Issue |
A&A
Volume 690, October 2024
|
|
---|---|---|
Article Number | A161 | |
Number of page(s) | 31 | |
Section | Catalogs and data | |
DOI | https://doi.org/10.1051/0004-6361/202450730 | |
Published online | 03 October 2024 |
Discovery of ~2200 new supernova remnants in 19 nearby star-forming galaxies with MUSE spectroscopy
1
Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg,
Mönchhofstraße 12–14,
69120
Heidelberg,
Germany
2
Department of Astronomy, The Ohio State University,
140 West 18th Avenue,
Columbus,
OH
43210,
USA
3
International Centre for Radio Astronomy Research, University of Western Australia,
7 Fairway,
Crawley,
WA
6009,
Australia
4
Space Telescope Science Institute,
3700 San Martin Drive,
Baltimore,
MD
21218,
USA
5
European Southern Observatory (ESO),
Alonso de Córdova 3107, Casilla 19,
Santiago
19001,
Chile
6
INAF – Arcetri Astrophysical Observatory,
Largo E. Fermi 5,
50125,
Florence,
Italy
7
Zentrum für Astronomie, Universität Heidelberg, Institut für Theoretische Astrophysik,
Albert-Ueberle-Str. 2,
69120
Heidelberg,
Germany
8
European Southern Observatory (ESO),
Karl-Schwarzschild-Straße 2,
85748
Garching,
Germany
9
Argelander-Institut für Astronomie, Universität Bonn,
Auf dem Hügel 71,
53121
Bonn,
Germany
10
Observatories of the Carnegie Institution for Science,
813 Santa Barbara Street,
Pasadena,
CA
91101,
USA
11
Departamento de Astronomía, Universidad de Chile,
Camino del Observatorio 1515, Las Condes,
Santiago,
Chile
12
Research School of Astronomy and Astrophysics, Australian National University,
Canberra,
ACT 2611,
Australia
13
Universität Heidelberg, Interdisziplinäres Zentrum für Wissenschaftliches Rechnen,
Im Neuenheimer Feld 205,
69120
Heidelberg,
Germany
14
Max-Planck-Institut für Astronomie,
Königstuhl 17,
69117
Heidelberg,
Germany
15
Sub-department of Astrophysics, Department of Physics, University of Oxford,
Keble Road,
Oxford
OX1 3RH,
UK
★ Corresponding author; e-mail: Jing.Li@uni-heidelberg.de
Received:
15
May
2024
Accepted:
26
July
2024
Supernova feedback injects energy and turbulence into the interstellar medium (ISM) in galaxies, influences the process of star formation, and is essential to understanding the formation and evolution of galaxies. In this paper we present the largest extragalactic survey of supernova remnant (SNR) candidates in nearby star-forming galaxies using exquisite spectroscopic maps from MUSE. Supernova remnants (SNRs) exhibit distinctive emission-line ratios and kinematic signatures, which are apparent in optical spectroscopy. Using optical integral field spectra from the PHANGS–MUSE project, we identified SNRs in 19 nearby galaxies at ~100 pc scales. We used five different optical diagnostics: (1) line ratio maps of [S II]/Hα (2) line ratio maps of [O I]/Hα (3) velocity dispersion map of the gas; and (4) and (5) two line ratio diagnostic diagrams from Baldwin, Phillips & Terlevich (BPT) diagrams to identify and distinguish SNRs from other nebulae. Given that our SNRs are seen in projection against H II regions and diffuse ionized gas, in our line ratio maps we used a novel technique to search for objects with [S II]/Hα or [O I]/Hα in excess of what is expected at fixed Hα surface brightness within photoionized gas. In total, we identified 2233 objects using at least one of our diagnostics, and defined a subsample of 1166 high-confidence SNRs that were detected with at least two diagnostics. The line ratios of these SNRs agree well with the MAPPINGS shock models, and we validate our technique using the well-studied nearby galaxy M83, where all the SNRs we found are also identified in literature catalogs, and we recovered 51% of the known SNRs. The remaining 1067 objects in our sample were detected with only one diagnostic, and we classified them as SNR candidates. We find that ~35% of all our objects overlap with the boundaries of H II regions from literature catalogs, highlighting the importance of using indicators beyond line intensity morphology to select SNRs. We find that the [O I]/Hα line ratio is responsible for selecting the most objects (1368; 61%); however, only half are classified as SNRs, demonstrating how the use of multiple diagnostics is key to increasing our sample size and improving our confidence in our SNR classifications.
Key words: catalogs / supernovae: general / ISM: supernova remnants / galaxies: ISM
© The Authors 2024
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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