DISCOVERY OF SHOCKED MOLECULAR CLOUDS ASSOCIATED WITH THE SHELL-TYPESUPERNOVA REMNANT RX J0046.5-7308 IN THE SMALL MAGELLANIC CLOUD

# Discovery of Shocked Molecular Clouds Associated With the Shell-Type Supernova Remnant Rx j0046.5−7308 in the Small Magellanic Cloud

[    H. Matsumura    [    P. Maggi    K. Fujii    [    [    [    [    [    [    [    [    K. Muraoka    [    [    [    [    N. Mizuno    H. Yamamoto    [    T. Inoue    [    F. Voisin    N. F. H. Tothill    [    [    Y. Fukui
###### Abstract

RX J0046.57308 is a shell-type supernova remnant (SNR) in the Small Magellanic Cloud (SMC). We carried out new CO( = 1–0, 3–2) observations toward the SNR using Mopra and ASTE. We reveled eight molecular clouds (A–H) along the X-ray shell of the SNR. The typical cloud size and mass are 10–15 pc and 2000–5000 , respectively. The X-ray shell is slightly deformed and has the brightest peak in the southwestern shell where two molecular clouds A and B are located. The four molecular clouds A, B, F, and G have high-intensity ratios of CO( = 3–2) / CO( = 1–0) , not attributable to any identified internal infrared sources or high-mass stars. The Hi cavity and its expanding motion are found toward the SNR, which are likely created by strong stellar winds from a massive progenitor. We suggest that the molecular clouds A–D, F, G, and Hi clouds within the wind-blown cavity at –122.5 km s are to be associated with the SNR. The X-ray spectroscopy reveals the dynamical age of yr and the progenitor mass of , which is also consistent with the proposed scenario. We determine physical conditions of the giant molecular cloud LIRS 36A using the large velocity gradient analysis with archival datasets of ALMA; the kinematic temperature is  K and the number density of molecular hydrogen is  cm. Next generation of -ray observations will allow us to study the pion-decay -rays from the GMC and molecular clouds in the SMC SNR.

ISM: clouds — ISM: supernova remnants — galaxies: Magellanic Clouds — ISM: individual objects (RX J0046.57308, DEM S23)

0000-0003-2062-5692]H. Sano \move@AU\move@AF\@affiliationInstitute for Advanced Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan; sano@a.phys.nagoya-u.ac.jp \move@AU\move@AF\@affiliationDepartment of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

\move@AU\move@AF\@affiliation

Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8583, Japan; hideaki.matsumura@ipmu.jp

0000-0001-8296-7482]Y. Yamane \move@AU\move@AF\@affiliationDepartment of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

\move@AU\move@AF\@affiliation

Observatoire Astronomique de Strasbourg, Université de Strasbourg, CNRS, 11 rue de l’Université, F-67000 Strasbourg, France

\move@AU\move@AF\@affiliation

Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 133-0033, Japan

0000-0002-2794-4840]K. Tsuge \move@AU\move@AF\@affiliationDepartment of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

0000-0002-2062-1600]K. Tokuda \move@AU\move@AF\@affiliationDepartment of Physical Science, Graduate School of Science, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Japan \move@AU\move@AF\@affiliationNational Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588, Japan

0000-0001-5609-7372]R. Z. E. Alsaberi \move@AU\move@AF\@affiliationWestern Sydney University, Locked Bag 1797, Penrith South DC, NSW 1797, Australia

0000-0002-4990-9288]M. D. Filipović \move@AU\move@AF\@affiliationWestern Sydney University, Locked Bag 1797, Penrith South DC, NSW 1797, Australia

0000-0003-2762-8378]N. Maxted \move@AU\move@AF\@affiliationSchool of Science, University of New South Wales, Australian Defence Force Academy, Canberra, ACT 2600, Australia

0000-0002-9516-1581]G. Rowell \move@AU\move@AF\@affiliationSchool of Physical Sciences, The University of Adelaide, North Terrace, Adelaide, SA 5005, Australia

0000-0003-1518-2188]H. Uchida \move@AU\move@AF\@affiliationDepartment of Physics, Graduate School of Science, Kyoto University, Kitashirakawa Oiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan

0000-0002-4383-0368]T. Tanaka \move@AU\move@AF\@affiliationDepartment of Physics, Graduate School of Science, Kyoto University, Kitashirakawa Oiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan

\move@AU\move@AF\@affiliation

Department of Physical Science, Graduate School of Science, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Japan

0000-0002-4124-797X]T. Takekoshi \move@AU\move@AF\@affiliationInstitute of Astronomy, The University of Tokyo, 2-21-1 Osawa, Mitaka, Tokyo 181-0015, Japan \move@AU\move@AF\@affiliationGraduate School of Informatics and Engineering, The University of Electro-Communications, Chofu, Tokyo 182-8585, Japan

0000-0001-7826-3837]T. Onishi \move@AU\move@AF\@affiliationDepartment of Physical Science, Graduate School of Science, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Japan

0000-0001-7813-0380]A. Kawamura \move@AU\move@AF\@affiliationNational Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588, Japan

