Low Frequency Array Research Articles

A search for intercluster filaments with LOFAR and eROSITA

ABSTRACT Cosmological simulations predict the presence of warm hot thermal gas in the cosmic filaments that connect galaxy clusters. This gas is thought to constitute an important part of the missing baryons in the Universe. In addition to the thermal gas, cosmic filaments could contain a population of relativistic particles and magnetic fields. A detection of magnetic fields in filaments can constrain early magnetogenesis in the cosmos. So far, the resulting diffuse synchrotron emission has only been indirectly detected. We present our search for thermal and non-thermal diffuse emission from intercluster regions of 106 paired galaxy clusters by stacking the 0.6–2.3 keV X-ray and 144 MHz radio data obtained with the eROSITA telescope onboard the Spectrum-Roentgen-Gamma (SRG) observatory and LOw Frequency ARray (LOFAR), respectively. The stacked data do not show the presence of X-ray and radio diffuse emission in the intercluster regions. This could be due to the sensitivity of the data sets and/or the limited number of cluster pairs used in this study. Assuming a constant radio emissivity in the filaments, we find that the mean radio emissivity is not higher than $1.2\times 10^{-44}\, {\rm erg \, s^{-1} \, cm^{-3} \, Hz^{-1}}$. Under equipartition conditions, our upper limit on the mean emissivity translates to an upper limit of $\sim 75\, {\rm nG}$ for the mean magnetic field strength in the filaments, depending on the spectral index and the minimum energy cutoff. We discuss the constraint for the magnetic field strength in the context of the models for the formation of magnetic fields in cosmic filaments.

Measurement of the scaling slope of compressible magnetohydrodynamic turbulence by synchrotron radiation statistics

ABSTRACT Based on magnetohydrodynamic (MHD) turbulence simulations, we generate synthetic synchrotron observations to explore the scaling slope of the underlying MHD turbulence. We propose the new Q-U cross-intensity X and cross-correlation intensity Y to measure the spectral properties of magnetic turbulence, together with statistics of the traditional synchrotron I and polarization PI intensities. By exploring the statistical behaviour of these diagnostics, we find that the new statistics X and Y can extend the inertial range of turbulence to improve measurement reliability. When focusing on different Alfvénic and sonic turbulence regimes, our results show that the diagnostics proposed in this paper not only reveal the spectral properties of the magnetic turbulence but also gain insight into the individual plasma modes of compressible MHD turbulence. The synergy of multiple statistical methods can extract more reliable turbulence information from the huge amount of observation data from the Low-Frequency Array for radio astronomy and the Square Kilometer Array.

LOFAR observations of gravitational wave merger events: O3 results and O4 strategy

ABSTRACT The electromagnetic counterparts to gravitational wave (GW) merger events hold immense scientific value, but are difficult to detect due to the typically large localization errors associated with GW events. The Low-Frequency Array (LOFAR) is an attractive GW follow-up instrument owing to its high sensitivity, large instantaneous field of view, and ability to automatically trigger on events to probe potential prompt emission within minutes. Here, we report on 144-MHz LOFAR radio observations of three GW merger events containing at least one neutron star that were detected during the third GW observing run. Specifically, we probe 9 and 16 per cent of the location probability density maps of S190426c and S200213t, respectively, and place limits at the location of an interesting optical transient (PS19hgw/AT2019wxt) found within the localization map of S191213g. While these GW events are not particularly significant, we use multi-epoch LOFAR data to devise a sensitive wide-field GW follow-up strategy to be used in future GW observing runs. In particular, we improve on our previously published strategy by implementing direction-dependent calibration and mosaicing, resulting in nearly an order of magnitude increase in sensitivity and more uniform coverage. We achieve a uniform 5σ sensitivity of 870 μJy beam−1 across a single instantaneous LOFAR pointing’s 21 deg2 core, and a median sensitivity of 1.1 mJy beam−1 when including the full 89 deg2 hexagonal beam pattern. We also place the deepest transient surface density limits yet on time-scales of the order of month for surveys between 60 and 340 MHz (0.017 deg−2 above 2.0 mJy beam−1 and 0.073 deg−2 above 1.5 mJy beam−1).

