# Properties of supernova remnants in SIGNALS galaxies - I . NGC 6822 and M33

Salvador Duarte Puertas1,2,3,4, Laurent Drissen3,4, Carmelle Robert3,4, Laurie
Rousseau-Nepton5,6,7, R. Pierre Martin8, Philippe Amram9, Thomas Martin3,10
1Departamento de Física Teórica y del Cosmos, Universidad de Granada, 18071
Granada, Spain
2Instituto Carlos I de Física Teórica y Computacional, Universidad de Granada,
Granada, Spain
3Département de physique, de génie physique et d’optique, Université Laval,
Québec (QC), G1V 0A6, Canada
4Centre de recherche en astrophysique du Québec
5Dunlap Institute of Astronomy and Astrophysics, University of Toronto, 50 St.
George St, Toronto, ON, M5S 3H4, Canada
6Canada-France-Hawaii Telescope, 65-1238 Mamalahoa Hwy, Kamuela, Hawaii 96743,
USA
7Department of Astronomy & Astrophysics at the University of Toronto, 50 St.
George St, Toronto, ON, M5S 3H4, Canada
8Department of Physics and Astronomy, University of Hawai’i at Hilo, Hilo, HI
96720, USA
9Aix Marseille Univ, CNRS, CNES, LAM, Marseille, France
10Cégep Garneau, 1660 Boulevard de l’Entente, Québec, QC G1S 4S3, Canada
E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

We present a spatially resolved study of the kinematical properties of known
supernova remnants (SNRs) in the nearest galaxies of the SIGNALS survey,
namely NGC 6822 (one object) and M33 (163 objects), based on data obtained
with the SITELLE Imaging Fourier Transform Spectrometer (iFTS) at the Canada-
France-Hawaii Telescope. The purpose of this paper is to provide a better
scheme of identification for extragalactic SNRs and, in particular, to
distinguish between HII regions and SNRs. For that we have used diagrams which
involve both the [SII]/H$\alpha$ ratio and the velocity dispersion ($\sigma$).
We also introduce a new parameter, $\xi={[SII]\over H\alpha}\times\sigma$,
which enhances still the contrast between SNRs and the rest of the ionised
gas. More than 90% of the SNRs in our entire sample show an integrated
[SII]/H$\alpha$ ratio larger than the canonical value (0.4). 86% of the SNRs
present in our field show a significant velocity dispersion. The spectral
resolution of our observations allows us to observe the complex velocity
structure of some SNRs.

###### keywords:

galaxies: individual: M33, NGC 6822 – galaxies: ISM – ISM: supernova remnants
– HII regions

††pubyear: 2024††pagerange: Properties of supernova remnants in SIGNALS
galaxies - I . NGC 6822 and M33–SUPPORTING INFORMATION

##  1 Introduction

A core-collapse supernova (SN) is the most dramatic stage in the life of a
massive ($>$ 8 M⊙) star, where it cannot maintain gravitational equilibrium
and its core collapses, bounces back, thus generating a shock wave which,
under favorable conditions (Gogilashvili & Murphy, 2022), leads to the fast
ejection of a large fraction of the stellar envelope. The result of the
interaction between this rapidly ejected material and the surrounding
circumstellar (in the very early stages) and interstellar medium (ISM), known
as a supernova remnant (SNR), brightly shines for thousands of years with
distinct signatures across the electromagnetic spectrum (Long, 2017). SNRs are
thus, in principle at least, relatively easy to identify in the Local
Universe. Because both Type Ia and core-collapse supernovae play a key role in
the chemical evolution of galaxies and the dynamics of the interstellar
medium, studying the properties of SNRs provides an essential element to our
understanding of the global ISM in nearby galaxies.

In the visible part of the spectrum, the [SII]/H$\alpha$ ratio is
traditionally used to distinguish between SNRs and HII regions: HII regions
typically have values of [SII]/H$\alpha\sim$ 0.1 (e.g., Dodorico & Sabbadin,
1976; Long et al., 2010) while SNRs have a value of at least 0.4. The diffuse
ionized medium (DIG) however also presents high values of this ratio,
complicating the unambiguous identification of SNRs. In addition to the
traditional one, there are other non-empirical identification methods using
different emission line ratios (e.g. Kopsacheili et al., 2020; Congiu et al.,
2023). Kopsacheili et al. (2020) point out that a large number of shock models
have [SII]/H$\alpha$ ratios lower than 0.4, and in particular that the use of
0.4 as a strict cutoff disfavours the identification of SNRs with slow shock
velocities (see however Winkler et al., 2023).

Long et al. (2018) noticed that a substantial number of SNR candidates in M33
show larger emission line widths than HII regions and suggests that velocity
broadening could be a potential discriminant to appropriately select SNRs.
Following this finding, Points et al. (2019) proposed to use measurements of
the kinematics of extragalactic SNR candidates in addition to the widely used
[SII]/H$\alpha$ ratio as a means to “purify" the surveys. They illustrate this
by using long-slit spectra of well-known SNRs in the Large Magellanic Clouds
and a sample in M83.

In the present work, we follow in their footsteps by studying known SNRs in
two Local Group galaxies, NGC 6822 (Dopita et al., 2019) and M33 (Long et al.,
2010; Lee & Lee, 2014), using datacubes obtained with the imaging Fourier
transform spectrometer (iFTS) SITELLE at the Canada-France-Hawaii telescope
(CFHT). These data are part of the SIGNALS survey (Rousseau-Nepton et al.,
2019), one of CFHT’s Large Programs, which aims at studying massive star
formation and HII regions in a sample of local (distance $\leq$ 10 Mpc)
extended galaxies by measuring bright line ratios and kinematics.

While most previous kinematics studies of SNRs in M33 are based on long-slit
and fibre spectroscopy and thus do not sample the entire area of the objects,
SITELLE (Drissen et al., 2019) allows us to perform a spatially resolved study
of all the targets alongside that of their surrounding HII regions and DIG,
thanks to its wide field-of-view (11${}^{\prime}\times 11^{\prime}$).
Moreover, in the H$\alpha$ spectral region111In the case of nearby galaxies,
such as the complete sample of galaxies in the SIGNALS project, the H$\alpha$
spectral region refers to the SN3 bandpass., SIGNALS’ nominal resolution of R
= 5000 (see below) is very close to that suggested by Points et al. (2019) for
the purpose of discriminating SNRs from HII regions.

The vast majority of SIGNALS target lie beyond the Local Group (median
distance = 4 Mpc), but selected fields in nearby galaxies (M33, M31, NGC 6822,
WLM, Sextans A and IC 1613) have also been targeted in order to serve as
templates for the rest of the sample. Although the focus of SIGNALS is on HII
regions and massive star formation, the sample is also very well suited for
the study of SNRs. The initial goal of the present work was to combine the
standard [SII]/H$\alpha$ criterion with the 2D and integrated velocity
dispersion ($\sigma$) information in order to provide a framework allowing a
clear and unambiguous identification of SNRs in the Local Group that could be
used for more distant gas-rich galaxies. This is thus the first in a series of
papers dedicated to this topic.

The structure of this paper is organised as follows: in Sect. 2 we describe
the observations, the data reduction and the analysis of the data. In Sect. 3
we present the morphological and kinematical results of Ho 12, the SNR in NGC
6822, and we show the scheme of identification proposed in this work. The
application of this identification scheme to a sample of SNR candidates from
M33 can be seen in Sect. 4; Finally, in Sect. 5 we present our conclusions.

##  2 Observations, data reduction and analysis

Table 1: Characteristics of the datacubes. Field | RA | Dec | Filter | R | Exposure/step | Num. Steps | Date
---|---|---|---|---|---|---|---
NGC 6822 | 19:44:47.6 | -14:45:22 | SN3 | 3300 | 21s | 590 | July 5, 2017
|  |  | SN2 | 560 | 82s | 132 | June 30, 2017
|  |  | SN1 | 400 | 139s | 69 | July 9, 2016
M33-F1 | 01:34:24.1 | +30:44:56 | SN3 | 2900 | 18s | 505 | October 12, 2017
|  |  | SN2 | 1020 | 38s | 219 | September 28, 2017
|  |  | SN1 | 1020 | 49s | 172 | September 28, 2017
M33-F2 | 01:33:36.2 | +30:42:57 | SN3 | 2900 | 18s | 505 | October 13, 2017
|  |  | SN2 | 1020 | 38s | 219 | September 28, 2017
|  |  | SN1 | 1020 | 49s | 172 | September 28, 2017
M33-F3 | 01:34:24.1 | +30:34:33 | SN3 | 2900 | 18s | 505 | October 17, 2017
|  |  | SN2 | 1020 | 38s | 219 | September 28, 2017
|  |  | SN1 | 1020 | 49s | 172 | September 28, 2017
M33-F4 | 01:33:33 | +30:32:55 | SN3 | 2200 | 18s | 403 | October 13, 2017
|  |  | SN2 | 1020 | 38s | 219 | September 28, 2017
|  |  | SN1 | 1020 | 49s | 172 | September 28, 2017
M33-F5 | 01:34:00.1 | +30:53:35 | SN3 | 5000 | 13s | 842 | October 2, 2021
|  |  | SN2 | 1020 | 46s | 219 | October 4, 2021
|  |  | SN1 | 1020 | 59s | 171 | October 6, 2021
M33-F6 | 01:33:19.1 | +30:51:51 | SN3 | 5000 | 13s | 842 | September 30, 2021
|  |  | SN2 | 1020 | 46s | 219 | November 5, 2021
|  |  | SN1 | 1020 | 59s | 171 | November 10, 2021
M33-F7 | 01:32:50.7 | +30:34:50 | SN3 | 5000 | 13s | 842 | October 4, 2018
|  |  | SN2 | 1020 | 46s | 220 | October 11, 2018
|  |  | SN1 | 1000 | 59s | 171 | October 12, 2018
M33-F8 | 01:32:51.1 | +30:22:34 | SN3 | 5000 | 13s | 842 | October 15, 2020
|  |  | SN2 | 1020 | 46s | 219 | December 8, 2020
| 01:32:47.1 | +30:22:44 | SN1 | 1000 | 59s | 171 | 17 November 2020
M33-F9 | 01:33:41.6 | +30:18:47 | SN3 | 5000 | 13s | 842 | September 29, 2019
| 01:33:42.6 | +30:20:57 | SN2 | 1020 | 46s | 220 | December 11, 2020
| 01:33:38.6 | +30:21:08 | SN1 | 1000 | 59s | 171 | November 14, 2020

SITELLE provides the spatially resolved spectrum of the sources in an
$11^{\prime}\times 11^{\prime}$ field of view with a sampling of
$0.32^{\prime\prime}$/pixel, in selected bandpasses of the visible range, with
a spectral resolution adapted to the need of the observer. Three bandpasses,
centered on the HII regions’ bright lines, are used in SIGNALS: SN3 (647 - 685
nm, R = 5000), SN2 (482 - 513 nm, R = 1000) and SN1 (363 - 386 nm, R = 1000).
The SN3 datacubes (which include H$\alpha$, the [NII] $\lambda\lambda$ 6548,84
doublet and the [SII] $\lambda\lambda$ 6717,31 doublet) provide the required
kinematics information as well as the [SII]/H$\alpha$ ratio traditionally used
to identify SNRs. In this paper, we will also show images extracted from the
SN1 and SN2 datacubes, although a detailed analysis of the line ratios will
not be presented.

Half of the data cubes used in this paper (NGC 6822, M33 Fields 1 to 4) were
observed as part of SIGNALS’ proof of concept program; the spectral resolution
and total exposure times of some of them therfore did not meet the SIGNALS
standards (exemplified by Fields 5 to 9 in M33, see Table 1). Nevertheless,
with a spectral resolution of R $\sim$3000 in the H$\alpha$ spectral region
(SN3 filter), these data are of sufficient quality to start our investigation
of SNRs in Local Group galaxies.

The raw data, consisting of two complementary 2D interferograms (acquired
using the two CCDs on the receiving end of the Michelson; see Drissen et al.,
2019) were transformed into a single fully calibrated spectral datacube with
ORBS, SITELLE’s dedicated data reduction software (Martin et al., 2015).
Photometric calibration is secured from images and data cubes of
spectrophotometric standard stars such as G93-48, P330E and HZ21. Wavelength
calibration is performed using a high spectral resolution laser data cube. It
may show distortions due to aberrations and deformations in the optical
structure, leading to zero-velocity offsets of $\sim 15-20$ km/s across the
field of view. We thus refine the wavelength calibration by measuring the
centroid positions of the night sky OH emission lines (in the SN3 filter) in
the science data cubes following the procedure described in Martin et al.
(2018), reducing the uncertainty on the velocity calibration across the entire
field to less than 2 km/s. We also applied a barycentric correction to the
observed spectra.

Spectral data from SITELLE (Fig. 1) can be a bit confusing for first-time
users, for two reasons. First, the natural units of an FTS are wavenumbers
(cm-1): in the SN3 datacube, the [SII] doublet is therefore to the left of
H$\alpha$. Secondly, each line is surrounded by oscillating sidelobes,
alternating between positive and negative values.This is because, as described
by Martin et al. (2016), SITELLE’s Instrument Line Shape (ILS) is a sinc
function. However, any line broadening caused by turbulent motion, an
expanding bubble or a velocity gradient along an extended aperture will
transform the natural ILS into a so-called sincgauss function, the convolution
of a sinc and a gaussian. ORCS, SITELLE’s analysis software suite (Martin &
Drissen, 2020), is thus used to fit the observed line profiles for each pixel
of the field of view (or an integrated region within it) and produce maps (or
single values) of line intensities, radial velocity, and velocity dispersion
(identified as $\sigma$) as well as their uncertainties.

We note that since $\sigma$ characterizes the gaussian function which,
convoluted with the ILS, reproduces the observed line shape, it represents the
natural line broadening beyond the instrumental one. The minimum line
broadening measurable with ORCS is a function of the cube’s spectral
resolution and the signal-to-noise ratio (S/N) of the data (see Fig. 2 in
Martin et al., 2016). With the current SN3 data cubes, this value is of the
order of 10 - 15 km s-1. Figure 1 shows fits to integrated (circles of 5 pixel
radius) spectra of three regions in the M33-F9 field, illustrating the effect
of line broadening on the spectral profile. On the left, a small ($\sim$ 25 pc
diameter) HII region with a barely detectable broadening. Note the oscillating
sidelobes of the iFTS sinc profile, which extend well beyond the [NII]
doublet. The central spectrum is that of a part of a large HII complex with
multiple expanding filaments along the line of sight, well discernable when
moving through the spectral cube. With an easily measurable line broadening,
we notice that the sidelobes display a significantly lower amplitude than the
left-hand spectrum. On the right, a portion of one SNR in M33; the width of
the central peak in indeed about twice that of the instrumental profile, and
the sinc sidelobes are barely detectable between H$\alpha$ and the [NII]
lines. These spectra are fits to real data, and are therefore noiseless and
thus amenable to a pedagogical demonstration. But, as we shall see throughout
this paper, actual data also clearly show this behaviour and ORCS’s ability to
fit them and extract the required properties of the source.

ORCS simultaneously fits all the lines within a given data cube, but allows
the user to either force identical velocities and velocity dispersion for all
the lines, to let them completely independent of each other, or to select
groups of lines with the same values. The maps and integrated spectra
presented in this paper were obtained with the first option, but we also
looked at the impact of allowing the values of velocity dispersion for the
[SII] doublet and H$\alpha$ to differ from each other (see section 4.2).

To produce the 2D maps, we chose to subtract a common background to all pixels
in a given cube, selected from a region without any obvious nebular
contribution. For the integrated spectrum of individual objects, a nearby
background devoid of bright HII regions was selected. This choice is also
discussed in section 4.2.

