, we report the detection of radio pulses from this object in multi-epoch ASKAP image data at frequencies between 744 MHz and 1800 MHz and a search for pulses made in Murchison Widefield Array data at 154 MHz. The ASKAP detections pre-date and extend other published observations and so support the belief the pulsar emission has been persistent. The non-detection of the pulsar in MWA data is consistent with a recent report that the spectrum turns over at low frequencies. An ASKAP image of the field centred at 943 MHz confirms the MeerKAT detection of diffuse emission surrounding the pulsar. Full article

Radio-loud high-redshift quasars (RHRQs) provide crucial insights into the evolution of relativistic jets and their connection to the growth of supermassive black holes. Beyond the extensively studied population at $z\ge 5$, the cosmic morning epoch ($3\lesssim z\lesssim 5$) marks the peak of active galactic nucleus (AGN) activity and black hole accretion, yet remains relatively unexplored. In this work, we compiled the radio high-redshift quasar catalog (RHzQCat) by cross-matching the SDSS DR16Q catalog with four major radio surveys—FIRST, NVSS, RACS, and GLEAM. Our tier-based cross-matching framework and visual validation ensured reliable source identification across surveys with diverse beam sizes. The catalog included 1629 reliable and 315 candidate RHRQs, with radio luminosities uniformly spanning ${10}^{25.5}$–${10}^{29.3}$ W Hz⁻¹. About 95% of the confirmed sources exhibited compact morphologies, consistent with Doppler-boosted or young AGN populations at high redshifts. Our catalog increases the number of known RHRQs at $z\ge 3$ by an order of magnitude, representing the largest and most homogeneous catalog of radio quasars at cosmic morning, filling the observational gap between the early ($z>6$) and local Universe. It provides a robust reference for future statistical studies of jet evolution, AGN feedback, and cosmic magnetism with next-generation facilities such as the Square Kilometer Array (SKA). Full article

The discovery of the fifth gravitational wave, GW170817, and its electromagnetic counterpart, resulting from the merger of neutron stars by the LIGO and Virgo teams, marked a major milestone in astronomy. It was the first time that gravitational waves and light from the same cosmic event were observed simultaneously. The LIGO detectors in the United States recorded the signal for 100 s, longer than in previous detections. The merging of neutron stars emits both gravitational and electromagnetic waves across all frequencies—from radio to gamma rays. However, pinpointing the exact source remains difficult, requiring rapid sky scanning to locate it. To address this challenge, the Gravitational-Wave Optical Transient Observer (GOTO) project was established. It is specifically designed to detect optical light from transient events associated with gravitational waves, enabling faster follow-up observations and a deeper study of these short-lived astronomical phenomena, which appear and disappear quickly in the universe. In astrophysics, it has become more important to find astronomical transient events like supernovae, gamma-ray bursts, and stellar flares because they are linked to extreme cosmic processes. However, finding these short-lived events in huge sky survey datasets, like those from the GOTO project, is very hard for traditional analysis methods. This study suggests a deep learning methodology employing Convolutional Neural Networks (CNNs) to enhance transient classification. CNNs are based on how biological vision systems work and how they are structured. They mimic how animal brains hierarchically process visual information, making it possible to automatically find complex spatial patterns in astronomical images. Transfer learning and fine-tuning on pretrained ImageNet models are utilized to emulate adaptive learning observed in biological organisms, enabling swift adaptation to new tasks with minimal data. Data augmentation methods like rotation, flipping, and noise injection mimic changes in the environment to improve model generalization. Dropout and different batch sizes are used to stop overfitting, which is similar to how biological systems use redundancy and noise tolerance. Ensemble learning strategies, such as Soft Voting and Weighted Voting, draw inspiration from collective intelligence in biological systems, integrating multiple CNN models to enhance decision-making robustness. Our findings indicate that this bio-inspired framework substantially improves the precision and dependability of transient detection, providing a scalable solution for real-time applications in extensive sky surveys such as GOTO. Full article