Radio Sources Research Articles

RadioSED I: Bayesian inference of radio SEDs from inhomogeneous surveys

Abstract We present here RadioSED, a Bayesian inference framework tailored to modelling and classifying broadband radio spectral energy distributions (SEDs) using only data from publicly-released, large-area surveys. We outline the functionality of RadioSED, with its focus on broadband radio emissions which can trace kiloparsec-scale absorption within both the radio jets and the circumgalactic medium of Active Galactic Nuclei (AGN). In particular, we discuss the capability of RadioSED to advance our understanding of AGN physics and composition within youngest and most compact sources, for which high resolution imaging is often unavailable. These young radio AGN typically manifest as peaked spectrum (PS) sources which, before RadioSED, were difficult to identify owing to the large, broadband frequency coverage typically required, and yet they provide an invaluable environment for understanding AGN evolution and feedback. We discuss the implementation details of RadioSED, and we validate our approach against both synthetic and observational data. Since the surveys used are drawn from multiple epochs of observation, we also consider the output from RadioSED in the context of AGN variability. Finally, we show that RadioSED recovers the expected SED shapes for a selection of well-characterised radio sources from the literature, and we discuss avenues for further study of these and other sources using radio SED fitting as a starting point. The scalability and modularity of this framework make it an exciting tool for multiwavelength astronomers as next-generation telescopes begin several all-sky surveys. Accordingly, we make the code for RadioSED, which is written in python, available on Github.

Constraining the Clustering and 21 cm Signature of Radio Galaxies at Cosmic Dawn

The efficiency of radio emission is an important unknown parameter of early galaxies at cosmic dawn, as models with high efficiency have been shown to modify the cosmological 21 cm signal substantially, deepening the absorption trough and boosting the 21 cm power spectrum. Such models have been previously directly constrained by the overall extragalactic radio background, as observed by Absolute Radiometer for Cosmology, Astrophysics, and Diffuse Emission 2 and Long Wavelength Array. In this work, we constrain the clustering of high-redshift radio sources by utilizing the observed upper limits on arcminute-scale anisotropy from the Very Large Array at 4.9 GHz and Australia Telescope Compact Array at 8.7 GHz. Using a seminumerical simulation of a plausible astrophysical model for illustration, we show that the clustering constraints on the radio efficiency are much stronger than those from the overall background intensity by a factor that varies between 18 and 55 in the redshift range of 7–22. As a result, the predicted maximum depth of the global 21 cm signal is lowered by a factor of 6 (to 1400 mK), and the maximum 21 cm power spectrum peak at cosmic dawn is lowered by a factor of 45 (to 1.3 × 105 mK2). We conclude that the observed clustering is the strongest current direct constraint on such models, but strong early radio emission from galaxies remains viable for producing a strongly enhanced 21 cm signal from cosmic dawn.

Radio Astrometry at Different Frequencies

The very long baseline interferometry technique allows us to determine the positions of thousands of radio sources using the absolute astrometry approach. I have investigated the impacts of a selection of observing frequencies in a range from 2 to 43 GHz in single-band, dual-band, and quad-band observing modes on astrometric results. I processed seven data sets in a range of 72,000 to 6.9 million observations, estimated source positions, and compared them. I found that source positions derived from dual-band, quad-band, and 23.6 GHz single-band data agree at a level below 0.2 mas. Comparison of independent data sets allowed me to assess the error levels of individual catalogs: 0.05–0.07 mas per position component. Further comparison showed that individual catalogs have systematic errors at the same level. The positions from 23.6 GHz single-band data show systematic errors related to the residual ionosphere contribution. Analysis of source position differences revealed systematic errors along jet directions at a level of 0.09 mas. Network-related systematic errors affect all the data, regardless of frequency. Comparison of position estimates allowed me to derive the stochastic error model that closes the error budget. Based on the collected evidence, I have made a conclusion that the development of frequency-dependent reference frames of the entire sky is not warranted. In most cases dual-band, quad-band, and single-band data at a frequency of 22 GHz and higher can be used interchangeably, which allows us to exploit the strength of a specific frequency setup for given objects. Mixing observations at different frequencies causes errors not exceeding 0.07 mas.

