# Discovery of Perun (G329.9-0.5): a new, young, Galactic SNR

Zachary J. Smeaton, Miroslav D. Filipović, Sanja Lazarević, Rami Z. E.

Alsaberi, Adeel Ahmad, Miguel Araya, Brianna D. Ball, Cristobal Bordiu, Carla S. Buemi, Filomena Bufano, et al.

► To cite this version:

Zachary J. Smeaton, Miroslav D. Filipović, Sanja Lazarević, Rami Z. E. Alsaberi, Adeel Ahmad, et al. Discovery of Perun (G329.9-0.5): a new, young, Galactic SNR. Monthly Notices of the Royal Astronomical Society, 2024, 534, pp.2918-2937. 10.1093/mnras/stae2237. insu-04833923

HAL Id: insu-04833923

https://insu.hal.science/insu-04833923v1

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# Discovery of Perun (G329.9–0.5): a new, young, Galactic SNR

Zachary J. Smeaton<sup>1,★</sup> Miroslav D. Filipović<sup>1,★</sup> Sanja Lazarević<sup>1,2,3</sup> Rami Z. E. Alsaberi<sup>1</sup>,<sup>1</sup>
Adeel Ahmad<sup>1</sup> Miguel Araya<sup>1,4</sup> Brianna D. Ball<sup>1,5</sup> Cristobal Bordiu<sup>1,6</sup> Carla S. Buemi<sup>1,6</sup>,
Filomena Bufano<sup>1,6</sup> Shi Dai<sup>1,2</sup> Frank Haberl<sup>1,7</sup> Andrew M. Hopkins<sup>1,8</sup> Adriano Ingallinera<sup>1,6</sup>,
Thomas Jarrett<sup>1,9,†</sup> Bärbel S. Koribalski<sup>1,2</sup> Roland Kothes<sup>10</sup> Renée C. Kraan-Korteweg<sup>1,9</sup>,
Denis Leahy<sup>11</sup> Peter Lundqvist<sup>1,12</sup> Chandreyee Maitra<sup>1,7</sup> Pierrick Martin<sup>1,13</sup> Jeffrey L. Payne<sup>1,1</sup>,
Gavin Rowell<sup>1,14</sup> Hidetoshi Sano<sup>1,15,16</sup> Manami Sasaki<sup>1,17</sup> Roberto Soria<sup>1,18,19</sup> Nadia Steyn<sup>1,20</sup>,
Grazia Umana<sup>1,6</sup> Dejan Urošević<sup>1,21</sup> Velibor Velović<sup>1,1</sup> Tessa Vernstrom<sup>1,20,22</sup> Branislav Vukotić<sup>1,3</sup>,
and Jennifer West<sup>1,10</sup>

*Affiliations are listed at the end of the paper*

Accepted 2024 September 24. Received 2024 September 22; in original form 2024 April 12

## ABSTRACT

We present the discovery of possibly the youngest Galactic supernova remnant (SNR) with associated pulsar-wind nebula (PWN), which we name Perun (G329.9–0.5). Perun was serendipitously discovered in the Australian Square Kilometre Array Pathfinder–Evolutionary Map of the Universe survey at 943 MHz, and subsequent follow-up observations were conducted with the Australia Telescope Compact Array observatory at 5500 and 9000 MHz. We combine these with additional radio observations from the MeerKAT, Molonglo Observatory Synthesis Telescope, and Murchison Widefield Array telescopes, infrared (IR) observations from the *Spitzer* *Space Telescope*, and X-ray observations from the *Chandra* X-ray observatory to perform a multifrequency analysis. The radio morphology shows a small angular size shell ($D = 70$ arcsec) with a luminous, central PWN. We measure a total spectral index of $\alpha = -0.49 \pm 0.05$, which should be typical for a young, composite SNR. Crucial evidence for Perun’s SNR classification comes from the detection of linear fractional polarization at radio frequencies of $\sim 7$ per cent–10 per cent with both radial and tangential orientations, similar to the young SNR G1.9+0.3. We use data from the Southern Galactic Plane Survey to perform an H I analysis and estimate a favoured distance range of 6–9 kpc, and thus a favoured age range of $\sim 70–500$ yr. We find no high-energy emission in *Fermi*-Large Area Telescope data. We detect Perun’s outer shell in $24 \ \mu$m indicating the possible presence of [O IV] and [Fe III] emission, also typical for young SNRs. Overall, these observations and analysis confirm Perun as a young, Galactic SNR with a prominent PWN.

**Key words:** supernovae: general - supernovae: individual (G329.9–0.5) – ISM: supernova remnants – radio continuum: general.

## 1 INTRODUCTION

Supernova (SN) explosions are one of the most violent and spectacular events in the universe. They occur when massive stars reach the end of their lives and are responsible for most of the chemical enrichment in galaxies (Lee et al. 2009; Mernier et al. 2020). An SN explosion belongs to one of two broad categories. Thermonuclear (TN, Type Ia) SN occur in binary systems when a white dwarf star accretes enough matter from its companion to cause an SN which destroys the progenitor star (Hillebrandt & Niemeyer 2000; Filipović & Tothill 2021). Core-collapse (CC) SN occur when a star with an initial mass, $M > 8 M_\odot$, fuses enough heavy material in its core that the core collapses into a compact source, either a neutron

star, pulsar, or black hole, triggering an explosion (Janka et al. 2007; Filipović & Tothill 2021). The SN shockwave forms an expanding structure known as an supernova remnant (SNR). Observations of SNRs allow us to create models of the initial SN event, and improve our knowledge of star formation (Xu, Wang & Miller 2011) and galaxy evolution (Conroy, White & Gunn 2009).

There are several different types of SNRs that can exhibit drastically different morphologies. The simplest case is a shell SNR that consists of a shockwave expanding out into the ambient medium (Ferrand 2020). This shockwave sweeps up the surrounding material and forms an expanding shell of enriched material that can emit light for up to $\sim 10^4–10^5$ yr (Sarbadhicary et al. 2016) before finally dissipating.

Another common type of SNR morphology are filled-centre or plerion SNRs, and these are characterized by the main emission being from a central pulsar-wind nebula (PWN). These PWNs are formed by the birth of a neutron star during the SN event, and so are typically produced during CC SN. The young, energetic neutron star can

<footnote>* E-mail: 19594271@student.westernsydney.edu.au (ZJS); M.Filipovic@westernsydney.edu.au (MDF)</footnote>

<footnote>† Deceased on 3 July 2024</footnote>
generate a surrounding nebula, composed of ultrarelativistic particles from the neutron star's strong stellar winds (Gaensler 2001). Other SNR types exhibit both of these morphologies; mixed-morphology SNRs have non-thermal synchrotron radio shells with central thermal X-ray emission (Dubner & Giacani 2015), and composite SNRs have a shell and a central non-thermal PWN. (Gaensler 2001; Dubner & Giacani 2015).

Despite their importance to astronomical research, Galactic SNRs are under-represented in the current catalogues. Present generation star formation models predict a population of up to 1500 Galactic SNRs (Ranasinghe & Leahy 2022; Ball et al. 2023), however there are currently only ~300–380 (Ferrand & Safi-Harb 2012; Green 2019, 2022) discovered. This deficit is generally attributed to observational difficulties (Dokara et al. 2021). Discoveries of new, young SNRs are expected to be quite rare due to their small, compact size (Ranasinghe, Leahy & Stil 2021), while older SNRs are difficult to identify as they are very dim and often fall under a telescope's sensitivity limit. SNRs also commonly form in very dense and complex star-forming regions, which makes them difficult to distinguish from other astronomical objects (Brogan et al. 2006; Anderson et al. 2017).

Of the currently known Galactic SNRs, fewer than 10 are believed to be under 1000 yr old (Misanovic, Cram & Green 2002; Green 2022). This means that young SNRs represent an even smaller percentage of an already underrepresented population. Therefore, models of early SNR evolution are incomplete, and we are constantly searching for new samples (Misanovic et al. 2002; Anderson et al. 2017; Ranasinghe et al. 2021). Most SNRs have been discovered with radio telescopes, as we are able to easily identify the characteristic radio synchrotron emission (Brogan et al. 2006; Anderson et al. 2017; Filipović & Tothill 2021).

With the newest generation of radio telescopes, we can survey the radio sky with better resolution and sensitivity than previously possible. Some such surveys are the Evolutionary Map of the Universe (EMU) survey (Norris et al. 2011, 2021) conducted using the Australian Square Kilometre Array Pathfinder (ASKAP) telescope and more recently the SARAO MeerKAT Galactic Plane Survey (SMGPS; Goedhart et al. 2024) conducted using the MeerKAT telescope. These new, improved observations have been used to perform detailed analyses of known SNRs and have resulted in the discovery of several new Galactic, intergalactic, and Magellanic Cloud (MC) SNRs (Filipović et al. 2022b, 2023; Ball et al. 2023; Bozzetto et al. 2023; Lazarević et al. 2024; Smeaton et al. 2024).

While the population of young SNRs is rather small, several members have been studied in detail. The youngest SNR ever discovered, with an age of 37 yr, is SN1987A located in a neighbouring dwarf galaxy, the Large Magellanic Cloud (LMC). This CC SN explosion was observed on 1987 February 23 in optical (Marsden 1987) and ultraviolet (Kirshner et al. 1987) frequencies, as well as neutrino observations which define the exact time of CC (Hirata et al. 1987). These observations of the initial SN explosion combined with ongoing observations of its subsequent evolution (Manchester et al. 2002; Dewey et al. 2012; Zanardo et al. 2018) and prior observations of the progenitor star (Blanco 1987; Gilmozzi et al. 1987) give us unique insight into the early evolution of SNRs.

Dedicated studies have been conducted on several young SNRs within our Local Group of Galaxies, including the youngest SN1987A (Cendes et al. 2018), as well as G1.9+0.3 (Borkowski et al. 2013; Enokiya et al. 2023) with an age of ~120–150 yr (De Horta et al. 2008; Pavlović 2017; Luken et al. 2020). Other young Galactic SNRs of note include Cassiopeia A (Cas A) at 344 yr old

(Thorstensen, Fesen & van den Bergh 2001; Fesen et al. 2006), Kepler at 420 yr old (De Angelis & Broccio 2021), Tycho at 452 yr old (Falkner 2021), the Crab Nebula (SN1054) at 970 yr old (Hester 2008), and SN1006 at 1018 yr old (Stephenson 2010).

In this paper, we contribute to this young SNR census by presenting the discovery of a new, young, Galactic CC SNR G329.9–0.5. We name this SNR Perun,<fnref n="1" /> and present our analysis indicating a favoured age range of ~70–500 yr old, making it potentially the youngest known Galactic SNR.

Perun has been previously observed as an infrared (IR) shell-like source in a catalogue by Mizuno et al. (2010). Following this, it is classified as a possible planetary nebulae (PNe), MN38, in catalogues by Gvaramadze, Kniazev & Fabrika (2010) and Chornay & Walton (2020). It also appears as a possible PNe, PNG 329.8–00.4, in the University of Hong Kong/Australian Astronomical Observatory/Strasbourg Observatory H-alpha Planetary Nebula (HASH PN) catalogue (Parker, Bojičić & Frew 2016).

The data used in these previous analyses consisted of the Multi-band Imaging Photometer for Spitzer (MIPS) 24 µm data discussed in Section 2.2.1 and Molonglo Observatory Synthesis Telescope (MOST) radio data discussed in Section 2.1.4. Due to MOST's modest resolution, Perun appears as a point source and its radio morphology cannot be properly resolved. Therefore, the previous classifications were based almost solely on Perun's IR morphology. For these reasons, we contest that Perun was previously misclassified. In this paper, we demonstrate that the observed non-thermal radio emission and radio linear polarization clearly show a young SNR/PWN system.