Figure 1: Normalized ORCS fits to the integrated spectrum of three regions in
M33, showing the effects of the line broadening on a datacube with R = 5000
spectral resolution. See text for details. Figure 2: Composite image
($10^{\prime}\times 10^{\prime}$, with North up and East to the left) of NGC
6822 from the SN2 and SN3 deep frames (see text). HII regions Hubble-I, II and
III (discussed later) are identified. The insert shows the location of Ho 12.
Asteroid (654) Zelinda is seen crossing the field of view near the center of
the image.

##  3 Ho 12 in NGC 6822

Barnard’s galaxy (NGC 6822) is the nearest target of the SIGNALS sample
($\sim$0.52 Mpc, see Table A.1 in Rousseau-Nepton et al., 2019) and as such
offers an excellent opportunity to study its nebular content with exquisite
details. At the distance of NGC 6822, 1${}^{\prime\prime}\sim$ 2.5 pc. The
oxygen abundance of NGC 6822 is 12+log(O/H) = 8.14 $\pm$ 0.08 (Bresolin et
al., 2016). Only one SNR has been identified in this dwarf irregular galaxy,
and it was first catalogued as an HII region (No. 12, hereafter Ho 12) by
Hodge (1969). Detailed analyses of this object have been performed by Kong et
al. (2004) using X-ray and radio data as well as narrow-band visible images,
and, more recently, by Dopita et al. (2019) using the integral field
spectrograph WiFeS at the ANU 2.3 m telescope. The later concentrated on the
analysis of Ho 12’s line ratios but did not provide information on its
kinematics.

Figure 3: (upper panel) H$\alpha$ image of Ho 12 (17.3′′, or 43 pc, on a
side), with the knots labelled. (Lower panel) Emission line maps:
[OII]$\lambda$3727 from the SN1 cube; H$\beta$ and [OIII]$\lambda$5007 from
the SN2 cube; H$\alpha$, [NII]$\lambda$6584 and [SII]$\lambda\lambda$6717,6731
from the SN3 cube. North is at top, East to the left.

Figure 4: Integrated spectrum (r = 4.2′′ = 10.5 pc) of NGC 6822-Ho 12, with
fits using one velocity component (panel a) and three velocity components
(panel b). Green and blue coloured lines show the fit obtained in the SN2
(panel c) and SN1 (panel d) filters, respectively; residuals from the fit are
also shown in the lower panels.

###  3.1 Morphology and integrated spectrum

Figure 2 presents Ho 12 in the context of SITELLE’s data. While Fourier
transforms of the interferograms collected by SITELLE lead to the spectral
content of the source, adding all the individual frames from these
interferograms provides a deep image in the bandpass of the filter. Figure 2
is a color-coded rendering of the SN2 (blue) and SN3 (orange) deep images of
the entire field, along with an insert enlarging the region around Ho 12 to
emphasize the spatial resolution of the data. The yellow stripe in the center
of this image is not an artefact, but rather the asteroid (654) Zelinda
crossing the field of view.

Composed of a series of knots seemingly aligned in a spiral shape, bathing in
a more diffuse component, all within a diameter of $\sim$21 pc (Fig. 3), Ho 12
shows a very peculiar morphology at all wavelengths. In the upper panel of
Fig. 3, we have identified 10 substructures for future reference. Knots 1, 5
and 10 are clearly elongated and could be further subdivided with higher
resolution data. The H$\alpha$ flux of these knots, their average heliocentric
velocity and velocity dispersion are presented in Table 2. The lower panel of
fig. 3 presents Ho 12 in different emission lines: [OII]$\lambda$3727 from the
SN1 cube; H$\beta$ and [OIII]$\lambda$5007 from the SN2 cube; H$\alpha$,
[NII]$\lambda$6584, and [SII]$\lambda\lambda$6717,6731 from the SN3 cube.
These images can be compared with fig. 3 from Dopita et al. (2019) and fig. 1
from Kong et al. (2004). Images at [NII] and [OII] have, to our knowledge,
never been published. As with all nebulae in NGC 6822, the [NII] lines are
weak, reflecting the low metallicity of this galaxy.

Ho 12’s background-subtracted, integrated spectrum in the SN3, SN2, and SN1
filters, using a circular aperture with a radius of 13 pixels (4.2′′, or 10.5
pc), is shown in Fig. 4. The upper panel of this figure also presents a fit,
using ORCS, considering only a single velocity component. Although the overall
fit is relatively good, a close inspection of the H$\alpha$ line and its
residuals reveals that the fit missed a weak red component, did not reproduce
the peak of the line, as well as the blue wing. We therefore included three
components in the fit, the result of which is shown in the lower panel of the
same figure. The flux, central velocities and broadening of these individual
components are:

F1(H$\alpha$) = $5.77\pm 0.31\times 10^{-14}$ erg cm-2 s-1, V${}_{1}=-63\pm 2$
km s-1, $\sigma_{1}=58\pm 3$ km s-1

F2(H$\alpha$) = $0.89\pm 0.15\times 10^{-14}$ erg cm-2 s-1, V${}_{2}=-194\pm
2$ km s-1, $\sigma_{2}=24\pm 8$ km s-1

F3(H$\alpha$) = $0.46\pm 0.12\times 10^{-14}$ erg cm-2 s-1, V${}_{3}=+138\pm
2$ km s-1, $\sigma_{3}=59\pm 14$ km s-1

The total flux, Ftot(H$\alpha$) = $7.12\pm 0.36\times 10^{-14}$ erg cm-2 s-1,
is in excellent agreement with the value of $6.9\times 10^{-14}$ erg cm-2 s-1
(no uncertainty provided) from Kong et al. (2004), obtained with a similar
aperture in narrow-band images from the Local Group Survey (Massey et al.,
2006). The global line ratios are [NII]/H$\alpha$ = 0.096 and [SII]/H$\alpha$
= 0.52, virtually identical to those obtained by Dopita et al. (2019). This
fit ensures a precise measurement of the line fluxes, but the real velocity
structure of Ho 12 is much more complex than a three-component model would
suggest, however good the fit might be, as we shall see in the next section.

Table 2: Properties of the knots in Ho 12. Values are obtained within the limits of the contours shown in Fig. 3. Knot | F(H$\alpha$) | Vhelio | $\sigma$
---|---|---|---
| 10-15erg cm${}^{-}2$ s-1 | km/s | km/s
1 | 6.1 | -160 | 71
2 | 4.1 | -115 | 73
3 | 1.3 | -111 | 83
4 | 2.7 | -44 | 58
5 | 9.6 | -57 | 65
6 | 2.1 | -60 | 57
7 | 1.4 | -70 | 45
8 | 0.8 | -57 | 60
9 | 1.8 | -63 | 45
10 | 3.4 | -36 | 70

###  3.2 Kinematics

Figure 5 presents the individual frames within the SN3 datacube, centered on
H$\alpha$, spanning nearly 400 km/s, showing the complex velocity structure of
Ho 12. This is emphasized in the three-dimensional view (R.A., Dec, and radial
velocity) shown in Fig. 6 as well as the upper left panel of Fig. 7, obtained
by fitting a single component to the spectra of individual pixels. We did not
attempt to fit two components (which would correspond to the receding and
approaching caps of the expanding supernova remnant) because the spectral
resolution was insufficient to clearly distinguish two peaks in the individual
spectra; therefore the resulting velocity is the flux-averaged one along the
line of sight, most likely favoring the blueshifted component. Indeed, while
the average heliocentric velocity of HII regions in the surroundings of Ho 12
is $\sim-50$ km/s, that of Ho 12 is $\sim-75$ km/s. The brightest component of
knot 1 shows the most blueshifted velocity (with an average of $\sim$-175
km/s) while the most redshifted region ($\sim$-5 km/s) corresponds to the
diffuse zone between knots 9 and 10.

Figure 7 shows the maps and three-dimensional views of the radial velocity
(upper panel) and velocity dispersion ($\sigma$, middle panel), and their
radial profiles along Ho 12. The outer, diffuse, component reaches velocities
($\sim-50$ km/s) virtually identical to those of neighboring HII regions. As
expected for an expanding shell, the velocity dispersion decreases towards the
outskirts of the supernova remnant222Geometrically, in the central part of an
expanding shell, the distance between the H$\alpha$ emission line produced by
the farthest and the nearest layers is maximum and the $\sigma$ will be
maximum; on the contrary, as we move towards the outermost part of the SNR,
the smaller the distance becomes the smaller the $\sigma$. This can be seen in
Ho 12 (see Fig. 7) and in the shell and compact SNRs in M33 (see Section
4.1)., but the complex knotty structure of Ho 12 is reflected in the broad
range of values at a given distance. Not surprisingly, the largest velocity
dispersion values (above 100 km/s, like nowhere else in the entire galaxy) are
found in the diffuse regions between the central knots: their flux is not
dominated by a single entity but reflects the kinematics of the gas from one
side to the other along the line of sight. We come back to these properties of
Ho 12 in comparison with the largest HII regions of NGC 6822 (Hubble I, II,
and III) in Sect. 3.4.

Figure 5: Consecutive frames centered on the H$\alpha$ line (from the SN3 data
cube) showing the velocity structure of Ho 12.

Figure 6: Three-dimensional view of Ho 12 (R.A., Dec, and radial velocity
diagram). The greyscale indicates the H$\alpha$ flux. Figure 7: Map of radial
velocity and three-dimensional view (R.A., Dec, and radial velocity)of Ho 12
color-coded by the radial velocity (upper panels), map of $\sigma$ and three
dimensional view color-coded by the $\sigma$ (middle panels), and its radial
profiles along Ho 12 (lower panels). Individual pixels in the radial profiles
are color-coded according to their radial velocity. Black crosses and red
solid lines represent the medians at a given projected distance and a
polynomial fit to the data, respectively. Figure 8: Maps of [SII]/H$\alpha$
(upper left panel), log([OIII]/H$\beta$) (upper middle panel), and
log([NII]/H$\alpha$) (upper right panel) of Ho 12 and their corresponding
radial profiles. All the pixels in the radial profiles are color-coded
according to their radial velocity, from the reddest (+15 km/s) to the bluest
color (-185 km/s). Black crosses and red solid lines represent the medians at
a given projected distance and a polynomial fit to the data, respectively.

###  3.3 Line ratios and global trends

Figure 8 shows the following line ratio maps of Ho 12: [SII]/H$\alpha$,
log([OIII]/H$\beta$), and log([NII]/H$\alpha$) and their corresponding radial
profiles. Throughout Ho 12, the vast majority of pixels ($>$ 95%) show an
[SII]/H$\alpha$ ratio larger than 0.4, where the highest values are reached in
the inner part. The log([NII]/H$\alpha$) ratio also decreases outwards, with
an average value of -1.01, typical for a low-metallicity galaxy. Adjacent
individual knots often have very different line ratios, and the
log([OIII]/H$\beta$) map is very patchy, which is reflected in its
corresponding radial profile with no clear radial trend. A detailed study of
individual knots in Ho 12, as well as that of the structure of M33 supernova
remnants, is certainly warranted but beyond the scope of this paper.

###  3.4 Simultaneous use of [SII]/H$\alpha$ and $\sigma$

Supernova remnants are not the only objects showing large values of
[SII]/H$\alpha$ or velocity dispersion in galaxies. Outside of AGNs (which
often display both concurrently), the central parts of giant HII regions show
significant velocity dispersion due to the effects of stellar winds and
supernovae (Terlevich et al., 2015), while their outskirts, like the diffuse
ionised gas, show large values of [SII]/H$\alpha$ (Pellegrini et al., 2020).
The purpose of this paper being to provide a better scheme of identification
for extragalactic SNRs and in particular to distinguish them from HII regions
using both the [SII]/H$\alpha$ ratio and $\sigma$ from SITELLE data cubes, we
will now make use of the product of these two properties, $\xi$ =
([SII]/H$\alpha)\times\sigma$, on a pixel-by-pixel basis and in the integrated
spectrum (see also Vicens-Mouret et al., 2023). We will also compare these
properties in Ho 12 and in three large HII regions in NGC 6822 as a testbed
for M33 and more distant galaxies.

Figure 9: Map of $\xi$ and three-dimensional view (R.A., Dec, and radial
velocity) of Ho 12 color-coded by $\xi$ (upper panels), and its radial profile
along Ho 12 (lower panels). All the points in the radial profiles are color-
coded by its radial velocity, red higher and blue lower. Black crosses and red
solid lines represent the medians and polynomial fit of each property and the
projected distance, respectively.

Figure 10: [SII]/H$\alpha$ ratio, $\sigma$, and $\xi$ maps of the large HII
regions Hubble I (region at north-west), Hubble III (region at north-east) and
Hubble II (region at south) in NGC 6822. The lower panels show, from top to
bottom, the normalized radial profiles, r/rmax, of [SII]/H$\alpha$,
log([OIII]/H$\beta$), log([NII]/H$\alpha$), radial velocity, $\sigma$, and
$\xi$. The median of each properties along the normalized radius in bins of
0.32 arcsec is shown for the SNR Ho 12 (red circles) and the HII regions
Hubble I (blue crosses), Hubble II (magenta squares) and Hubble III (green
diamonds). To derive the medians of each HII regions we considered all pixels
with signal-to-noise ratio in [SII] and H$\alpha$ greater than 1, while for Ho
12 greater than 5 in both [SII] and H$\alpha$. Right panels: in the vertical
grey band, the typical uncertainties of each parameter and region are
represented. Figure 11: Blue and red velocity components for Hubble I, II and
III extracted from the SN3 data cube and separated by 115 km/s. The right
panel is a color composite, or Doppler image.

In Fig. 9 we show the map and three-dimensional view of $\xi$, and its radial
profile along Ho 12, color-coded by the radial velocity. As expected, the
product of these two properties emphasizes the contrast between the inner and
outer parts of the SNR. But its usefulness is event more obvious in Fig. 10,
where Ho 12 is compared with three large HII regions first identified by
Hubble (1925), i.e. Hubble I, II, and III. The upper panel of this figure
presents the maps of the [SII]/H$\alpha$ ratio, the velocity dispersion, and
the product of these two properties, while their radial profiles (along the
normalized radius in bins of 0.32 arcsec) are shown in the lower panels. The
right panels show the typical uncertainties of each parameter (i.e.
[SII]/H$\alpha$, radial velocity, $\sigma$, and $\xi$) for each region. Hubble
I, II, and III have larger uncertainties than Ho 12 because we have considered
pixels with lower S/N ($\geq$1) than in the case of Ho 12 ($\geq$5), standing
out in the case of the [SII]/H$\alpha$ parameter for the Hubble II region.
However, the radial distributions shown for Hubble I, II and III evolve
smoothly for each of the properties considered in Fig. 10.