Super-resolution diffractive neural network for all-optical direction of arrival estimation beyond diffraction limits

Wireless sensing of the wave propagation direction from radio sources lays the foundation for communication, radar, navigation, etc. However, the existing signal processing paradigm for the direction of arrival estimation requires the radio frequency electronic circuit to demodulate and sample the multichannel baseband signals followed by a complicated computing process, which places the fundamental limit on its sensing speed and energy efficiency. Here, we propose the super-resolution diffractive neural networks (S-DNN) to process electromagnetic (EM) waves directly for the DOA estimation at the speed of light. The multilayer meta-structures of S-DNN generate super-oscillatory angular responses in local angular regions that can perform the all-optical DOA estimation with angular resolutions beyond the diffraction limit. The spatial-temporal multiplexing of passive and reconfigurable S-DNNs is utilized to achieve high-resolution DOA estimation over a wide field of view. The S-DNN is validated for the DOA estimation of multiple radio sources over 5 GHz frequency bandwidth with estimation latency over two to four orders of magnitude lower than the state-of-the-art commercial devices in principle. The results achieve the angular resolution over an order of magnitude, experimentally demonstrated with four times, higher than diffraction-limited resolution. We also apply S-DNN’s edge computing capability, assisted by reconfigurable intelligent surfaces, for extremely low-latency integrated sensing and communication with low power consumption. Our work is a significant step towards utilizing photonic computing processors to facilitate various wireless sensing and communication tasks with advantages in both computing paradigms and performance over electronic computing.

The radio properties of z>3.5 quasars: Are most high-redshift radio-loud active galactic nuclei obscured?

We explore the radio properties of powerful (rest-frame luminosity $ at 500 MHz) high-redshift ($z 3.5$) quasars. The aim of this study is to gain a better understanding of radio-loud sources at the epoch when they reach the highest space density. We selected 29 radio-loud quasars at low radio frequencies (76 MHz). Their radio spectra, covering the range from 76 MHz to 5 GHz, are generally well reproduced by a single power law. We created samples that were matched in radio luminosity at lower redshift (from $z to $z to investigate any spectral evolution. We find that the fraction of flat-spectrum radio quasars (FSRQs) strongly increases with redshift (from $ 8<!PCT!>$ at z=1.2 to $ 45<!PCT!>$ at z$>$3.5). This effect is also observed in quasars with lower luminosities (down to $ The increase in the fraction of FSRQs with redshift corresponds to a decrease in the steep- spectrum radio quasars. This result can be explained when we assume that the beaming factor and the slope of the luminosity function do not change with redshift and if high-redshift radio-loud sources can be recognized as quasars only when they are seen at a small viewing angle ($ but most of them, about 90<!PCT!> are obscured in the UV and optical bands. We also found a trend for the size of radio sources to decrease with increasing redshift. Because projection effects are insufficient to cause this trend, we suggest that the large amount of gas causing the nuclear obscuration also hampers the growth of the more distant sources.

Sensitive 3 mm Imaging of Discrete Sources in the Fields of Thermal Sunyaev–Zel’dovich Effect–Selected Galaxy Clusters