In Section 2, we describe our observations and data analysis methods. In Section 3, we summarize our observational results and outline Perun's physical characteristics. These results are then used in Section 4 to estimate properties without direct measurements, such as intrinsic size, age, and distance. We analyse Perun's observed polarization and map the intrinsic magnetic field in Section 3.6, followed by the summary and conclusion in Section 5.

## 2 OBSERVATIONS AND DATA

We serendipitously discovered Perun in the ASKAP-EMU pilot survey and then followed up with dedicated Australia Telescope Compact Array (ATCA) observations. We also include radio observations taken with the MeerKAT telescope, MOST, and Murchison Widefield Array (MWA), as well as IR observations from the Spitzer Space Telescope to characterize Perun's multifrequency properties. These observations are summarized in Table 1. We also utilize H1 data from Southern Galactic Plane Survey (SGPS; McClure-Griffiths et al. 2005) to probe the surrounding interstellar environment.

We searched for any signature of Perun in X-rays (ROSAT, Chandra, and XMM-Newton), gamma-rays [Fermi and High Energy Stereoscopic System (H.E.S.S.)] and optical [Sloan Digital Sky Survey (SDSS) and SuperCOSMOS H-alpha Survey (SHS)].

The only X-ray emission we find comes from two previous Chandra observations, however Perun's location is significantly off-axis from the target pointings. While it appears X-ray emission is present, we are unable to properly resolve any of Perun's X-ray morphology (see Section 3.5). No corresponding emission was found in the H.E.S.S. source catalogue (H.E.S.S. Collaboration 2018) or

<footnote n="1">¹Perun was the supreme god of the Slavic pantheon. He was the god of thunder and lightning, and the earliest historical references date back to the 6th century CE (https://www.thoughtco.com/perun-slavic-god-4781747).</footnote>
<table><caption>**Table 1.** Details of the main observations used in this work. Note that ATCA observations consist of observations of two array configurations observed at different times, EW352 (shown by †) and 6C (shown by ‡). The Parkes/ATCA entry represents the SGPS which consists of combined Parkes and ATCA observations. For the units used, MHz and mJy beam⁻¹ apply to radio observations, while µm and MJy sr⁻¹ apply only to *Spitzer*.</caption><thead><tr><th>Telescope</th><th>Date</th><th>Frequency/wavelength<br>(MHz/µm)</th><th>Beam size<br>(arcsec × arcsec)</th><th>RMS<br>(mJy beam<sup>-1</sup>/<br>MJy sr<sup>-1</sup>)</th></tr></thead><tbody><tr><td rowspan="4">MWA</td><td rowspan="4">2013 Aug 9–2014 June 18</td><td>88</td><td>343×322</td><td>&gt;150</td></tr><tr><td>118</td><td>263×244</td><td>&gt;70</td></tr><tr><td>155</td><td>200×180</td><td>&gt;50</td></tr><tr><td>200</td><td>165×150</td><td>&gt;20</td></tr><tr><td>MOST</td><td>1999 Mar 17–2001 Dec 24</td><td>843</td><td>45×45</td><td>0.3</td></tr><tr><td>ASKAP</td><td>2021 Nov 6</td><td>943.5</td><td>12×11</td><td>0.025</td></tr><tr><td>MeerKAT</td><td>2018 Aug 26</td><td>886–1681</td><td>8×8</td><td>0.020</td></tr><tr><td rowspan="2">Parkes/ATCA</td><td>2000 Jan 28–Aug 4</td><td>1428</td><td>100×100</td><td>0.030</td></tr><tr><td>2022 Nov 6–7†</td><td>5500</td><td>4×4</td><td>0.020</td></tr><tr><td rowspan="3">ATCA</td><td>2023 Jan 4–5‡</td><td></td><td></td><td></td></tr><tr><td>2022 Nov 6–7†</td><td>9000</td><td>4×4</td><td>0.040</td></tr><tr><td>2023 Jan 4–5‡</td><td></td><td></td><td></td></tr><tr><td rowspan="3">Spitzer</td><td>2006 April 13</td><td>24</td><td>6×6</td><td>15</td></tr><tr><td>2004 April 1</td><td>8</td><td>2×2</td><td>30</td></tr><tr><td>2004 April 1</td><td>3.6</td><td>1.7×1.7</td><td>15</td></tr></tbody></table>

the *Fermi* source catalogue (Ballet et al. 2023). The only detected gamma-ray emission from this area is from three observed Gamma-ray bursts (GRBs) as documented in the *Fermi* GBM Burst Catalogue (Gruber et al. 2014; Von Kienlin et al. 2014, 2020; Bhat et al. 2016), however, there is no indication that they are related to Perun. No optical emission is observed in the SDSS or SHS.

## 2.1 Radio observations

### 2.1.1 ASKAP

The ASKAP observations were conducted in 2021 November as part of the EMU Pilot survey (AS101) using a complete array of 36 antennas. ASKAP’s modern phased array feed technology gives it an instantaneous field of view of ~30 deg<fnref n="2" /> allowing wide-field imaging surveys (Johnston et al. 2008; Hotan et al. 2021). Perun is located in tile EMU 1554–55 corresponding with scheduling block SB33284, and the image was taken at 943.5 MHz with a bandwidth of 288 MHz. The quoted beam size and root mean squared (RMS, see Table 1) are measured from this specific image tile. The resulting image was processed using the standard ASKAP pipeline, ASKAPSoft, as detailed by Guzman et al. (2019). The final image of Perun shown in Fig. 2(a) has a restoring beam of 12 × 11 arcsec<fnref n="2" /> and a sensitivity of 25 µJy beam⁻¹.

### 2.1.2 ATCA

The ATCA follow-up observations were taken at central frequencies of 5500 and 9000 MHz, each with a bandwidth of 2048 MHz. The observations were conducted under the ATCA project code C3523 (PI: S. Lazarević). The observations were taken using standard ATCA arrays 6C and EW352 and details of these configurations can be found on the Australia Telescope National Facility (ATNF) website.<fnref n="2" /> The telescope was calibrated on standard ATCA calibrators,

PKS 1600–48 for gain calibration and PKS 1934–638 for bandpass calibration. Details of these calibrators can be found in the ATCA calibrator database.<fnref n="3" /> The ATCA observations contain polarization data for all four Stokes parameters, which is used for the polarimetric analysis in Section 3.6.

The data were reduced using the Multichannel Image Reconstruction, Image Analysis and Display (MIRIAD; Sault, Teuben & Wright 1995) software from the ATNF using the standard pipeline for multifrequency data. A Briggs weighting robust value of −0.5 was used during imaging (Briggs 1995). This value was chosen as it emphasizes sidelobe reduction, thus preventing substantial smearing from the bright PWN and allowing a clear view of the dimmer shell. The higher RMS noise, while notable, does not significantly impact our signal-to-noise ratio, and this robust value allows us to differentiate between the PWN and outer shell. Both the 5500 and 9000 MHz images are smoothed to a restoring beam of 4 × 4 arcsec<fnref n="2" /> to reduce oversampling and the Stokes I images are shown in Figs 2(c) and (d).

### 2.1.3 MeerKAT

The MeerKAT data were obtained from the SMGPS (Goedhart et al. 2024) whose observations were conducted on 2018 August 26. The observations were taken in the MeerKAT L band between the frequencies of 886–1681 MHz. They contain both the broadband image centred at 1359.7 MHz as well as 14 separate channels with varying bandwidths between ~43–74 MHz. Twelve of these channels have been used for analysis as two contain corrupted data. The survey’s angular resolution is 8 × 8 arcsec<fnref n="2" /> with a broadband RMS sensitivity of 10–20 µJy beam⁻¹. The data were reduced and the mosaicked broad-band image was created following the process described in Goedhart et al. (2024).

<footnote n="2">²https://www.narrabri.atnf.csiro.au/operations/array_configurations/configurations.html</footnote>

<footnote n="3">³https://www.narrabri.atnf.csiro.au/calibrators/calibrator_database.html</footnote>
<figure><img src="image_3.png" /><figcaption>**Figure 1.** Composite RGB image where the total intensity map of Perun, observed by ASKAP at $v = 944$ MHz, is in red and blue and *Spitzer* 24 µm IR map is in green. To present the structure of Perun, we used different colour maps and adjusted contrast levels. Red and blue display the same ASKAP image using a linear colour scale, with red showing only the brightest emission to emphasize the PWN. A logarithmic scale is applied to the *Spitzer* image to enhance the IR emission. For all quantitative information refer to Table 1.</figcaption></figure>

### 2.1.4 MOST

Perun has also been observed in the Sydney University Molonglo Sky Survey (SUMSS), a Galactic plane radio survey conducted using the MOST observatory at a central frequency of 843 MHz. Perun appears in the second epoch Molonglo Galactic Plane Survey (MGPS) compact source catalogue (Murphy et al. 2007). The data consist of a mosaicked image of nine separate SUMSS observations taken between 1999 March and 2001 December. The image is convolved to a $45 \times 45$ arcsec$^2$ restoring beam and we measure an average local RMS noise level of ~300 µJy beam$^{-1}$. The flux value used in our analysis is that measured from the MGPS compact source catalogue (see Table 2).

### 2.1.5 MWA

We obtained archival radio images of Perun from the MWA taken during the GaLactic Extragalactic All-sky MWA survey (Wayth et al. 2015; Hurley-Walker et al. 2017, 2019a). We obtained four separate frequency images over the range of 72–231 MHz taken between 2013 August and 2014 June, centred at frequencies of 88, 118, 155, and 200 MHz. The restoring beam size and measured RMS noise levels vary between these images (see Table 1; Hurley-Walker et al. 2019b).

### 2.1.6 SGPS

We have obtained archival HI from the SGPS (McClure-Griffiths et al. 2005; Haverkorn et al. 2006), a large-scale radio survey of the Galactic plane conducted between 1996 and 2004. The survey combined data from two separate surveys, a lower resolution (15 arcmin) survey taken with the Parkes 64 m radio telescope using the 21 cm Multibeam Receiver, and a higher resolution (2 arcmin) survey taken with ATCA, to map the H1 spectral line from the Galactic plane (see McClure-Griffiths et al. (2005) for more information on this combination). The survey achieved a resolution of ~1.6 K for the H1 data cubes and these data are used in the analysis in Section 3.3.

## 2.2 IR observations

### 2.2.1 Spitzer

The IR data consist of mosaicked images from the *Spitzer Space Telescope* (Rieke et al. 2004) at wavelengths of 3.6, 8.0, and 24 µm and resolutions of 1.7, 2.0, and 6.0 arcsec, respectively. The 3.6 and 8.0 µm data were taken using the Infrared Array Camera (IRAC) instrument, and the 24 µm data come from the MIPS instrument. The
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Radio images of Galactic SNR Perun (G329.9−0.5). All images show the corresponding beam (resolution) in the bottom left corner and have linearly scaled colour bars. (a) ASKAP EMU image at 944 MHz. The image has a resolution of 12×11 arcsec² and a sensitivity (RMS) of 25 µJy beam⁻¹. (b) MeerKAT image at 1360 MHz. The image has a resolution of 8×8 arcsec² and a sensitivity (RMS) of 20 µJy beam⁻¹. (c) ATCA image at 5500 MHz. The image has a resolution of 4×4 arcsec² and a sensitivity (RMS) of 20 µJy beam⁻¹. (d) ATCA image at 9000 MHz. The image has a resolution of 4×4 arcsec² and a sensitivity (RMS) of 40 µJy beam⁻¹.</figcaption></figure>

images were downloaded from the *Spitzer* Data Archive,<fnref n="4" /> where they
were created following the standard reduction pipelines as outlined in
the respective instruments handbooks.<fnref n="5" />,<fnref n="6" /> A combined colour image
of these wavelengths is shown in Fig. 3, where red shows 24 µm,
green shows 8.0 µm, and blue shows 3.6 µm.

