Cassiopeia A, Cygnus A, Taurus A, and Virgo A at ultra-low radio frequencies
F. de Gasperin, J. Vink, J.P. McKean, A. Asgekar, M.J. Bentum, R. Blaauw, A. Bonafede, M. Bruggen, F. Breitling, W.N. Brouw, H.R. Butcher, B. Ciardi, V. Cuciti, M. de Vos, S. Duscha, J. Eisloffel, D. Engels, R.A. Fallows, T.M.O. Franzen, M.A. Garrett, A.W. Gunst, J. Horandel, G. Heald, L.V.E. Koopmans, A. Krankowski, P. Maat, G. Mann, M. Mevius, G. Miley, A. Nelles, M.J. Norden, A.R. Offringa, E. Orru, H. Paas, M. Pandey-Pommier, R. Pizzo, W. Reich, A. Rowlinson, D.J. Schwarz, A. Shulevski, O. Smirnov, M. Soida, M. Tagger, M.C. Toribio, A. van Ardenne, A.J. van der Horst, M.P. van Haarlem, R. J. van Weeren, C. Vocks, O. Wucknitz, P. Zarka, P. Zucca
AAstronomy & Astrophysics manuscript no. LBAateam c (cid:13)
ESO 2020February 25, 2020
Cassiopeia A, Cygnus A, Taurus A, and Virgo Aat ultra-low radio frequencies
F. de Gasperin J. Vink , , J.P. McKean , A. Asgekar , M.J. Bentum , R. Blaauw A. Bonafede , , M. Br¨uggen F. Breitling W.N. Brouw , H.R. Butcher B. Ciardi V. Cuciti M. de Vos S. Duscha J. Eisl¨o ff el D. Engels R.A. Fallows T.M.O. Franzen M.A. Garrett , A.W. Gunst J. H¨orandel , , G. Heald L.V.E. Koopmans A.Krankowski P. Maat G. Mann M. Mevius G. Miley A. Nelles , M.J. Norden A.R. O ff ringa , E. Orr´u H.Paas M. Pandey-Pommier , R. Pizzo W. Reich A. Rowlinson , D.J. Schwarz A. Shulevski O. Smirnov , M. Soida M. Tagger M.C. Toribio A. van Ardenne A.J. van der Horst , M.P. van Haarlem R. J. van Weeren C. Vocks O. Wucknitz P. Zarka P. Zucca (A ffi liations can be found after the references) Received ... / Accepted ...
Abstract
Context.
The four persistent radio sources in the northern sky with the highest flux density at metre wavelengths are Cassiopeia A, Cygnus A,Taurus A, and Virgo A; collectively they are called the A-team. Their flux densities at ultra-low frequencies ( <
100 MHz) can reach severalthousands of janskys, and they often contaminate observations of the low-frequency sky by interfering with image processing. Furthermore, thesesources are foreground objects for all-sky observations hampering the study of faint signals, such as the cosmological 21 cm line from the epochof reionisation.
Aims.
We aim to produce robust models for the surface brightness emission as a function of frequency for the A-team sources at ultra-lowfrequencies. These models are needed for the calibration and imaging of wide-area surveys of the sky with low-frequency interferometers. Thisrequires obtaining images at an angular resolution better than 15 (cid:48)(cid:48) with a high dynamic range and good image fidelity.
Methods.
We observed the A-team with the Low Frequency Array (LOFAR) at frequencies between 30 MHz and 77 MHz using the Low BandAntenna (LBA) system. We reduced the datasets and obtained an image for each A-team source.
Results.
The paper presents the best models to date for the sources Cassiopeia A, Cygnus A, Taurus A, and Virgo A between 30 MHz and 77 MHz.We were able to obtain the aimed resolution and dynamic range in all cases. Owing to its compactness and complexity, observations with the longbaselines of the International LOFAR Telescope will be required to improve the source model for Cygnus A further.
Key words.