Let’s first consider the [SII]/H$\alpha$ ratio: the behaviour of Hubble I and
III is typical of photoionised regions, with values lower than the standard
0.4 threshold everywhere and increasing towards the outer edge. Ho 12’s
[SII]/H$\alpha$ ratio is larger than 0.4 throughout and decreasing outwards,
which is expected from a typical SNR. But Hubble II is intriguing: its
[SII]/H$\alpha$ ratio is very close to 0.4 in the inner regions and, contrary
to the other HII regions, it decreases outwards. Hubble II also displays
relatively high values of velocity dispersion (50 - 70 km/s) in its inner
regions, like Hubble III. Going through the data cube indeed reveals both caps
of their expanding shell, as shown in Fig. 11. Hubble I is much more quiet in
this respect and its [SII]/H$\alpha$ ratio is on average very low. So the
innermost parts of some large HII regions such as Hubble II and III
(r/r$\rm{}_{max}<0.1$) almost rival those of Ho 12 in terms of velocity
dispersion. It is thus in the $\xi$ radial distribution that the distinction
between Ho 12 and all three HII regions becomes obvious: the SNR shows
systematically higher values than the HII regions. The average value of $\xi$
in Ho 12 is above 40 until r/r$\rm{}_{max}\sim 0.4$, while for the HII regions
it is almost always smaller than 20. We also note that the overall difference
in radial velocity (i.e., maximum - minimum value) in Ho 12 ($\sim$150 km/s)
is much larger than that of the HII regions ($\sim$30 km/s). This is
compatible with the high velocity ejected material associated with the SN
explosion itself, and contributes to the significantly larger value of
$\sigma$ ($\sim$70 km/s) in the integrated spectrum of Ho 12 compared to that
of the HII regions ($\sim$30 km/s for Hubble II and III, 15 km/s for Hubble
I): see Table 3 where the integrated characteristics of Ho 12, Hubble I,
Hubble II, and Hubble III are presented.

Table 3: Integrated properties of Ho 12, Hubble I, II, and III. Region | [SII]/H$\alpha$ | [OIII]/H$\beta$ | [NII]/H$\alpha$ | Vhelio | $\sigma$ | $\xi$
---|---|---|---|---|---|---
|  |  |  | km/s | km/s | km/s
Ho 12 | 0.52$\pm$0.03 | 0.75$\pm$0.08 | 0.10$\pm$0.02 | -75$\pm$1 | 69$\pm$1 | 36$\pm$2
Hubble I | 0.11$\pm$0.02 | 3.59$\pm$0.54 | 0.03$\pm$0.01 | -82$\pm$1 | 15$\pm$1 | 2$\pm$1
Hubble II | 0.29$\pm$0.02 | 1.14$\pm$0.09 | 0.08$\pm$0.01 | -82$\pm$1 | 30$\pm$1 | 9$\pm$1
Hubble III | 0.23$\pm$0.02 | 1.70$\pm$0.16 | 0.06$\pm$0.01 | -78$\pm$1 | 28$\pm$1 | 6$\pm$1

Figure 12 presents $\sigma$ as a function of the [SII]/H$\alpha$ ratio, for
all the pixels having a S/N ratio larger than 5 in both [SII] and H$\alpha$ in
the entire field of view for Ho 12 (red hexbin) and all the HII regions (blue
hexbin). This diagram presents a very clear separation between the SNR and the
HII regions. HII regions in NGC 6822 can be summarized by the following
characteristics: i) most pixels have lower $\sigma$ and [SII]/H$\alpha$ values
than Ho 12 values; ii) pixels with [SII]/H$\alpha$ values $\geq$ 0.4 show
$\sigma$ values lower than Ho 12; and iii) pixels with $\sigma$ values greater
than 30 km s-1 show values of [SII]/H$\alpha$ $<$ 0.4. The same pixels are
also represented in Fig. 13, which depicts their distribution of the $\xi$
parameter. Again, the distribution of the HII regions is clearly different
from that of the SNR.

We conclude this section with a standard a diagnostic diagram,
log([OIII]/H$\beta$) versus log([SII]/H$\alpha$) (Fig. 14), but with a twist
since each pixel is now color-coded according to its velocity dispersion,
$\sigma$. In this figure we take into account all the ionised gas in NGC 6822.
The SNR (identified with filled circles) stands out in the lower right part of
this diagram, but there is a significant overlap between the SNR and HII
regions: the number of pixels from HII regions for which the [SII]/H$\alpha$
ratio exceeds the threshold value used to detect SNRs (0.4) is not negligible.
As shown in Fig. 10, these pixels tend to concentrate on the outskirts of the
HII regions. On the other hand, pixels with a significant $\sigma$ within HII
regions have [SII]/H$\alpha\leq 0.3$.

We have shown that, in NGC 6822 at least, the addition of the velocity
dispersion parameter to the standard [SII]/H$\alpha$ ratio, all based on the
same data cube, is an excellent asset to discriminate between HII regions and
supernova remnants. There are however some potential caveats that we should be
aware of:

  * •

Only one SNR, Ho 12, is known in NGC 6822; its morphology is very peculiar,
and thus may not be representative of all SNRs in nearby galaxies.

  * •

Ho 12 has a high surface brightness, is very well isolated from any HII region
and the DIG, and belongs to the nearest galaxy in the SIGNALS survey. This
obviously helps in its unambiguous identification as an SNR. In the next
section, we explore M33 and we will see that, even though it is also a member
of the Local Group, its large number of HII regions and the ubiquity of the
DIG complicate our case.

  * •

Some zones in Hubble II, a large HII region, simultaneously present both a
high [SII]/H$\alpha$ ratio (0.35 - 0.45) and a relatively high velocity
dispersion (50 - 65 km/s). This might suggest that it has it been the site of
a supernova blast in the recent past.

Figure 12: Velocity dispersion as a function of the [SII]/H$\alpha$ ratio.
Only those pixels with S/N $\geq$ 5 for H$\alpha$ and [SII] have been
considered. The red hexbins correspond to the pixels of SNR Ho 12 while the
blue hexbins correspond to all pixels coming from the HII regions of NGC 6822.
Figure 13: Distribution of $\xi$ for the same pixels as in Fig. 12. Figure 14:
Composite BPT diagram of all HII regions identified in NGC 6822 and the SNR Ho
12. Only those pixels with S/N $\geq$ 5 for H$\alpha$, H$\beta$ and [SII], and
[OIII] have been considered. Each point and square represents a pixel coming
from Ho 12 and HII regions, respectively, and is color-coded according to its
$\sigma$. The red rectangle shows the theoretical area corresponding to the
SNRs.

##  4 M33

The actively star-forming Triangulum galaxy hosts $\sim$200 SNR candidates,
most of them spectroscopically confirmed and well studied, both in the visible
band, the radio and X-rays (e.g., Dodorico et al., 1978; Gordon et al., 1998,
1999; Long et al., 2010; Lee & Lee, 2014; Long et al., 2018, and references
therein). The central oxygen abundance of M33, as determined with the direct
method, is 12+log(O/H) = 8.59 $\pm$ 0.02, with a galactocentric gradient of
-0.037 $\pm$ 0.007 dex kpc-1(Rogers et al., 2022). The combination of the
proximity of this galaxy (D = 0.86 Mpc, de Grijs & Bono, 2014) and the large
number of known SNRs make M33 a perfect candidate to study the suitability of
the [SII]/H$\alpha$ vs. $\sigma$ diagram proposed in Sect. 3.4 and expand our
analysis beyond the single case of Ho 12 in NGC 6822. In this second part of
the paper we analyse a sample of 163 among the 217 known SNR candidates in M33
provided by Long et al. (2010) \- herafter L10 - and Lee & Lee (2014) \-
hereafter L14, which are included in nine pointings observed with SITELLE (see
Table 1) for the SIGNALS survey. In Fig. 15 we present a color-coded mosaic of
the four central fields of M33 (Fields 1, 2, 3, and 4 in Table 1). In Fig. 16
we show the H$\alpha$ map of Field 7 (left panel, highlighting the location of
known SNR candidates) and its corresponding continuum map.

Figure 15: Color-coded mosaic of the four central fields of M33 (fields 1, 2,
3, and 4 in Table 1). H$\alpha$ in orange and a combination of [OII] and
[OIII] in blue. The field of view is $\sim 22^{\prime}\times 22^{\prime}$,
with North at the top and East to the left. Figure 16: H$\alpha$ map (left
panel) and continuum map (right panel, composition of the continuum maps in
SN1, SN2, and SN3) of Field 7 in M33. In the left panel, we highlight the
position of all the SNRs known in this field. FOV is $11^{\prime}\times
11^{\prime}$, with North at the top and East to the left.

As explained in Sect. 2, we fitted the [OII]$\lambda$3727,
[OIII]$\lambda\lambda$ 4959,5007, H$\beta$, [NII]$\lambda\lambda$6548,84,
H$\alpha$, and [SII]$\lambda\lambda$6717,6731 emission lines for each of the
163 SNR candidates considering only one velocity component. Among those, 12
are located in overlapping regions of some fields (the duplicates). We thus
kept for subsequent analysis the data from the cube having the best spectral
resolution and S/N ratio. Figure 17 shows the comparison between the
properties (line ratios and $\sigma$) of the selected and discarded
duplicates: the values are in good agreement regardless of the spectral
resolution, with the exception of two objects for which the spectral
resolution of one of the data cubes was insufficient to distinguish the
observed line width from that of the ILS (and were therefore attributed a
value of $\sigma=0$ in this dataset).

Figure 18 presents a comparison between our spatially integrated properties of
the individual objects in terms of line ratios (log([SII]/H$\alpha$) on the
left panel, log([OIII]/H$\beta$) on the central panel, and
log([NII]/H$\alpha$) on the right panel) with the work of Long et al. (2018).
In general, the agreement is good, with the largest discrepancies occurring
for the SNR candidates presented by Lee & Lee (2014), which tend to be more
extended and diffuse than those found previously. But the large scatter in
this figure is not surprising, given the noticeable spatial variations in line
ratios within a given object and the fact that neither of the previous studies
completely cover the whole SNR, as slits and fibres (with 1.5 arcsec radius)
were used, whereas our line ratios represent the integrated spectrum of each
object.

Figure 17: Comparison of line ratios and velocity dispersions for all SNRs
present in two data cubes. All the emission lines have a signal-to-noise ratio
higher than 5. The X axis represents the values for the selected cube while
the Y axis represents those of the other cube. Objects shown in black dots
come from Long et al. (2018) catalogue while the red squares come from Lee &
Lee (2014). The black solid line indicates the 1:1 relation. Figure 18:
Comparison of the line ratios obtained in this work (x-axis) with those of
Long et al. (2018) (y-axis). SNRs with S/N $\geq$ 5 (in the emission lines
shown in each panel) are shown in black dots while those with S/N < 5 are
represented by red squares. The black solid line indicates the 1:1 relation.

###  4.1 Morphology and properties of the sample

In this section we study the implication of the morphology of the SNRs in the
[SII]/H$\alpha$ vs. $\sigma$ diagram. For this purpose, we only considered the
SNRs and the morphology defined by Long et al. (2010); therefore, the sample
decreases to 118 objects. We did not consider Lee & Lee (2014) SNR
morphologies as they are not defined in the same way than Long et al.
(2010).333The SNRs in Lee & Lee (2014) are divided into more morphological
subcategories than Long et al. (2010). We may add uncertainties to our results
by erroneously including them in the morphological categories of Long et al.
(2010).

Long et al. (2010) defined four morphological types in their sample of SNR: i)
Type A, practically complete shells; ii) type A′ (A2 in this article), small
and bright objects, which are not shell-like but are well defined (they
present an elongated shape); iii) type B, partial shells; and iv) type C,
amorphous or poorly defined objects that may be a single filament. We define
an additional morphological type, A3, corresponding to compact and bright
objects. According to this classification there are 67 SNRs in type A, 5 in
type A2, 4 in type A3, 22 in type B, and 20 in type C. Table 4 presents the
median and standard deviation values of the properties [SII]/H$\alpha$,
$\sigma$, and $\xi$ when grouping all the SNRs according to their
morphological classification.

Figure 19: Distributions of [SII]/H$\alpha$ (left panel) and $\xi$ (right
panel) for each morphological type (from top to bottom: type A, A2, A3, B, and
C). In both panels, the distributions of the integrated values and for all the
pixels of each SNR are shown as grey line and coloured histogram,
respectively. The grey and coloured arrows indicate the position of the median
value for each morphological type of the integrated value and the pixels
contained in each SNR. The dotted vertical lines show the limit value of
[SII]/H$\alpha$=0.4 (left panel) and $\xi$=12 (right panel).

Figure 19 shows the distributions of [SII]/H$\alpha$ (left panel) and $\xi$
(right panel) for each morphological type. We first note that while the
[SII]/H$\alpha$ values span a wide range of values regardless of the
morphological type, the most compact ones (A2 and A3) show higher median
values (0.82 and 1.03, respectively) than the more extended types A and B
(0.77 and 0.72, respectively). On the other hand, type C objects (poorly
defined structure) show the lowest [SII]/H$\alpha$ values on average (0.6), as
expected.

Differences among the morphological types are more pronounced for $\xi$ than
for [SII]/H$\alpha$ (right-hand panels of Fig. 19). Type A3 shows the highest
median values ($\sim$76, with a wide distribution), followed by type A2
($\sim$38). No SNR of the A2 and A3 types (and only $\sim$1% of the pixels)
shows values of $\xi$ lower than 12. When considering the integrated values,
10% of the candidates of type A presents values of $\xi$ lower than 12. It is
tempting to suggest an evolutionary link between the compact A3 type to type
A2 and then the type A shells. The average values of $\xi$ determined for
types B and C are significantly lower ($\sim$19 and $\sim$13, respectively)
and could represent the final stages of detectable SNRs before a complete
dissolution into the ISM. The range of $\xi$ spanned in both cases is similar,
but only $\sim$10% of type B candidates also show values lower than 12, while
in type C they are $\sim$45%. This is possibly due to the fact that type B
objects evolve into type C.

In Fig. 20 we show the H$\alpha$ flux maps (left panel), and the
[SII]/H$\alpha$ vs. $\sigma$ diagram (right panel) for a subsample of 16
selected SNRs in M33 representative of all morphological types. SNRs with A,
A2, or A3 morphological types present higher values of $\sigma$ in the central
parts, decreasing as we move towards the outer parts of the SNR, as in the
case of Ho 12 (see Sect. 3.2). In the case of the A2 and A3 types shown in
this section, except for L10-121, we see that the value of [SII]/H$\alpha$
remain constant as $\sigma$ decreases until r/r${}_{max}\ \sim$0.5, from which
it begins to decrease with $\sigma$. In the case of B and C types, this
dependence is less evident, although in L10-002 and L10-037 it is. Moreover,
it can be seen that the scatter of [SII]/H$\alpha$ at a constant $\sigma$
value is lower in the A2 and A3 types than in the rest of the morphological
types.

Figure 20: Left panel: H$\alpha$ flux images of SNRs illustrating the
different morphological types. The region used to fit the integrated spectrum
is shown as a red ellipse. Right panel: $\sigma$ vs. [SII]/H$\alpha$ diagram
for the same objects; identification numbers are from Long et al. (2010). The
green stars in each plot represents the integrated value. The coloured dots
correspond to all pixels with F(H$\alpha$) $\geq$ 3$\times$10-17 erg s-1 cm-2
enclosed inside the red ellipse in the left panel and have been colour-coded
by their radial distance (r/rmax). Figure 21: Velocity dispersion as a
function of the [SII]/H$\alpha$ ratio. Red dots, blue stars, cyan squares,
green diamonds, and magenta hexagons represent A3, A, A2, B, and C
morphological type of SNR, respectively. The red cross shows the position in
this diagram for Ho 12 in NGC 6822.