Matching LOFAR sources across radio bands

Aims. The recent preliminary release of the LOFAR LBA Sky Survey (LoLSS) is the first wide-area, ultra-low frequency observation published from the Low Frequency Array (LOFAR). Our aim is to combine this data set with other surveys at higher frequencies to study the spectral properties of a large sample of radio sources. Methods. We present a new cross-matching algorithm that takes into account the sizes of the radio sources. We applied it to the LoLSS-PR, LoTSS-DR1, LoTSS-DR2 (all LOFAR), TGSS-ADR1 (GMRT), WENSS (WSRT), and NVSS (VLA) catalogues. We then studied the number of matched counterparts for LoLSS radio sources and their spectral properties. Results. We found counterparts for 22 607 (89.5%) LoLSS sources. The remaining 2640 sources (10.5%) were identified either as an artefact in the LoLSS survey (3.6%) or flagged due to their closeness to bright sources (6.9%). We found an average spectral index of α = −0.77 ± 0.18 between LoLSS and NVSS. Between LoLSS and LoTSS-DR2, we found α = −0.71 ± 0.31. The average spectral index is independent of the flux density above S54 = 181 mJy. A comparison of the spectral slopes from LoLSS-LoTSS-DR2 with LoTSS-DR2–NVSS indicates that the probed population of radio sources shows evidence of a negative spectral curvature.

Finding AGN remnant candidates based on radio morphology with machine learning

Context. Remnant radio galaxies represent the dying phase of radio-loud active galactic nuclei (AGN). Large samples of remnant radio galaxies are important for quantifying the radio-galaxy life cycle. The remnants of radio-loud AGN can be identified in radio sky surveys based on their spectral index, and identifications can be confirmed through visual inspection based on their radio morphology. However, this latter confirmation process is extremely time-consuming when applied to the new large and sensitive radio surveys. Aims. Here, we aim to reduce the amount of visual inspection required to find AGN remnants based on their morphology using supervised machine learning trained on an existing sample of remnant candidates. Methods. For a dataset of 4107 radio sources with angular sizes of larger than 60 arcsec from the LOw Frequency ARray (LOFAR) Two-Metre Sky Survey second data release (LoTSS-DR2), we started with 151 radio sources that were visually classified as ‘AGN remnant candidate’. We derived a wide range of morphological features for all radio sources from their corresponding Stokes-I images: from simple source-catalogue-derived properties to clustered Haralick-features and self-organising-map(SOM)-derived morphological features. We trained a random forest classifier to separate the AGN remnant candidates from the yet-to-be inspected sources. Results. The SOM-derived features and the total-to-peak flux ratio of a source are shown to have the greatest influence on the classifier. For each source, our classifier outputs a positive prediction, if it believes the source to be a likely AGN remnant candidate, or a negative prediction. The positive predictions of our model include all initially inspected AGN remnant candidates, plus a number of yet-to-be inspected sources. We estimate that 31 ± 5% of sources with positive predictions from our classifier will be labelled AGN remnant candidates upon visual inspection, while we estimate the upper bound of the 95% confidence interval for AGN remnant candidates in the negative predictions to be 8%. Visual inspection of just the positive predictions reduces the number of radio sources requiring visual inspection by 73%. Conclusions. This work shows the usefulness of SOM-derived morphological features and source-catalogue-derived properties in capturing the morphology of AGN remnant candidates. The dataset and method outlined in this work bring us closer to the automatic identification of AGN remnant candidates based on radio morphology alone and the method can be used in similar projects that require automatic morphology-based classification in conjunction with small labelled sample sizes.