In this paper, we present the results of a blind survey for compact sources in 243 Galaxy clusters that were identified using the thermal Sunyaev–Zel'dovich effect (tSZ). The survey was carried out at 90 GHz using MUSTANG2 on the Green Bank Telescope and achieved a 5σ detection limit of 1 mJy in the center of each cluster. We detected 24 discrete sources. The majority (18) of these correspond to known radio sources, and of these, five show signs of significant variability, either with time or in spectral index. The remaining sources have no clear counterparts at other wavelengths. Searches for galaxy clusters via the tSZ strongly rely on observations at 90 GHz, and the sources found have the potential to bias mass estimates of clusters. We compare our results to the Websky simulation that can be used to estimate the source contamination in galaxy cluster catalogs. While the simulation shows a good match to our observations at the clusters’ centers, it does not match our source distribution further out. Sources over 104″ from a cluster’s center bias the tSZ signal high, for some of the sources found, by over 50%. When averaged over the whole cluster population, the effect is smaller but still at a level of 1%–2%. We also discovered that unlike previous measurements and simulations, we see an enhancement of source counts in the outer regions of the clusters and fewer sources than expected in the centers of this tSZ-selected sample.

Analysis of the Causes of the Magnetic Storm on December 1–2, 2023 Based on Observations of Interplanetary Scintillations at the BSA Radio Telescope of the Lebedev Physical Institute

The results of the analysis of observational data of interplanetary scintillations obtained at the Big Synphasic Antenna radio telescope of the Lebedev Physical Institute (BSA LPI) before, during and after the magnetic storm that occurred on December 1–2, 2023. Observational data were compared with model calculations for corotating and propagating large-scale disturbances. The results of observations of scintillations of radio sources indicate that the magnetic storm that took place was caused by the superposition of two types of large-scale disturbances of the solar wind. On the day before the start of the magnetic storm, signs of interaction of the Earth’s magnetosphere with the corotating region of multi-velocity solar wind flows were observed, whereas later signs of disturbance of the magnetosphere by a coronal mass ejection propagating after the M9.8 flare on November 28, 2023 were observed.

Unveiling the Interplanetary Solar Radio Bursts of the 2024 Mother’s Day Solar Storm

We report on a comprehensive study of interplanetary type III radio bursts linked to X-class solar flares from NOAA active region 13664, which instigated the intense 2024 Mother’s Day solar storm, marked by a geomagnetic storm of −412 nT, the strongest in over two decades. Utilizing novel localization techniques with direction-finding data from STEREO-A, we identify an average eastward drift of 13.°42 ± 11.°63 in radio source locations relative to GOES observations. Our analysis reveals a significant correlation between solar flare intensity and longitude (Kendall’s tau = 0.535) and a strong correlation between radio flux at 1 MHz and GOES 1–8 Å soft X-ray flux (Kendall’s tau = 0.648). The timing analysis shows that peak soft X-ray fluxes typically follow electron beam liftoff by 3.24 ± 4.42 minutes. These insights into solar radio burst propagation and localization enhance our understanding of solar–terrestrial interactions and improve space weather forecasting capabilities.

Very Long Baseline Interferometry Detection of an Active Radio Source Potentially Driving 100 kpc Scale Emission in the Ultraluminous Infrared Galaxy IRAS F01004–2237

The nearby ultraluminous infrared galaxy (ULIRG) IRAS F01004−2237 exhibits 100 kpc scale continuum emission at radio wavelengths. The absence of extended X-ray emission in IRAS F01004−2237 has suggested an active galactic nucleus (AGN) origin for the extended radio emission, whose properties and role in merging systems still need to be better understood. We present the results of multifrequency observations of IRAS F01004−2237 conducted by the Very Long Baseline Array at 2.3 and 8.4 GHz. Compact 8.4 GHz continuum emission was detected on a 1 pc scale in the nuclear region with an intrinsic brightness temperature of 108.1 K suggesting that the radio source originated from an AGN, potentially driving the extended emission. In contrast, no significant emission was observed at 2.3 GHz, indicating the presence of low-frequency absorption. This absorption cannot be attributed solely to synchrotron self-absorption; alternatively, free–free absorption due to thermal plasma is mainly at work in the spectrum. From combined perspectives, including mid-infrared and X-ray data, the AGN is obscured in a dense environment. The kinetic power of the nonthermal jet, as inferred from the extended emission, can play a more important role in dispersing the surrounding medium than the thermal outflow in IRAS F01004−2237. These findings hint that jet activities in ULIRGs may contribute to AGN feedback during galaxy evolution induced by merger events.