0000-0001-9778-6692]T. Minamidani \move@AU\move@AF\@affiliationNobeyama Radio Observatory, National Astronomical Observatory of Japan (NAOJ), National Institutes of Natural Sciences (NINS), 462-2, Nobeyama, Minamimaki, Minamisaku, Nagano 384-1305, Japan \move@AU\move@AF\@affiliationDepartment of Astronomical Science, School of Physical Science, SOKENDAI (The Graduate University for Advanced Studies), 2-21-1, Osawa, Mitaka, Tokyo 181-8588, Japan

\move@AU\move@AF\@affiliation

National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588, Japan

\move@AU\move@AF\@affiliation

Department of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

0000-0002-1411-5410]K. Tachihara \move@AU\move@AF\@affiliationDepartment of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

\move@AU\move@AF\@affiliation

Department of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

0000-0003-4366-6518]S. Inutsuka \move@AU\move@AF\@affiliationDepartment of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

\move@AU\move@AF\@affiliation

School of Physical Sciences, The University of Adelaide, North Terrace, Adelaide, SA 5005, Australia

\move@AU\move@AF\@affiliation

Western Sydney University, Locked Bag 1797, Penrith South DC, NSW 1797, Australia

0000-0001-5302-1866]M. Sasaki \move@AU\move@AF\@affiliationDr. Karl Remeis-Sternwarte, Erlangen Centre for Astroparticle Physics, Friedrich-Alexander-Universitt Erlangen-Nrnberg, Sternwartstrae 7, D-96049 Bamberg, Germany

0000-0003-2730-957X]N. M. McClure-Griffiths \move@AU\move@AF\@affiliationResearch School of Astronomy & Astrophysics, The Australian National University, Canberra, ACT 2611, Australia

\move@AU\move@AF\@affiliation

Institute for Advanced Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan; sano@a.phys.nagoya-u.ac.jp \move@AU\move@AF\@affiliationDepartment of Physics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan

## 1 Introduction

In our Galaxy, molecular clouds associated with supernova remnants (SNRs) play an essential role in understanding not only the shock heating/compression of the interstellar medium (ISM), but also the origins of thermal/non-thermal X-rays, -rays, and cosmic rays. The shock-cloud interaction excites turbulence that enhances the magnetic field up to 1 mG (e.g., Uchiyama et al., 2007; Inoue et al., 2009), which can be observed as shocked gas clumps with limb brightening in the synchrotron X-rays (e.g., Sano et al., 2010, 2013; Okuno et al., 2018). For the ionized plasma in the Galactic SNR RCW 86, Sano et al. (2017a) found a positive correlation between the thermal X-ray flux and gas density around the shocked region, indicating that shock ionization occurred. The interstellar protons also act as a target for cosmic-ray protons producing GeV/TeV -rays via neutral pion decay. The good spatial correspondence between the interstellar protons and -rays provides evidence for cosmic-ray acceleration in the Galactic SNRs (e.g., Fukui et al., 2003; Aharonian et al., 2008; Fukui et al., 2012, 2017; Yoshiike et al., 2013).

The Magellanic Clouds—consisting of the Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC)—provide us with unique laboratories for studying the shock interaction because of their well-known distance ( kpc for the LMC, Pietrzyński et al. 2013; kpc for the SMC, Hilditch et al. 2005) and low ISM metallicity ( 0.3–0.5  for the LMC; Westerlund 1997, 0.05–0.2  for the SMC; Russell & Dopita 1992, Rolleston et al. 1999). The smaller contamination along the line-of-sight is also advantage to identify molecular clouds associated with the SNRs. For LMC SNRs N23, N49, and N132D, Banas et al. (1997) carried out pioneering CO studies by using the Swedish-ESO Submillimetre Telescope. Recent CO observations using the Atacama Submillimeter Telescope Experiment (ASTE), Mopra, and Atacama Large Millimeter/ submillimeter Array (ALMA) revealed clumpy molecular clouds associated with the X-ray bright LMC SNRs with an angular resolution of , corresponding to the spatial resolution of 0.5–11 pc (Sano et al., 2015, 2017b, 2017c, 2018a, 2019; Yamane et al., 2018). Most recently, Alsaberi et al. (2019) revealed an Hi cavity interacting with the SMC SNR DEM S5. The Hi data was obtained using the Australian Square Kilometre Array Pathfinder (ASKAP) with an angular resolution of , corresponding to the spatial resolution of 9 pc at the SMC distance. We are therefore entering a new age in studying the Magellanic SNRs yielding a spatial resolution comparable to what had been possible only for Galactic SNRs. However, there are no CO observations toward the SMC SNRs.