Improved Type III solar radio burst detection using congruent deep learning models

Solar flares are energetic events in the solar atmosphere that are often linked with solar radio bursts (SRBs). SRBs are observed at metric to decametric wavelengths and are classified into five spectral classes (Type I–V) based on their signature in dynamic spectra. The automatic detection and classification of SRBs is a challenge due to their heterogeneous form. Near-real time detection and classification of SRBs has become a necessity in recent years due to large data rates generated by advanced radio telescopes such as the LOw Frequency ARray (LOFAR). For this study, we implemented congruent deep learning models to automatically detect and classify Type III SRBs. We generated simulated Type III SRBs, which were comparable to Type IIIs seen in real observations, using a deep learning method known as the generative adversarial network (GAN). This simulated data were combined with observations from LOFAR to produce a training set that was used to train an object detection model known as you only look once (YOLOv2). Using this congruent deep learning model system, we can accurately detect Type III SRBs at a mean Average Precision (mAP) value of 77.71%.

LOFAR Deep Fields: Probing faint Galactic polarised emission in ELAIS-N1

We present the first deep polarimetric study of Galactic synchrotron emission at low radio frequencies. Our study is based on 21 observations of the European Large Area Infrared Space Observatory Survey-North 1 (ELAIS-N1) field using the Low-Frequency Array (LOFAR) at frequencies from 114.9 to 177.4 MHz. These data are a part of the LOFAR Two-metre Sky Survey Deep Fields Data Release 1. We used very low-resolution (4.3′) Stokes QU data cubes of this release. We applied rotation measure (RM) synthesis to decompose the distribution of polarised structures in Faraday depth, and cross-correlation RM synthesis to align different observations in Faraday depth. We stacked images of about 150 h of the ELAIS-N1 observations to produce the deepest Faraday cube at low radio frequencies to date, tailored to studies of Galactic synchrotron emission and the intervening magneto-ionic interstellar medium. This Faraday cube covers ~36 deg2 of the sky and has a noise of 27 µJy PSF−1 RMSF−1 in polarised intensity. This is an improvement in noise by a factor of approximately the square root of the number of stacked data cubes (~√20), as expected, compared to the one in a single data cube based on five-to-eight-hour observations. We detect a faint component of diffuse polarised emission in the stacked cube, which was not detected previously. Additionally, we verify the reliability of the ionospheric Faraday rotation corrections estimated from the satellite-based total electron content measurements to be of ~0.05 гad m−2. We also demonstrate that diffuse polarised emission itself can be used to account for the relative ionospheric Faraday rotation corrections with respect to a reference observation.

The LOFAR Two-metre Sky Survey: the radio view of the cosmic star formation history

ABSTRACT We present a detailed study of the cosmic star formation history over 90 per cent of cosmic time (0 ≲ z ≲ 4), using deep, radio continuum observations that probe star formation activity independent of dust. The Low Frequency Array Two Metre Sky Survey has imaged three well-studied extragalactic fields, Elais-N1, Boötes, and the Lockman Hole, reaching $\sim 20\, \mu \rm {Jy\,beam^{-1}}$ rms sensitivity at $150\, \rm {MHz}$. The availability of high-quality ancillary data from ultraviolet to far-infrared wavelengths has enabled accurate photometric redshifts and the robust separation of radio-bright AGN from their star-forming counterparts. We capitalize on this unique combination of deep, wide fields and robustly selected star-forming galaxies to construct radio luminosity functions and derive the cosmic star formation rate density. We carefully constrain and correct for scatter in the $L_{150\, \rm {MHz}}-\rm {SFR}$ relation, which we find to be $\sim 0.3\, \rm {dex}$. Our derived star formation rate density lies between previous measurements at all redshifts studied. We derive higher star formation rate densities between z ∼ 0 and z ∼ 3 than are typically inferred from short wavelength emission; at earlier times, this discrepancy is reduced. Our measurements are generally in good agreement with far-infrared and radio-based studies, with small offsets resulting from differing star formation rate calibrations.