Radio continuum: general – Techniques: interferometric – Supernovae: individual: Cassiopeia A – Galaxies: individual: Cygnus A –Supernovae: individual: Taurus A – Galaxies: individual: Virgo A
1. Introduction
Historically, the radio sources with the highest flux density inthe sky were named after the constellation in which they werefound followed by a letter starting with “A”. They were thengrouped in the so-called A-team . In this work, we focus onthe four persistent radio sources with the highest flux den-sity (below GHz frequency) in the northern sky: Cassiopeia A,Cygnus A, Taurus A, and Virgo A (see Table 1), which areall very di ff erent in nature. Cassiopeia A is a prototypical su-pernova remnant, while a large fraction of the radio emissionfrom Taurus A is powered by the central Crab pulsar and itsassociated shocked pulsar wind; Cygnus A is a very powerfulFanaro ff -Riley (FR) type-II radio galaxy at the centre of a mas-sive, merging galaxy cluster (Markevitch et al. 2002); and VirgoA is an amorphous radio source powered by a black hole withmass M BH = (6 . ± . × M (cid:12) (Event Horizon TelescopeCollaboration et al. 2019) at the centre of a small, nearby galaxycluster. Cygnus A is at the distance of 232 Mpc ( z = . L . (cid:39) . × W Hz − (assum-ing a flat Λ CDM cosmology with H =
71 km s − Mpc − and Ω M = . This is also a famous TV series from the 1980s. galaxies. Virgo A is at the centre of the closest galaxy cluster atthe distance of 16.5 Mpc ( z = . L . (cid:39) . × W Hz − . Cassiopeia A and Taurus A areGalactic sources at the distance of 3.4 kpc (Reed et al. 1995) and ∼ ff ect of the A-team in the data.A possibility is to predict the time–frequency regions of the ob-servation where one side lobe of the beam crosses one of theA-team sources (Shimwell et al. 2017). If the predicted contam-inating flux density is above a certain threshold, then that partof the data is discarded. This procedure is usually fast and it hasbeen proven to be robust for observations with the High BandAntenna (HBA) system of the Low Frequency Array (LOFAR;van Haarlem et al. 2013), but it requires an accurate modellingof the primary beam side lobes. In the case of HBA observa-tions, the amount of data loss is typically 5 to 10 %. Anothertechnique that has been developed is the so-called demix (Van a r X i v : . [ a s t r o - ph . H E ] F e b . de Gasperin et al.: A-team at ultra-low radio frequencies der Tol 2009). This technique requires high-frequency and timeresolution data and it is conceptually similar to the “peeling”process (Noordam 2004). The dataset is phase-shifted towardsthe direction of the A-team source and is averaged down in timeand frequency to smear all other sources. A calibration is thenperformed against a pre-existing model. Then, the model visibil-ities of the A-team source, corrupted with the solutions just ob-tained, is subtracted from the full-resolution dataset. When theA-team source is very close to a given target field ( < ◦ ), a stan-dard peeling (Noordam 2004) or a multi-directional solve (e.g.Kazemi et al. 2011; Smirnov & Tasse 2015) are viable solutions.In all the aforementioned cases, a good model for the surfacebrightness distribution of the A-team source is extremely valu-able and, in many cases, essential.Recently, the detection of a broad absorption profile, cen-tred at 78 ± z ∼
30 to 15) and possi-bly even into the Dark Ages ( z ∼
200 to 30). The largest com-plication in these experiments is the subtraction of the strongastrophysical and instrumental foregrounds. The Galactic planeand the A-team sources are major contributors to the astrophys-ical foreground and a good model of these sources is paramountfor their removal. Low-frequency, wide-field surveys have alsorenewed the interest of the broader scientific community (e.g.Shimwell et al. 2016; Intema et al. 2017; Hurley-Walker et al.2017). For example, tracing cosmic rays (electrons) to the lowestenergies provides insight into their ine ffi cient acceleration mech-anisms (e.g. de Gasperin et al. 2017). Low-frequency radio sur-veys can detect active galaxies in their late stages (e.g. Brienzaet al. 2016), radio haloes and radio cluster shocks in mergingclusters (e.g. Hoang et al. 2017), and also the highest redshift ra-dio sources (e.g. Saxena et al. 2018). Again, our ability to carryout such surveys is limited by the extent that we can remove thecontaminating emission from the bright A-team sources.With the aim of determining accurate models for the sur-face brightness distribution of the A-team sources at low radiofrequencies, we have carried out an imaging campaign with theLow Band Antenna (LBA) system of LOFAR, using the Dutcharray. In Sec. 2, we describe the observations of the four sourcesand in Sec. 3 we discuss the data reduction. In Sec. 4, we de-scribe the models that we are releasing to the astronomical com-munity, and in Sec. 5 we briefly describe the main scientific out-come of this work.