RX J0046.57308 (also known as SNR B004473.4, HFPK 414, or DEM S32) is an X-ray SNR located in the southwestern part of the SMC (e.g., Haberl et al., 2000; van der Heyden et al., 2004; Filipović et al., 2008; Haberl et al., 2012; Roper et al., 2015). The description of the source first appeared in the X-ray survey paper of the SMC (Wang & Wu, 1992). Subsequent optical, radio continuum, and X-ray observations confirmed that RX J0046.57308 is a shell-type SNR on the vicinity of the Hii region N19 (e.g., Rosado et al., 1994; Dickel et al., 2001; van der Heyden et al., 2004; Filipović et al., 2005; Payne et al., 2007). The size of X-ray shell is about 40.7 pc 46.5 pc (Filipović et al., 2008), which spatially coincides with the radio continuum shell with spectral index of (e.g., Dickel et al., 2001; Filipović et al., 2005). Recently, a flatter spectral index of was derived, indicating the thermal origin of the radio continuum and an evolved SNR (Maggi et al., in preparation). In fact, in previous - studies the X-ray spectra were well described by a simple non-equilibrium ionization (NEI) plasma model without synchrotron X-rays (e.g., van der Heyden et al., 2004). Assuming the Sedov model, the ionization age was estimated as 15,000 yr. Although the progenitor type could not be determined , the rich star-forming environment (N19) might suggest that RX J0046.57308 is a core-collapse (CC) SNR. This means that the SNR has a potential to be associated with dense molecular clouds. Rubio et al. (1993a, b) revealed a giant molecular cloud (GMC) located in north of the SNR, corresponding to the Hii region DEM S23 (also known as N12A or NGC 261). The fundamental physical properties have been derived: e.g., virial mass 17000  and radius 18.6 pc (Rubio et al., 1993b; Lequeux et al., 1994; Nikolić et al., 2007), but the physical relation between the GMC and SNR has not been discussed. The issue is further complicated by the large depth along the line of sight of the SMC (Scowcroft et al., 2016), making GMC/SNR association less likely based on projected location only.

In this paper, we report the first detection of molecular clouds and atomic gas associated with the SMC SNR RX J0046.57308 using the ASTE, Mopra, and ASKAP. We also present physical properties of the GMC in DEM S23 and its relation with the SNR using archival CO data taken with ALMA. Section 2 describes observations and data reductions of CO, Hi, and X-rays. Section 3.1 gives large-scale maps of X-ray and CO; Sections 3.2, 3.3, and 3.4 describe physical properties of molecular clouds; Section 3.5 presents Hi distribution; 3.6 gives a X-ray spectral analysis. Discussion and conclusions are provided in Sections 4 and 5.

## 2 Observations and Data Reductions

### 2.1 Co

Observations of CO( = 3–2) line emission at 345.795990 GHz were carried out during August 2014 by using the ASTE 10 m radio telescope (Ezawa et al., 2004), which was operated by the National Astronomical Observatory of Japan (NAOJ). We observed rectangular region centered at (, ) (, ) using the on-the-fly (OTF) mapping mode with Nyquist sampling. The front end was a side-band separating Superconductor-Insulator-Superconductor mixer receiver “CATS345” (Inoue et al., 2008). We utilized a digital FX spectrometer “MAC” (Sorai et al., 2000) as the backend. The bandwidth of the spectrometer is 128 MHz with 1024 channels, corresponding to the velocity coverage of 111 km s and the velocity resolution of 0.11 km s. The typical system temperature was 200–300 K, including the atmosphere in the single-side band (SSB). To derive the main beam efficiency, we observed N12A [(, ) (, )] (Nikolić et al., 2007), and then we obtained the main beam efficiency of 0.71. The pointing accuracy was checked every half-hour to achieve an offset within . After smoothing with a two-dimensional Gaussian kernel, we obtained the data cube with the beam size of (8 pc at the distance to the SMC). The typical noise fluctuation is 0.038 K at the velocity resolution of 0.4 km s.

Observations of CO( = 1–0) line emission at 115.271202 GHz were executed from July to September 2014 using the Mopra 22 m radio telescope of the Commonwealth Scientific and Industrial Research Organization (CSIRO). We used the OTF mapping mode with Nyquist sampling. The map size and center position are the same as that of CO( = 3–2). The frontend was an Indium Phosphide (InP) High Electron Mobility Transistor receiver (HEMT). We utilized a digital filter-bank spectrometer (MOPS) system as the backend. The spectrometer has 4096 channels with the bandwidth of 137.5 MHz, corresponding to the velocity resolution of 0.1 km s and the velocity coverage of 360 km s. The typical system temperature was 700–800 K including the atmosphere in the SSB. The pointing accuracy was checked every 2 hours and was achieved to be within an offset of . We also derived the main beam efficiency of 0.46 by observing Ori-KL [(, ) (, )] (Ladd et al., 2005) as the absolute intensity calibrator. After two-dimensional Gaussian smoothing, we obtained the data with the beam size of (13 pc at the SMC). Finally, we combined the data with archival Mopra data “MAGMA-SMC” (Muller et al., 2013) using the root-mean-square weighting scheme. The final noise fluctuation of the data was 0.067 K at the velocity resolution of 0.53 km s.

To derive the density and kinematic temperature of the GMC LIRS 36, we used archival CO datasets obtained with ALMA Band 3 (86–116 GHz) and Band 6 (211–275 GHz) as a Cycle 3 project #2015.1.00196.S (PI: J. Roman-Duval). Observations of CO( = 2–1) line emission at 230.538000 GHz and CO( = 2–1) line emission at 220.398684 GHz were conducted in June and August 2016 using 3 antennas of total power (TP) array. The OTF mapping mode with Nyquist sampling was used. The map size is about rectangular region centered at the GMC LIRS 36 [(, ) (, )]. We utilized the product dataset through the pipeline processes using Common Astronomy Software Application (CASA; McMullin et al., 2007) package version 4.5.3 with the Pipeline version r36660 (Pipeline-Cycle3-R4-B). The beam size is for CO( = 2–1) and is for CO( = 2–1), corresponding to a spatial resolution of 9 pc at the distance of the SMC. The typical noise fluctuations of the CO( = 2–1) and CO( = 2–1) data are 0.011 K and 0.014 K at the velocity resolution of 0.32 km s, respectively.