## 2.3 Gamma-ray observations

### 2.3.1 Fermi-LAT observations

The *Fermi* Large Area Telescope (LAT) is a converter/tracker
detecting photons with energies from ~20 MeV to >1 TeV and
surveying the entire sky since 2008 (Atwood et al. 2009). We

obtained Pass 8 data collected from 2008 August 4 (mission elapsed
time, MET, 239557417) to 2023 December 19 (MET 724674862)
in the energy range 0.2–500 GeV. We analysed the data with FER-
MITOOLS version 2.2.0 through the FERMIPY package version 1.1.6
using the response functions P8R3_SOURCE_V3. We selected good
quality front and back-converted events in the SOURCE class with
the options evclass = 128, evtype = 3, DATA QUAL > 0
inside a region of interest (RoI) with a radius of 15° from the
location of Perun, and having zenith angles lower than 90° to avoid
events from Earth’s limb. We binned the data with a spatial scale
of 0.05 pixel⁻¹ and 10 bins in energy for exposure calculation. We
modelled the region including sources from the latest incremental
version of the Fermi-LAT Fourth Source Catalog (4FGL-DR4;
Abdollahi et al. 2020; Ballet et al. 2023) located within 20° of the
RoI centre. There are no catalogued sources at the location of Perun,
which would appear as a point source for the LAT. We applied the
maximum-likelihood technique (Mattox et al. 1996) to obtain source
parameters and source detection significance. The model included the
Galactic diffuse emission using the file gll_iem_v07.fits and
the isotropic and residual cosmic-ray background as described by

<footnote n="4">⁴https://irsa.ipac.caltech.edu/data/SPITZER/docs/spitzerdataarchives/</footnote>

<footnote n="5">⁵https://irsa.ipac.caltech.edu/data/SPITZER/docs/irac/
iracinstrumenthandbook/</footnote>

<footnote n="6">⁶https://irsa.ipac.caltech.edu/data/SPITZER/docs/mips/
mipsinstrumenthandbook/</footnote>
<table><caption>**Table 2.** Measured radio flux densities of Perun and its components. Total and PWN flux density are measured directly and shell flux density is calculated as the difference. All radio images (excluding MWA and MOST) have been convolved to the resolution of 12 × 11 arcsec² before the flux density extraction. Errors are estimated as 10 per cent.</caption><thead><tr><th>Telescope</th><th>v<br>(MHz)</th><th>S<sub>total</sub><br>(mJy)</th><th>S<sub>PWN</sub><br>(mJy)</th><th>S<sub>shell</sub><br>(mJy)</th></tr></thead><tbody><tr><td rowspan="4">MWA</td><td>88</td><td>910 ± 91</td><td></td><td></td></tr><tr><td>118</td><td>760 ± 76</td><td></td><td></td></tr><tr><td>155</td><td>623 ± 62</td><td></td><td></td></tr><tr><td>200</td><td>551 ± 55</td><td></td><td></td></tr><tr><td>MOST</td><td>843</td><td>187 ± 19</td><td></td><td></td></tr><tr><td>MeerKAT</td><td>907</td><td>174 ± 17</td><td>29.5 ± 3.0</td><td>145 ± 14</td></tr><tr><td rowspan="10">ASKAP</td><td>944</td><td>161 ± 16</td><td>28.4 ± 2.8</td><td>133 ± 13</td></tr><tr><td>952</td><td>173 ± 17</td><td>29.6 ± 3.0</td><td>144 ± 14</td></tr><tr><td>997</td><td>173 ± 17</td><td>29.5 ± 3.0</td><td>144 ± 14</td></tr><tr><td>1044</td><td>169 ± 17</td><td>29.5 ± 3.0</td><td>140 ± 14</td></tr><tr><td>1093</td><td>164 ± 16</td><td>29.0 ± 2.9</td><td>135 ± 14</td></tr><tr><td>1145</td><td>160 ± 16</td><td>28.6 ± 2.9</td><td>131 ± 13</td></tr><tr><td>1318</td><td>142 ± 14</td><td>27.2 ± 2.7</td><td>115 ± 12</td></tr><tr><td>1382</td><td>142 ± 14</td><td>27.1 ± 2.7</td><td>115 ± 12</td></tr><tr><td>1450</td><td>141 ± 14</td><td>27.2 ± 2.7</td><td>114 ± 11</td></tr><tr><td rowspan="8">MeerKAT</td><td>1520</td><td>140 ± 14</td><td>27.4 ± 2.7</td><td>113 ± 11</td></tr><tr><td>1594</td><td>134 ± 13</td><td>27.0 ± 2.7</td><td>107 ± 11</td></tr><tr><td>1657</td><td>140 ± 14</td><td>28.5 ± 2.9</td><td>112 ± 11</td></tr><tr><td>4605</td><td>92.5 ± 9.3</td><td>20.3 ± 2.0</td><td>72.2 ± 7.2</td></tr><tr><td>4860</td><td>92.8 ± 9.3</td><td>20.2 ± 2.0</td><td>72.6 ± 7.3</td></tr><tr><td>5116</td><td>91.5 ± 9.2</td><td>20.2 ± 2.0</td><td>71.3 ± 7.1</td></tr><tr><td>5372</td><td>90.7 ± 9.1</td><td>20.1 ± 2.0</td><td>70.6 ± 7.1</td></tr><tr><td>5628</td><td>91.5 ± 9.2</td><td>20.2 ± 2.0</td><td>71.3 ± 7.1</td></tr><tr><td>5884</td><td>88.3 ± 8.8</td><td>20.3 ± 2.0</td><td>68.0 ± 6.8</td></tr><tr><td rowspan="10">ATCA</td><td>6140</td><td>88.8 ± 8.9</td><td>20.4 ± 2.0</td><td>68.4 ± 6.8</td></tr><tr><td>6396</td><td>89.3 ± 8.9</td><td>20.4 ± 2.0</td><td>68.9 ± 6.9</td></tr><tr><td>8104</td><td>76.2 ± 7.6</td><td>18.1 ± 1.8</td><td>58.1 ± 5.8</td></tr><tr><td>8360</td><td>75.4 ± 7.5</td><td>17.9 ± 1.8</td><td>57.5 ± 5.8</td></tr><tr><td>8616</td><td>73.3 ± 7.3</td><td>17.4 ± 1.7</td><td>55.9 ± 5.6</td></tr><tr><td>8872</td><td>72.2 ± 7.2</td><td>17.2 ± 1.7</td><td>55.0 ± 5.5</td></tr><tr><td>9128</td><td>72.2 ± 7.2</td><td>17.2 ± 1.7</td><td>55.0 ± 5.5</td></tr><tr><td>9384</td><td>79.7 ± 8.0</td><td>17.8 ± 1.8</td><td>61.9 ± 6.2</td></tr><tr><td>9640</td><td>73.8 ± 7.4</td><td>17.1 ± 1.7</td><td>56.7 ± 5.7</td></tr><tr><td>9896</td><td>78.4 ± 7.8</td><td>17.0 ± 1.7</td><td>61.4 ± 6.1</td></tr><tr><td>α</td><td></td><td>-0.49 ± 0.05</td><td>-0.23 ± 0.02</td><td>-0.39 ± 0.04</td></tr></tbody></table>

iso_P8R3_SOURCE_V3_v1.txt.<fnref n="7" /> Energy dispersion correction was not applied to the isotropic component as recommended by the LAT team.<fnref n="8" /> We left free the spectral normalizations of the sources within 5° of the RoI centre as well as the normalizations and spectral indices of the sources within 3° of the centre. After the fit, we added new point sources at locations in the RoI having a significance greater than 4σ to improve the background description and optimized their spectral parameters assuming a power law as the differential spectrum. At lower energies (≈ 5 GeV), the difference between data and model maps shows negative residuals in the region of Perun, indicating issues with the Galactic diffuse emission model. We repeated the procedure with events having energies in the energy range 5–500 GeV and set a 95 per cent-confidence level upper

limit on the integrated energy flux from Perun of $1.9 \times 10^{-7}$ MeV cm$^{-2}$ s$^{-1}$ in this range, assuming a point source with a power-law differential spectrum and a spectral index of 2. This corresponds to an upper limit on the source luminosity of $3.7 \times 10^{31} d_{kpc}^2$ erg s$^{-1}$ (5–500 GeV), where $d_{kpc}$ is the source distance in units of kpc.

## 3 RESULTS

We determine the centre of Perun to be at coordinates RA(J2000) = 16h05m52.6s, Dec.(J2000) = -52°50m37.2s, corresponding with Galactic coordinates $l = 329°877$ and $b = -0°458$. These show that Perun is located within the Galactic plane where the longitudinal line of sight is within 30° of the Galactic centre and passes through several Galactic spiral arms. This complex positioning can cause observational difficulties, particularly at optical and IR wavelengths, due to significant extinction and reddening effects from interstellar dust along the line of sight.

Perun's shell and suggested PWN are not observed at optical wavelengths but there are several optical point sources within Perun's radius. These sources appear to have a random distribution over Perun's radius and do not spatially correlate with any of Perun's features. They were investigated using the Aladin Sky Atlas,<fnref n="9" /> (Baumann et al. 2022) and are determined to have varying distances from the available Gaia Data Release 3 (DR3) (Gaia Collaboration 2016, 2023). Thus, we conclude that these point sources are a consequence of Perun's crowded location within the Galactic plane and have no obvious correlation with Perun itself.

### 3.1 Perun's classification

Perun's observed properties resemble that of a young Galactic SNR. However, we do also consider other possible scenarios, such as Perun being a Luminous Blue Variable (LBV), PN, or Nova (super)remnant.

Two of the main criteria for SNR classification are non-thermal radio emission combined with linear polarization. This combination implies the presence of synchrotron emission, caused by the acceleration of particles to relativistic speeds within the compressed magnetic field in the shockwave (Dubner & Giacani 2015; Filipović & Tothill 2021) There are other objects that can appear morphologically similar to SNRs, such as LBVs, PNe, and H II regions, however all of these objects are known thermal emitters at radio wavelengths (Terzian 1965; Duncan & White 2002; Hajduk et al. 2018). Thus, the presence of non-thermal emission, as demonstrated in Section 3.2.2, provide evidence against these classifications, and the presence of linear polarization, Section 3.6, provides strong evidence for an SNR classification. Both non-thermal radio emission and linear polarization have been used to discover numerous SNRs (Helfand et al. 2006; Brogan et al. 2006; Green, Reeves & Murphy 2014; Ball et al. 2023)

It is also possible that Perun could be a Nova (super)remnant, such as the one around the recurrent Nova GK Persei (Anupama & Kantharia 2005; Balman 2005; Harvey et al. 2016) or the classical Nova Scorpii AD 1437 (Shara et al. 2017), which can sometimes appear morphologically similar to SNRs. In this case, Perun's outer shell would be the remains of a century-old outburst, and the central emission would be a much more recent (decade-old) outburst. This possibility could account for Perun's low X-ray emission, as shown in Section 3.5. However, deeper X-ray observations and a more accurate map of the absorbing column density across the region are

<footnote n="7">⁷https://fermi.gsfc.nasa.gov/ssc/data/access/lat/BackgroundModels.html</footnote>

<footnote n="8">⁸https://fermi.gsfc.nasa.gov/ssc/data/analysis/documentation/Pass8_edisp_usage.html</footnote>

<footnote n="9">⁹https://aladin.cds.unistra.fr/</footnote>
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Spitzer RGB image of Perun showing 24 µm shell and surrounding environment. Red is MIPS image at 24 µm, green is IRAC4 at 8.0 µm, and blue is IRAC1 at 3.6 µm. The inset shows Perun in more detail with contours from the ATCA 5500 MHz image. Contours are at levels 0.1, 0.2, 0.3, 0.4, and 0.7 mJy beam⁻¹.</figcaption></figure>

required, before we can measure Perun’s intrinsic X-ray luminosity and spectral shape. In the Nova (super)remnant scenario, the flatter radio spectral index of the central emission compared with the shell emission (Section 3.2.2) could be caused by synchrotron self-absorption or by the presence of a compact jet in the more recent outburst. As in the case of Galactic SNRs, there is also a large number of missing Galactic Novae (De et al. 2021) and their remnants, and new discoveries are crucial to fill this gap. The data at hand neither rule out nor strongly support the Nova scenario. For this work, we focus instead on the SNR scenario, which we consider the most likely overall interpretation of the multiband observations.