2. Observations
The LOFAR (van Haarlem et al. 2013) radio interferometer iscapable of observing at very low frequencies (10 to 250 MHz).Each LOFAR station is composed of two sets of antennas: theLBA, which operates between 10 and 90 MHz, and the HBA,which operates between 110 and 250 MHz. Currently, LOFAR iscomposed of 24 core stations (CS; maximum baseline: ∼ ∼
120 km), and 14international stations (IS; maximum baseline: ∼ ∼ ff ringa et al. 2010),the visibility datasets were averaged down to 10 s and 1 chan-nel per SB. Some of the SBs were removed after inspection ofthe data if RFI was visible. We carried out the observations inLBA OUTER mode, which uses only the outer half dipoles ofeach 96-antenna LBA field. This reduces the field of view to afull width at half maximum (FWHM) of ∼
3. Data reduction
The data reduction follows roughly the strategy that has beenoutlined by de Gasperin et al. (2019), which was designed forpoint-like calibrator sources using the LBA system of LOFAR.All of our targets can also be considered bright calibrators, butthe main di ff erence is the complexity of their structure on ∼ (cid:48)(cid:48) to arcminute scales. To compensate for this, we had to rely ona large number of self-calibration cycles to reconstruct the mor-phology of the sources. The initial model for the self-calibration was taken from the lit-erature or from archival data. Each model was rescaled to matchthe expected integrated flux density for a given frequency. Theintegrated flux density is modelled following Perley & Butler(2017),log( S [Jy]) = a + a log( ν [GHz]) + a [log( ν [GHz])] + ..., (1)where ν is the frequency and A i a set of coe ffi cients. At these lowfrequencies Faraday depolarisation is very e ffi cient, therefore allmodels are unpolarised. We now explain how we build up theinitial model for each target.Cassiopeia A: As a starting model, we used the LOFAR LBAimage produced by Oonk et al. (2017). The model wasrescaled to match the Perley & Butler (2017) flux densityusing the parameters they derived as follows: a = . a = − . a = − . a = − . (cid:48)(cid:48) . The model has a higherresolution than what is needed to start our self-calibrationprocess, and the source is known to undergo a rapid turnoverin the bright hotspots below 100 MHz (McKean et al. 2016).This makes the extrapolation of the HBA model just anapproximation of the expected emission at LBA frequencies.The flux scale for Cygnus A has been estimated follow-ing Perley & Butler (2017). The best fit is a polynomialfunction of the fifth order with parameters a = . a = − . a = − . a = . a = .
2. de Gasperin et al.: A-team at ultra-low radio frequenciesSource name Coordinates Flux density (Jy) Size a RA (J2000) DEC (J2000) @ 50 MHz @ 150 MHz @ 1.4 GHz (arcmin)Cassiopeia A (3C 461) 23 h m s + ◦ (cid:48) (cid:48)(cid:48) h m s + ◦ (cid:48) (cid:48)(cid:48) h m s + ◦ (cid:48) (cid:48)(cid:48) h m s + ◦ (cid:48) (cid:48)(cid:48) a Largest angular size as measured from LOFAR images at 50 MHz.
Table 1: The A-team: coordinates, flux densities, and sizes
Source Obs. date Obs. length Number of SBs Resolution a Rms noise Dynamic(h) (arcsec) (mJy beam − ) rangeCassiopeia A 26-Aug-2015 16 244 10 (cid:48)(cid:48) × (cid:48)(cid:48)
11 7700Cygnus A 04-May-2015 11 242 9 (cid:48)(cid:48) × (cid:48)(cid:48)
40 18000Taurus A 03-Mar-2016 9 244 11 (cid:48)(cid:48) × (cid:48)(cid:48) (cid:48)(cid:48) × (cid:48)(cid:48) a At the mean frequency of 54 MHz.