\twocolumngrid

### 2.2 Hi

We used Hi data published by McClure-Griffiths et al. (2018) and Di Teodoro et al. (2019). The Hi data were obtained using the Australian Square Kilometre Array Pathfinder (ASKAP; DeBoer et al., 2009). The angular resolution of the Hi data is 3503 2696 with a position angle of 8962, corresponding to the spatial resolution of 9 pc at the SMC. The typical noise fluctuations of the Hi is 0.7 K at the velocity resolution of 3.9 km s.

### 2.3 X-rays

We used archival X-ray data obtained by using Chandra, for which the observation IDs (Obs IDs) are 3904 (PI: R. Williams), 14674, 15507, and 16367 (PI: A. Zezas), which have been published some papers (e.g., Williams et al., 2006; Guerrero & Chu, 2008; Schnurr et al., 2008; Christodoulou et al., 2016; Israel et al., 2016; Yang et al., 2017a, b; Christodoulou et al., 2017; Hong et al., 2017; Ducci et al., 2018). The datasets were taken with the Advanced CCD Imaging Spectrometer S-array (ACIS-S2) on January 2003 for Obs ID 3904 and with ACIS I-array on March and September 2013 for Obs IDs 14674, 15507, and 16367. We utilized Chandra Interactive Analysis of Observations (CIAO; Fruscione et al., 2006) software version 4.10 with CALDB 4.7.8 for data reduction and imaging. The datasets were reprocessed using the chandra_repro tool. We created an energy-filtered, exposure-corrected image using the fluximage tool in the energy band 0.3–2.1 keV. The total effective exposure is  ks. We finally smoothed the data with a Gaussian kernel of (FWHM). For spectral analysis, we reduced and processed the data using the HEADAS software version 6.19. We created spectra with the four Chandra data using the specextract tools. The ACIS-I spectra were combined by using the combine_spectra tool. We did not combine the ACIS-S and ACIS-I spectra since they have different response (intrinsically and because of increased filter contamination over the ten years separating the two sets of data) All X-ray spectral fits are performed with XSPEC version 12.10.0e. The plasma models are calculated with ATOMDB version 3.0.9 with the solar abundance given by Wilms et al. (2000). The errors are quoted at 1 confidence levels in the text, tables, and figures in the X-ray analysis.

## 3 Results

### 3.1 Large Scale Distribution of the CO and X-rays

Figure 1(a) shows an X-ray image of RX J0046.57308 obtained with Chandra in the energy band of 0.3–2.1 keV. The incomplate X-ray shell with a possible blowout feature towards the northwest is spatially resolved. The spatial extent of the SNR is about 55 pc 45 pc, which is roughly consistent with the previous radio continuum and X-ray studies (e.g., Dickel et al., 2001; van der Heyden et al., 2004; Filipović et al., 2008). We find multiple local peaks of X-rays on the shell; the brightest X-ray peak appears in the southwestern rim. We also note that an X-ray point source (, ) (, ) coincides with the O3/4V-type star LIN 78, which is an exciting star of DEM S23. An X-ray source (, ) (, ) is on the edge of another SNR RX J0047.57308 (also known as IKT 2 or MCSNR J00477308).

Figure 1(b) shows a large-scale distribution of CO( = 3–2) toward the SNR RX J0046.57308. We have discovered eight molecular clouds A–H along the X-ray shell: four of them (A–D) delineate the southern shell, while the others (E–H) are located in outer boundaries of the northern shell. The clouds C and D are possibly associated with infrared source and B-type star. We also find complementary spatial distributions between the molecular clouds and X-ray peaks especially in the cloud B. The typical separation between the peaks of CO and X-rays is from a few pc to 10 pc.

### 3.2 Physical properties of eight molecular clouds

Figure 2.1 shows line profiles of CO. All molecular clouds were significantly detected in CO( = 3–2), which are well described by a single Gaussian model for peaks A–E, G, and F or a double Gaussian model for peak F. The CO peaks C, E, F, and G show slightly larger linewidth km s, but we could not find reliable evidence of shock-broadening or wing-like profiles of CO possibly due to the coarse angular resolution of the current datasets. The properties of CO clouds (position, peak intensity/velocity, line width, size, and mass) are summarized in Table 2.1.

For the mass estimation, we used two different methods. One gives the virial mass using the virial theorem as following equation:

 Mvir=210R(ΔV)2 (1)

where is the radius of CO cloud and is the FWHM of linewidth derived by the Gaussian fitting (see Tabel 2.1). The other is the CO-derived mass, , using the following equation:

 MCO=mHμD2Ω∑i[Ni(H2)], (2) N(H2)=XCO⋅W(CO), (3)

where is the atomic hydrogen mass, is the mean molecular weight of 2.7, is the distance to the SMC, is the solid angle of each pixel, is the column density of molecular hydrogen for each pixel , is the CO-to-H conversion factor, and is the integrated intensity of CO( = 1–0) line emission. In the present paper, we used (K km s) cm (Muraoka et al., 2017). To circulate , we used the ASTE CO( = 3–2) data instead of the Mopra CO( = 1–0) data, because the CO( = 3–2) data have higher angular resolution and better sensitivity than the CO( = 1–0) data. We converted from the integrated intensity of CO( = 3–2) into using the intensity ratio of CO( = 3–2) / CO( = 1–0) (hereafter ) for each cloud. The typical cloud size, virial mass, and CO-derived mass are 10–15 pc, 2000–5000 , and 1000–3000 , respectively.