A Strong Pulsing Nature of Negative Intracloud Dart Leaders Accompanied by Regular Trains of Microsecond‐Scale Pulses

AbstractWe report the first observations of negative intracloud (IC) dart‐stepped leaders accompanied by regular trains of microsecond‐scale pulses, simultaneously detected by shielded broadband magnetic loop antennas and the radio telescope Low Frequency Array (LOFAR). Four investigated pulse trains occurred during complicated IC flashes on 18 June 2021, when heavy thunderstorms hit the Netherlands. The pulses within the trains are unipolar, a few microseconds wide, and with an average inter‐pulse interval of 5–7 μs. The broadband pulses perfectly match energetic, regularly distributed, and relatively isolated bursts of very high frequency sources localized by LOFAR. All trains were generated by negative dart‐stepped leaders propagating at a lower speed than usual dart leaders. They followed channels of previous leaders occurring within the same flash several tens of milliseconds before the reported observations. The physical mechanism remains unclear as to why we observe dart‐stepped leaders, which show mostly regular stepping, emitting energetic microsecond‐scale pulses.

Spectral age distribution for radio-loud active galaxies in the XMM-LSS field

ABSTRACT Jets of energetic particles, as seen in FR type-I and FR type-II sources, ejected from the centre of radio-loud AGN affect the sources surrounding the intracluster medium/intergalactic medium. Placing constraints on the age of such sources is important in order to measure the jet powers and determine the effects on feedback. To evaluate the age of these sources using spectral age models, we require high-resolution multiwavelength data. The new sensitive and high-resolution MIGHTEE survey of the XMM-LSS field, along with data from the Low Frequency Array (LOFAR) and the Giant Metrewave Radio Telescope (GMRT) provide data taken at different frequencies with similar resolution, which enables us to determine the spectral age distribution for radio-loud AGN in the survey field. In this study, we present a sample of 28 radio galaxies with their best-fitting spectral age distribution analysed using the Jaffe–Perola (JP) model on a pixel-by-pixel basis. Fits are generally good, and objects in our sample show maximum ages within the range of 2.8 to 115 Myr with a median of 8.71 Myr. High-resolution maps over a range of frequencies are required to observe detailed age distributions for small sources, and high-sensitivity maps will be needed in order to observe fainter extended emission. We do not observe any correlation between the total physical size of the sources and their age, and we speculate that both dynamical models and the approach to spectral age analysis may need some modification to account for our observations.

The LOFAR LBA Sky Survey

Context. The Low Frequency Array (LOFAR) is the only existing radio interferometer able to observe at ultra-low frequencies (<100 MHz) with high resolution (<15") and high sensitivity (<1 mJy beam−1). To exploit these capabilities, the LOFAR Surveys Key Science Project is using the LOFAR Low Band Antenna (LBA) to carry out a sensitive wide-area survey at 41–66 MHz named the LOFAR LBA Sky Survey (LoLSS). Aims. LoLSS is covering the whole northern sky above declination 24° with a resolution of 15" and a sensitivity of 1–2 mJy beam−1 (1σ) depending on declination, field properties, and observing conditions. Here we present the first data release, including a discussion of the calibration strategy and the properties of the released images and catalogues. Methods. A fully automated pipeline was used to reduce the 95 fields included in this data release. The data reduction procedures developed for this project have a general application and are currently being used to process almost all LOFAR LBA interferometric observations. Compared to the preliminary release, direction-dependent errors have been derived and corrected for during the calibration process. This results in a typical sensitivity of 1.55 mJy beam−1, which is four times better than for the preliminary release, at the target resolution of 15". Results. The first data release of the LOFAR LBA Sky Survey covers 650 deg2 in the HETDEX spring field. The resultant data products released to the community include mosaic images (I and V Stokes) of the region, and a catalogue of 42 463 detected sources and related Gaussian components used to describe the sources' morphologies. Separate catalogues for the six in-band frequencies of 44, 48, 52, 56, 60, and 64 MHz are also released. Conclusions. The first data release of LoLSS shows that, despite the influences of the ionosphere and radio frequency interference, LOFAR can conduct large-scale surveys in the frequency window 42-66 MHz with unprecedentedly high sensitivity and resolution. The data can be used to derive unique information on the low-frequency spectral properties of many thousands of sources with a wide range of applications in extragalactic and galactic astronomy.