Figure 21 shows the $\sigma$ vs. [SII]/H$\alpha$ diagram taking into account
the morphology of each SNR candidate. According to this diagram, the evolution
of a SNR could be interpreted as follows: compact objects (type A3) have very
high values of [SII]/H$\alpha$ and $\sigma$, following a well-defined path,
with a small dispersion in [SII]/H$\alpha$ at constant $\sigma$. These SNRs
would evolve into more elongated type A2 objects, where their $\sigma$ would
decrease as they expand through the interstellar medium. As they expand, the
shell-like structure (type A) becomes more evident. The central parts of type
A SNRs can still show high $\sigma$ values, more likely because the velocity
components of the approaching and receding parts of the shell are detected
simultaneously, see Sect. 4.3. The expansion and interaction with the ISM
cause $\sigma$ and [SII]/H$\alpha$ to decrease. We observe that the
[SII]/H$\alpha$ vs. $\sigma$ relation is no longer as well defined as the more
compact objects (i.e., the dispersion is larger), as expected. As they
continue expanding, the structures become less obvious, the type B SNRs have
not yet fully mixed with the ISM and retain sufficiently high values of
[SII]/H$\alpha$ and $\sigma$ in their innermost parts to allow their
detection. Type C objects have already evolved much further, it is difficult
to identify the structure of the SNR clearly, and we are often only able to
observe a filament. The value of $\sigma$ is low, although some of them still
maintain values of [SII]/H$\alpha$ higher than 0.4. We note that Ho 12 in NGC
6822 does not follow the global trend defined by the M33 SNRs in the $\sigma$
vs. [SII]/H$\alpha$ diagram. This may be related to the metallicity of the
host galaxies. Taking into account that [NII] emission depends on metallicity
(e.g. Pettini & Pagel, 2004; Pérez-Montero & Contini, 2009) we show the
distribution of log([NII]/H$\alpha$) in Fig.22. In this Figure we notice that
the log([NII]/H$\alpha$) values for Ho 12 are lower than those of the SNR
candidates of M33. The most likely explanation is that the global metallicity
of M33 is higher than what has been found in NGC6822, although the
[NII]/H$\alpha$ ratio is also sensitive to other nebular properties like the
ionization parameter and the abundance of secondary nitrogen. We will explore
further this topic with a larger number of SNRs in galaxies of the SIGNALS
survey (Duarte Puertas et al., in prep.).

Figure 22: Distribution of log([NII]/H$\alpha$) for the SNR candidates in M33 and Ho 12. Solid green histogram (with diagonal line hatch) and dashed green histogram (with dotted hatch) represent the distribution for all the pixels and the integrated values from the 163 SNR candidates in M33, respectively. Solid red histogram and vertical dashed red line show the distribution of all the pixels and the integrated values from Ho 12, respectively. Table 4: Morphological properties of SNRs from L10 in M33. | A | A2 | A3 | B | C | All
---|---|---|---|---|---|---
[SII]/H$\alpha$ | 0.78$\pm$0.22 | 0.82$\pm$0.15 | 1.03$\pm$0.06 | 0.72$\pm$0.22 | 0.60$\pm$0.14 | 0.73$\pm$0.22
$\sigma$ | 33$\pm$17 | 48$\pm$4 | 73$\pm$21 | 28$\pm$12 | 25$\pm$11 | 30$\pm$18
$\xi$ | 26$\pm$20 | 38$\pm$4 | 76$\pm$17 | 19$\pm$12 | 15$\pm$8 | 22$\pm$20
Number of objects | 67 | 5 | 4 | 22 | 20 | 118

Figures 23, 24, 25, 26, 27, and 28 present some examples of SNRs with
different morphologies (e.g., L10-105, L10-096, L10-096, L10-071, and
L10-050). In each figure we show: i) the flux maps for the [OII], H$\beta$,
[OIII], H$\alpha$, [NII] and [SII] emission lines; ii) the maps of
[SII]/H$\alpha$, radial velocity, and $\sigma$; iii) the log([SII]/H$\alpha$)
vs. $\sigma$ diagram; and iv) the integrated SNR spectrum and the fit obtained
with ORCS in the SN3 bandpass. The remaining SNRs are shown in Sect. 4.2 and
in the Appendix (Supplementary material).

Figure 23 shows L10-105. According to Long et al. (2010), the morphological
type for this SNR is A. It has a similar shape in H$\alpha$ and [SII], with a
prominent south-eastern wall, which is however almost invisible in [OIII]. The
[SII]/H$\alpha$ ratio is high in the whole SNR, however $\sigma$ presents
higher values in the central part than in the outermost part, as expected from
an expanding shell. The integrated spectrum hints at at least one additional
velocity component, which could be attributed to the ISM filament crossing the
field of view.

Figure 24 presents L10-096. This object is in some ways similar to Ho 12 in
NGC 6822, showing a series of knots along the outer ring. The morphology at
the different wavelengths is similar, except that the strongest [OIII]
emission is seen slightly further out the ring. We also note that the largest
values of $\sigma$ are seen in the knots of the outer ring. A small expanding
(with larger values of $\sigma$ at its core), purely photoionized, HII region
is seen at its lower left.

L10-011 shows an A2 morphology (see Fig. 25). Its kinematics show a bipolar
behaviour, with lower radial velocities in the northwest and higher in the
southeast. This southeastern part shows higher values of $\sigma$ than the
northwestern part. An HII region to the west and the SNR candidate L14-023 to
the south can be observed close to L10-011. There is a filament with a large
value of [SII]/H$\alpha$ that crosses the SNR from behind, connecting both the
HII region and the SNR candidate. This filament has a low $\sigma$ value
($\sim$20 km/s). Its average radial velocity is $\sim$-160 km/s and has a
[SII]/H$\alpha$ value larger than 0.4, being larger on the outside of the
filament than on the inside. Moreover, taking into account the $\sigma$ map,
it can be seen how to the northeast of this SNR there is a zone with higher
$\sigma$ values than 20 km/s. Taking into account the radial velocity of this
zone and comparing it with the velocity of L10-011, it is compatible with
being material associated with this SNR.

L10-071 is a compact SNR (Fig. 26); its outer ring is barely resolved.
Morphologically it is similar in the different emission lines. The behaviour
in the log([SII]/H$\alpha$) vs. $\sigma$ diagram has already been discussed in
the previous section.

Figure 27 presents L10-064. It is a type B SNR. Its western part shows a
similar morphology in all emission lines, while the eastern part is open. A
filament is visible from north to south, the southern part being the
brightest. As in the cases of L10-011 and L10-105, the filament has high
[SII]/H$\alpha$ and low $\sigma$ values. L10-064 presents high [SII]/H$\alpha$
values and tentatively higher values of $\sigma$ in the central part
($\sim$120 km/s) than in the outer part ($\lesssim$40 km/s).

In Fig. 28 we show L10-050, of type C: it is fragmented and stands out as a
filament. The morphology is similar in all visible emission lines, although
[OIII] is rather faint. [SII]/H$\alpha$ is high but $\sigma$ is low ($\sim$20
km/s).

Figure 23: Properties of L10-105. Top panel: emission line maps
(32${}^{\prime\prime}\times 32^{\prime\prime}$), from left to right : [OII],
H$\beta$, [OIII], H$\alpha$, [NII], and [SII]. Middle panel, left:
log(H$\alpha$) flux, [SII]/H$\alpha$ ratio, heliocentric radial velocity, and
$\sigma$.Middle panel, right: $\sigma$ vs. [SII]/H$\alpha$ diagram for all
pixels in the maps, with the coloured dots corresponding to all pixels with
F(H$\alpha$) $\geq$ 1$\times$10-17 erg s-1 cm-2 enclosed by the red ellipse in
the left panel and have been colour-coded by r/rmax. The green star shows the
position of the integrated value within the ellipse. Lower panel: Continuum-
subtracted integrated spectrum of the region shown as a red (or black) ellipse
above. The grey line shows the real spectrum and the red coloured line show
the fit obtained with ORCS in the SN3 bandpass. Figure 24: Same as Fig. 23 for
L10-096. Figure 25: Same as Fig. 23 for L10-011. Figure 26: Same as Fig. 23
for L10-071. Figure 27: Same as Fig. 23 for L10-064. Figure 28: Same as Fig.
23 for L10-050.

###  4.2 Detectability, spectral characteristics of SNRs and their immediate
environment

The detectability of SNRs in galaxies outside the Local Group obviously
depends on their evolutionary status and location with respect to bright ISM
regions: an old SNR within a dense HII region is less likely to be detected
with optical data than an isolated younger one. In addition, the diffuse
ionized gas (DIG) is known to harbor large values of [SII]/H$\alpha$ (Mannucci
et al., 2021), albeit with small velocity dispersion. Without any information
on the velocity dispersion, some filaments of the DIG could thus be mistaken
for SNRs (see for instance the case of NGC 4214: Leonidaki et al., 2013;
Vicens-Mouret et al., 2023). In M33, L10-011 and L10-064 are examples of SNRs
which are seen superimposed on large DIG filaments with values of
[SII]/H$\alpha$ larger than 0.4.

For the same reasons, the spectral characteristics of SNRs, in terms of line
ratios and kinematics, depend on the choice of the background used to extract
their net spectrum; this choice is not obvious in cases where the SNR lies in
a highly inhomogeneous nebular structure of filament. As we mentioned before,
we have deliberately chosen to subtract a general background as much devoid of
nebular features as possible to produce the maps and the integrated spectra of
SNRs presented here and forced ORCS to use the same velocity dispersion for
all the lines in the SN3 cube. This has little impact for the vast majority of
objects, since the contrast between the SNRs and their surroundings is high.

We have however visually noticed a few cases for which the width of the
H$\alpha$ line was noticeably smaller than that of the [SII] doublet. We have
therefore performed another fit on the integrated spectrum of all SNRs with
ORCS, but this time allowing it to fit different velocity dispersions for
H$\alpha$ and the forbidden lines. The values of $\sigma_{H\alpha}$ and
$\sigma_{[SII]}$ are compiled in Table 5 and plotted in Fig. 29; examples of
spectra from selected objects are shown in Fig. 30. Although there is a small
offset globally (the average difference is 2 km/s), about 87% of the SNRs show
no significant difference between the two values of velocity dispersion.
Twelve objects (7% of the sample) have a difference larger than 15 km/s in
favor of [SII], the most obvious one being L10-025 (upper panel of Fig. 30 and
Fig. 31), which is indeed surrounded by a bright HII region. We infer that in
more distant galaxies, a much larger fraction of SNRs will display a
significant difference between the two values of velocity dispersion: extra
care will then need to be taken to subtract a proper background.

Figure 29: Difference between the velocity dispersions of the H$\alpha$ line
($\sigma_{H\alpha}$) and the [SII] doublet ($\sigma_{[SII]}$) for our sample
of 163 SNRs in M33. Coloured squares highlight the position of a few selected
objects SNRs, the spectrum of which are displayed in Fig. 30: red, blue,
green, magenta, orange, and salmon for L10-025, L10-039, L10-034, L10-071,
L10-121, and L10-049, respectively. Figure 30: Spectra of the SNRs identified
in Fig. 29. In each panel, the grey line shows the real spectrum and the red
lines show the fit obtained with ORCS. Grey dotted lines show the locations of
the emission lines from SN3 filter. The SNR label is indicated in each panel
(upper right part). Figure 31: Same as Fig. 23 for L10-025.

###  4.3 Velocity structure: SNRs with multiple components

While a large velocity dispersion is a clear indication of an expansion in
SNRs, a combination of a proper morphology, significant expansion velocity and
appropriate spectral resolution can allow us to distinguish the two layers
(the farthest and the closest) of these objects. A few SNRs in our fields
could be studied this way, and we present here the best examples, namely
L10-008 (Fig. 32) and L10-105 (Fig. 33), for which the approaching and
receding velocity components can be clearly separated, both spectroscopically
and spatially. The figures present the integrated H$\alpha$ map, the
integrated spectrum (dominated by the outer ring), a spectrum of a selected
inner region where the two distinct components are seen, as well as a series
of images corresponding to the complete range of velocities seen in the data
cube. The emission line profile of the integrated spectrum in the central part
of the SNR can be resolved and shows two velocity components (separated by 94
km/s for L10-008 and 125 km/s for L10-105). Both the approaching and the
receding caps of the expanding shell are clearly visible.

Figure 32: Spatial and velocity structure of L10-008. The upper left panel
(35′′ on a side) shows the integrated H$\alpha$ flux map with ellipses
corresponding to regions chosen to represent the integrated spectrum (red) and
a selected region of the interior (magenta). The corresponding spectra and
their fits are shown on the upper right panel. The lower panel (50′′ on a
side) shows the individual frames within the datacube, centred on H$\alpha$,
where the transition in radial velocity between the two outermost layers of
the central part of the SNRs can be seen.  Figure 33: Same as Fig. 32, for
L10-105.

###  4.4 Global properties of SNRs and the threshold for detection

Table 5 presents the values of some properties of SNRs in M33 from this work.
Only 15 objects in our sample of 163 (9%) have an integrated [SII]/H$\alpha$
ratio inferior to the canonical value of 0.4 (six objects have a ratio between
0.37 and 0.4). Such a high ”success rate” is expected given that this ratio
was originally used to select the SNRs (although not on an integrated value
basis). But the situation is not as unequivocal when the integrated velocity
dispersion of the objects is considered, nor the product of these two
parameters, $\xi$. We also note significant differences between the L10 and
L14 samples (we consider here in the L14 samples only the new SNRs which were
not previously detected by L10).

What would be the ideal discriminant between SNRs and HII regions (or
superbubbles driven by stellar winds) if both the velocity dispersion and the
[SII]/H$\alpha$ ratio are available? In NGC 6822, we saw (Fig. 13) that $\xi$
= 12 clearly separates the individual pixels in Ho12 from those of the largest
HII regions; this is also true for their integrated properties (Table 3). But
the sample is very small in this galaxy, and the HII regions studied here can
be considered as giant, harbouring a large number of massive stars. The M33
data provide a better framework for this purpose. We have thus measured the
integrated values of $\sigma$ and $\xi$ for dozens of HII regions and ring
nebulae in our fields (Drissen et al., in prep.): excluding the central parts
of giant HII regions NGC 588, NGC 592, NGC 595 and NGC 604 and all SNRs,
$\sigma$ varies between 8 km/s and 20 km/s and $\xi$ between 1.5 and 9. The
value of $\xi=12$ based on the NGC 6822 data alone thus seems a bit too
conservative and could be slightly reduced. Before examining the impact of
varying the threshold value for $\xi$, we must emphasize important differences
between the L10 and L14 samples.

While the number of SNRs in the L10 sample with no measurable integrated
velocity dispersion in our data ($\sigma$ = 0) is low (8, or 7%), this
fraction rises to 33% in the L14 sample. The average value of velocity
dispersion in the L10 sample ($\overline{\sigma}_{L10}$ = 34 km/s) is in fact
twice as large as that of the new candidates from the L14 sample
($\overline{\sigma}_{L14}$ = 17 km/s), although this criterion was never
considered in either study. We find no correlation between the values of the
[SII]/H$\alpha$ ratio (nor the velocity dispersion) and the origin of the
supernova (core collapse or type Ia) as determined by Lee & Lee (2014) based
on the distance between the SNR and groups of OB stars.

Table 6 presents the impact of the choice of $\xi$ on the fraction of SNRs in
the L10 and L14 samples that do not meet the threshold value. Again, the
dichotomy between the two samples is clear, with a large fraction of L14
candidates being excluded, even with a low threshold value. But the vast
majority of these objects nevertheless have a [SII]/H$\alpha$ ratio larger
than 0.4. They could be older SNRs.

Table 5: Properties of SNRs in M33. Reddening corrected line fluxes relative
to H$\beta$ = 100.