## 3.2 Radio-continuum properties

### 3.2.1 Radio morphology

Perun is not resolved in the low-resolution radio-continuum images from MWA and MOST. However, we can detect the inner morphology in the ATCA, ASKAP, and MeerKAT images (see Figs 1 and 2). In these images, we see a circular shell with a region of bright emission in the centre, which we identify as a PWN. This brighter emission is clearly shown in Fig. 1, where the red image has been restricted to show only the brightest PWN emission.

We fit a circular region around the shell and an elliptical region around the central PWN using the astronomical imaging software, Cube Analysis and Rendering Tool for Astronomy (CARTA; Comrie et al. 2021). We measure the shell to have an angular diameter of 70.0 arcsec (± 0.5 arcsec) and the PWN to have a semimajor axis of 11.5 arcsec and a semiminor axis of 6.6 arcsec (± 0.1 arcsec) with a position angle of 55° (relative to the Galactic latitude lines).

It is expected that a young PWN would be powered by a highly energetic pulsar at its centre. We are unable to fully resolve a central, compact source within the PWN with these observations. This is

not surprising as the bright radio emission from the ultrarelativistic pulsar wind would likely conceal the pulsar, and a dedicated pulsar search would be required to detect it.

We also compared radio observations taken at different times (Table 1) to search for any signs of shell expansion. The largest epoch difference in the higher resolution images is approximately 4.5 yr (see Table 1), between the MeerKAT and ATCA observations, and we detect no measurable size difference between these images. This is expected as the time difference is only a few years and the resolution of radio observations is such that even a rapid expansion (~15 000 km s⁻¹) would require a longer time difference to detect any expansion. We also attempted to measure a size difference between the MOST and ATCA observations, as they have an epoch difference of 22 yr. Again, we observe no measurable expansion, however, this is possibly due to the modest resolution of MOST (45 × 45 arcsec²) making such a sensitive measurement challenging.

Perun’s shell is circular but has an asymmetric brightness distribution, with areas of brighter emission in the south-western half and along the edge of the shell. This brighter emission could indicate expansion into a denser medium, such as interaction with an H1 cloud(s), as we discuss in Section 3.3. The radio emission in the shell is caused by synchrotron radiation as demonstrated by the spectral index analysed in Section 3.2.2. Ejected electrons in the shell are accelerated to relativistic speeds in the shockwave front causing this emission. Therefore, the observed radio shell represents the total size and shape of the SNR as it is mapping the forward shock. This small angular size and spherical symmetry are indicative of a young SNR, as evolutionary models show that SNRs become larger and more asymmetrical as the shockwave expands further into the ambient medium (Stafford et al. 2019). We know of only a handful of similar examples that display almost perfect symmetry, such as the young MC SNRs SN1987A (Cendes et al. 2018), J0509−6731 (Bozzetto et al. 2014; Roper et al. 2018), 1E0102−72
(Alsaberi et al. 2023), N103B (Alsaberi et al. 2019), and the young Galactic SNR G11.2–0.3 (Borkowski, Reynolds & Roberts 2016).

### 3.2.2 Spectral index

We measure the radio flux densities of Perun at all radio-continuum frequencies as listed in Table 1 to calculate the spectral index of Perun. The ATCA bandwidths of 5500 and 9000 MHz were divided into 8 sub-bands each of 256 MHz and all 12 usable channels from the MeerKAT L band were used, thus increasing the overall number of data points used to calculate the spectral index and ensure that any small scale changes are adequately measured at these frequencies.

All images (excluding those from MWA and MOST) were convolved to a common beam size (12 arcsec × 11 arcsec) before measurement to ensure consistent scaling as described in Hurley-Walker et al. (2019b, section 2.4). The MWA measurements were excluded from this convolving as they already have a much larger intrinsic beam size, and we lose significant resolution attempting to convolve the other radio images to the MWA beam.

We measured flux densities separately for the total area of Perun and for the PWN where possible. We calculate Perun’s shell flux density as the difference of these two values. Given that Perun is only somewhat larger than the radio beam sizes and our radio observations provide a well-sampled $u-v$ coverage, we estimate the errors incurred from missing short spacings to be < 5 per cent. We thus assume a total 10 per cent error as per a similar analysis shown in Filipović et al. (2022b) and the measured flux densities are shown in Table 2. These measured flux density values are then fitted to the standard power law used to represent radio spectral indices, $S \propto v^{\alpha}$, where S is the flux density, v is the frequency, and α is the spectral index.

The radio-continuum emission from a composite SNR comes from the combination of two distinct emission mechanisms. The synchrotron emission from the shell is explained by a diffusive shock acceleration (DSA) model, where electrons are accelerated to relativistic speeds by multiple crossings over the expanding shock-wave. The motion of these accelerated charged particles through the compressed ambient magnetic field generates the characteristic synchrotron emission. The energy distribution predicted by DSA theory for SNRs indicate an average value of $\alpha \sim -0.5$ for the radio spectral index (Bell 1978), and this theoretical value matches with the average value of observed SNRs (Reynolds, Gaensler & Bocchino 2012; Galvin & Filipovic 2014; Bozzetto et al. 2017; Maggi et al. 2019; Filipović & Tothill 2022).

Conversely, the PWN synchrotron emission comes from the pulsar wind of ultrarelativistic particles generated by the rapidly rotating pulsar. Due to the constant energy input from the pulsar, this electron energy distribution results in a significantly flatter spectral index, $\alpha > -0.3$ (Reynolds et al. 2012).

A recent analysis by Ranasinghe & Leahy (2023) shows an average spectral index of $\alpha = -0.41 \pm 0.03$ for Galactic composite SNRs, which is only slightly flatter than the value given by DSA theory. This difference is likely caused by the DSA theory only being applicable to the shell synchrotron emission, and so the contribution from the flatter PWN is not sufficiently accounted for in averages that predominantly consider shell-type SNRs.

Perun’s spectral index is illustrated in Fig. 4. The steep spectral index of $\alpha = -0.49 \pm 0.05$ is steeper than average for composite SNRs. Young SNRs typically have a steeper spectral index than their older counterparts, and so this is a reasonable value for a

<figure><img src="image_6.png" /><figcaption>**Figure 4.** Spectral index graph of Perun and its components, calculated using fluxes from Table 2. Top: the total spectral index. The dotted line represents the linear fit and the solid line represents the concave-up fit. Bottom: the shell and PWN spectral indices. The dotted line with the blue points (top line) represents the shell and the dashed line with the green points (bottom line) represents the PWN. Spectral index errors are calculated as 10 per cent.</figcaption></figure>

young, composite SNR. We measure a spectral index of $\alpha_{\text{shell}} = -0.39 \pm 0.04$ in Perun’s shell, somewhat flatter than the overall spectrum. This slightly flatter value can be attributed to the fact that the shell component can only be separately measured in our higher frequency images. Since the diffuse shell emission fades with increasing frequency, lower frequency measurements are essential to obtain a true measure of the index steepness. This effect is particularly important if non-linear DSA effects are at play, as these effects flatten the spectral index at higher frequencies (Urošević 2014). The PWN exhibits a flat spectral index of $\alpha_{\text{PWN}} = -0.23 \pm 0.02$, a typical value for a PWN.

We note that the data points for the total spectral index do not appear to follow the linear power law and are instead better fit with a curved (concave-up) power law, as shown in Fig. 4 (top). Such a consistent difference across the data points is unlikely to be due to inherent errors and potentially indicates a deviation from the pure DSA power law. We note that this concave-up spectral index is based on total flux densities from lower (MWA) frequencies where Perun is a point-like source, that is, we cannot resolve into the shell and PWN contribution.

This deviation could be caused by the composite nature of Perun, that is the fading shell causes the PWN to become more dominant at higher frequencies resulting in a flatter index. However, such a strong deviation could be caused by non-linear DSA emission as explained
<figure><img src="image_7.png" /><figcaption>**Figure 5.** Spectral index map of Perun. Calculated from 944 MHz ASKAP data, 5500 and 9000 MHz ATCA data, and all separate channels for the MeerKAT L-band data as listed in Table 2. The colour bar to the right is created with a linear scale and has units representing spectral index values. Contours are radio contours from ATCA 5500 MHz at 0.1, 0.2, 0.3, 0.4, and 0.7 mJy beam⁻¹.</figcaption></figure>

in Urošević (2014). This is where non-linear acceleration effects on the relativistic electrons result in a curved power-law electron energy distribution. For young SNRs, the non-linear DSA theory predicts a concave-up spectrum, as observed in Fig. 4, and this phenomenon has been observed in several other young SNRs, such as Tycho (Reynolds & Ellison 1992), Kepler (Reynolds & Ellison 1992), SN 1006 (Allen, Houck & Sturner 2008), and Cas A (Onic & Urošević 2015). The presence of such a prominent concave-up spectrum highlights the similarities with other young SNRs and provides more evidence for Perun’s young age estimate. However, none of these previously studied SNRs contain PWN and it is questionable if one can apply the same principles.

The spectral index differs between the shell and PWN, as shown in the spectral index map in Fig. 5. This spectral map was generated using the ASKAP, MeerKAT, and ATCA images only, as the higher resolution allows us to clearly differentiate between the PWN and the shell. The MeerKAT data used consists of all 12 usable channels from the L band. We observe that the PWN emission is fairly constant in the radio observations while the shell fades at higher frequencies. These observations are as expected, and support the identification of Perun as a young SNR with a prominent PWN.

One important note is that previous studies of young SNRs have shown that the flux density can increase over time, making the measurement of a spectral index using historical data potentially problematic. This phenomenon has been observed in SN1987A by Zanardo et al. (2010, 2013) and in G1.9+0.3 by Green et al. (2008); Murphy, Gaensler & Chatterjee (2008); and Luken et al. (2020). Given that there is an epoch difference between our radio observations of up to 22 yr (Table 1), we acknowledge that this effect may cause biased spectral index calculations. Because of this and combined with the inherent errors in the flux density measurements, we determine our total spectral index error to be in the order of 10 per cent.

<table><caption>**Table 3.** Perun flux densities scaled at 1 GHz and calculated radio surface brightness for different morphological sections. The 1 GHz fluxes for the total and PWN are calculated using their spectral index values given in Table 2 and the shell flux is calculated as the difference.</caption><thead><tr><th>Area</th><th>S<sub>1GHz</sub><br>(mJy)</th><th>Σ<sub>1GHz</sub><br>(W m<sup>-2</sup> Hz<sup>-1</sup> sr<sup>-1</sup> × 10<sup>-20</sup>)</th></tr></thead><tbody><tr><td>Total</td><td>197</td><td>2.2</td></tr><tr><td>PWN</td><td>29.6</td><td>5.3</td></tr><tr><td>Shell</td><td>167</td><td>2.0</td></tr></tbody></table>

### 3.2.3 Surface brightness

Using the estimated spectral indices shown in Fig. 4, we calculate Perun’s scaled flux densities at 1 GHz. We calculate the total and PWN flux densities directly using their spectral index values, and we calculate the shell flux as the difference, to ensure consistency with the previous method used. Combining these fluxes with the measured angular sizes (Section 3.2.1), we estimate the radio surface brightness of Perun using the relationship $\Sigma_{1GHz} = S_{1GHz}/\Omega$, where $\Sigma_{1GHz}$ is radio surface brightness, $S_{1GHz}$ is the scaled flux density at 1 GHz, and $\Omega$ is the angular area. Results are shown in Table 3. We use these values to estimate certain physical properties using the $\Sigma-D$ relationship for SNRs as shown in Section 4.1.