Table 2: Observations and image parametersprovides ∼
10% of the total flux density, or about 300 Jy at50 MHz. We therefore started the self-calibration processassuming a point source model at the field centre and usingonly the shortest baselines (so that the entire source wasseen as a point source) or the longest baselines (so thatthe extended component was resolved out and only theemission from the pulsar dominated the visibilities). In thisway, we could obtain initial phase solutions for the LBAstations, which we then used to reconstruct the extendedcomponent of the source and continue the self-calibrationprocess. The final model, with all of the components, wasrescaled to match the Perley & Butler (2017) scale using theparameters a = . a = − . a = − . a = − . a = a = − . a = − . The calibration procedure for all targets is described followingthe radio interferometer measurement equation (RIME) formal-ism (Hamaker et al. 1996; Smirnov 2011). First, all of the datapoints on baselines shorter than 30 λ were flagged to remove anyextended structure associated with the Galactic plane. We alsoretained only the part of the observations where the targets wereabove 15 ◦ elevation. Then, a first round of (direction indepen-dent) calibration was performed. Initially, for each SB we solvedfor a diagonal and a rotational matrix simultaneously, so that theFaraday rotation e ff ect is channelled into the rotational matrix,while all other e ff ects remain in the diagonal matrix. The latterwas then used to compare the XX and YY solutions (the twodiagonal elements of the matrix) and to extract from the phasesthe di ff erential delay between the two polarisations. This e ff ectwas then applied together with the element beam model of theLOFAR LBA (van Haarlem et al. 2013). The data were then con-verted into a circular polarisation basis. In this basis, the e ff ect ofFaraday rotation can be described by a phase-only diagonal ma-trix with an opposite sign on the two circular polarisations. Wesolved per SB for a diagonal matrix and for each time step we fit the ∝ ν − Faraday rotation e ff ect on the di ff erence betweenthe two diagonal elements RR and LL. The dataset was thenconverted back to linear polarisation and corrected for Faradayrotation. Finally, a last diagonal matrix solve was performed athigh frequency and time resolution to correct for ionospheric de-lay, clock errors, and the bandpass amplitude. These correctionswere then applied and the dataset was ready for imaging anddeconvolution. The imaging procedure for each self-calibration iteration wassimilar for all four targets. We used
WSclean (O ff ringa et al.2014) to perform the deconvolution. We weighted the visibilitydata using a Briggs (1995) weighting of − − . − . ff erent large and smallscales of our targets. In all cases, we used multi-scale Clean witha large number of truncated Gaussian components, with scalesup to the source extent. During imaging, the datasets were di-vided into 61 frequency blocks and imaged separately. All 61images were combined to search for the peak emission to sub-tract during minor cycles. When the location of the clean com-ponent was determined, the brightness for that pixel was foundfor each image and a fourth order polynomial function was fittedthrough those measurements. These “smooth” components werethen added to the model. The final images are shown in Fig. 1.The resolution of Cygnus A is higher than for the other sourcesto trace the more complex and compact structure for the source.However, the increase weighting of the data from the isolatedLOFAR remote stations has an e ff ect on the rms noise that, inthis case, is four or more times higher than for the other sources.We did not perform any primary beam correction because, giventhe total extent of the sources, the average primary beam e ff ect,even at the edges of our largest source, Virgo A, was always neg-ligible ( < θ res < (cid:48)(cid:48) ).
4. Models
With this paper we provide the highest resolution models of thefour A-team sources Cygnus A, Cassiopeia A, Taurus A, and
3. de Gasperin et al.: A-team at ultra-low radio frequencies
Figure 1: Images of Cassiopeia A, Cygnus A, Taurus A, and Virgo A at a frequency of 50 MHz (using a bandwidth 30 to 77 MHz).Sources are scaled to show the correct apparent size ratio. The rms noise and resolution of each image are given in Table 2.