Weakly interacting massive particle cross section limits from LOFAR observations of dwarf spheroidal galaxies

Context. Weakly interacting massive particles (WIMPs) can self-annihilate, thus providing us with a way to indirectly detect dark matter (DM). Dwarf spheroidal (dSph) galaxies are excellent places to search for annihilation signals because they are rich in DM and background emission is low. If O(0.1–10 μG) magnetic fields in dSph galaxies exist, the particles produced in DM annihilation emit synchrotron radiation in the radio band. Aims. We used the non-detection of 150 MHz radio continuum emission from dSph galaxies with the LOw Frequency ARray (LOFAR) to derive constraints on the annihilation cross section of WIMPs in electron–positron pairs. Our main underlying assumption is that the transport of the cosmic rays can be described by the diffusion approximation, which necessitates the existence of magnetic fields. Methods. We used observations of six dSph galaxies in the LOFAR Two-metre Sky Survey (LoTSS). The data were reimaged, and a radial profile was generated for each galaxy. We also used stacking to increase the sensitivity. In order to derive upper limits on the WIMP cross section, we injected fake Gaussian sources into the data, which were then detected with 2σ significance in the radial profile. These sources represent the lowest emission we would have been able to detect. Results. We present limits from the observations of individual galaxies as well as from stacking. We explored the uncertainty due to the choice of diffusion and magnetic field parameters by constructing three different model scenarios: optimistic (OPT), intermediate (INT), and pessimistic (PES). Assuming monochromatic annihilation into electron–positron pairs, the limits from the INT scenario exclude thermal WIMPs (⟨σv⟩≈2.2 × 10−26 cm3 s−1) below 20 GeV, and the limits from the OPT scenario even exclude thermal WIMPs below 70 GeV. The INT limits can compete with limits set by Fermi-LAT using γ-ray observations of multiple dwarf galaxies, and they are especially strong for low WIMP masses.

Interpreting the Hi 21-cm cosmology maps through Largest Cluster Statistics. Part I. Impact of the synthetic SKA1-Low observations

We analyse the evolution of the largest ionized region using the topological and morphological evolution of the redshifted 21-cm signal coming from the neutral hydrogen distribution during the different stages of reionization. For this analysis, we use the “Largest Cluster Statistics” — LCS. We mainly study the impact of the array synthesized beam on the LCS analysis of the 21-cm signal considering the upcoming low-frequency Square Kilometer Array (SKA1-Low) observations using a realistic simulation for such observation based on the 21cmE2E-pipeline using OSKAR. We find that bias in LCS estimation is introduced in synthetic observations due to the array beam. This in turn shifts the apparent percolation transition point towards the later stages of reionization. The biased estimates of LCS, occurring due to the effect of the lower resolution (lack of longer baselines) and the telescope synthesized beam will lead to a biased interpretation of the reionization history. This is important to note while interpreting any future 21-cm signal images from upcoming or future telescopes like the SKA, HERA, etc. We conclude that one may need denser uv-coverage at longer baselines for a better deconvolution of the array synthesized beam from the 21-cm images and a relatively unbiased estimate of LCS from such images.