Energy efficient scheme for improving network lifetime using BAT algorithm in wireless sensor network

SummaryWireless sensor networks consist of several autonomous nodes that are outfitted with sensors, radio, processors, memory storage, and power sources. These nodes track, sense, and send data using radio. While establishing a network, the two most essential characteristics are coverage and connectivity. For better connectivity and a longer network life, it's important to make the coverage area as big as possible with the fewest number of sensor nodes. The goal of this research is to make a connected sensor network that uses less energy and can be used in situations where the sensors need to be placed in the best way to make the network last as long as possible. The probabilistic sensing model is used, and improved network lifetime is the goal of the research work by using problem‐specific intelligent optimization techniques like BAT, ACO, and JOA to maximize the coverage area with respect to energy and points of interest. This work introduces a novel approach that optimizes both coverage and connectivity. The modified binary bat algorithm overcomes computational complexities and local optima observed in existing methods. Uniquely, it models the three states of each sensor node and includes innovative features like a greedy initialization and a weighted cost function for improving network efficiency. After investigation, it was analyzed that the proposed solution significantly improves network lifetime by over 10% to 12% compared to existing methods like JOA and ACO. The proposed approach converges faster and performs more efficiently.

A VLITE Search for Millisecond Pulsars in Globular Clusters: Discovery of a Pulsar in GLIMPSE-C01

We present results from a search for pulsars in globular clusters, including the discovery of a new millisecond pulsar in the stellar cluster GLIMPSE-C01. We searched for low-frequency radio sources within 97 globular clusters using images from the VLA Low-band Ionosphere and Transient Experiment (VLITE) and epochs 1 and 2 of the VLITE Commensal Sky Survey. We discovered 10 sources in our search area, four more than expected from extragalactic source counts at our sensitivity limits. The strongest pulsar candidate was a point source found in GLIMPSE-C01 with a spectral index ∼ − 2.6, and we present additional measurements at 0.675 and 1.25 GHz from the GMRT and 1.52 GHz from the VLA that confirm the spectral index. Using archival Green Bank Telescope S-band data from 2005, we detect a binary pulsar with a spin period of 19.78 ms within the cluster. Although we cannot confirm that this pulsar is at the same position as the steep-spectrum source using the existing data, the pulse flux is consistent with the predicted flux density from other frequencies, making it a probable match. The source also shows strong X-ray emission, indicative of a higher magnetic field than most millisecond pulsars, suggesting that its recycling was interrupted. We demonstrate that low-frequency searches for steep-spectrum sources are an effective way to identify pulsar candidates, in particular on sightlines with high dispersion.

Ultra-low-frequency LOFAR spectral indices of cluster radio halos

A fraction of galaxy clusters harbor diffuse radio sources known as radio halos. The prevailing theory regarding their formation is based on second-order Fermi reacceleration of seed electrons caused by merger-driven turbulence in the intra-cluster medium. This mechanism is expected to be inefficient, which implies that a significant fraction of halos should have very steep energy spectra ($ We start investigating the potential and current limitations of the combination of the two surveys conducted by LOFAR, LoTSS (144 MHz) and LoLSS (54 MHz), to probe the origin of radio halos. We followed up the 20 radio halos detected in Data Release 1 of LoTSS, which covers the HETDEX field, with the LoLSS survey, and we studied their spectral properties between 54 and 144 MHz. After removing compact sources, nine halos were excluded due to unreliable halo flux density measurements at 54 MHz. Our main finding is that 7 out of 11 (sim 64<!PCT!>) exhibit an ultra-steep spectrum ($ < -1.5$), which is a key prediction of turbulent reacceleration models. We also note a tentative trend for more massive systems to host flatter halos, although the currently poor statistics do not allow for a deeper analysis. Our sample suffers from low angular resolution at 54 MHz, which limits the accuracy of the compact-source subtraction. Nevertheless, this study is the first step toward providing compelling evidence for the existence of a large fraction of radio halos with a very steep spectrum, which is a fundamental prediction of turbulent reacceleration models. In this regard, the forthcoming second data release of LoLSS, along with the integration of LOFAR international stations and the instrumental upgrade to LOFAR2.0, will improve both the statistics and the low-frequency angular resolution, allowing us to determine the origin of radio halos in galaxy clusters conclusively.