### 3.3 The GMCs of LIRS 36A and LIRS 36B

Two GMCs—hereafter referred to as “LIRS 36A” and “LIRS 36B”—are also detected toward the north of the SNR [see Figure 1(b)], which were named as a single molecular cloud “LIRS 36” by the previous CO studies (e.g., Rubio et al., 1993b, 1996; Nikolić et al., 2007). The GMCs may not be strongly related with the SNR owing to their large separation from the northern shell boundary, but are possibly influenced by UV-radiation from the massive star in the Hii region DEM S23 because of their low-metal environment (e.g., Israel et al., 2003). To reveal detailed physical conditions of the GMC LIRS 36A, we performed the Large Velocity Gradient (LVG) analysis (e.g., Goldreich & Kwan, 1974; Scoville & Solomon, 1974) using the ALMA CO( = 2–1) and CO( = 2–1) data and the ASTE CO( = 3–2) data. The CO line data are suitable for deriving the velocity gradient because it traces the densest part of the cloud. We adopt the velocity gradient = 1.2 km s / 5.4 pc = 0.22 km s pc, where is the FWHM linewidth of CO( = 2–1) and is determined as an effective radius of the area whose integrated CO( = 2–1) intensity exceeds half the peak. We also assumed the abundance ratios [CO/H] and [CO/CO] = 35, following the previous GMC studies of SMC N27 and N83C (Heikkilä et al., 1999; Muraoka et al., 2017). Therefore, we adopt (km s pc), where is the abundance ratio of [CO/H].

Figure 3.2(a) shows CO profiles toward the GMC LIRS 36A. Each spectrum was smoothed to match the beam size of the ALMA CO( = 2–1) data (). We find the intensity ratios of CO( = 3–2)/CO( = 2–1) (hereafter ) 0.86, CO( = 3–2)/CO( = 2–1) (hereafter ) 4.97, and CO( = 2–1)/CO( = 2–1) (hereafter ) 0.17. The results of the LVG analysis are shown in Figure 3.2(b). The red, green, and blue lines represent , , and , respectively. The errors—as shown in shaded areas for each ratio—are estimated with noise level for each spectrum, and by assuming the relative calibration error of for the ALMA data and of for the ASTE data. Thanks to the low noise fluctuation and high calibration accuracy of the ALMA data, we finally obtained the number density of molecular hydrogen (H cm and the kinematic temperature K, which are roughly consistent with previous studies (e.g., Nikolić et al., 2007). The high is consistent with the heating due to the strong UV-radiation of LIN 78.

### 3.4 CO 3–2/1–0 Intensity Ratio

We investigate the physical condition of the molecular clouds A–H by using the ASTE CO( = 3–2) and Mopra CO( = 1–0) datasets. Figure 3.4 shows the intensity ratio map of toward RX J0046.57308. Each CO data was smoothed to match the beam size of the Mopra CO( = 1–0) data (45). We present only regions that both the data were significantly detected ( level or higher). We find that the high-intensity ratios of are seen toward southwest (clouds A–B), southeast (clouds C–D), and northwest (clouds F–G) of the SNR. By contrast, the CO clouds E and H show a relatively low intensity ratio of 0.7 or lower.

### 3.5 Hi Distribution

Figure 3.5(a) shows a large-scale Hi map obtained with ASKAP superposed on the X-rays and ASTE CO contours. We selected integration velocity range from 117.1 to 122.5 km s, which is covered the molecular clouds A–D, F, and G showing the high-intensity ratio of (see also Figure 3.4 and Table 2.1). There is an Hi intensity gradient increasing from West to East, and the brightest feature, with intensities above 700 K km s. In the direction of the SNR, we find a cavity-like structure of Hi. The boundary of Hi cavity is nicely along the X-ray shell especially in the northeastern half. On the other hand, the southwestern SNR shell has no prominent Hi structure where the molecular clouds A and B are located.

Figure 3.5(b) shows a position velocity diagram of Hi and CO. The Hi clouds lie on the velocity range from 115 to 135 km s. We find that the Hi is hollowed out at the position of (, ) (120 km s, ). The hollowed out regions is over the velocity range that shown in Figure 3.5(a) ( 117.1–122.5 km s). Moreover, the spatial extent of the hollowed out region is roughy similar to the shell size of the SNR. We also confirmed the observational trends using an archival Hi dataset (angular resolution of , velocity resolution of km s) obtained with the Australia Telescope Compact Array and the Parkes telescope published by Stanimirovic et al. (1999).

### 3.6 X-Ray Spectral Analysis

We extracted ACIS-S and ACIS-I spectra from the source region indicated in Figure 1. Background is selected as a source-free region centered at (, ) (8) with a radius of . Figure 3.6 shows the background-subtracted spectra of RX J0046.5-7308. We find O, Ne, Mg, Si, and S K-shell line emission and Fe L complex, indicating that these atoms are highly ionized.