## 3.3 H I properties

In order to reveal the physical relation between the SNR and its surroundings, we analysed the archival ATCA H I data taken from SGPS which has an angular resolution of 2.2 arcmin (McClure-Griffiths et al. 2005; Haverkorn et al. 2006). We also checked the CO data taken by the NANTEN and Mopra radio telescopes (e.g. Mizuno & Fukui 2004; Cubuk et al. 2023) to search for signs of molecular cloud interaction, as has been observed in several other Galactic SNRs (Jiang et al. 2010; Slane et al. 2015; Chen et al. 2017; Zhou et al. 2024). Although the angular resolution is low compared to the apparent size of Perun, we found three possible candidates of H I clouds that are along the line of sight and that could be associated with Perun. Fig. 6 shows the velocity-integrated intensity map of H I towards Perun. Namely, we found H I in the velocity range from

(i) the H I cloud at $\sim -100 \text{ km s}^{-1}$ (Fig. 6a) which translates to a distance of $\sim 6-9 \text{ kpc}$. In Fig. 6(d), we can see a possible expanding gas motion in the $p-v$ diagram,

(ii) the clumpy H I cloud at $\sim +10 \text{ km s}^{-1}$ (Fig. 6b), which equates to a distance of $\sim 15 \text{ kpc}$, is also lying in the vicinity of Perun’s line of sight, and

(iii) the H I cloud at $\sim +30 \text{ km s}^{-1}$ (Fig. 6c), which equates to a distance of $\sim 19 \text{ kpc}$, also shows a large bubble-like distribution and Perun could be located at the edge of the bubble.

All of the above kinematic distances were calculated using the rotation curve model of Brand & Blitz (1993), which adopts the International Astronomical Union recommended values of $R_\odot = 8.5 \text{ kpc}$ and $V = 220 \text{ km s}^{-1}$ (Kerr & Lynden-Bell 1986).

As H I gas and clouds are concentrated in the spiral arms, it is plausible that these distances correspond with the spiral arm distances at this Galactic longitude. This is further evidenced by these values closely matching those of Table 4. Since these areas of denser H I represent areas of higher gas concentration, and thus star formation, it is plausible that CC SNRs are more likely to form in these regions. This is because the massive progenitor star is not able to travel far from its birth place due to its short life span.
<figure><img src="image_8.png" /><figcaption>**Figure 6.** (a) Intensity distribution of H I around Perun obtained from SGPS (McClure-Griffiths et al. 2005). The integration velocity ranges from (a) −103.1 to −93.2 km s⁻¹, (b) 5.8 to 13.2 km s⁻¹, and (c) 19.8 to 39.6 km s⁻¹. The superposed circle indicates the position of Perun. (d) Position–velocity (p–v) diagrams of H I at l = 329.84 to 329.91 and velocity range from −120.0 to +45.0 km s⁻¹. The dashed curve in the p–v diagram indicates the most likely candidate of an H I expanding shell.</figcaption></figure>
<table><caption>**Table 4.** The average distances to spiral arms shown along the Galactic longitude vector *l* = 329.9 (column 2). Perun's measured angular diameter is *D* = 70 arcsec and we convert it to a linear diameter in column 3. Note that there are two values given for the Norma spiral arm as Perun's Galactic longitude passes through this arm tangentially. The values given are where the longitude vector enters the arm at ~6 kpc and where it leaves the arm at ~11 kpc.</caption><thead><tr><th>Milky Way<br>Spiral arm</th><th>Average<br>distance<br>(kpc)</th><th>Perun<br>diameter<br>(pc)</th></tr></thead><tbody><tr><td>Sagittarius (inner)</td><td>1.5</td><td>0.5</td></tr><tr><td>Scutum-Centarus (inner)</td><td>3.5</td><td>1.2</td></tr><tr><td>Norma Arm</td><td>6–11</td><td>2.0–3.7</td></tr><tr><td>Scutum-Centarus (outer)</td><td>15</td><td>5.1</td></tr><tr><td>Sagittarius (outer)</td><td>19</td><td>6.5</td></tr></tbody></table>

Association with surrounding H I clouds is not required for SNRs, however there are several observed cases of such an association, such as in SNRs (Reynoso et al. 2006; Fukui et al. 2012, 2017; Fukuda et al. 2014; Sano et al. 2019). Furthermore, Bozzetto et al. (2017) found that the LMC SNR population traces the observed LMC H I peaks, and this is particularly pronounced for CC SNRs. Perun's radio emission also indicates expansion into a slightly denser ambient medium to the southwest, as shown by the brighter southwestern shell in Fig. 2. This can be explained if Perun is located on the boundary of a denser H I region. Due to this, we therefore conclude that an H I association is plausible for Perun and deem these distances more favourable.

Figs 6(a) and 6(c) show that velocities of ~−100 and ~+30 km s⁻¹ correspond with environments where the denser H I regions, indicated by the yellow to red colours in the H I diagrams, are located southwest of Perun.

In the *p*–*v* diagram (Fig. 6d), we also note the presence of a possible H I cavity located at Perun's Galactic latitude, indicated by the dashed semicircle. This cavity, combined with the possible expanding gas motion we see, could indicate an expanding H I shell. Such a cavity could be caused by the initial SN expanding shockwaves or strong stellar winds from the progenitor star creating a bubble of rarefied density. SNR expansion into such cavities has been observed in several SNRs (e.g. Kes 75; Su et al. 2009, CTB 87; Liu et al. 2018, RCW 86; Sano et al. 2017, and N103B; Sano et al. 2018). Expansion into a cavity of such rarefied space would also explain Perun's spherical shape.

The possible H I cavity approximately matches Perun's size, shape, and position. We note that the cavity is slightly offset to the north and is larger than Perun. This discrepancy may be caused by the modest resolution of the SGPS data. That is, the observed cavity is approximately equal to the SGPS beam size of 2.2 arcmin, and so any finer detail is not able to be resolved. It is also possible that this cavity was caused by the strong stellar winds of the progenitor, and that the shock front has not yet expanded enough to reach the edge of the cavity. This is supported by Perun's symmetrical shape indicating that there has not yet been any substantial interaction with dense surrounding medium. If this is the case, it is not unexpected that the H I cavity would not spatially correlate with Perun exactly, however its presence indicates expanding gas motion.

We also attempted an H I absorption emission analysis towards Perun, however we are unable to see any absorption features. Since Perun's angular size (70 ± 0.5 arcsec) is smaller than the SGPS beam size (2.2 arcmin), it is possible that any absorption features are being diluted below the noise level and are not able to be resolved. To test

this possibility, we attempted to measure H I absorption for several other nearby sources, and found that we only observe absorption features for sources with peak ASKAP flux greater than 300 mJy beam⁻¹. Since Perun has a peak ASKAP flux of ~37 mJy beam⁻¹, it is not surprising that we see no absorption features. Therefore, we cannot use H I absorption to constrain the distance without higher resolution H I data, and instead conclude that the observed H I cavity is the strongest evidence available to provide a distance estimate.

We deem the velocity range of −103.1 to −93.2 km s⁻¹ to be more favourable, corresponding to a distance of ~6–9 kpc. However, we cannot completely rule out the other possible velocities due to the modest angular resolution of this data.

## 3.4 IR properties

We detect 24 µm emission from Perun's outer shell (Figs 1 and 3) but no observable IR emission from the PWN. Perun's shell emits exclusively at the 24 µm wavelength, and no observable emission is detected at 8.0 and 3.6 µm. We also searched the 4.5 and 5.8 µm IRAC bands, and the 70 µm band from the Photodetector Array Camera and Spectrometer (PACS; Poglitsch et al. 2010) instrument on the Herschel Space Observatory<fnref n="10" /> (Pilbratt et al. 2010), however no emission is observed.

We measure the shell by fitting a circular region in CARTA, as described in Section 3.2.1, and find a diameter *D* = 70.0 arcsec, matching with the radio morphology. The IR emission is brightest in the south-western half of the shell, corresponding with the brightest radio emission.

We also observe several IR point sources at 3.6 and 8.0 µm as shown in Fig. 3. Similar to the optical point sources discussed in Section 3, these were investigated using Aladin with similar results. They do not spatially correlate with Perun's radio or 24 µm morphology, and most of them have Gaia DR3 entries, so we determine that they have variable distances and are likely not related to each other or to Perun.

The 24 µm observed shell may be emission from interstellar dust caught up in Perun's expanding shockwave and heated to IR emission temperatures (Lakićević et al. 2015). However, this type of thermal dust emission is typically observable at 8.0 and 70 µm, even with high levels of extinction. Specifically, the 70 µm wavelength is particularly adept at tracking cold dust in SNRs (Seok, Koo & Onaka 2013; Lakićević et al. 2015), and so the lack of emission strongly indicates that the IR ring is not a dust feature. Therefore, it is more plausible that this 24 µm emission is caused by strong emission lines from the shocked material, most likely the [O IV] line at 26 µm and the [Fe III] line at 23 µm as observed in the young Galactic SNR Cassiopeia A (Isensee et al. 2012). The wavelength of these shocked emission lines falls within the Spitzer MIPS bandwidth and their presence is characteristic of young SNR ejecta. Both of these emission mechanisms would cause the IR emission to map the forward shock expansion, thus explaining why the IR emission is observed in the same areas as the radio synchrotron emission.

Another possible explanation for the IR shell is that it is leftover from some form of pre-SN eruption event. Kotak & Vink (2006) and Smith et al. (2011) proposed that LBV stars are immediate predecessors to SN events and there are recorded cases of LBV-like eruptions prior to an SN event (Pastorello et al. 2007). This scenario would result in the dusty IR shell being formed prior to the SN

<footnote n="10">¹⁰The PACS data are available from the Herschel Science Archive https://archives.esac.esa.int/hsa/whsa/</footnote>
event and indicate that the subsequent SNR is still expanding within the shell. This is a tentative hypothetical scenario, however the SN event occurring within a dusty shell would provide an explanation for why the SN was not observed. If Perun is still expanding within the rarefied interior of the shell, this would also help to explain Perun's remarkable symmetry and indicate a very young age.

Finally, we note that the presence of the IR shell at 24 µm suggests relatively high densities and therefore one could expect substantial thermal X-ray emission from Perun's shell.

## 3.5 X-ray properties

We searched for X-ray observations of Perun in the ROSAT, XMM-Newton, and Chandra archives. While no ROSAT or XMM-Newton observations were found, two Chandra observations covered the source position. One observation (obsID 20285) was too short (3.5 ks) to yield a detection, although it can still give us a useful upper limit. The other observation (obsID 7422 from 2007 May 4) with an exposure time of ~20 ks, was analysed in more detail and provides marginal but intriguing results. We analysed the archival data with the Chandra Interactive Analysis of Observations (CIAO) software, version 4.15 (Fruscione et al. 2006), with Calibration Database version 4.10.4. We created new level-2 event files for observation 7422, with the CIAO task chandra_repro. We then filtered the event file with the task dmcopy, creating images in different energy bands.

In obsID 7422, Perun is located on the S3 chip of an observation centred on the Advanced CCD Imaging Spectrometer (ACIS-I) instrument; thus, it is ≈17 arcmin from the aim point. As a result, the point spread function is very spread out and distorted. At that distance, the 70 per cent enclosed energy radius for a point-like source is ~20 arcsec. Although we cannot resolve the morphology of the X-ray emission, or determine whether there is a central point-like source, we do detect a significant excess of counts above the background level, in a region centred at Galactic longitude $b = 329.8804$ and Galactic latitude $l = -0.4544$. The excess is statistically significant at the 90 per cent confidence level in the 0.5–3.0 keV energy band, while it gets swamped by diffuse background emission at higher energies. The size of the region with excess X-ray counts (~20 arcsec radius) is consistent with the point spread function of a point source, but we cannot rule out a slightly extended region. Excess net counts are statistically significant also when we consider a source extraction region coincident with the whole radio extent of the shell (radius of ~35 arcsec, Section 3.2.1), but we find that ~90 per cent of the net source counts are associated with the smaller region mentioned above.