Name Type Ra Dec I SpectralIndex Ref.Frequency MajorAxis MinorAxis(Jy) (Hz) (arcsec) (arcsec)s0c0 POINT 05:34:32.65 21.57.16.2 0.141 [-0.018, 0.066, 1.504, -0.762] 55369567 – –s1c1 GAUSSIAN 05:34:23.88 22.03.22.1 1.473 [-0.945, 1.228, 1.427, -12.222] 55369567 70.644 70.644
Table 3: Two example lines from the clean component list files. The “Orientation” column (not shown) is always set at 0 ◦ .Virgo A at ultra-low radio frequencies. The models are givenin the on-line material in two di ff erent formats that are compat-ible with WSclean (O ff ringa et al. 2014). The first is a set ofmodel FITS files including the clean components at 61 di ff er-ent frequencies, equally divided in the frequency range from 30MHz to 77 MHz. The second is a text file including a list ofclean components; the associated spectral shape is described bya seventh order polynomial function for Cygnus A, CassiopeiaA, and Taurus A, and by a fifth order polynomial function forVirgo A (see Table 3). Each clean component is one line of thefile . Some aspects to note: the type of clean component can onlybe “POINT” (for point-like components) and “GAUSSIAN” forextended components. In the second case, the MajorAxis andMinorAxis are saved to represent the FWHM of the component. The data format is explained in detail at https://sourceforge.net/p/wsclean/wiki/ComponentList/ . The I column represents the flux density in Jy at the referencefrequency. The SpectralIndex column shows the coe ffi cients ofthe polynomial function when normalised to the reference fre-quency. The polynomial function is given by S ν = I + C ( ν/ν − + C ( ν/ν − + ..., (2)where I is the Stokes total intensity value, ν is the refer-ence frequency, and C , C , ... are the coe ffi cients saved in theSpectralIndex column. The − I be the correct value at the refer-ence frequency. Currently, all Gaussian clean components arecircular, that is, the MajorAxis and MinorAxis are the same.We also provide a low-resolution model in text-file format ob-tained by re-imaging the data at 45 (cid:48)(cid:48) resolution. These modelshave fewer clean components and can be e ffi ciently used in ar-rays with a more compact configurations.
4. de Gasperin et al.: A-team at ultra-low radio frequencies
With these models the A-team sources can also be used ascalibrators for ultra-low-frequency observations. However, if thesources are strongly resolved, then the flux density on the longestbaselines might not be enough. In these cases, fainter but morecompact sources such as 3c 196, 3c 380, or 2c 295 are preferred.
5. Discussion and conclusions
We obtained data for the four radio sources with highest fluxdensity in the northern sky using the LOFAR LBA system(Dutch array). We release these high-fidelity, high-resolutionmodels of these sources in the frequency range 30 to 77 MHz. Adetailed analysis of each source is beyond the scope of this pa-per, and will be carried out in separate individual publications foreach object. Nonetheless, in this section, we report an overviewof our findings.Cassiopeia A: LOFAR LBA data for Cassiopeia A, a ∼
330 yrold supernova remnant, has been analysed recently by Ariaset al. (2018). However, we note that the data and reductionmethods presented in this work are new. The most strikingfeature of Cassiopeia A at low radio frequencies is the ef-fect of internal free-free absorption from cold ( ∼
100 K;Arias et al. 2018; Oonk et al. 2017), unshocked supernovaejecta material. As a result, the central region of CassiopeiaA (interior to the bright shell) is less bright than in the gi-gahertz band. The presence of such internal absorption wasfirst noted by Kassim et al. (1995), and further investigatedby Delaney et al. (2014) with images down to 74 MHz.The overall flux density within a beam centred onCassiopeia A is always a ff ected by free-free absorption byrelatively cool free electrons between us and the source, aswell as internal absorption in the central region. As a conse-quence, for a given beam, the flux density can be describedas (Arias et al. 2018) S ν = S (cid:32) νν (cid:33) − α (cid:2) f + (1 − f ) e − τ ν, int (cid:3) e − τ ν, ISM , (3)where f , the flux fraction, comes from the unobscured part ofthe shell, and (1 − f ) the covering fraction (i.e. the back sideof the supernova-remnant shell); τ ν, int is the optical depthdue to free-free absorption from the unshocked ejecta, and τ ν, ISM is the free-free absorption due to the free electrons be-tween us and Cassiopeia A. The free-free absorption scalesas τ ν ∝ ν − T − / n e (cid:80) i n i , which shows that the internal massestimate is dependent on the temperature of the free elec-trons and the composition and degree of ionisation of the un-shocked supernova ejecta. Moreover, clumping of the ejectamay seriously a ff ect the relation between the internal, un-shocked mass, and the internal free-free absorption.The e ff ect of the internal absorption is that the central part ofCassiopeia A is less bright below 100 MHz than at high fre-quencies. Once τ ν, int (cid:29) S ν ∝ ν α , but with a flux reduced by (1 − f ) com-pared to the extrapolation from high frequencies, except thatthe external free-free absorption causes an overall reductionof the flux density. As a result, the maximum flux density ofCassiopeia A occurs around 20 MHz (Baars et al. 1977).The multi-channel LOFAR LBA data provide a more preciselocalisation of the e ff ect and infer an unshocked ejecta massof (3 ± .