First very long baseline interferometry detection of Fornax A

Radio galaxies harbouring jetted active galactic nuclei are a frequent target of very long baseline interferometry (VLBI) because they play an essential role in our exploration of how jets form and propagate. Hence, only a few have not yet been detected with VLBI; Fornax A was one of the most famous examples. Here we present the first detection of the compact core region of Fornax A with VLBI. At 8.4 GHz the faint core is consistent with an unresolved point source. We constrained its flux density to be S0 = 47.5 − 62.3 mJy and its diameter to be D0min ≤ 70 μas. The high values of the measured brightness temperature (TB ≳ 1011 K) imply that the observed radiation is of non-thermal origin, likely associated with the synchrotron emission from the active galactic nucleus. We also investigated the possibility of a second radio source being present within the field of view. Adding a second Gaussian component to the geometrical model fit does not significantly improve the quality of the fit, and we therefore, conclude that our detection corresponds to the compact core of Fornax A. Analysis of the non-trivial closure phases provides evidence for the detection of a more extended flux density, on the angular scale of ∼4000 μas. Finally, the fractional circular polarisation of the core is consistent with zero, with a conservative upper limit being mcirc ≤ 4%.

Flux dependence of redshift distribution and clustering of LOFAR radio sources

We study the flux density dependence of the redshift distribution of low-frequency radio sources observed in the LOFAR Two-metre Sky Survey (LoTSS) deep fields and apply it to estimate the clustering length of the large-scale structure of the Universe, examining flux density limited samples (1 mJy, 2 mJy, 4 mJy and 8 mJy) of LoTSS wide field radio sources. We utilise and combine the posterior probability distributions of photometric redshift determinations for LoTSS deep field observations from three different fields (Boötes, Lockman hole and ELAIS-N1, together about $26$ square degrees of sky), which are available for between $91<!PCT!>$ to $96<!PCT!>$ of all sources above the studied flux density thresholds and observed in the area covered by multi-frequency data. We estimate uncertainties by a bootstrap method. We apply the inferred redshift distribution on the LoTSS wide area radio sources from the HETDEX field (LoTSS-DR1; about $424$ square degrees) and make use of the Limber approximation and a power-law model of three dimensional clustering to measure the clustering length, $r_0$, for various models of the evolution of clustering. We find that the redshift distributions from all three LoTSS deep fields agree within expected uncertainties. We show that the radio source population probed by LoTSS at flux densities above $1$ mJy has a median redshift of at least $0.9$. At $2$ mJy, we measure the clustering length of LoTSS radio sources to be $r_0 = (10.1 $Mpc in the context of the comoving clustering model. Our findings are in agreement with measurements at higher flux density thresholds at the same frequency and with measurements at higher frequencies in the context of the comoving clustering model. Based on the inferred flux density limited redshift distribution of LoTSS deep field radio sources, the full wide area LoTSS will eventually cover an effective (source weighted) comoving volume of about $10\ $ Gpc$^3$.