According to a previous study with XMM-Newton (van der Heyden et al., 2004), the SNR spectrum can be well reproduced by an NEI plasma model with the electron temperature  keV and the ionization parameter s. Following them, we fitted the spectrum with an NEI model (VVRNEI in XSPEC). We separately set absorption column densities in the Milky Way () and the SMC (). We used the Tuebingen-Boulder ISM absorption model (TBabs, Wilms et al., 2000) and fixed at (Dickey & Lockman, 1990). We allowed , , and volume emission measure (VEM ) to vary. The abundances of O, Ne, Mg, Si, S and Fe are free parameters whereas those of Ar, Ca and Ni are linked to S, S and Fe, respectively. The other elements were fixed to the SMC values in the literature (He = 0.74, C = 0.21, N = 0.07, others = 0.20; Russell & Dopita, 1992).

Figure 3.6(a) and Table 3.6 show the fitting results and the best-fit parameters, respectively. The spectra are reproduced by the NEI model with  keV and s (). Obtained metal abundances of O, Ne, Mg, Si, S, and Fe are significant higher than the SMC values (O = 0.30, Ne = 0.33, Mg = 0.39, Si = 0.48, S = 0.35 and Fe = 0.40; Russell & Dopita, 1992), suggesting that the SNR plasma is possibly originating from the SN ejecta.

SNRs in the Sedov phase are generally contaminated by swept-up ISM. To estimate the contribution of the emission from the shock-heated ISM, we attempted to fit the spectra with a two-plasma model composed of the ISM and ejecta. For the ejecta component, we adopted an NEI model same as the previous fit. For the swept-up ISM, we first applied an NEI model whose abundances are fixed to the SMC values (Russell & Dopita, 1992), but its becomes larger than s. Therefore, we treat the plasma as a CIE by fixing at s. The results and the best-fit parameters are shown in Figure 3.6(b) and Table 3.6. The two-components model well reproduces the spectrum with . The fit improves the reduced from the single NEI fit, but the improvement is not statistically significant with an F-test probability of 0.13. The shell-bright X-ray morphology suggests that the shock wave heated the swept-up ISM and the SNR plasma contains a large amount of the ISM. It is consistent with our result that the VEM of the ISM component is much higher than that of the ejecta component. Therefore, we conclude that the two-components model is more suitable than the single-NEI model.

## 4 Discussion

### 4.1 Estimation of the age and typing of the SNR

In the X-ray spectral analysis, we reproduced the SNR plasma with the NEI CIE model composed of the ejecta and the swept-up ISM. We found that the ISM plasma is in the CIE state where is larger than (Masai, 1994), suggesting that RX J0046.57308 is a middle-aged SNR.

In the Sedov–Taylor phase (Sedov, 1959), the dynamical age of the SNR is descried by

 tdyn=2Rsh5Vsh (4)

where is the shock velocity, and is the radius of the SNR. We here adopt pc, which is the mean radius of the X-ray shell size (Filipović et al., 2008). Assuming the ion–electron temperature equilibration, can be derived as follows:

 Vsh=√16kBTsh3μmH (5)

where is mean atomic weight, is Boltzmann’s constant, and is the obtained shock temperature of keV (see Table 3.6). We then obtain the shock velocity km s and the dynamical age yr, which is roughly consistent with the previous X-ray study (van der Heyden et al., 2004). Since the estimated age is long, the reverse shock probably reached the center of the remnant and heated the ejecta from the surface to the core.

The spectral analysis also revealed the abundances of O, Ne, Mg, Si, S, and Fe of the ejecta component. In order to identify the SN type of RX J0046.57308, we compared the abundance pattern of the ejecta and those derived from theoretical simulations. Figure 4.2 shows abundance ratios of Ne, Mg, Si, S, and Fe to O with abundance patterns of Ia SN models (Nomoto et al., 1984; Maeda et al., 2010) and CC SN models (Kobayashi et al., 2006). The ratio Fe/O has been shown to be a better estimator of the progenitor mass than the more commonly use X/Si ratio which is usually the only one accessible for the heavily absorbed Galactic SNRs (Katsuda et al., 2018). Although it is difficult to estimate the SN type from the ratios of Ne/O, Mg/O, Si/O, and S/O because of their large uncertainties, the ratio of Fe/O clearly indicates that the remnant is a CC SN origin with a progenitor mass of and disfavours a more massive progenitor, at odds with the interpretation of Auchettl et al. (2019), based on local stellar population alone. Such a result is however consistent with X-ray spectroscopy using XMM-Newton (Maggi et al., in preparation).