5) M (cid:12) . We plan to update this result using the newcalibration and data reduction procedures presented in thiswork (Arias et al. in prep.). ° ' ' Right Ascension (J2000) D e c li n a t i o n ( J ) D APlume 50 kpc0 20 40 60 80 100Surface brightness (Jy/b)
Figure 2: LOFAR HBA image of Cygnus A (central frequencyof 146 MHz). The resulting rms map noise is 43 mJy beam − andthe FWHM beam size is 3.8 (cid:48)(cid:48) × (cid:48)(cid:48) (from McKean et al. 2016).Contours from the LBA map at − .
3, 10, 30, 100, 300 Jy beam − are superimposed. The circles represent the regions where weextracted the LBA in-band spectral index.Cygnus A: This is the first work examining this source bothat this frequency and resolution. We report the work ofLazio et al. (2006), which reached a similar resolution ofour LOFAR images at 74 MHz. The most striking featurein the new LOFAR LBA image of Cygnus A is the absenceof hotspots that are seen at higher frequencies McKeanet al. (2016). After convolving all of the LBA images to thesame resolution, we attempted the extraction of the in-bandspectral index α (with s ν ∝ ν α ) in three regions with a sizethat is equivalent to the convolved beam. We positionedtwo regions close to the east and west edges of the source,and they gave spectral index values of α = . ± .
05 and α = . ± .
05, respectively, for hotspots A and D (definedin McKean et al. 2016, see Fig. 2) between 30 MHz and 77MHz. The third region was positioned at the source centre,close to the southern plume, which gave a spectral index of α = − . ± .
05 between 30 and 77 MHz. We note thatbeam dilution almost certainly biases the results towardssteeper values in the case of the hotspots. To calculatethe uncertainties, a conservative flux error of 10% in eachmeasurement was added to the error estimated from the mapnoise.As discussed by McKean et al. (2016), the spectral energydistribution in the hotspot regions A and D peaks between140 and 160 MHz, and then starts decreasing towards lowerfrequencies. The two main models proposed to explainthe turnover are as follows: (i) free-free absorption orsynchrotron self-absorption processes within the hotspots oralong the line of sight (Kassim 1989) and / or (ii) a cut-o ff in the electron energy distribution at low energies (Carilliet al. 1991). From the LOFAR HBA data, in combinationwith higher frequency data from the VLA, McKean et al.(2016) found that the strong turnover in the spectral indexruled out a cut-o ff in the electron energy distribution atlow energies, and the limit in the spectral index providedby the new LOFAR LBA imaging is consistent with thatconclusion. McKean et al. (2016) also found that the
5. de Gasperin et al.: A-team at ultra-low radio frequencies synchrotron self-absorption model was also unlikely, giventhe very large magnetic field strengths needed to cause sucha turnover ( B ≈ B ≈ µ G). The free-free modelwas also challenging to explain the data since the impliedelectron densities ( n e ≈ − ) should result in a significantde-polarisation of the emission seen at GHz frequencies,which is not the case. Only low-frequency observations ofthe hotspots in the LOFAR LBA can distinguish betweendi ff erent models. However, our resolution is not su ffi cient toconstrain such models, and therefore observations with theinternational baselines, to achieve the arcsecond resolutionneeded, are planned. Nevertheless, our inverted spectrum forthe hotspot regions confirms that some form of absorptionmust be at least partially responsible for the observedturnover.The plume extending from the central part of the sourcetowards the south is also visible and the in-band spectralindex is in line with what is measured at higher frequenciesby McKean et al. (2016). Finally, we report the detectionof di ff use emission, with an extension ∼ (cid:48) towards thenorth-east of Cygnus A. The classification of this source isdi ffi cult because of the dynamic range of the image. It couldbe a background radio galaxy or some emission related tothe intra-cluster medium dynamics.Taurus A: This radio source is associated with the CrabNebula (see Hester 2008; B¨uhler & Blandford 2014, fora review), which is the supernova remnant of SN 1054(e.g. Stephenson & Green 2002). However, most of theelectromagnetic radiation is coming from the pulsar windnebula (PWN) that is powered by the Crab Pulsar (PSRB0531 + E = . × erg s − . Taurus A is uniquein that synchrotron emission is dominating the spectrumfrom low radio frequencies up to ∼