Host galaxy of low-luminosity compact sources

The term `active galactic nuclei' (AGN) is applied to a huge variety of objects, classified on the basis of their properties at different wavelengths. Peaked sources (PSs) represent a class of AGN at the first stage of evolution, characterised by a peaked radio spectrum. Among these radio sources, low-luminosity compact (LLC) sources can be identified as PSs accreting with a high Eddington rate, harbouring low-power jets, and hosting low-mass black holes. These properties are also shared by narrow-line Seyfert 1 galaxies (NLS1s). In 2016, LLCs were hypothesised to be the parent population of NLS1s with a flat radio spectrum (F-NLS1s), suggesting that the former may be the same objects as the latter but, instead, seen at a higher inclination. Based on radio luminosity functions and optical spectra analysis, ten LLCs were identified as valid F-NLS1s candidates. To account for the missing piece to the puzzle and verifying whether these LLCs could be hosted in late-type galaxies as NLS1s, we performed a photometric decomposition of their Pan-STARRS1 images in all five filters. We used the 2D fitting algorithm GALFIT for the single-band analysis and its extension GALFITM for the multi-band analysis. Considering that the morphological type and the structural parameters of the host may be dependent on the wavelength, we found six out of ten LLCs hosted in late-type galaxies, probably with pseudo-bulges, along with three point-like sources and one object of an uncertain classification. Although this study is based on a small sample, it represents the first morphological analysis of LLC host galaxies. These results confirm the trend observed in NLS1s, indicating late-type and disc-like host galaxies for LLCs and supporting the validity of the parent population scenario.

Identification of multicomponent LOFAR sources with multimodal deep learning

ABSTRACT Modern high-sensitivity radio telescopes are discovering an increased number of resolved sources with intricate radio structures and fainter radio emissions. These sources often present a challenge because source detectors might identify them as separate radio sources rather than components belonging to the same physically connected radio source. Currently, there are no reliable automatic methods to determine which radio components are single radio sources or part of multicomponent sources. We propose a deep-learning classifier to identify those sources that are part of a multicomponent system and require component association on data from the LOFAR Two-Metre Sky Survey. We combine different types of input data using multimodal deep learning to extract spatial and local information about the radio source components: a convolutional neural network component that processes radio images is combined with a neural network component that uses parameters measured from the radio sources and their nearest neighbours. Our model retrieves 94 per cent of the sources with multiple components on a balanced test set with 2683 sources and achieves almost 97 per cent accuracy in the real imbalanced data (323 103 sources). The approach holds potential for integration into pipelines for automatic radio component association and cross-identification. Our work demonstrates how deep learning can be used to integrate different types of data and create an effective solution for managing modern radio surveys.

Transient study using LoTSS – framework development and preliminary results

ABSTRACT We present a search for transient radio sources on time-scales of seconds to hours at 144 MHz using the LOFAR Two-metre Sky Survey (LoTSS). This search is conducted by examining short time-scale images derived from the LoTSS data. To allow imaging of LoTSS on short time-scales, a modern imaging procedure and fast filtering strategy are introduced. This includes sky model source subtraction, no cleaning or primary beam correction, a simple source finder, fast filtering schemes, and source catalogue matching. This new strategy is first tested by injecting simulated transients, with a range of flux densities and durations, into the data. We find the limiting sensitivity to be 113 and 6 mJy for 8 s and 1 h transients, respectively. The new imaging and filtering strategies are applied to 58 fields of the LoTSS survey, corresponding to LoTSS-DR1 (2 per cent of the survey). One transient source is identified in the 8 s and 2 min snapshot images. The source shows 1 min duration flare in the 8 h observation. Our method puts the most sensitive constraints on/estimates of the transient surface density at low frequencies at time-scales of seconds to hours; <4.0 × 10−4 deg−2 at 1 h at a sensitivity of 6.3 mJy; 5.7 × 10−7 deg−2 at 2 min at a sensitivity of 30 mJy; and 3.6 × 10−8 deg−2 at 8 s at a sensitivity of 113 mJy. In the future, we plan to apply the strategies presented in this paper to all LoTSS data.

Mathematical model of single-channel search for signals of mobile radio communications with one degree of detection in the frequency-time domain.