### 4.2 Molecular and Atomic clouds associated with the SMC SNR RX J0046.5−7308

Over the last three decades, we have learned how to identify shocked gas clouds associated with SNRs except for morphological aspects. For the middle aged SNRs (10,000 years old), there are two pieces of evidence for the shocked molecular cloud. One is the high-intensity ratio between the CO( = 3–2) and CO( = 1–0) transitions. This ratio is a good indicator of the degree of the rotational excitation in CO because the = 3 state lies at 33.2 K from the = 0 ground state, which is 28 K above the = 1 state at 5.5 K. Arikawa et al. (1999) demonstrated that a shocked molecular cloud in W28 has a high-intensity ratio of 1.2–2.8 with OH masers (1720.5 MHz), whereas an unshocked cloud shows a low intensity ratio of 0.4–0.7. Similar trends were found in both the Galactic and Magellanic SNRs (e.g., IC 443, White 1994; Kesteven 79, Kuriki et al. 2018; LMC SNR N49, Yamane et al. 2018). The other is a broad-line profile of CO emission. A shocked molecular cloud can be accelerated about a few 10 km s if the shock-interacting time is long enough. The accelerated clouds are therefore observed as broad-line profiles in the CO emission (e.g., Wootten, 1977; Seta et al., 1998; Yoshiike et al., 2013). Recently, Sano et al. (2017a) proposed a new method to identify the interstellar gas associated with SNRs by using velocity information of gas cloud. The authors presented a hole-like (or hollowed out) structure of Hi in the position-velocity diagram toward the young SNR RCW 86 (1,800 years old). The hole-like structure means an expanding gas motion so called “wind-blown shell” created by gas winds from the progenitor system: e.g., stellar winds from a massive progenitor or accretion winds (also referred to as “disk wind”) from a single-degenerated progenitor system of the Type Ia explosion. The size of wind-blown shell generally coincides with the diameter of SNR because the free-expansion phase is short enough. Subsequent studies confirmed this idea in both the Galactic and Magellanic SNRs (e.g., Kesteven 79, Kuriki et al. 2018; LMC SNR N103B, Sano et al. 2018a; Alsaberi et al. 2019).

For RX J0046.57308, we first claim that the molecular clouds A, B, F, and G are most likely interacting with the shock waves. The physical relations between the molecular clouds and shockwaves are supported by the high-intensity ratios of without the infrared sources and/or massive stars, indicating that the shock heating occurred (e.g., White, 1994; Arikawa et al., 1999; Kuriki et al., 2018; Yamane et al., 2018). We also note that the virial mass of these clouds is typically twice higher than the CO-derived mass (see Table 2.1), possibly indicating that the SNR shocks might perturb the molecular clouds. In the morphological aspects, these molecular clouds are nicely along the X-ray shell [see Figure 1(b)]. The southwestern shell is slightly deformed along the CO clouds A and B with the brightest X-ray peak, indicating that the shock-ionization occurred (e.g., Sano et al., 2017a). On the other hand, we could not find the broad-line profiles of CO emission in the shocked molecular clouds. This is inconsistent with the old dynamical age of yr. It is possible that the sensitivity and angular resolution of ASTE CO data are not high enough to detect the broad-line profiles of CO emission. Further ALMA observations with the high-angular resolution ( pc) and high sensitivity are needed to detect the shock-accelerated molecular clouds in RX J0046.57308.

Next, we argue that Hi clouds at 117.1–122.5 km s and the molecular clouds C and D are also associated with the SNR in addition to the clouds A, B, F, and G. The hollowed out structure in the position-velocity diagram of Hi is likely an expanding gas motion originated by stellar winds from a massive progenitor. The expanding velocity is estimated to be 3 km s, which is roughly consistent with the Galactic CC SNR Kesteven 79 (4 km s, Kuriki et al., 2018). In fact, the metal abundances of the SNR favor the CC explosion (see Section 4.1), which can create the wind-blown bubble. If the interpretation is correct, the radial velocity of shock-interacting gas is to be 117.1–122.5 km s, corresponding to the velocity range of the expanding Hi shell. The molecular clouds C and D are therefore associated with the SNR because their radial velocity are 120 km s. In light of these considerations, we conclude that the molecular clouds A–D, F, G, and Hi gas at the velocity range of 117.1–122.5 km s are associated with the SNR RX J0046.57308.

### 4.3 Prospects for gamma-ray observations

We also discuss future prospects for -ray observations toward RX J0046.57308. -rays from middle-aged SNRs are mainly produced by two mechanisms: hadronic and leptonic processes. For the hadronic process, the interaction between cosmic ray and interstellar proton creates a neutral pion that quickly decays into the two -ray photons. Therefore it is also referred to as the pion-decay -rays. For the leptonic process, cosmic-ray electron energizes a low-energy photon (e.g., cosmic-microwave background and infrared photons) into the -ray energy through the inverse Compton scattering. The cosmic-ray electrons also emit -rays via non-thermal Bremsstrahlung. There are two ways to distinguish the hadronic and leptonic processes. One is searching for the spectral-break (or refer to as “pion-decay bump”) of hadronic -rays below 200 MeV (e.g., Giuliani et al., 2011; Ackermann et al., 2013). Since each neutral pion having an energy of 67.5 MeV in the rest frame, the hadronic -ray number spectrum shows symmetric about 67.5 MeV in a log-log representation (Stecker, 1971). The hadronic -ray spectrum therefore rises steeply below 200 MeV in the representation. The other is probing the good spatial correspondence between the -rays and interstellar protons, which is an essential signature of the hadronic -rays (Fukui et al., 2003, 2012, 2017; Fukui, 2013; Aharonian et al., 1994, 2008; Hayakawa et al., 2012; Yoshiike et al., 2013; Maxted et al., 2013a, b, 2018a, 2018b, 2018c; Fukuda et al., 2014; Lau et al., 2017, 2019; de Wilt et al., 2017; Sano et al., 2017c, 2018b; Kuriki et al., 2018). For RX J0046.57308, the eight molecular clouds have the potential to be detected by the TeV -rays using the Cherenkov Telescope Array with deep exposure. The -rays produced by escaped cosmic-ray protons may be detected from the nearby GMC because the physical conditions of the GMC LIRS 36A—size, mass, and the separation from the SNR—are similar to the Galactic -ray SNR W28 (e.g., Aharonian et al., 2008; Giuliani et al., 2010; Abdo et al., 2010). RX J0046.57308 and its surroundings possibly provide us with the best laboratory to search the hadronic -rays originated by the shock-accelerated and/or escaped cosmic ray protons in the SMC.