(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | (13) | (14) | (15) | (16)
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
Name | Field | RA | Dec |  [SII]/H$\alpha$ | $\sigma$ |  $\sigma$([SII]) | $\xi$ | Morphology |  F(H$\alpha$) | [OII]3727 | [OIII]5007 |  H$\alpha$ | [NII]6584 | [SII]6717 | [SII]6717
ID |  |  |  |  |  km s-1 |  km s-1 |  |  |  10-15 erg cm-2 s-1 |  |  |  |  |  |
L10-001 | Field8 | 01:32:30.41 | +30:27:41.00 | 0.76 | 50 | 49 | 38 | A | $\rm 71.32\pm 2.21$ | $\rm 468.8\pm 28.4$ | $\rm 51.0\pm 4.3$ | $\rm 286.0\pm 14.2$ | $\rm 13.3\pm 3.0$ | $\rm 44.4\pm 3.1$ | $\rm 31.2\pm 2.5$
L10-002 | Field7 | 01:32:31.26 | +30:35:30.79 | 0.60 | 28 | 29 | 17 | C | $\rm 17.56\pm 0.29$ | $\rm 402.7\pm 24.2$ | $\rm 278.6\pm 15.1$ | $\rm 286.0\pm 15.4$ | $\rm 14.7\pm 1.6$ | $\rm 34.7\pm 1.6$ | $\rm 25.3\pm 1.4$
L10-003 | Field8 | 01:32:42.54 | +30:20:58.00 | 0.56 | 31 | 33 | 17 | A | $\rm 101.90\pm 1.40$ | $\rm 663.0\pm 44.8$ | $\rm 57.9\pm 4.0$ | $\rm 286.0\pm 10.3$ | $\rm 15.8\pm 1.4$ | $\rm 32.7\pm 1.4$ | $\rm 23.0\pm 1.2$
L10-004 | Field8 | 01:32:44.72 | +30:22:14.60 | 0.72 | 42 | 45 | 30 | A | $\rm 14.02\pm 0.42$ | $\rm 805.4\pm 77.8$ | $\rm 36.5\pm 4.6$ | $\rm 286.0\pm 15.1$ | $\rm 13.5\pm 2.8$ | $\rm 41.9\pm 3.1$ | $\rm 29.9\pm 2.6$
L10-005 | Field7 | 01:32:46.73 | +30:34:37.80 | 0.73 | 57 | 68 | 42 | A | $\rm 20.53\pm 1.00$ | $\rm 999.8\pm 87.8$ | $\rm 350.3\pm 27.4$ | $\rm 286.0\pm 25.7$ | $\rm 16.9\pm 4.4$ | $\rm 42.4\pm 5.2$ | $\rm 31.0\pm 4.3$
L10-006 | Field7 | 01:32:52.71 | +30:38:12.60 | 0.54 | 24 | 21 | 13 | A | $\rm 42.72\pm 0.74$ | $\rm 883.0\pm 33.1$ | $\rm 303.9\pm 11.0$ | $\rm 286.0\pm 11.0$ | $\rm 17.3\pm 1.5$ | $\rm 30.4\pm 1.6$ | $\rm 23.2\pm 1.4$
L10-008 | Field7 | 01:32:53.40 | +30:37:56.90 | 0.55 | 36 | 40 | 20 | A | $\rm 70.91\pm 1.04$ | $\rm 559.7\pm 21.6$ | $\rm 52.9\pm 2.4$ | $\rm 286.0\pm 7.4$ | $\rm 14.7\pm 1.4$ | $\rm 32.1\pm 1.5$ | $\rm 23.0\pm 1.3$
L10-009 | Field8 | 01:32:54.10 | +30:25:31.80 | 0.75 | 30 | 31 | 22 | C | $\rm 16.36\pm 0.37$ | $\rm 832.1\pm 60.8$ | $\rm 280.3\pm 16.4$ | $\rm 286.0\pm 17.0$ | $\rm 22.3\pm 2.4$ | $\rm 43.9\pm 2.3$ | $\rm 30.7\pm 1.9$
L10-011 | Field7 | 01:32:57.02 | +30:39:27.10 | 0.82 | 46 | 51 | 38 | A2 | $\rm 34.94\pm 0.78$ | $\rm 632.9\pm 16.9$ | $\rm 144.5\pm 2.7$ | $\rm 286.0\pm 7.7$ | $\rm 19.9\pm 2.5$ | $\rm 43.4\pm 2.3$ | $\rm 38.3\pm 2.1$
L10-012 | Field7 | 01:33:00.15 | +30:30:46.20 | 0.35 | 21 | 21 | 7 | B | $\rm 447.08\pm 3.56$ | $\rm 419.5\pm 14.2$ | $\rm 175.1\pm 5.8$ | $\rm 286.0\pm 8.4$ | $\rm 12.6\pm 0.7$ | $\rm 20.7\pm 0.8$ | $\rm 14.6\pm 0.7$
L10-014 | Field7 | 01:33:00.57 | +30:31:00.67 | 0.54 | 27 | 27 | 15 | B | $\rm 247.57\pm 2.31$ | $\rm 483.7\pm 14.1$ | $\rm 100.3\pm 3.3$ | $\rm 286.0\pm 7.1$ | $\rm 15.6\pm 0.8$ | $\rm 31.5\pm 0.9$ | $\rm 22.7\pm 0.8$
L10-015 | Field7 | 01:33:01.51 | +30:30:49.60 | 0.51 | 32 | 29 | 16 | B | $\rm 50.06\pm 0.63$ | $\rm 586.2\pm 25.0$ | $\rm 203.3\pm 8.3$ | $\rm 286.0\pm 11.1$ | $\rm 16.8\pm 1.1$ | $\rm 29.8\pm 1.1$ | $\rm 21.4\pm 1.0$
L10-016 | Field7 | 01:33:02.93 | +30:32:29.20 | 0.70 | 26 | 29 | 18 | A | $\rm 48.17\pm 0.73$ | $\rm 639.3\pm 46.6$ | $\rm 191.4\pm 10.1$ | $\rm 286.0\pm 14.0$ | $\rm 21.2\pm 1.4$ | $\rm 41.7\pm 1.6$ | $\rm 28.6\pm 1.4$
L10-017 | Field7 | 01:33:03.52 | +30:31:20.90 | 0.89 | 44 | 44 | 39 | A | $\rm 27.50\pm 0.59$ | $\rm 823.6\pm 44.7$ | $\rm 153.7\pm 7.8$ | $\rm 286.0\pm 13.5$ | $\rm 21.2\pm 2.0$ | $\rm 53.2\pm 2.3$ | $\rm 36.0\pm 1.8$
L10-018 | Field7 | 01:33:03.95 | +30:39:53.70 | 0.61 | 30 | 37 | 19 | A | $\rm 70.43\pm 0.95$ | $\rm 620.9\pm 20.1$ | $\rm 92.7\pm 1.6$ | $\rm 286.0\pm 5.2$ | $\rm 20.4\pm 1.4$ | $\rm 35.1\pm 1.5$ | $\rm 26.3\pm 1.3$
L10-020 | Field8 | 01:33:08.98 | +30:26:58.90 | 0.74 | 35 | 41 | 26 | A | $\rm 26.45\pm 0.61$ | $\rm 619.9\pm 39.2$ | $\rm 187.0\pm 12.1$ | $\rm 286.0\pm 17.4$ | $\rm 25.4\pm 2.6$ | $\rm 43.4\pm 2.6$ | $\rm 30.1\pm 2.1$
L10-021 | Field7 | 01:33:09.87 | +30:39:34.90 | 0.53 | 28 | 29 | 15 | A | $\rm 111.47\pm 1.74$ | $\rm 660.7\pm 38.3$ | $\rm 149.5\pm 3.2$ | $\rm 286.0\pm 6.8$ | $\rm 24.4\pm 1.6$ | $\rm 31.1\pm 1.6$ | $\rm 22.1\pm 1.3$
L10-023 | Field7 | 01:33:11.19 | +30:39:42.96 | 0.71 | 55 | 62 | 38 | A2 | $\rm 13.12\pm 0.37$ | $\rm 887.5\pm 46.4$ | $\rm 235.2\pm 8.4$ | $\rm 286.0\pm 12.4$ | $\rm 23.2\pm 3.0$ | $\rm 37.0\pm 2.8$ | $\rm 33.5\pm 2.6$
L10-024 | Field7 | 01:33:11.28 | +30:34:23.50 | 0.47 | 20 | 16 | 10 | A | $\rm 195.51\pm 2.29$ | $\rm 464.5\pm 13.4$ | $\rm 20.8\pm 1.7$ | $\rm 286.0\pm 5.8$ | $\rm 21.3\pm 1.1$ | $\rm 27.5\pm 1.1$ | $\rm 19.7\pm 0.9$
L10-025 | Field7 | 01:33:11.58 | +30:38:41.39 | 0.54 | 37 | 81 | 20 | A | $\rm 32.50\pm 0.71$ | $\rm 496.1\pm 31.2$ | $\rm 297.0\pm 12.0$ | $\rm 286.0\pm 12.6$ | $\rm 25.1\pm 4.0$ | $\rm 27.8\pm 3.1$ | $\rm 25.7\pm 3.0$
L10-026 | Field2 | 01:33:16.73 | +30:46:10.30 | 0.57 | 24 | 27 | 14 | B | $\rm 78.22\pm 0.82$ | $\rm 464.0\pm 14.6$ | $\rm 119.9\pm 4.6$ | $\rm 286.0\pm 8.9$ | $\rm 23.6\pm 1.0$ | $\rm 33.3\pm 1.1$ | $\rm 24.0\pm 0.9$
L10-027 | Field4 | 01:33:17.44 | +30:31:28.50 | 0.78 | 30 | 31 | 23 | C | $\rm 19.52\pm 0.44$ | $\rm 211.2\pm 12.3$ | $\rm 47.5\pm 5.9$ | $\rm 267.0\pm 15.7$ | $\rm 22.0\pm 2.1$ | $\rm 46.5\pm 2.5$ | $\rm 31.7\pm 2.1$
L10-029 | Field6 | 01:33:18.94 | +30:46:50.04 | 0.95 | 44 | 52 | 42 | A | $\rm 39.21\pm 1.48$ | $\rm 464.2\pm 49.2$ | $\rm 113.0\pm 13.2$ | $\rm 286.0\pm 26.8$ | $\rm 28.8\pm 3.8$ | $\rm 57.2\pm 4.4$ | $\rm 38.0\pm 3.4$
L10-030 | Field4 | 01:33:21.64 | +30:31:31.10 | 0.44 | 24 | 14 | 10 | A | $\rm 63.52\pm 1.37$ | $\rm 232.7\pm 9.7$ | $\rm 41.3\pm 4.0$ | $\rm 245.1\pm 11.0$ | $\rm 23.3\pm 2.0$ | $\rm 26.4\pm 2.2$ | $\rm 17.6\pm 1.8$
L10-033 | Field6 | 01:33:27.07 | +30:47:48.60 | 0.67 | 26 | 26 | 17 | C | $\rm 56.99\pm 0.89$ | $\rm 242.6\pm 25.5$ | – | $\rm 286.0\pm 18.0$ | $\rm 18.6\pm 1.5$ | $\rm 39.4\pm 1.6$ | $\rm 27.6\pm 1.3$
L10-034 | Field4 | 01:33:28.08 | +30:31:35.00 | 0.66 | 50 | 72 | 33 | B | $\rm 25.54\pm 0.49$ | $\rm 391.9\pm 25.5$ | $\rm 429.5\pm 27.2$ | $\rm 259.3\pm 16.7$ | $\rm 33.0\pm 2.4$ | $\rm 38.3\pm 2.4$ | $\rm 27.9\pm 2.0$
L10-035† | Field6 | 01:33:28.99 | +30:47:42.80 | 0.29 | 22 | 21 | 6 | C | $\rm 5.38\pm 0.30$ | – | – | $\rm 286.0\pm 96.7$ | $\rm 15.4\pm 5.7$ | $\rm 17.7\pm 5.3$ | $\rm 11.5\pm 4.5$
L10-036 | Field2 | 01:33:29.05 | +30:42:17.00 | 1.06 | 74 | 88 | 78 | A3 | $\rm 67.35\pm 1.30$ | $\rm 453.2\pm 17.1$ | $\rm 160.0\pm 6.6$ | $\rm 286.0\pm 11.5$ | $\rm 47.7\pm 2.3$ | $\rm 52.0\pm 2.0$ | $\rm 54.2\pm 2.1$
L10-037 | Field6 | 01:33:29.45 | +30:49:10.80 | 0.74 | 52 | 63 | 38 | B | $\rm 13.33\pm 0.60$ | $\rm 574.4\pm 71.3$ | $\rm 305.8\pm 36.5$ | $\rm 286.0\pm 34.7$ | $\rm 32.3\pm 4.9$ | $\rm 41.3\pm 4.8$ | $\rm 32.8\pm 4.2$
L10-038 | Field6 | 01:33:30.21 | +30:47:43.80 | 0.42 | 20 | 21 | 8 | C | $\rm 55.88\pm 0.55$ | $\rm 204.2\pm 18.7$ | $\rm 90.0\pm 7.0$ | $\rm 286.0\pm 15.3$ | $\rm 17.6\pm 0.9$ | $\rm 25.1\pm 1.0$ | $\rm 17.0\pm 0.8$
L10-039 | Field4 | 01:33:31.20 | +30:33:33.40 | 0.98 | 116 | 139 | 113 | A3 | $\rm 76.43\pm 1.60$ | $\rm 443.7\pm 23.2$ | $\rm 445.9\pm 23.5$ | $\rm 286.0\pm 16.0$ | $\rm 63.4\pm 2.6$ | $\rm 43.6\pm 2.0$ | $\rm 54.1\pm 2.3$
L10-040 | Field2 | 01:33:31.34 | +30:42:18.30 | 0.30 | 20 | 17 | 6 | A | $\rm 63.29\pm 0.90$ | $\rm 256.5\pm 9.5$ | $\rm 104.6\pm 5.0$ | $\rm 286.0\pm 10.8$ | $\rm 22.2\pm 1.4$ | $\rm 17.3\pm 1.4$ | $\rm 12.7\pm 1.2$
L10-041 | Field4 | 01:33:31.80 | +30:31:01.10 | 0.96 | 27 | 25 | 26 | A | $\rm 22.82\pm 1.50$ | $\rm 272.6\pm 36.0$ | $\rm 74.3\pm 12.0$ | $\rm 244.9\pm 29.1$ | $\rm 25.1\pm 6.2$ | $\rm 57.0\pm 7.6$ | $\rm 39.1\pm 6.2$
L10-043 | Field2 | 01:33:35.39 | +30:42:32.10 | 0.49 | 26 | 25 | 13 | C | $\rm 29.29\pm 0.35$ | $\rm 318.8\pm 12.3$ | $\rm 59.0\pm 4.1$ | $\rm 286.0\pm 10.6$ | $\rm 26.6\pm 1.1$ | $\rm 28.1\pm 1.2$ | $\rm 21.4\pm 1.1$
L10-044 | Field6 | 01:33:35.63 | +30:49:22.63 | 0.95 | 56 | 55 | 53 | A | $\rm 22.82\pm 0.60$ | $\rm 617.8\pm 50.4$ | $\rm 100.7\pm 9.7$ | $\rm 286.0\pm 20.9$ | $\rm 31.9\pm 2.8$ | $\rm 54.0\pm 2.7$ | $\rm 40.6\pm 2.3$
L10-045 | Field4 | 01:33:36.09 | +30:36:27.01 | 0.83 | 54 | 70 | 45 | A2 | $\rm 144.35\pm 1.83$ | $\rm 352.1\pm 7.9$ | $\rm 221.1\pm 5.0$ | $\rm 286.0\pm 6.9$ | $\rm 41.3\pm 1.5$ | $\rm 46.0\pm 1.5$ | $\rm 37.4\pm 1.3$
L10-046 | Field4 | 01:33:37.09 | +30:32:53.50 | 0.99 | 48 | 52 | 48 | A | $\rm 18.32\pm 0.24$ | $\rm 475.6\pm 27.3$ | $\rm 105.5\pm 7.3$ | $\rm 286.0\pm 14.7$ | $\rm 38.2\pm 1.5$ | $\rm 58.2\pm 1.5$ | $\rm 40.6\pm 1.3$
L10-047 | Field2 | 01:33:37.75 | +30:40:09.20 | 0.96 | 41 | 40 | 39 | A | $\rm 22.45\pm 0.69$ | $\rm 1279.4\pm 136.6$ | $\rm 236.6\pm 27.0$ | $\rm 286.0\pm 31.3$ | $\rm 41.9\pm 3.4$ | $\rm 55.7\pm 3.4$ | $\rm 40.4\pm 2.8$
L10-048 | Field2 | 01:33:38.01 | +30:42:18.20 | 0.53 | 21 | 17 | 11 | A | $\rm 16.70\pm 0.22$ | $\rm 233.2\pm 10.1$ | $\rm 22.1\pm 4.2$ | $\rm 286.0\pm 11.6$ | $\rm 26.8\pm 1.2$ | $\rm 31.2\pm 1.3$ | $\rm 22.2\pm 1.1$
L10-049 | Field2 | 01:33:40.66 | +30:39:40.80 | 0.79 | 33 | 40 | 26 | A | $\rm 34.53\pm 0.68$ | $\rm 887.9\pm 71.3$ | $\rm 154.8\pm 14.3$ | $\rm 286.0\pm 22.8$ | $\rm 37.8\pm 2.0$ | $\rm 46.0\pm 2.2$ | $\rm 32.9\pm 1.9$
L10-050 | Field2 | 01:33:40.73 | +30:42:35.70 | 0.60 | 20 | 17 | 12 | C | $\rm 110.80\pm 1.10$ | $\rm 343.6\pm 10.3$ | $\rm 41.4\pm 3.0$ | $\rm 286.0\pm 8.5$ | $\rm 31.8\pm 1.0$ | $\rm 35.0\pm 1.0$ | $\rm 25.0\pm 0.9$
L10-051 | Field6 | 01:33:40.91 | +30:52:14.49 | 0.72 | 29 | 33 | 21 | A | $\rm 39.25\pm 0.92$ | $\rm 346.7\pm 38.2$ | $\rm 84.5\pm 11.5$ | $\rm 286.0\pm 27.1$ | $\rm 24.7\pm 2.4$ | $\rm 42.5\pm 2.5$ | $\rm 30.0\pm 2.1$
L10-052 | Field4 | 01:33:41.30 | +30:32:28.40 | 0.48 | 27 | 23 | 13 | C | $\rm 15.99\pm 0.26$ | $\rm 329.8\pm 23.2$ | $\rm 53.9\pm 6.3$ | $\rm 286.0\pm 16.4$ | $\rm 23.5\pm 1.5$ | $\rm 28.5\pm 1.7$ | $\rm 19.5\pm 1.4$
L10-053 | Field9 | 01:33:41.69 | +30:21:04.10 | 0.57 | 32 | 32 | 18 | A | $\rm 73.98\pm 1.07$ | $\rm 637.5\pm 19.9$ | $\rm 114.5\pm 4.3$ | $\rm 286.0\pm 9.2$ | $\rm 17.3\pm 1.4$ | $\rm 33.9\pm 1.4$ | $\rm 23.3\pm 1.2$
L10-054 | Field9 | 01:33:42.20 | +30:20:58.00 | 0.77 | 37 | 45 | 29 | A | $\rm 43.42\pm 1.13$ | $\rm 587.2\pm 26.5$ | $\rm 82.3\pm 5.4$ | $\rm 286.0\pm 14.3$ | $\rm 18.9\pm 3.0$ | $\rm 45.8\pm 3.0$ | $\rm 30.8\pm 2.4$
L10-055 | Field2 | 01:33:42.91 | +30:41:49.50 | 0.53 | 17 | 16 | 9 | C | $\rm 51.99\pm 0.53$ | $\rm 267.6\pm 11.3$ | $\rm 23.5\pm 4.2$ | $\rm 286.0\pm 11.0$ | $\rm 25.2\pm 1.0$ | $\rm 30.7\pm 1.1$ | $\rm 22.2\pm 0.9$
L10-056 | Field2 | 01:33:43.49 | +30:41:03.80 | 0.72 | 29 | 36 | 21 | B | $\rm 15.54\pm 0.25$ | $\rm 606.0\pm 37.6$ | $\rm 59.4\pm 6.3$ | $\rm 286.0\pm 16.1$ | $\rm 36.0\pm 1.8$ | $\rm 41.6\pm 1.8$ | $\rm 30.7\pm 1.5$
L10-057 | Field4 | 01:33:43.70 | +30:36:11.50 | 0.59 | 17 | 21 | 10 | C | $\rm 36.48\pm 0.38$ | $\rm 259.6\pm 7.8$ | $\rm 38.9\pm 2.8$ | $\rm 286.0\pm 7.9$ | $\rm 27.8\pm 1.1$ | $\rm 35.0\pm 1.2$ | $\rm 24.3\pm 1.0$
L10-058 | Field4 | 01:33:45.26 | +30:32:20.10 | 0.59 | 23 | 14 | 13 | A | $\rm 86.78\pm 0.70$ | $\rm 269.4\pm 6.8$ | $\rm 14.4\pm 2.2$ | $\rm 286.0\pm 6.5$ | $\rm 27.9\pm 0.8$ | $\rm 34.7\pm 0.8$ | $\rm 24.5\pm 0.7$
L10-059† | Field2 | 01:33:47.46 | +30:39:44.70 | 0.99 | 36 | 44 | 36 | A | $\rm 29.75\pm 0.86$ | $\rm<1016.6\pm 341.0$ | $\rm<200.0\pm 65.7$ | $\rm 286.0\pm 95.7$ | $\rm 51.1\pm 3.2$ | $\rm 56.4\pm 3.5$ | $\rm 42.7\pm 3.0$
L10-060 | Field2 | 01:33:48.35 | +30:39:28.40 | 0.67 | 30 | 40 | 20 | C | $\rm 20.92\pm 0.27$ | $\rm 484.3\pm 26.8$ | $\rm 80.3\pm 7.2$ | $\rm 286.0\pm 15.5$ | $\rm 40.9\pm 1.5$ | $\rm 38.3\pm 1.5$ | $\rm 28.5\pm 1.3$
L10-061 | Field4 | 01:33:48.50 | +30:33:07.90 | 0.73 | 22 | 24 | 16 | B | $\rm 125.10\pm 1.13$ | $\rm 285.7\pm 6.1$ | $\rm 59.9\pm 2.3$ | $\rm 286.0\pm 6.4$ | $\rm 31.6\pm 0.9$ | $\rm 42.8\pm 1.0$ | $\rm 29.8\pm 0.8$
L10-062 | Field4 | 01:33:49.75 | +30:30:49.70 | 0.68 | 0 | 0 | 0 | A | $\rm 23.22\pm 0.42$ | $\rm 289.1\pm 17.7$ | $\rm 36.0\pm 5.7$ | $\rm 267.0\pm 15.1$ | $\rm 24.0\pm 1.8$ | $\rm 40.5\pm 2.0$ | $\rm 27.9\pm 2.0$