In the context of a full-scale invasion and military operations for Ukraine's independence, the issues of radio monitoring of radio emission sources of telecommunication networks and systems are gaining special attention and require fundamentally new approaches to the level of informatization, technical implementation and increase of their efficiency. Today, the technical means of radio interception, monitoring and direction finding in the networks of mobile radio communication systems are realized in the form of software and hardware complexes, the most important performance indicators of which are considered to be speed, accuracy of detection and probability of recognition of mobile radio communication means with their information content. At the same time, these issues still remain problematic and require further development of methods and techniques for searching and detecting signals of mobile radio communications in both frequency and time telecommunication channels and their information processing. To solve this issue, the authors propose a mathematical model for searching for mobile radio signals in the frequency-time domain with one degree of detection. The description of the mathematical model for determining the spectral components of signals in the frequency and time domains is carried out using the basic provisions of the theory of directed probability graphs, geometric probabilities with its well-known problem of meeting in a given time interval, and the theoretical foundations of statistical information processing. The analysis of the proposed model shows that the probability of successful completion of the search for a signal with one degree of detection in the frequency-time domain for a given time depends on the value of the signal duration, the number of analyzed frequency channels, the time of signal analysis in each channel, and the probabilities of errors of the first and second kinds The article presents the results of calculations of the value of the probability of successful completion of the signal search as a function of the search time at different values of the analysis time. It is shown that the application of the mathematical model of single-channel search for signals of mobile radio communication means with one degree of detection in the frequency-time domain in practice will make it possible to determine the quality of the radio monitoring process and increase the efficiency of evaluating the spectral components of radio signals in terms of speed, detection accuracy and probability of recognition of mobile radio communication means with further determination of their information content.

Ray Tracing for Jupiter's Icy Moon Ionospheric Occultation of Jovian Auroral Radio Sources

AbstractThe ionospheres of Jupiter's icy moons have been observed by in situ plasma measurements and radio science. However, their spatial structures have not yet been fully characterized. To address this, we developed a new ray tracing method for modeling the radio occultation of the ionospheres using Jovian auroral radio sources. Applying our method to Jovian auroral radio observations with the Galileo spacecraft, we derived the electron density of the ionosphere of Ganymede and Callisto. For Ganymede's ionosphere, we found that the maximum electron density on the surface was 76.5–288.5 cm−3 in the open magnetic field line regions and 5.0–20.5 cm−3 in the closed magnetic field line region during the Galileo Ganymede 01 flyby. The difference in the electron density distribution was correlated with the accessibility of Jovian magnetospheric plasma to the atmosphere and surface of the moons. These results indicated that electron‐impact ionization of the Ganymede exosphere and sputtering of the surface water ice were effective for the producing Ganymede's ionosphere. For Callisto's ionosphere, we found that the densities were approximately 350 and 12.5 cm−3 on the night side hemisphere during Callisto 09 and 30 flybys, respectively. These results combined with previous observations indicated that atmospheric production through sublimation controlled the ionospheric density of Callisto. This method is also applicable to upcoming Jovian radio observation data from the Jupiter Icy Moon Explorer, JUICE.

Very long baseline interferometry detection of nearby (<100 pc) young stars

To increase the number of sources with very long baseline interferometry (VLBI) astrometry available for comparison with the Gaia results, we have observed 31 young stars with recently reported radio emission. These stars are all in the Gaia DR3 catalog and were suggested, on the basis of conventional interferometry observations, to be nonthermal radio emitters and are therefore good candidates for VLBI detections. The observations were carried out with the Very Long Baseline Array (VLBA) at two epochs separated by a few days and yielded ten detections (a roughly 30% detection rate). Using the astrometric Gaia results, we extrapolated the target positions to the epochs of our radio observations and compared them with the position of the radio sources. For seven objects, the optical and radio positions are coincident within five times their combined position errors. Three targets, however, have position discrepancies above eight times the position errors, indicating different emitting sources at optical and radio wavelengths. In one case, the VLBA emission is very likely associated with a known companion of the primary target. In the two other cases, we associated the VLBA emission with previously unknown companions, but further observations will be needed to confirm this.