The LOFAR Two-metre Sky Survey: Deep Fields data release 1. V. Survey description, source classifications, and host galaxy properties

ABSTRACT Source classifications, stellar masses, and star-formation rates are presented for ≈80 000 radio sources from the first data release of the Low Frequency Array Two-metre Sky Survey (LoTSS) Deep Fields, which represents the widest deep radio survey ever undertaken. Using deep multi-wavelength data spanning from the ultraviolet to the far-infrared, spectral energy distribution (SED) fitting is carried out for all of the LoTSS Deep host galaxies using four different SED codes, two of which include modelling of the contributions from an active galactic nucleus (AGN). Comparing the results of the four codes, galaxies that host a radiative AGN are identified, and an optimized consensus estimate of the stellar mass and star-formation rate for each galaxy is derived. Those galaxies with an excess of radio emission over that expected from star formation are then identified, and the LoTSS Deep sources are divided into four classes: star-forming galaxies, radio-quiet AGN, and radio-loud high-excitation and low-excitation AGN. Ninety-five per cent of the sources can be reliably classified, of which more than two-thirds are star-forming galaxies, ranging from normal galaxies in the nearby Universe to highly-starbursting systems at z > 4. Star-forming galaxies become the dominant population below 150-MHz flux densities of ≈1 mJy, accounting for 90 per cent of sources at S150MHz ∼ 100 μJy. Radio-quiet AGN comprise ≈10 per cent of the overall population. Results are compared against the predictions of the SKADS and T-RECS radio sky simulations, and improvements to the simulations are suggested.

MaNGA integral-field stellar kinematics of LoTSS radio galaxies: Luminous radio galaxies tend to be slow rotators

The radio jets of an active galactic nucleus (AGN) can heat up the gas around a host galaxy and quench star formation activity. The presence of a radio jet could be related to the evolutionary path of the host galaxy and may be imprinted in the morphology and kinematics of the galaxy. In this work, we use data from the Sloan Digital Sky Survey’s Mapping Nearby Galaxies at Apache Point Observatory survey and the Low Frequency Array (LOFAR) Two-Metre Sky Survey as well as the National Radio Astronomy Observatory (NRAO) the Karl G. Jansky Very Large Array (VLA) Sky Survey and the Faint Images of the Radio Sky at Twenty Centimeter survey. We combine these integral field spectroscopic data and radio data to study the link between stellar kinematics and radio AGNs. We find that the luminosity-weighted stellar angular momentum λRe is tightly related to the range of radio luminosity and the fraction of radio AGNs Fradio present in galaxies, as high-luminosity radio AGNs are only in galaxies with a small λRe, and the Fradio at a fixed stellar mass decreases with λRe. These results indicate that galaxies with stronger random stellar motions with respect to the ordered motions might be better breeding grounds for powerful radio AGNs. This would also imply that the merger events of galaxies are important in the triggering of powerful radio jets in our sample.

Radio multifrequency observations of the galaxy cluster pair Abell 399 − 401 with WSRT

ABSTRACT Galaxy clusters are assembled via merging of smaller structures, in a process that generates shocks and turbulence in the intra cluster medium and produces radio diffuse emission in the form of halos and relics. The cluster pair A 399–A 401 represents a special case: both clusters host a radio halo. Recent Low Frequency Array (LOFAR) observations at 140 MHz revealed the presence of a radio bridge connecting the two clusters along with two relic candidates. These relics include one South of A 399 and the other in between the two clusters, in proximity of a shock front detected in X-ray observations. In this paper we present observations of the A 399–A 401 cluster pair at 1.7, 1.4, 1.2 GHz, and 346 MHz from the Westerbork Synthesis Radio Telescope (WSRT). We detect the radio halo in the A 399 cluster at 346 MHz, extending up to ∼650 kpc and with a 125 ± 6 mJy flux density. Its spectral index between 140 MHz and 346 MHz is α = 1.75 ± 0.14. The two candidate relics are also seen at 346 MHz and we determine their spectral indices to be α = 1.10 ± 0.14 and α = 1.46 ± 0.14. The low surface brightness bridge connecting the two clusters is below the noise level at 346 MHz therefore we constrain the bridge average spectral index to be steep, i.e. α > 1.5 at 95 per cent confidence level. This result favours the scenario where dynamically-induced turbulence is a viable mechanism to reaccelerate a population of mildly relativistic particles and amplify magnetic fields on scales of a few Mpcs.