Fig. 7 shows a multiband RGB view of Perun: red maps the ATCA 5500 MHz emission, green the Spitzer 24 µm emission, and blue the Chandra 0.5–3.0 keV emission. The Chandra emission was binned to obtain a pixel size of 1.1 arcsec × 1.1 arcsec and smoothed with a Gaussian kernel size of 7 pixels. The brightest patch of X-ray emission corresponds to the dimmest IR emission inside the radio-bright outer shell, rather than the central radio source. However, the low X-ray resolution makes this a very tentative anticorrelation. Dedicated on-axis X-ray observations with sufficient exposure times are required to determine if this is a true anticorrelation and to properly resolve Perun's X-ray morphology.

With only ~ (45±20) net X-ray counts from the brighter X-ray patch, multiparameter spectral fitting is impossible. The intrinsic X-ray luminosity strongly depends on the assumed value of the absorbing column density. The line-of-sight hydrogen column density in the direction of Perun is $N_H \approx 1.75 \times 10^{22} \text{ cm}^{-2}$ (Kalberla et al. 2005; HI4PI Collaboration 2016). If Perun is located only half-

<figure><img src="image_9.png" /><figcaption>**Figure 7.** RGB image of Perun showing multifrequency emission. Red is the ATCA 5500 MHz emission, green is the Spitzer 24 µm emission, and blue is the smoothed Chandra 0.5–3 keV emission.</figcaption></figure>

way across the Galactic disc (Section 3.3), this value provides an upper limit to the line-of-sight absorption; on the other hand, there may be additional (intrinsic) absorption inside the shell. Column densities much lower than $10^{22} \text{ cm}^{-2}$ are unlikely, given the small number of net X-ray counts below 0.7 keV; values higher than a few times $10^{22} \text{ cm}^{-2}$ are also unlikely, given the detection of net emission around 1 keV. We applied the CIAO task srcflux with a range of column densities between $10^{22}$ and $2 \times 10^{22} \text{ cm}^{-2}$, and two alternative choices of spectral models: a power-law with photon index between 1.5 and 2.5, and an optically thin thermal plasma model (apec) with temperatures between 0.5 and 1.0 keV. We estimate an observed flux $f_{(0.5-3)} \approx (2 \pm 1) \times 10^{-14} \text{ erg cm}^{-2} \text{ s}^{-1}$, and an absorption-corrected flux of $f_{(0.5-3),0} \approx (2.0^{+1.5}_{-1.0}) \times 10^{-13} \text{ erg cm}^{-2} \text{ s}^{-1}$. At the lowest plausible distance of 6 kpc, this corresponds to an unabsorbed luminosity $L_{0.5-3} \approx 10^{33} \text{ erg s}^{-1}$ (uncertainty of a factor of 2); at the highest distance of 19 kpc, $L_{0.5-3} \approx 10^{34} \text{ erg s}^{-1}$. As a further independent check of these values, we also estimated the upper limit to the X-ray flux in the snapshot obsID 20285, which has no significant detection; the upper limit to the net counts, and hence to the observed flux, was obtained from the low-count statistics of Kraft, Burrows & Nousek (1991). We estimate an observed flux $f_{(0.5-3)} \lesssim 4 \times 10^{-14} \text{ erg cm}^{-2} \text{ s}^{-1}$ (90 per cent confidence limit), consistent with the marginal detection in obsID 20285.

The intrinsic X-ray luminosities estimated above are at least an order of magnitude fainter than young SNRs of comparable size in the MCs (Maggi et al. 2016, 2019; Ou et al. 2018; Leahy & Filipović 2022; Zangrandi et al. 2024), while they are consistent with the luminosity of shocked gas around Novae, for example, GK Persei (Balman 2005). However, the predicted luminosities are strongly dependent on the density of the interstellar medium. If the ambient density is $n_H \lesssim 0.01 \text{ cm}^{-3}$, the low X-ray luminosity would be consistent with an SNR (Ou et al. 2018). What is clear, at least, is that we do not see evidence of a bright X-ray pulsar in the centre of Perun.

## 3.6 Polarization

Linear polarization is expected for SNRs and is an indicator of the emission mechanism. The presence of polarization in both the shell and PWN is caused by non-thermal emission from high-energy
electrons, indicative of the characteristic synchrotron emission of SNRs (Dubner & Giacani 2015; Filipović & Tothill 2021). The polarization angle can change as it travels through the interstellar medium before reaching us, and by measuring the radio emission at different frequencies we can estimate this rotation effect, known as rotation measure (Ferrière, West & Jaffe 2021). This rotation measure then allows us to remove this rotation effect, and estimate the source's intrinsic polarization, and thus deduce its intrinsic magnetic field orientation.

The rotation measure can be used to infer properties about the SNR's environment where polarized regions typically rotate more while travelling through denser mediums, and so we can use this measure to infer properties such as the surrounding environment, as well as probe the interstellar medium along the line of sight. The magnetic field of an SNR can give indications about its age. Typically, younger SNRs have a radial magnetic field and they become more tangential and disordered as the SNR ages (Reynolds et al. 2012). This property can be confused, however, as interaction with surrounding inhomogeneous medium can cause Rayleigh-Taylor instabilities that cause the magnetic field to become more disordered.

### 3.6.1 Linear polarization

Polarization data for Perun was obtained during the ATCA observations. We observe linear polarization for Perun in Stokes Q and U images, however no circular polarization is observed. The polarization images were created using each 2048 MHz bandwidth, centred at values of 5500 and 9000 MHz, respectively. The images were convolved to a common beam size of 8×8 arcsec² for a better analysis, due to the lower signal-to-noise ratio of the Stokes Q and U images. The final fractional polarization image was created by combining the Stokes Q, U, and I images at 5500 MHz using the MIRIAD task IMPOL. We measured an average linear polarization of 7.3 ± 2.7 per cent at 5500 MHz and 10.3 ± 2.7 per cent at 9000 MHz. The peak polarizations are measured as 21.2 ± 7.8 per cent at 5500 MHz and 42.7 ± 11.8 per cent at 9000 MHz. We created a fractional polarization map at 5500 MHz (Fig. 8). We see the greatest fractional polarization at 5500 MHz occurs in the north-eastern shell section.

We see greater linear polarization at 9000 MHz than in 5500 MHz, which may indicate depolarization effects at 5500 MHz. Given that Perun is located within the Galactic plane and possibly at a significant distance, these depolarization effects may be caused by the light's travel through areas of inhomogeneous interstellar medium.

### 3.6.2 Rotation measure

We are able to create a rotation measure map by splitting the 5500 MHz bandwidth into four smaller sub-bands, centred at 4732, 5244, 5756, and 6268 MHz. By measuring the polarization angle difference between the differing frequencies, we can estimate a measure of the rotation using the MIRIAD task IMRM, and generate a rotation measure map (Fig. 9, left).

From Fig. 9 (left), we see that Perun consists of two distinct areas of different rotation measures. We observe the north-eastern shell to have an average value of -390 rad m⁻² and the PWN and south-western shell area to have an average value of -860 rad m⁻², with the western edge reaching values of ~-1200 rad m⁻². We note that these distinct areas also correspond with the fractional polarization map, with the lower absolute rotation measure spatially corresponding with the higher fractional polarization.

<figure><img src="image_10.png" /><figcaption>**Figure 8.** Fractional polarization map for ATCA 5500 MHz images. The image was convolved to a restoring beam of 8 × 8 arcsec² before polarization was measured. Contours are from 5500 MHz Stokes I images overlaid at values of 0.1, 0.2, 0.3, 0.4, and 0.7 mJy beam⁻¹.</figcaption></figure>

As discussed above, a higher absolute rotation measure may indicate that the light is travelling through a denser medium before reaching us. This would imply that there is a denser medium around the south-western edge compared with the north-eastern. This matches with the results from the radio morphology (Section 3.2.1) and HI analysis (Section 3.3). The higher absolute rotation measure spatially correlates with the brighter radio emission, providing further indication of an expansion into a denser medium, and the HI data show the possibility of an HI cloud at this location. Therefore, the higher absolute rotation measure detected along the south-western edge is possible indication of expansion into this HI cloud.

### 3.6.3 Magnetic field

We are able to estimate the magnetic field orientation at the source by derotating the observed polarization according to the measured rotation measure. This is done using the MIRIAD task IMRM and a map is generated showing the initial polarization orientation. We then rotate this by an additional 90° and produce a magnetic field map of the source at 5500 MHz (Fig. 9, right).

We observe different magnetic field orientations over the PWN and shell of Perun. The PWN shows an ordered magnetic field over its entirety, and the shell shows regions of radial orientation, that is the north-west and south-east sections, and a more tangential orientation is shown in the north-eastern shell. The south-western shell shows a disordered magnetic field, possibly indicating turbulence or Rayleigh-Taylor instabilities in this area. This provides further evidence for expansion into a possible HI cloud, as this expansion into a denser medium can introduce Rayleigh-Taylor instabilities that disrupt the ordered magnetic field.

For a young SNR, we typically expect a distinctly radial magnetic field, differing from what we see in Perun. Perun's magnetic field orientation can be explained by the magnetic field being disrupted by expansion into an HI cloud to the south-west. Another possible explanation could be that the PWN's magnetic field is dominat-
<figure><img src="image_11.png" /><figcaption>**Figure 9.** Perun's rotation measure and magnetic field map from ATCA 5500 MHz bandwidth. All images were convolved to a restoring beam of 8 × 8 arcsec² before polarization measurements were done. The left image shows the rotation measure map. Contours are from 5500 MHz image at values of 0.1, 0.2, 0.3, 0.4, and 0.7 mJy beam⁻¹. The right image shows the magnetic field. The vectors represent the magnetic field orientation and have been corrected for Faraday rotation. They are overlaid on the 5500 MHz Stokes *I* image. The Stokes *I* image was convolved with a restoring beam of 4 × 4 arcsec², shown in the bottom left corner.</figcaption></figure>

ing that of the shell, causing differences in the shell's magnetic field.

We do note similarities between Perun's polarimetric morphology and that of the young SNR, G1.9+0.3. The polarimetry measurements of G1.9 + 0.3 (Luken et al. 2020) show two distinct shell halves of differing rotation measure values and the magnetic field orientation switching between these sections. This is similar to what we observe in Perun with the obvious difference in rotation measure between the shell halves.

# 4 DISCUSSION

## 4.1 Σ–D analysis

We now attempt to estimate some of Perun's physical parameters by relating the radio surface brightness (Table 3) with the range of estimated diameters (Table 4) using the Σ–D relationship from Pavlović et al. (2018). We annotate Fig. 10 (Pavlović et al. 2018, fig. 3) with the red line representing Perun's possible diameters and see that it intersects with the cyan-coloured line at diameters of ~2 and 6.5 pc, corresponding to distances of ~6 and 19 kpc. These intrinsic diameters are reasonable estimates for a young SNR and the corresponding distances are well within the Milky Way.

It should be noted that inaccuracies may come with comparing this model with Perun due to the choice of specific parameters chosen for this model creation. Pavlović et al. (2018) state that their choice of certain parameters is characteristic of later evolutionary phases and has the potential to overestimate radio emission in young SNRs. It should also be noted that the catalogue of Galactic SNRs with known distances used to create this model consisted mainly of shell-type SNRs with very few composite SNRs and this could cause inconsistencies when comparing this model with Perun.

From this position on the Σ–D diagram, we can estimate an ambient density $n_H$ cm⁻³ = 0.005 and an initial explosion energy of $5 \times 10^{50}$ erg. These estimates indicate that Perun could be formed by

a subenergetic SN in a low-density environment. A rarefied ambient density, combined with Perun's young age, would help explain the observed symmetrical shape. It would also explain the much lower X-ray luminosity compared with typical young SNRs in nearby galaxies (Section 3.5).