  * •

Continued.

(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | (13) | (14) | (15) | (16)
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
Name | Field | RA | Dec |  [SII]/H$\alpha$ | $\sigma$ |  $\sigma$([SII]) | $\xi$ | Morphology |  F(H$\alpha$) | [OII]3727 | [OIII]5007 |  H$\alpha$ | [NII]6584 | [SII]6717 | [SII]6717
ID |  |  |  |  |  km s-1 |  km s-1 |  |  |  10-15 erg cm-2 s-1 |  |  |  |  |  |
L10-063 | Field4 | 01:33:49.90 | +30:30:16.70 | 1.09 | 28 | 13 | 30 | A | $\rm 4.57\pm 0.40$ | $\rm 561.3\pm 115.9$ | $\rm 249.4\pm 53.1$ | $\rm 236.8\pm 49.9$ | $\rm 55.9\pm 11.1$ | $\rm 65.9\pm 10.2$ | $\rm 42.7\pm 7.9$
L10-064 | Field4 | 01:33:50.12 | +30:35:28.60 | 0.79 | 34 | 40 | 27 | B | $\rm 27.23\pm 0.48$ | $\rm 465.9\pm 25.8$ | $\rm 224.8\pm 13.2$ | $\rm 286.0\pm 16.0$ | $\rm 37.7\pm 1.9$ | $\rm 45.4\pm 2.0$ | $\rm 33.6\pm 1.7$
L10-065 | Field2 | 01:33:51.06 | +30:43:56.20 | 0.55 | 24 | 21 | 13 | B | $\rm 90.09\pm 0.63$ | $\rm 348.1\pm 7.1$ | $\rm 32.2\pm 1.8$ | $\rm 286.0\pm 5.4$ | $\rm 31.7\pm 0.7$ | $\rm 32.0\pm 0.7$ | $\rm 23.2\pm 0.6$
L10-066 | Field4 | 01:33:51.67 | +30:30:59.60 | 1.19 | 55 | 46 | 65 | A | $\rm 13.49\pm 0.52$ | $\rm 457.5\pm 51.1$ | $\rm 135.7\pm 19.0$ | $\rm 286.0\pm 33.2$ | $\rm 33.6\pm 3.8$ | $\rm 67.4\pm 4.4$ | $\rm 51.3\pm 3.7$
L10-067 | Field4 | 01:33:51.61 | +30:30:42.64 | 0.79 | 23 | 34 | 18 | C | $\rm 9.76\pm 0.25$ | $\rm 344.3\pm 23.5$ | $\rm 55.1\pm 5.9$ | $\rm 244.2\pm 14.0$ | $\rm 33.6\pm 2.9$ | $\rm 48.3\pm 3.1$ | $\rm 30.4\pm 2.5$
L10-068 | Field5 | 01:33:52.15 | +30:56:33.40 | 0.48 | 20 | 17 | 10 | A | $\rm 175.07\pm 2.03$ | $\rm 270.6\pm 16.2$ | $\rm 384.5\pm 21.5$ | $\rm 286.0\pm 15.8$ | $\rm 20.4\pm 1.1$ | $\rm 27.9\pm 1.1$ | $\rm 19.7\pm 0.9$
L10-069 | Field4 | 01:33:54.28 | +30:33:47.90 | 0.83 | 31 | 32 | 25 | A | $\rm 52.43\pm 0.64$ | $\rm 313.3\pm 8.1$ | $\rm 37.2\pm 2.4$ | $\rm 286.0\pm 7.3$ | $\rm 28.5\pm 1.3$ | $\rm 48.8\pm 1.4$ | $\rm 34.0\pm 1.2$
L10-070 | Field2 | 01:33:54.49 | +30:45:18.70 | 0.77 | 37 | 47 | 28 | B | $\rm 88.19\pm 0.71$ | $\rm 402.5\pm 7.0$ | $\rm 71.1\pm 2.0$ | $\rm 286.0\pm 5.2$ | $\rm 37.0\pm 0.9$ | $\rm 44.5\pm 0.9$ | $\rm 32.4\pm 0.8$
L10-071 | Field4 | 01:33:54.91 | +30:33:11.00 | 1.00 | 73 | 94 | 73 | A3 | $\rm 78.17\pm 1.34$ | $\rm 439.8\pm 12.8$ | $\rm 203.9\pm 6.3$ | $\rm 267.1\pm 8.7$ | $\rm 41.2\pm 2.0$ | $\rm 52.9\pm 2.0$ | $\rm 47.3\pm 1.9$
L10-072† | Field2 | 01:33:55.01 | +30:39:57.30 | 1.33 | 13 | 22 | 17 | B | $\rm 11.28\pm 0.73$ | $\rm<813.6\pm 273.3$ | $\rm<97.4\pm 36.3$ | $\rm 286.0\pm 97.1$ | $\rm 75.8\pm 9.0$ | $\rm 75.8\pm 8.3$ | $\rm 57.0\pm 7.0$
L10-073 | Field9 | 01:33:56.49 | +30:21:27.00 | 0.84 | 48 | 49 | 40 | A | $\rm 27.85\pm 0.78$ | $\rm 890.5\pm 54.4$ | $\rm 118.7\pm 7.9$ | $\rm 286.0\pm 16.6$ | $\rm 20.9\pm 2.5$ | $\rm 50.2\pm 3.0$ | $\rm 34.2\pm 2.3$
L10-074 | Field4 | 01:33:56.97 | +30:34:58.70 | 0.93 | 36 | 41 | 33 | B | $\rm 24.72\pm 0.49$ | $\rm 419.9\pm 13.3$ | $\rm 106.8\pm 4.3$ | $\rm 286.0\pm 10.1$ | $\rm 33.2\pm 2.0$ | $\rm 53.9\pm 2.3$ | $\rm 39.4\pm 2.0$
L10-075 | Field2 | 01:33:57.13 | +30:40:48.50 | 1.01 | 22 | 33 | 22 | A | $\rm 24.29\pm 1.05$ | $\rm 1584.4\pm 324.7$ | $\rm 64.3\pm 23.8$ | $\rm 286.0\pm 58.3$ | $\rm 45.9\pm 5.3$ | $\rm 58.5\pm 5.3$ | $\rm 42.1\pm 4.5$
L10-076 | Field4 | 01:33:57.13 | +30:35:06.10 | 0.49 | 19 | 30 | 9 | B | $\rm 19.74\pm 0.27$ | $\rm 410.9\pm 10.7$ | $\rm 166.8\pm 4.8$ | $\rm 286.0\pm 8.1$ | $\rm 33.9\pm 1.4$ | $\rm 28.6\pm 1.5$ | $\rm 20.0\pm 1.3$
L10-077 | Field4 | 01:33:58.06 | +30:32:09.60 | 0.44 | 0 | 0 | 0 | C | $\rm 26.19\pm 0.21$ | $\rm 190.5\pm 5.3$ | $\rm 20.0\pm 2.6$ | $\rm 286.0\pm 7.1$ | $\rm 22.8\pm 0.8$ | $\rm 26.5\pm 0.9$ | $\rm 17.9\pm 0.9$
L10-078 | Field2 | 01:33:58.13 | +30:37:53.04 | 1.13 | 45 | 46 | 50 | A2 | $\rm 18.01\pm 0.45$ | $\rm 1017.9\pm 70.1$ | $\rm 206.9\pm 16.0$ | $\rm 286.0\pm 20.8$ | $\rm 53.5\pm 2.9$ | $\rm 64.2\pm 2.9$ | $\rm 48.6\pm 2.4$
L10-079 | Field5 | 01:33:58.15 | +30:48:36.40 | 0.55 | 28 | 27 | 15 | A | $\rm 10.23\pm 0.24$ | $\rm 247.1\pm 14.5$ | $\rm 22.8\pm 4.3$ | $\rm 286.0\pm 13.7$ | $\rm 26.5\pm 2.4$ | $\rm 32.4\pm 2.2$ | $\rm 22.1\pm 1.9$
L10-080 | Field4 | 01:33:58.42 | +30:36:24.30 | 1.14 | 61 | 54 | 70 | A3 | $\rm 3.65\pm 0.17$ | $\rm 1108.7\pm 138.8$ | $\rm 281.7\pm 31.7$ | $\rm 286.0\pm 33.1$ | $\rm 50.4\pm 4.9$ | $\rm 62.9\pm 5.1$ | $\rm 50.8\pm 4.4$
L10-081 | Field4 | 01:33:58.51 | +30:33:32.30 | 0.68 | 30 | 37 | 20 | C | $\rm 13.87\pm 0.32$ | $\rm 554.1\pm 29.9$ | $\rm 167.8\pm 8.9$ | $\rm 286.0\pm 14.6$ | $\rm 31.9\pm 2.4$ | $\rm 40.3\pm 2.6$ | $\rm 27.4\pm 2.2$
L10-082 | Field5 | 01:33:58.52 | +30:51:54.30 | 0.86 | 45 | 65 | 38 | A | $\rm 30.57\pm 1.37$ | $\rm 524.9\pm 55.4$ | $\rm 427.2\pm 45.1$ | $\rm 286.0\pm 31.9$ | $\rm 37.2\pm 5.3$ | $\rm 53.1\pm 5.7$ | $\rm 32.5\pm 4.3$
L10-084 | Field2 | 01:34:00.31 | +30:42:19.40 | 1.13 | 92 | 87 | 103 | A | $\rm 22.34\pm 0.84$ | $\rm 859.4\pm 94.3$ | $\rm 442.6\pm 48.9$ | $\rm 286.0\pm 32.7$ | $\rm 57.2\pm 3.9$ | $\rm 62.9\pm 4.0$ | $\rm 50.1\pm 3.4$
L10-085 | Field2 | 01:34:00.32 | +30:47:24.10 | 0.97 | 52 | 51 | 50 | B | $\rm 19.26\pm 0.50$ | $\rm 922.6\pm 99.6$ | $\rm 358.6\pm 39.9$ | $\rm 286.0\pm 31.4$ | $\rm 42.4\pm 2.7$ | $\rm 55.9\pm 2.8$ | $\rm 41.0\pm 2.3$
L10-086 | Field5 | 01:34:00.53 | +30:49:02.71 | 0.60 | 46 | 43 | 28 | C | $\rm 0.81\pm 0.08$ | $\rm 375.9\pm 64.2$ | $\rm 123.2\pm 25.0$ | $\rm 286.0\pm 52.6$ | $\rm 27.6\pm 6.9$ | $\rm 27.7\pm 7.8$ | $\rm 32.8\pm 8.6$
L10-087 | Field3 | 01:34:01.34 | +30:35:20.20 | 0.88 | 29 | 38 | 26 | A | $\rm 40.87\pm 1.14$ | $\rm 852.4\pm 63.9$ | $\rm 59.4\pm 7.7$ | $\rm 286.0\pm 20.5$ | $\rm 31.6\pm 3.2$ | $\rm 50.4\pm 3.3$ | $\rm 37.6\pm 2.8$
L10-088 | Field3 | 01:34:02.24 | +30:31:06.80 | 0.91 | 41 | 46 | 37 | A | $\rm 41.90\pm 1.28$ | $\rm 1005.5\pm 61.7$ | $\rm 132.7\pm 9.1$ | $\rm 286.0\pm 17.9$ | $\rm 31.4\pm 3.7$ | $\rm 51.0\pm 3.4$ | $\rm 39.8\pm 3.0$
L10-089 | Field3 | 01:34:03.31 | +30:36:22.90 | 0.58 | 28 | 25 | 16 | A | $\rm 284.02\pm 6.09$ | $\rm 499.4\pm 18.1$ | $\rm 46.1\pm 3.1$ | $\rm 286.0\pm 10.0$ | $\rm 26.6\pm 2.2$ | $\rm 32.9\pm 2.1$ | $\rm 24.6\pm 1.9$
L10-090 | Field1 | 01:34:03.48 | +30:44:43.80 | 0.99 | 47 | 41 | 46 | A | $\rm 13.78\pm 0.79$ | $\rm 786.6\pm 97.5$ | $\rm 669.7\pm 83.2$ | $\rm 286.0\pm 38.7$ | $\rm 51.7\pm 5.8$ | $\rm 59.3\pm 5.9$ | $\rm 39.9\pm 4.8$