100 MeV ( ∼ Hz).Synchrotron emission even dominates the optical and UVband (Miller 1978), but the optical also reveals strong lineemission from the filaments of ionised supernova ejecta. Theradio synchrotron spectrum has a spectral index of α ≈ − . α ≈ − . α ≈ − . B ≈
100 to200 µ G and an age of ∼
950 yr, but the steep X-ray spectrumis not well understood. One suggestion is that there are twopopulations of relativistic electron / positron: one responsi-ble for the radio emission and another for the UV / X-rayemission (e.g. Meyer et al. 2010). The radio populationcould be the result of a past injection of particles ;(i.e. “relicelectrons / positrons” Atoyan & Aharonian 1996), or twodi ff erent electron / positron acceleration mechanisms, suchas reconnection for the low-energy population associatedwith the radio emission, and di ff usive shock accelerationfor the higher energy particles responsible for X-rays. Tocomplicate things, the injection of fresh electron / positronsseems to occur on the inside of the bright optical / X-raytorus (Hester 2008, and reference therein), but some X-rayemission is also associated with two jets that are roughlyorientated south-east to north-west. The radio emission from Taurus A in the LOFAR LBA, asseen in Fig. 1, is elongated, in the south-east to north-westdirection. This is similar to higher frequency maps (e.g.Bietenholz & Nugent 2015, for a 5.5 GHz VLA map).However, what is at least qualitatively di ff erent betweenthe low- and high-frequency radio maps is that at lowfrequencies there seems to be relatively less emission fromthe torus region and more emission associated with the”jets”, suggesting that these two components have di ff erentspectral indices, which could potentially shed new lightinto whether the PWN consists of a single electron / positronpopulation with a complicated energy distribution or two oreven more populations with di ff erent physical origins. Wecaution, however, that this needs to be further investigatedas the dynamical range and the uv-coverage of the LOFARLBA and 5.5 GHz VLA maps are not similar, requiring careto assess quantitative di ff erences. We will come back tothis issue in a future paper dedicated to the LOFAR LBAobservation of Taurus A presented in this work.Finally, we note that the centre of Taurus A is dominatedby the emission from the steep spectrum of pulsar with anin-band spectral index of α = − . ± .
05, in line withprevious measurements (Bridle 1970).Virgo A: This is the most extended of the A-team sources,reaching an apparent scale of about 15 (cid:48) . Virgo A is the ra-dio emission associated with the active galaxy M 87 andis famous for hosting one of the best-studied supermassiveblack holes (recently imaged by Event Horizon TelescopeCollaboration et al. 2019). The central cocoon, which atthese frequencies accounts for just ∼
30% of the total sourceflux density, hosts the well-known one-sided jet and morpho-logically resembles an FR II radio galaxy. However, Virgo Aemission extends well beyond the central cocoon and the ma-jority of the flux density comes from a relatively low-surfacebrightness envelope filled with filamentary structures. In thisregion, clear connection between the radio and the X-rayemission shows one of the best examples of active galac-tic nucleii feedback in action, where cold gas is uplifted bybuoyantly rising bubbles towards the outskirts of the galaxypotential well (Forman et al. 2007). The external boundariesof the source appear well confined even at ultra-low frequen-cies; this was already observed at higher frequencies (Owenet al. 2000; de Gasperin et al. 2012). The resolution of thesenew maps will enable the first detailed spectral study of thesource envelope and of the embedded filamentary structures.This analysis will be part of a future publication.
Acknowledgements.
The Leiden LOFAR team gratefully acknowledgesupport from the European Research Council under the European UnionsSeventh Framework Programme (FP / / ERC Advanced GrantNEWCLUSTERS-321271.AB acknowledges financial support from the Italian Minister for Researchand Education (MIUR), project FARE SMS, code R16RMPN87T and from theERC-Stg DRANOEL, no 714245.LOFAR, the Low Frequency Array designed and constructed by ASTRON,has facilities in several countries, that are owned by various parties (each withtheir own funding sources), and that are collectively operated by the InternationalLOFAR Telescope (ILT) foundation under a joint scientific policy. This researchhas made use of NASA’s Astrophysics Data System.
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