To estimate Perun's distance and diameter, the bidimensional Σ–D calibration (Vukotić et al. 2019) is used. Fig. 11 presents the distance/diameter probability distribution at the fixed surface brightness (shell + PWN) of $\Sigma_{1\text{GHz}} = 2.2 \times 10^{-20} \text{ W m}^{-2} \text{ Hz}^{-1} \text{ sr}^{-1}$.

The median value of the distribution is at 25(72) pc(kpc) diameterensities, respectively. The 4–72 pc diameter interval represents the 95 per cent quantile range, symmetric around the median value, with matching distances range of 10–213 kpc. The corresponding orthogonal fit calibration from Vukotić et al. (2019) gives a diameter of 18 pc which translates to a distance of 52 kpc.

It is evident from Fig. 10 (also from fig. 1 in Vukotić et al. 2019) that the expected Σ–D graph position of Perun does not overlap with the position of the Galactic SNRs sample for the given surface brightness. The resulting Σ–D calibration distance might thus be a significant overestimate. However, even such calibration gives a 1 in 20 chance that Perun is located closer than 10 kpc. The same calibration gives 80 per cent quantile range for (22, 157) kpc distance interval that leaves a 1 in 5 chance that Perun's location can still be considered as within the Milky Way.

Due to Perun's location within the direction of the Galactic plane, and that we can resolve the small-scale features with the radio observations, it is reasonable to assume that it is located within the Milky Way. It is thus far more likely that the Σ–D analysis is significantly overestimating the estimated distance due to the initial calibration being based on an older SNR population.

## 4.2 Position in the Milky Way

Since CC SN only occur for massive, short-lived stars, it is widely accepted that they typically occur in areas of massive star formation
<figure><img src="image_12.png" /><figcaption>**Figure 10.** Radio surface brightness to diameter diagram for SNRs at frequency $\nu = 1$ GHz, obtained from Pavlović et al. (2018, fig. 3), shown as black triangles. Different line colours represent different ambient densities and different line types represent different explosion energies. The open circle is young Galactic SNR G1.9+0.3, and the open triangle represents Cassiopeia A. The numbers represent SNRs (1): CTB 37A, (2): Kes 97, (3): CTB 37B, and (4): G65.1 + 0.6. The red line represents Perun at measured surface brightness from Section 3.2.3 and spans the diameter ranges from Table 4.</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>**Figure 11.** Diameter probability distribution at the fixed surface brightness of $\Sigma_{1\text{GHz}} = 2.2 \times 10^{-20} \text{ W m}^{-2} \text{ Hz}^{-1} \text{ sr}^{-1}$ (distance calibration from Vukotić et al. 2019). The matching distance scale is given on the top axis. A solid vertical line indicates the distribution mean, while 95 per cent quantile range, symmetric around the mean, is presented with dashed vertical lines.</figcaption></figure>

(Bartunov, Tsvetkov & Filimonova 1994; Anderson et al. 2017; Verberne & Vink 2021). We observe that Galactic SNRs typically have low Galactic latitudes and are predominantly located within or near the Galactic plane (Ferrand & Safi-Harb 2012; Green 2022). However, it is difficult to comprehensively map the 3D spatial distribution of Galactic SNRs due to inherent uncertainties in Galactic distance measurements. Observations of nearby face-on galaxies have shown that SNRs are predominantly distributed along the spiral arms (Bartunov et al. 1994; Matonick & Fesen 1997; Galvin & Filipovic 2014; Bozzetto et al. 2017) in projection. Therefore, assuming the Milky Way follows the same trend, we can conclude that Galactic SNRs are more likely to be associated with spiral arms rather than occurring in interarm regions.

Therefore, if we assume Perun is located within a spiral arm, we can use current Galactic models to estimate possible distances. There have been many surveys and models that map the Galactic structure, such as those by Churchwell et al. (2009); Efremov (2011); Filipovic et al. (2013); Hou & Han (2014); and Vallée (2017). All these models map the spiral structure of the Milky Way, employing methods such as mapping different Galactic spiral arm tracers or using geometric models of spiral galaxy structure. They assume a generic spiral galaxy structure and provide similar values for distances and directions to each spiral arm. For this analysis, we use the model from Churchwell et al. (2009), as they provide a comprehensive visual map that allows us to readily measure spiral arm distances along Perun's Galactic longitude, $l = 329.9$ (Fig. 12).

We use these estimated distances, along with Perun's measured angular size, to estimate possible values for Perun's intrinsic size, and these results are shown in Table 4. In order to estimate the most probable size and distance for Perun, we compare these estimated diameters (Table 4; column 3) to other young Galactic SNRs (Table 5). As expected, we see a general trend of older SNRs having larger diameters. A notable exception to this is SN1054 (Crab Nebula), with an average diameter of 3.5 pc and an age of 969 yr.<fnref n="11" /> This inconsistency with the general trend can be explained by noting that SN1054 is a plerion SNR, meaning that unlike shell and composite SNRs there is no clearly defined outer shell. Therefore, a comparison between SN1054 and Perun will only have physical meaning if we compare this size to the size of Perun's PWN and ignore Perun's outer shell. Since Perun has had time to develop a prominent PWN, we conclude it is unlikely to be as young as SN1987A. It is therefore unlikely that Perun has a diameter of ~0.5 pc, and the inner Scutum-Centaurus arm at ~3.5 kpc is the closest probable distance.

Our H I analysis in Section 3.3 showed possibly associated H I clouds at distances of 6–9, 15, and 19 kpc and a possible H I cavity at 6–9 kpc. These derived H I distances match with distances to some of the Galactic spiral arms in Table 4. Since CC SNRs are more likely to be associated with spiral arms, we take these as our favoured distances. We also assume a lower limit on the distance of 3.5 kpc. We therefore conclude that a reasonable distance range is between 3.5–19 kpc with the Galactic arm distances being more favoured, and the most favourable distance corresponding with the observed H I cavity at 6–9 kpc.

<footnote n="11">¹¹For the historical overview of this object see Filipović et al. (2021a, b, 2022a).</footnote>
<figure><img src="image_14.png" /><figcaption>**Figure 12.** Artistic impression of the Milky Way from Churchwell et al. (2009, fig. 16) as it appears head-on inferred from optical, IR, and radio data. Sketch was created by Robert Hurt of the *Spitzer* Science Center in consultation with Robert Benjamin at the University of Wisconsin-Whitewater. Galactic coordinates are overlaid along with the position of the Sun and the spiral arms. The arrow represents Perun's Galactic longitude *l* = 329.9, starting at the sun and extending outside the Milky Way. The circles represent possible spiral arm crossings along with corresponding distances.</figcaption></figure>

## 4.3 Age determination

Using the estimated values for size and distance calculated in Section 4, we now infer a favoured age range for Perun. Based on the general trend of SNRs shown in Table 5, we conclude that an age greater than ~1000 years is unlikely, and place this as a tentative upper limit for our estimations.

Typical expansion velocities for SNRs display substantial variability (Ellison et al. 1994; Chevalier 2005; Gaensler & Slane 2006; Reynolds et al. 2008; Luken et al. 2020), however, it is generally accepted that young SNRs in their free expansion phase have higher expansion velocities. To accommodate for these different scenarios, we explore a broad range of velocities between 1000–15 000 km s⁻¹. We use the estimated distances as shown in Table 4, along with our chosen velocity range, to estimate a favoured age range for Perun. We restrict our distances to the spiral arm distances, as these are the most favourable distances and they provide a good sampling of the total reasonable distance range as outlined in Section 4.2. For

this calculation, we assume a simple free expansion model and the estimated values are shown in Table 6. The entire reasonable distance range is calculated and the favoured values, determined from the presence of the H I cavity, are highlighted in bold.

If we assume a minimum distance of 3.5 kpc and a maximum age of 1000 yr, from comparison with Table 5, we estimate a reasonable age range of 39–1000 yr. Using the favoured distance from the H I cavity analysis, we estimate a favoured age range of 67–501 yr.

This shows that Perun could be the youngest Galactic SNR, especially since at this distance only SN1987A would have a smaller diameter. At the favoured distance of 6–9 kpc, Perun would have a diameter of 2.0–3.1 pc. Comparing this with the youngest SNR, G1.9+0.3 with a diameter of 4 pc, we see that Perun may be smaller. This may suggest that Perun is younger than G1.9+0.3, arguing for a lower age range of between 67–150 yr old.

The possibility of such a young age raises the question of why the initial SN was not observed, since they are typically luminous
<table><caption>**Table 5.** List of young SNRs with corresponding intrinsic diameters, ages, SN type, and references. SN type refers to either TN or CC.</caption><thead><tr><th>SNR name</th><th>Host galaxy</th><th>SN type</th><th>Age (yr)</th><th>Diameter (pc)</th><th>Σ<sub>1 GHz</sub>(×10<sup>-20</sup>) (W m<sup>-2</sup> Hz<sup>-1</sup> sr<sup>-1</sup>)</th><th>References</th></tr></thead><tbody><tr><td>SN1987A</td><td>LMC</td><td>CC</td><td>37</td><td>0.4</td><td>13 700</td><td>Bozzetto et al. (2017); Arendt et al. (2023)</td></tr><tr><td>G1.9+0.3</td><td>MW</td><td>CC/TN</td><td>120–150</td><td>4</td><td>6.7</td><td>De Horta et al. (2008); Pavlović (2017); Luken et al. (2020)</td></tr><tr><td>J0509–6731</td><td>LMC</td><td>TN</td><td>310</td><td>7.5</td><td>5.72</td><td>Bozzetto et al. (2017); Roper et al. (2018)</td></tr><tr><td>Cassiopeia A</td><td>MW</td><td>CC</td><td>344</td><td>4–5.4†</td><td>1145.27</td><td>Thorstensen et al. (2001); Vukotić et al. (2019)</td></tr><tr><td><i>Kepler</i></td><td>MW</td><td>TN</td><td>420</td><td>5.3</td><td>31.78</td><td>Sankrit et al. (2016); Vukotić et al. (2019)</td></tr><tr><td><i>Tycho</i></td><td>MW</td><td>TN</td><td>452</td><td>5.8–7‡</td><td>13.17</td><td>Tian & Leahy (2011); Vukotić et al. (2019)</td></tr><tr><td>G29.7–0.3</td><td>MW</td><td>CC</td><td>480</td><td>5</td><td>16.7</td><td>Green (2014); Reynolds, Borkowski & Gwynne (2018)</td></tr><tr><td>0519–69.0</td><td>LMC</td><td>TN</td><td>600</td><td>8</td><td>6.09</td><td>Rest et al. (2005); Kosenko, Helder & Vink (2010); Bozzetto et al. (2017)</td></tr><tr><td>N 103B</td><td>LMC</td><td>TN</td><td>380–860</td><td>6.8</td><td>60</td><td>Rest et al. (2005); Alsaberi et al. (2019)</td></tr><tr><td>SN1054</td><td>MW</td><td>CC</td><td>970</td><td>3.5§</td><td>450</td><td>Kothes (1998); Kaplan et al. (2008)</td></tr><tr><td>SN1006</td><td>MW</td><td>TN</td><td>1018</td><td>19</td><td>0.32</td><td>Winkler et al. (2014); Vukotić et al. (2019)</td></tr><tr><td>1E0102–72</td><td>SMC</td><td>CC</td><td>1738</td><td>13</td><td>9.17</td><td>Banovetz et al. (2021); Alsaberi et al. (2023)</td></tr></tbody></table>

Notes. †Diameters given include diameter of the shell as 4 pc and diameter of the forward expanding shockwave as 5.4 pc.

‡Diameters given are for a range of probable distances, as the distance to *Tycho* is not exactly known.

§SN1054 is an irregular shape, and there are uncertainties in distance measurements. This is an estimate calculated from the nominal distance measurement of ~2 kpc and an average optical diameter of 6 arcmin.