L10-091 | Field3 | 01:34:04.26 | +30:32:57.10 | 0.87 | 53 | 48 | 46 | B | $\rm 7.83\pm 0.60$ | $\rm 4220.7\pm 1032.1$ | $\rm 621.7\pm 149.8$ | $\rm 286.0\pm 71.5$ | $\rm 30.2\pm 5.9$ | $\rm 50.2\pm 7.7$ | $\rm 37.2\pm 6.5$
L10-092 | Field3 | 01:34:07.23 | +30:36:22.00 | 0.80 | 25 | 23 | 20 | A | $\rm 162.24\pm 3.93$ | $\rm 565.2\pm 23.9$ | $\rm 56.1\pm 3.7$ | $\rm 286.0\pm 11.5$ | $\rm 28.3\pm 2.5$ | $\rm 45.6\pm 2.5$ | $\rm 34.7\pm 2.2$
L10-093 | Field3 | 01:34:07.50 | +30:37:08.00 | 0.95 | 29 | 33 | 27 | B | $\rm 3.94\pm 0.21$ | $\rm 3612.9\pm 840.9$ | $\rm 595.8\pm 135.8$ | $\rm 286.0\pm 66.0$ | $\rm 33.8\pm 6.3$ | $\rm 50.2\pm 5.8$ | $\rm 44.4\pm 5.4$
L10-094 | Field1 | 01:34:08.37 | +30:46:33.20 | 0.69 | 24 | 43 | 17 | C | $\rm 7.88\pm 0.31$ | $\rm 427.6\pm 41.8$ | $\rm 377.9\pm 35.7$ | $\rm 286.0\pm 28.5$ | $\rm 39.9\pm 4.7$ | $\rm 39.3\pm 4.0$ | $\rm 29.7\pm 3.6$
L10-095 | Field1 | 01:34:10.02 | +30:47:14.90 | 0.90 | 65 | 71 | 58 | A | $\rm 8.26\pm 0.35$ | $\rm 599.2\pm 48.9$ | $\rm 452.5\pm 36.8$ | $\rm 286.0\pm 25.7$ | $\rm 37.4\pm 4.0$ | $\rm 51.7\pm 4.4$ | $\rm 38.0\pm 3.8$
L10-096 | Field1 | 01:34:10.70 | +30:42:24.00 | 1.29 | 57 | 53 | 74 | A | $\rm 49.83\pm 0.88$ | $\rm 274.5\pm 6.9$ | $\rm 126.5\pm 3.9$ | $\rm 286.0\pm 8.6$ | $\rm 42.9\pm 1.9$ | $\rm 71.4\pm 1.9$ | $\rm 57.5\pm 1.7$
L10-097 | Field3 | 01:34:11.04 | +30:38:59.90 | 0.81 | 47 | 55 | 38 | B | $\rm 8.90\pm 0.30$ | $\rm 840.0\pm 91.3$ | $\rm 166.2\pm 19.4$ | $\rm 286.0\pm 30.0$ | $\rm 33.5\pm 4.1$ | $\rm 44.7\pm 3.8$ | $\rm 36.2\pm 3.4$
L10-098 | Field3 | 01:34:12.69 | +30:35:12.00 | 0.44 | 0 | 0 | 0 | A | $\rm 90.76\pm 1.39$ | $\rm 425.4\pm 18.3$ | $\rm 96.0\pm 4.5$ | $\rm 286.0\pm 10.3$ | $\rm 18.7\pm 1.5$ | $\rm 24.4\pm 1.6$ | $\rm 19.3\pm 1.6$
L10-099 | Field5 | 01:34:13.11 | +30:48:33.47 | 0.64 | 27 | 28 | 17 | C | $\rm 91.26\pm 1.10$ | $\rm 199.8\pm 7.8$ | $\rm 38.2\pm 3.3$ | $\rm 286.0\pm 9.3$ | $\rm 26.6\pm 1.2$ | $\rm 37.4\pm 1.2$ | $\rm 26.2\pm 1.0$
L10-100 | Field1 | 01:34:13.65 | +30:43:27.00 | 0.86 | 56 | 64 | 48 | A | $\rm 5.11\pm 0.23$ | $\rm 579.8\pm 95.7$ | $\rm 509.7\pm 81.8$ | $\rm 286.0\pm 46.8$ | $\rm 38.1\pm 4.8$ | $\rm 52.4\pm 4.8$ | $\rm 33.2\pm 3.9$
L10-101 | Field1 | 01:34:13.71 | +30:48:17.50 | 0.74 | 27 | 24 | 20 | B | $\rm 54.32\pm 1.10$ | $\rm 297.8\pm 8.3$ | $\rm 34.3\pm 2.4$ | $\rm 286.0\pm 8.7$ | $\rm 30.3\pm 2.2$ | $\rm 44.8\pm 2.0$ | $\rm 29.5\pm 1.7$
L10-102 | Field3 | 01:34:14.10 | +30:34:30.90 | 0.50 | 32 | 30 | 16 | B | $\rm 122.34\pm 2.45$ | $\rm 357.3\pm 11.9$ | $\rm 49.2\pm 3.1$ | $\rm 286.0\pm 9.8$ | $\rm 16.7\pm 1.9$ | $\rm 28.2\pm 2.0$ | $\rm 22.0\pm 1.8$
L10-103 | Field1 | 01:34:14.35 | +30:41:53.60 | 0.87 | 36 | 33 | 31 | A | $\rm 11.29\pm 0.32$ | $\rm 436.1\pm 46.2$ | $\rm 226.3\pm 25.8$ | $\rm 286.0\pm 30.4$ | $\rm 39.9\pm 2.9$ | $\rm 50.7\pm 2.8$ | $\rm 35.9\pm 2.4$
L10-104 | Field3 | 01:34:14.38 | +30:39:41.60 | 1.07 | 45 | 45 | 48 | A | $\rm 21.29\pm 0.70$ | $\rm 1818.5\pm 178.0$ | $\rm 143.3\pm 16.1$ | $\rm 286.0\pm 27.9$ | $\rm 32.3\pm 3.5$ | $\rm 61.3\pm 3.7$ | $\rm 45.3\pm 3.1$
L10-105 | Field5 | 01:34:14.36 | +30:53:51.90 | 0.98 | 45 | 56 | 44 | A | $\rm 57.29\pm 1.74$ | $\rm 447.1\pm 25.2$ | $\rm 159.5\pm 9.4$ | $\rm 286.0\pm 16.6$ | $\rm 30.6\pm 3.2$ | $\rm 58.2\pm 3.6$ | $\rm 39.7\pm 2.9$
L10-106 | Field3 | 01:34:14.67 | +30:31:50.90 | 0.93 | 33 | 36 | 30 | A | $\rm 18.77\pm 0.70$ | $\rm 1063.0\pm 196.3$ | $\rm 462.6\pm 83.4$ | $\rm 286.0\pm 51.4$ | $\rm 37.0\pm 4.2$ | $\rm 50.5\pm 4.1$ | $\rm 42.0\pm 3.8$
L10-107 | Field3 | 01:34:15.57 | +30:32:59.90 | 0.82 | 40 | 50 | 33 | A | $\rm 20.84\pm 0.60$ | $\rm 847.6\pm 108.7$ | $\rm 273.0\pm 36.6$ | $\rm 286.0\pm 37.0$ | $\rm 31.5\pm 3.6$ | $\rm 46.2\pm 3.3$ | $\rm 35.8\pm 2.9$
L10-108 | Field5 | 01:34:16.31 | +30:52:32.70 | 0.57 | 27 | 28 | 15 | A | $\rm 150.10\pm 1.79$ | $\rm 204.3\pm 8.5$ | $\rm 68.7\pm 4.1$ | $\rm 286.0\pm 10.2$ | $\rm 22.1\pm 1.2$ | $\rm 33.5\pm 1.2$ | $\rm 23.0\pm 1.0$
L10-109 | Field5 | 01:34:17.00 | +30:51:47.10 | 0.39 | 23 | 28 | 9 | B | $\rm 127.26\pm 1.31$ | $\rm 173.5\pm 8.4$ | $\rm 192.1\pm 9.3$ | $\rm 286.0\pm 12.6$ | $\rm 18.8\pm 1.0$ | $\rm 22.5\pm 1.1$ | $\rm 16.1\pm 0.9$
L10-110 | Field3 | 01:34:17.03 | +30:33:57.70 | 0.55 | 22 | 23 | 12 | B | $\rm 139.04\pm 2.99$ | $\rm 387.9\pm 13.1$ | $\rm 46.6\pm 3.4$ | $\rm 286.0\pm 10.5$ | $\rm 16.7\pm 2.1$ | $\rm 31.1\pm 2.2$ | $\rm 24.1\pm 2.0$
L10-111 | Field1 | 01:34:17.61 | +30:41:23.30 | 1.01 | 66 | 71 | 67 | A | $\rm 24.42\pm 0.58$ | $\rm 424.4\pm 26.5$ | $\rm 354.7\pm 21.7$ | $\rm 280.8\pm 17.7$ | $\rm 42.5\pm 2.5$ | $\rm 58.5\pm 2.6$ | $\rm 42.5\pm 2.2$
L10-112 | Field5 | 01:34:18.32 | +30:54:05.80 | 0.88 | 21 | 25 | 19 | A | $\rm 30.34\pm 1.33$ | $\rm 1249.3\pm 215.0$ | $\rm 233.1\pm 42.3$ | $\rm 286.0\pm 49.3$ | $\rm 35.2\pm 4.5$ | $\rm 50.9\pm 4.9$ | $\rm 36.6\pm 4.2$
L10-113 | Field3 | 01:34:19.28 | +30:33:45.90 | 0.48 | 25 | 23 | 12 | A | $\rm 153.91\pm 3.27$ | $\rm 448.6\pm 32.5$ | $\rm 298.3\pm 22.4$ | $\rm 286.0\pm 21.3$ | $\rm 15.7\pm 1.9$ | $\rm 27.1\pm 2.1$ | $\rm 21.2\pm 1.9$
L10-114 | Field3 | 01:34:19.87 | +30:33:56.00 | 0.69 | 29 | 29 | 20 | A | $\rm 60.52\pm 1.30$ | $\rm 504.9\pm 41.0$ | $\rm 336.4\pm 28.1$ | $\rm 286.0\pm 23.8$ | $\rm 20.6\pm 2.1$ | $\rm 38.6\pm 2.2$ | $\rm 30.5\pm 2.0$
L10-116 | Field5 | 01:34:23.54 | +30:54:23.23 | 0.83 | 32 | 48 | 27 | A | $\rm 1.89\pm 0.15$ | $\rm 872.2\pm 261.8$ | $\rm 489.8\pm 149.0$ | $\rm 286.0\pm 88.0$ | $\rm 35.3\pm 7.2$ | $\rm 52.6\pm 10.8$ | $\rm 30.5\pm 8.0$
L10-118 | Field1 | 01:34:25.33 | +30:48:30.30 | 0.78 | 47 | 40 | 37 | A | $\rm 10.51\pm 0.56$ | $\rm 255.8\pm 21.1$ | $\rm 87.2\pm 10.0$ | $\rm 281.7\pm 25.9$ | $\rm 32.2\pm 6.2$ | $\rm 46.2\pm 5.2$ | $\rm 32.1\pm 4.4$
L10-119 | Field3 | 01:34:25.87 | +30:33:16.80 | 0.45 | 0 | 0 | 0 | A | $\rm 4.29\pm 0.16$ | $\rm 327.5\pm 56.9$ | $\rm 56.1\pm 15.1$ | $\rm 286.0\pm 39.0$ | $\rm 12.3\pm 3.6$ | $\rm 28.2\pm 4.1$ | $\rm 16.5\pm 4.0$
L10-120 | Field1 | 01:34:29.61 | +30:41:33.40 | 0.62 | 0 | 0 | 0 | C | $\rm 14.21\pm 0.18$ | $\rm 334.7\pm 22.8$ | $\rm 358.8\pm 24.8$ | $\rm 248.1\pm 16.8$ | $\rm 32.2\pm 1.3$ | $\rm 38.1\pm 1.4$ | $\rm 24.0\pm 1.4$
L10-121 | Field3 | 01:34:30.29 | +30:35:44.80 | 0.97 | 54 | 54 | 52 | A | $\rm 30.03\pm 1.15$ | $\rm 992.3\pm 98.2$ | $\rm 311.6\pm 31.1$ | $\rm 286.0\pm 29.6$ | $\rm 21.9\pm 3.0$ | $\rm 55.4\pm 4.1$ | $\rm 41.3\pm 3.5$

  * •

Continued.