Small‐Scale Discharges Observed Near the Top of a Thunderstorm

AbstractWe have used the LOw‐Frequency ARray (LOFAR) to image a few lightning flashes during a particularly severe thunderstorm. The images show an exceptional amount of VHF activity at altitudes above 10 km. Much of this is in the form of small‐scale discharges, not exceeding a few hundred meter, occurring seemingly randomly around the centers of active storm cells. To emphasize the incidental nature of these small‐scale discharges or sparks we refer to them as “sparkles.” A detailed investigation shows evidence that these sparkles are indicative of positive leader channels and that they are equivalent to the needle activity seen around positive leader tracks at lower altitudes.

Revisiting the alignment of radio galaxies in the ELAIS-N1 field

Aims. Previous studies reported an alignment of the major axes of radio galaxies on various angular scales. Here, we study the alignment of radio galaxies in the ELAIS-N1 Low Frequency ARray (LOFAR) deep field, which covers an area of 25 deg2. Methods. The low noise level of about 20 μJy beam−1 of the LOFAR deep field observations at 150 MHz enabled the identification of 447 extended (> 30″) radio galaxies for which we measured the position angle of the major axis. We find that 95% of these sources have either photometric or spectroscopic redshifts, which we then used for a three-dimensional (3D) analysis. Results. We show the distribution of the position angles of radio galaxies in the ELAIS-N1 field and the results of multiple statistical tests carried out to decipher whether the radio galaxies are randomly oriented. We find that the distribution of position angles is consistent with being uniform. Two peaks around position angles of 50 and 140 deg are spurious and are not caused by an alignment, as shown by a 3D analysis. In conclusion, our results do not support a 2D or 3D alignment of radio galaxies on scales of smaller than ∼4 deg.

Identifying lightning structures via machine learning

Lightning is a fascinating yet insufficiently understood phenomenon. Very high frequency (VHF, 30–300 MHz) observations of lightning yield an ever-growing amount of data. In particular, LOFAR (LOw Frequency ARray) can reach meter and nanosecond precision with up to a million radio source locations per second. This lightning data is extremely complex, as a single lightning flash can contain hundreds of lightning channels and a myriad of different phenomena. However, so far this process has been mostly analyzed by-eye, which is very time-consuming. Thus, this increase in complexity of VHF lightning data calls for the application of machine learning algorithms. To identify structures from numerous spatio-temporal points in a high dimensional space, we designed an analysis pipeline combining a t-distributed stochastic neighbor embedding (t-SNE) algorithm and a clustering algorithm. We show that this combination allows for distinguishing correlated structures in an unsupervised approach. This novel method is a powerful tool to search vast multidimensional data sets for unique structures.

New mechanisms for forming multiple hotspots in radio jets

ABSTRACTHotspots of radio galaxies are regions of shock-driven particle acceleration. Multiple hotspots have long been identified as potential indicators of jet movement or precession. Two frequent explanations describe a secondary hotspot as either the location of a prior jet termination point or a deflected backflow-driven shock: the so-called dentist’s drill and splatter-spot models. We created high-resolution simulations of precessing jets with a range of parameters. In addition to the existing mechanisms, our results show three additional mechanisms for multiple hotspot formation: (1) the splitting of a large terminal hotspot into passive and active components; (2) jet stream splitting resulting in two active hotspots; and (3) dynamic multiple hotspot complexes that form as a result of jet termination in a turbulent cocoon, linked here to rapid precession. We show that these distinct types of multiple hotspots are difficult to differentiate in synthetic radio maps, particularly hotspot complexes that can easily be mistaken for the jet itself. We discuss the implication for hypothesized binary supermassive black hole systems where jet precession is a key component of the morphology, and show a selection of potential precession candidates found using the Low-Frequency Array Two-metre Sky Survey Data Release 2.