<table><caption>**Table 6.** Possible values for Perun's age calculated using possible expansion velocities between 1000–15 000 km s⁻¹ and estimated distances from Table 4. The favoured distances and ages as per the discussion text are in bold.</caption><thead><tr><th rowspan="2">Distance (kpc)</th><th rowspan="2">Diameter (pc)</th><th colspan="10">Velocity (km s<sup>-1</sup>)</th></tr><tr><th>1000</th><th>3000</th><th>5000</th><th>7000</th><th>9000</th><th>10 000</th><th>12 000</th><th>13 000</th><th>14 000</th><th>15 000</th></tr><tr><th></th><th></th><th>Time (yr)</th><th>Time (yr)</th><th>Time (yr)</th><th>Time (yr)</th><th>Time (yr)</th><th>Time (yr)</th><th>Time (yr)</th><th>Time (yr)</th><th>Time (yr)</th><th>Time (yr)</th></tr></thead><tbody><tr><td>1.5</td><td>0.5</td><td>250</td><td>83</td><td>50</td><td>36</td><td>28</td><td>25</td><td>21</td><td>19</td><td>18</td><td>17</td></tr><tr><td>3.5</td><td>1.2</td><td>582</td><td>194</td><td>116</td><td>83</td><td>65</td><td>58</td><td>49</td><td>45</td><td>42</td><td>39</td></tr><tr><td><b>6</b></td><td>2.0</td><td>1003</td><td><b>334</b></td><td><b>201</b></td><td><b>143</b></td><td><b>111</b></td><td><b>100</b></td><td><b>84</b></td><td><b>77</b></td><td><b>72</b></td><td><b>67</b></td></tr><tr><td><b>7</b></td><td>2.4</td><td>1164</td><td><b>388</b></td><td><b>233</b></td><td><b>166</b></td><td><b>129</b></td><td><b>116</b></td><td><b>97</b></td><td><b>90</b></td><td><b>83</b></td><td><b>78</b></td></tr><tr><td><b>8</b></td><td>2.7</td><td>1326</td><td><b>442</b></td><td><b>265</b></td><td><b>189</b></td><td><b>147</b></td><td><b>133</b></td><td><b>110</b></td><td><b>102</b></td><td><b>95</b></td><td><b>88</b></td></tr><tr><td><b>9</b></td><td>3.1</td><td>1502</td><td><b>501</b></td><td><b>300</b></td><td><b>215</b></td><td><b>167</b></td><td><b>150</b></td><td><b>125</b></td><td><b>116</b></td><td><b>108</b></td><td><b>100</b></td></tr><tr><td>11</td><td>3.8</td><td>1825</td><td>608</td><td>365</td><td>261</td><td>203</td><td>183</td><td>152</td><td>140</td><td>130</td><td>122</td></tr><tr><td>15</td><td>5.1</td><td>2490</td><td>830</td><td>498</td><td>356</td><td>277</td><td>249</td><td>208</td><td>192</td><td>178</td><td>166</td></tr><tr><td>19</td><td>6.5</td><td>3156</td><td>1052</td><td>631</td><td>451</td><td>351</td><td>316</td><td>263</td><td>243</td><td>225</td><td>210</td></tr></tbody></table>

and energetic events. Perun's position in the Galactic plane indicates that it is located in a dense area of the Galactic plane. This crowded location could explain the lack of any obvious historical sightings as in the case of G1.9+0.3.

## 5 CONCLUSION

We have presented the discovery of possibly the youngest observed Galactic SNR, Perun (G329.9–0.5). The observed spectral index clearly indicates non-thermal emission. This, combined with the linear radio polarization, demonstrates synchrotron emission typical for SNRs, confirming its identity as a new Galactic SNR.

It is located within the Galactic plane, and we estimate a distance range of 3.5–19 kpc, with the favoured distance of 6–9 kpc. From this, we estimate an age range of ~40–1000 yr, and a favoured age range of ~70–150 yr. We performed a multifrequency analysis of Perun's properties using a combination of radio data from ASKAP, MeerKAT, ATCA, MOST, SGPS, and MWA, along with IR data from *Spitzer* and X-ray data from *Chandra*.

At radio frequencies, we observe a small angular size ($D = 70$ arcsec) for Perun, consisting of a prominent PWN within a spherical shell. We measure an overall spectral index of $\alpha = -0.49 \pm 0.05$.

and spectral indices for the shell and PWN as $\alpha_{\text{shell}} = -0.39 \pm 0.04$ and $\alpha_{\text{PWN}} = -0.23 \pm 0.02$, respectively. We also observe a concave-up spectral index that indicates non-linear DSA effects, a phenomenon that has been previously observed in young SNRs.

We measure linear polarization from the ATCA observations, with average polarizations of $7.3 \pm 2.7$ per cent at 5500 MHz and $10.3 \pm 2.7$ per cent at 9000 MHz. We observe a magnetic field exhibiting both radial and tangential sections, similar to that observed in the young SNR G1.9+0.3.

The IR observations show that Perun is detected only at 24 µm in IR. Due to the lack of observable emission at other IR frequencies, we attribute this emission to shocked material in the shell, specifically [O IV] and [Fe III] emission lines, indicative of young SNR ejecta.

We utilize H I data from SGPS to probe interactions with the surrounding interstellar environment and determine the three favoured estimates for Perun's distance, between 6–19 kpc, with the favoured location being within the Norma Arm at 6–9 kpc. We then compare Perun with other known young SNRs, and these comparisons allow us to estimate a favoured intrinsic age range of ~70–150 yr.

These multifrequency properties support the identification of Perun as a new, Galactic SNR. Its small size and symmetrical shape provide justification for our young age estimate, making Perun a
possible candidate for the youngest known Galactic SNR discovered
to date.

ACKNOWLEDGEMENTS

This scientific work uses data obtained from Inyarrimanha Ilgari Bundara/the Murchison Radio-astronomy Observatory. We acknowledge the Wajarri Yamaji People as the Traditional Owners and native title holders of the Observatory site. CSIRO's ASKAP radio telescope is part of the ATNF.<fnref n="12" /> Operation of ASKAP is funded by the Australian Government with support from the National Collaborative Research Infrastructure Strategy. ASKAP uses the resources of the Pawsey Supercomputing Research Centre. Establishment of ASKAP, Inyarrimanha Ilgari Bundara, the CSIRO Murchison Radio-astronomy Observatory, and the Pawsey Supercomputing Research Centre are initiatives of the Australian Government, with support from the Government of Western Australia and the Science and Industry Endowment Fund.

The Australia Telescope Compact Array is part of the Australia Telescope National Facility<fnref n="12" /> which is funded by the Australian Government for operation as a National Facility managed by CSIRO. We acknowledge the Gomeroi people as the Traditional Owners of the Observatory site.

The MeerKAT telescope is operated by the South African Radio Astronomy Observatory, which is a facility of the National Research Foundation, an agency of the Department of Science and Innovation.

This work is based [in part] on observations made with the
*Spitzer Space Telescope*, which was operated by the Jet Propulsion
Laboratory, California Institute of Technology under a contract with
NASA.

This research has made use of 'Aladin sky atlas' developed at
CDS, Strasbourg Observatory, France

This work has made use of data from the European Space Agency (ESA) mission Gaia,<fnref n="13" /> processed by the Gaia Data Processing and Analysis Consortium (DPAC<fnref n="14" />). Funding for the DPAC has been provided by national institutions, in particular, the institutions participating in the Gaia Multilateral Agreement.

This research has made use of the HASH PN database at
hashpn.space.

This research has also benefited from the use of the software
CARTA (Comrie et al. 2021) and SAOImage DS9 (Joye & Man-
del 2003), as well as the software package MIRIAD (Sault et al.
1995).

MDF, GR, and SL acknowledge Australian Research Council (ARC) funding through discovery project grant DP200100784. SL and BV were supported by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia (MST-DIRS) through contract no. 451-03-66/2024-03/200002 made with Astronomical Observatory (Belgrade). SD is the recipient of an ARC Discovery Early Career Award (DE210101738) funded by the Australian Government.

We thank Stephen P. Reynolds and Kazimierz Borkowski for their
suggestions and support.

We thank an anonymous referee for comments and suggestions
that greatly improved our paper.

DATA AVAILABILITY

Data and images used within this paper are available upon reasonable
request from the corresponding author. The ASKAP data used
are available through the CSIRO ASKAP Science Data Archive
(CASDA) website,<fnref n="15" /> the ATCA data through the Australia Telescope
Online Archive website,<fnref n="16" /> the MeerKAT data through the SARAO
archive,<fnref n="17" /> and the *Spitzer* data from the Spitzer Data Archive.<fnref n="18" />

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This paper has been typeset from a TEX/LATEX file prepared by the author.

<footnote n="1">¹School of Science, Western Sydney University, Locked Bag 1797, Penrith South DC, NSW 2751, Australia</footnote>

<footnote n="2">²CSIRO Space and Astronomy, Australia Telescope National Facility, PO Box 76, Epping, NSW 1710, Australia</footnote>

<footnote n="3">³Astronomical Observatory, Volgina 7, 11060 Belgrade, Serbia</footnote>

<footnote n="4">⁴Escuela de Física, Universidad de Costa Rica, San José 11501-2060, Costa Rica</footnote>

<footnote n="5">⁵Department of Physics, University of Alberta, 4-181 CCIS, Edmonton, Alberta T6G 2E1, Canada</footnote>

<footnote n="6">⁶INAF – Osservatorio Astrofisico di Catania, Via Santa Sofia 78, I-95123 Catania, Italy</footnote>

<footnote n="7">⁷Max-Planck-Institut für Extraterrestrische Physik, Gießenbachstraße 1, D-85748 Garching, Germany</footnote>

<footnote n="8">⁸School of Mathematical and Physical Sciences, 12 Wally's Walk, Macquarie University, NSW 2109, Australia</footnote>

<footnote n="9">⁹Department of Astronomy, University of Cape Town, Private Bag X3, Rondebosch 7701, South Africa</footnote>

<footnote n="10">¹⁰Dominion Radio Astrophysical Observatory, Herzberg Astronomy and Astrophysics, National Research Council Canada, PO Box 248, Penticton, BC V2A 6J9, Canada</footnote>

<footnote n="11">¹¹Department of Physics and Astronomy, University of Calgary, Calgary, Alberta T2N 1N4, Canada</footnote>

<footnote n="12">¹²The Oscar Klein Centre, Department of Astronomy, Stockholm University, AlbaNova, SE-10691 Stockholm, Sweden</footnote>

<footnote n="13">¹³IRAP, Université de Toulouse, CNRS, CNES, F-31028 Toulouse, France</footnote>

<footnote n="14">¹⁴School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide 5005, Australia</footnote>

<footnote n="15">¹⁵Faculty of Engineering, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan</footnote>

<footnote n="16">¹⁶Center for Space Research and Utilization Promotion (c-SRUP), Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan</footnote>

<footnote n="17">¹⁷Dr Karl Remeis Observatory, Erlangen Centre for Astroparticle Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Sternwartstraße 7, D-96049 Bamberg, Germany</footnote>

<footnote n="18">¹⁸INAF – Osservatorio Astrofisico di Torino, Strada Osservatorio 20, I-10025 Pino Torinese, Italy</footnote>

<footnote n="19">¹⁹Sydney Institute for Astronomy, School of Physics A28, The University of Sydney, Sydney, NSW 2006, Australia</footnote>

<footnote n="20">²⁰International Centre for Radio Astronomy Research (ICRAR), The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia</footnote>

<footnote n="21">²¹Department of Astronomy, Faculty of Mathematics, University of Belgrade, Studentski trg 16, 11000 Belgrade, Serbia</footnote>

<footnote n="22">²²CSIRO Space and Astronomy, PO Box 1130, Bentley, WA 6102, Australia</footnote>