## 5 Conclusions

We have presented new CO( = 1–0, 2–1, 3–2) and CO( = 2–1) observations and Hi toward the SMC SNR RX J0046.57308 using ASTE, Mopra, ALMA, and ASKAP. The primary conclusions are summarized as below.

1. We have reveled the eight molecular clouds A–H along the X-ray shell of the SNR, which are significantly detected by CO( = 3–2) line emission obtained with ASTE. The typical cloud size and mass are 10–15 pc and 2000–5000 , respectively. The X-ray shell is slightly deformed and has the brightest peak in the southwestern shell where the molecular clouds A and B are associated. The four molecular clouds A, B, F, and G show the high-intensity ratios of without the infrared sources and/or massive stars. These results provide the first evidence for the shock-heated molecular clouds in the SMC.

2. The Hi cavity-like structure is found toward the SNR, which is also observed as a hollowed out structure in the position-velocity diagram. The hollowed out structure of Hi is likely an expanding gas motion with an expanding velocity of 3 km s, which originated by stellar winds from massive progenitor. If the interpretation is correct, the radial velocity of shock-interacting gas is to be 117.1–122.5 km s, including the peak radial velocities of molecular clouds C and D. We finally conclude that the molecular clouds A–D, F, G, and Hi gas within a velocity range of 117.1–122.5 km s are to be associated with the SNR RX J0046.57308.

3. The X-ray spectral analysis revealed that the SNR plasma can be reproduced the NEI CIE model composed of the ejecta and the swept-up ISM. Assuming the Sedov–Taylor phase, the dynamical age of the SNR is estimated to be yr, which is roughly consistent with the previous X-ray studies (van der Heyden et al., 2004). We also obtained the abundances of O, Ne, Mg, Si, S, and Fe of the ejecta. The lower ratio of Fe/O suggesting that the SNR is originated by a CC SN with a progenitor mass of .

4. To derive the physical conditions of the GMC LIRS 36A, we carried out the LVG analysis using the CO( = 2–1, 3–2) and CO( = 2–1) datasets obtained with ASTE and ALMA. We obtained the number density of molecular hydrogen of cm and the kinematic temperature of K. Since the GMC is located far from the shell boundary of the SNR, the GMC may not be affected by the SNR shockwaves. The high kinematic temperature is therefore due to the heating by the massive exciting star LIN 78 in the Hii region DEM S23.

5. We found that the physical conditions of the molecular clouds toward RX J0046.57308 are similar to that of the Galactic -ray SNR W28. We therefore suggest that RX J0046.57308 and its surrounding molecular clouds provide us with the best laboratory to search the pion-decay -rays originated by the shock-accelerated and/or escaped cosmic ray protons in the SMC.

This paper makes use of the following ALMA data: ADS/JAO.ALMA #2015.1.00196.S. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada) and NSC and ASIAA (Taiwan) and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO and NAOJ. The ASTE radio telescope is operated by NAOJ. The Mopra radio telescope and Australian SKA Pathfinder (ASKAP) are part of the Australia Telescope National Facility which is managed by CSIRO. The University of New South Wales Mopra Spectrometer Digital Filter Bank used for these Mopra observations was provided with support from the Australian Research Council, together with the University of New South Wales, the University of Adelaide, University of Sydney, Monash University, and the CSIRO. 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 Centre. Establishment of ASKAP, the Murchison Radio-astronomy Observatory, and the Pawsey Supercomputing Centre are initiatives of the Australian Government, with support from the Government of Western Australia and the Science and Industry Endowment Fund. We acknowledge the Wajarri Yamatji people as the traditional owners of the Observatory site. The scientific results reported in this article are based on data obtained from the Chandra Data Archive (Obs ID: 3904, 14674, 15507, and 16367). This research has made use of software provided by the Chandra X-ray Center (CXC) in the application packages CIAO (v 4.10). This study was financially supported by Grants-in-Aid for Scientific Research (KAKENHI) of the Japanese Society for the Promotion of Science (JSPS, grant No. 16K17664 and 18J01417). H.S. was supported by “Building of Consortia for the Development of Human Resources in Science and Technology” of Ministry of Education, Culture, Sports, Science and Technology (MEXT, grant No. 01-M1-0305). H.M. was supported by World Premier International Research Center Initiative (WPI). K. Tokuda was supported by NAOJ ALMA Scientific Research (grant No. 2016-03B). H.S. was also supported by the ALMA Japan Research Grant of NAOJ Chile Observatory (grant Nos. NAOJ-ALMA-201 and NAOJ-ALMA-208). Software: CASA (v 4.5.3.: McMullin et al., 2007), CIAO (v 4.10: Fruscione et al., 2006).

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