(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | (13) | (14) | (15) | (16)
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---
Name | Field | RA | Dec |  [SII]/H$\alpha$ | $\sigma$ |  $\sigma$([SII]) | $\xi$ | Morphology |  F(H$\alpha$) | [OII]3727 | [OIII]5007 |  H$\alpha$ | [NII]6584 | [SII]6717 | [SII]6717
ID |  |  |  |  |  km s-1 |  km s-1 |  |  |  10-15 erg cm-2 s-1 |  |  |  |  |  |
L10-123 | Field3 | 01:34:32.34 | +30:35:32.60 | 1.03 | 47 | 51 | 48 | A | $\rm 17.03\pm 0.59$ | $\rm 1134.5\pm 73.4$ | $\rm 135.0\pm 9.5$ | $\rm 286.0\pm 18.9$ | $\rm 23.9\pm 3.5$ | $\rm 56.1\pm 3.8$ | $\rm 46.6\pm 3.4$
L10-124 | Field1 | 01:34:33.02 | +30:46:39.02 | 0.72 | 48 | 55 | 34 | A2 | $\rm 37.22\pm 0.70$ | $\rm 192.9\pm 3.4$ | $\rm 137.7\pm 2.8$ | $\rm 284.5\pm 7.1$ | $\rm 26.5\pm 1.9$ | $\rm 40.5\pm 1.9$ | $\rm 31.4\pm 1.7$
L10-126 | Field3 | 01:34:36.22 | +30:36:23.60 | 0.69 | 0 | 0 | 0 | A | $\rm 12.52\pm 0.30$ | $\rm 407.2\pm 66.4$ | $\rm 508.0\pm 81.2$ | $\rm 286.0\pm 45.7$ | $\rm 32.9\pm 2.4$ | $\rm 39.6\pm 2.7$ | $\rm 28.9\pm 2.6$
L10-127 | Field3 | 01:34:39.00 | +30:37:59.80 | 0.38 | 0 | 0 | 0 | A | $\rm 79.16\pm 1.39$ | $\rm 236.2\pm 12.7$ | $\rm 36.7\pm 3.9$ | $\rm 286.0\pm 12.3$ | $\rm 12.9\pm 1.7$ | $\rm 22.6\pm 1.9$ | $\rm 15.7\pm 1.9$
L10-128 | Field1 | 01:34:40.73 | +30:43:36.40 | 0.77 | 45 | 43 | 34 | A | $\rm 43.28\pm 0.72$ | $\rm 261.7\pm 7.8$ | $\rm 141.7\pm 5.0$ | $\rm 250.0\pm 8.3$ | $\rm 26.6\pm 1.6$ | $\rm 45.8\pm 1.6$ | $\rm 30.8\pm 1.4$
L10-129 | Field1 | 01:34:41.10 | +30:43:28.30 | 0.96 | 58 | 60 | 55 | A | $\rm 89.42\pm 1.84$ | $\rm 337.7\pm 12.6$ | $\rm 247.0\pm 9.8$ | $\rm 257.6\pm 10.9$ | $\rm 35.1\pm 2.1$ | $\rm 56.0\pm 2.2$ | $\rm 39.6\pm 1.8$
L10-130 | Field1 | 01:34:41.16 | +30:43:55.40 | 0.64 | 41 | 40 | 26 | A | $\rm 9.02\pm 0.38$ | $\rm 357.2\pm 32.7$ | $\rm 387.1\pm 35.5$ | $\rm 262.2\pm 25.8$ | $\rm 25.0\pm 4.1$ | $\rm 39.3\pm 4.1$ | $\rm 24.8\pm 3.4$
L10-131 | Field3 | 01:34:41.89 | +30:37:35.20 | 0.39 | 0 | 0 | 0 | A | $\rm 145.33\pm 2.92$ | $\rm 209.9\pm 12.6$ | $\rm 45.5\pm 4.7$ | $\rm 286.0\pm 13.5$ | $\rm 13.3\pm 1.9$ | $\rm 23.2\pm 2.2$ | $\rm 15.3\pm 2.1$
L10-132 | Field1 | 01:34:44.62 | +30:42:38.80 | 0.31 | 6 | 2 | 2 | C | $\rm 34.96\pm 0.91$ | $\rm 130.0\pm 5.1$ | $\rm 10.1\pm 2.1$ | $\rm 278.1\pm 9.2$ | $\rm 19.2\pm 2.9$ | $\rm 18.4\pm 2.3$ | $\rm 13.0\pm 2.1$
L14-002 | Field7 | 01:32:27.85 | +30:35:44.60 | 0.62 | 38 | 45 | 24 | – | $\rm 29.55\pm 1.34$ | $\rm 558.0\pm 62.2$ | $\rm 139.5\pm 14.6$ | $\rm 286.0\pm 28.3$ | $\rm 19.0\pm 5.3$ | $\rm 37.2\pm 5.0$ | $\rm 25.0\pm 4.0$
L14-004 | Field7 | 01:32:35.36 | +30:35:19.80 | 0.30 | 0 | 0 | 0 | – | $\rm 45.61\pm 0.58$ | $\rm 281.7\pm 16.9$ | $\rm 30.2\pm 5.1$ | $\rm 286.0\pm 12.6$ | $\rm 8.8\pm 1.2$ | $\rm 17.4\pm 1.3$ | $\rm 13.0\pm 1.3$
L14-005 | Field8 | 01:32:37.16 | +30:17:54.30 | 0.41 | 0 | 0 | 0 | – | $\rm 12.62\pm 0.35$ | $\rm 505.6\pm 47.1$ | $\rm 434.6\pm 35.0$ | $\rm 266.9\pm 22.2$ | $\rm 12.7\pm 2.7$ | $\rm 27.3\pm 3.0$ | $\rm 14.2\pm 2.9$
L14-009 | Field7 | 01:32:40.94 | +30:31:50.00 | 0.28 | 16 | 17 | 5 | – | $\rm 42.35\pm 0.96$ | $\rm 548.5\pm 58.6$ | $\rm 57.9\pm 4.1$ | $\rm 286.0\pm 11.9$ | $\rm 15.3\pm 2.2$ | $\rm 18.2\pm 2.2$ | $\rm 10.3\pm 1.8$
L14-010 | Field7 | 01:32:42.71 | +30:36:18.71 | 0.42 | 18 | 15 | 8 | – | $\rm 27.40\pm 0.56$ | $\rm 646.8\pm 67.8$ | $\rm 27.1\pm 4.6$ | $\rm 286.0\pm 13.8$ | $\rm 12.0\pm 1.7$ | $\rm 25.3\pm 1.9$ | $\rm 16.6\pm 1.6$
L14-012 | Field8 | 01:32:45.47 | +30:23:14.20 | 0.42 | 14 | 10 | 6 | – | $\rm 9.46\pm 0.27$ | $\rm 296.1\pm 48.9$ | – | $\rm 281.4\pm 16.7$ | $\rm 19.6\pm 3.1$ | $\rm 25.2\pm 2.7$ | $\rm 16.3\pm 2.3$
L14-016 | Field7 | 01:32:52.80 | +30:31:34.20 | 0.47 | 19 | 18 | 9 | – | $\rm 51.25\pm 0.76$ | $\rm 356.6\pm 17.2$ | $\rm 29.6\pm 3.2$ | $\rm 286.0\pm 9.6$ | $\rm 12.7\pm 1.4$ | $\rm 27.5\pm 1.4$ | $\rm 19.4\pm 1.2$
L14-020 | Field7 | 01:32:56.12 | +30:33:30.40 | 0.85 | 28 | 24 | 24 | – | $\rm 35.73\pm 1.14$ | $\rm 1082.3\pm 109.7$ | $\rm 57.4\pm 5.5$ | $\rm 286.0\pm 16.4$ | $\rm 22.8\pm 3.1$ | $\rm 52.0\pm 3.2$ | $\rm 32.6\pm 2.5$
L14-023 | Field7 | 01:32:57.18 | +30:39:14.70 | 0.41 | 18 | 16 | 7 | – | $\rm 19.82\pm 0.36$ | $\rm 531.3\pm 42.0$ | $\rm 10.5\pm 3.0$ | $\rm 286.0\pm 9.9$ | $\rm 10.0\pm 1.5$ | $\rm 23.0\pm 1.7$ | $\rm 17.7\pm 1.5$
L14-038 | Field4 | 01:33:13.46 | +30:28:13.10 | 0.47 | 21 | 22 | 10 | – | $\rm 40.92\pm 0.80$ | $\rm 216.9\pm 13.4$ | $\rm 67.0\pm 6.8$ | $\rm 219.7\pm 13.6$ | $\rm 24.4\pm 1.9$ | $\rm 28.7\pm 2.1$ | $\rm 18.2\pm 1.7$
L14-039 | Field7 | 01:33:13.81 | +30:39:44.00 | 0.42 | 30 | 26 | 13 | – | $\rm 54.38\pm 1.71$ | $\rm 546.6\pm 84.9$ | $\rm 54.0\pm 4.7$ | $\rm 286.0\pm 14.9$ | $\rm 17.5\pm 3.7$ | $\rm 23.5\pm 2.7$ | $\rm 18.7\pm 2.5$
L14-040 | Field7 | 01:33:15.35 | +30:35:36.70 | 0.39 | 0 | 0 | 0 | – | $\rm 11.90\pm 0.35$ | $\rm 513.5\pm 127.7$ | – | $\rm 286.0\pm 29.6$ | $\rm 21.2\pm 2.9$ | $\rm 23.2\pm 3.2$ | $\rm 15.6\pm 3.1$
L14-043 | Field6 | 01:33:17.52 | +30:46:43.66 | 0.50 | 23 | 22 | 11 | – | $\rm 99.08\pm 1.26$ | $\rm 333.8\pm 25.6$ | $\rm 165.0\pm 11.1$ | $\rm 286.0\pm 16.8$ | $\rm 23.1\pm 1.2$ | $\rm 30.2\pm 1.2$ | $\rm 19.9\pm 1.0$
L14-044 | Field4 | 01:33:18.13 | +30:33:38.60 | 0.32 | 0 | 0 | 0 | – | $\rm 4.87\pm 0.12$ | $\rm 108.3\pm 40.0$ | – | $\rm 286.0\pm 37.9$ | $\rm 9.9\pm 2.3$ | $\rm 17.6\pm 2.5$ | $\rm 14.8\pm 2.5$
L14-048 | Field9 | 01:33:21.19 | +30:19:20.63 | 0.28 | 0 | 0 | 0 | – | $\rm 13.06\pm 0.27$ | $\rm 314.4\pm 43.4$ | – | $\rm 286.0\pm 23.8$ | $\rm 12.2\pm 2.0$ | $\rm 15.7\pm 2.2$ | $\rm 12.3\pm 2.2$
L14-049 | Field4 | 01:33:21.33 | +30:30:31.60 | 0.40 | 19 | 19 | 8 | – | $\rm 22.55\pm 0.33$ | $\rm 209.8\pm 11.9$ | – | $\rm 261.6\pm 14.2$ | $\rm 18.9\pm 1.4$ | $\rm 23.1\pm 1.5$ | $\rm 17.4\pm 1.3$
L14-054 | Field4 | 01:33:24.01 | +30:36:56.80 | 0.41 | 0 | 0 | 0 | – | $\rm 15.98\pm 0.29$ | $\rm 195.8\pm 20.5$ | – | $\rm 263.9\pm 24.2$ | $\rm 25.0\pm 1.8$ | $\rm 23.1\pm 2.0$ | $\rm 17.8\pm 2.0$
L14-055 | Field4 | 01:33:24.34 | +30:28:50.41 | 0.91 | 0 | 0 | 0 | – | $\rm 2.52\pm 0.19$ | $\rm 294.0\pm 63.6$ | $\rm 277.3\pm 61.8$ | $\rm 160.0\pm 35.6$ | $\rm 36.8\pm 7.6$ | $\rm 56.2\pm 8.9$ | $\rm 35.1\pm 8.3$
L14-058 | Field9 | 01:33:27.94 | +30:18:17.04 | 0.86 | 49 | 50 | 42 | – | $\rm 9.06\pm 0.54$ | $\rm 966.2\pm 122.0$ | $\rm 207.8\pm 28.2$ | $\rm 286.0\pm 39.0$ | $\rm 19.5\pm 4.6$ | $\rm 51.8\pm 6.4$ | $\rm 34.0\pm 4.9$
L14-059 | Field9 | 01:33:27.97 | +30:15:59.49 | 0.37 | 0 | 0 | 0 | – | $\rm 2.40\pm 0.10$ | – | – | $\rm 286.0\pm 49.2$ | – | $\rm 21.2\pm 4.5$ | $\rm 15.5\pm 4.5$
L14-065 | Field9 | 01:33:30.64 | +30:21:01.50 | 0.65 | 29 | 30 | 19 | – | $\rm 36.72\pm 1.05$ | $\rm 568.7\pm 39.5$ | – | $\rm 286.0\pm 18.9$ | $\rm 18.3\pm 3.3$ | $\rm 37.5\pm 2.9$ | $\rm 27.6\pm 2.5$
L14-066 | Field9 | 01:33:31.20 | +30:21:14.26 | 0.67 | 23 | 24 | 15 | – | $\rm 21.16\pm 0.66$ | $\rm 403.0\pm 48.8$ | – | $\rm 286.0\pm 34.0$ | $\rm 15.4\pm 2.7$ | $\rm 38.5\pm 3.2$ | $\rm 28.7\pm 2.8$
L14-070 | Field9 | 01:33:35.05 | +30:19:24.64 | 0.59 | 15 | 14 | 9 | – | $\rm 13.99\pm 0.62$ | $\rm 614.7\pm 73.5$ | $\rm 26.2\pm 10.6$ | $\rm 286.0\pm 31.7$ | $\rm 28.3\pm 7.6$ | $\rm 32.9\pm 4.3$ | $\rm 26.2\pm 3.9$
L14-072 | Field4 | 01:33:34.99 | +30:29:54.60 | 0.95 | 52 | 56 | 50 | – | $\rm 7.72\pm 0.13$ | $\rm 386.4\pm 19.8$ | $\rm 202.5\pm 10.6$ | $\rm 259.4\pm 13.0$ | $\rm 31.5\pm 1.7$ | $\rm 55.0\pm 2.0$ | $\rm 40.3\pm 1.6$
L14-075 | Field4 | 01:33:37.02 | +30:33:10.00 | 0.60 | 27 | 30 | 16 | – | $\rm 63.01\pm 0.66$ | $\rm 298.1\pm 10.6$ | $\rm 95.3\pm 4.5$ | $\rm 286.0\pm 9.8$ | $\rm 26.8\pm 1.1$ | $\rm 36.2\pm 1.2$ | $\rm 23.8\pm 1.0$
L14-080 | Field4 | 01:33:39.84 | +30:34:30.54 | 0.90 | 19 | 26 | 17 | – | $\rm 10.05\pm 0.17$ | $\rm 443.8\pm 31.2$ | $\rm 103.0\pm 8.3$ | $\rm 286.0\pm 17.3$ | $\rm 39.2\pm 1.9$ | $\rm 53.6\pm 2.0$ | $\rm 36.3\pm 1.7$
L14-092 | Field9 | 01:33:47.51 | +30:17:13.77 | 0.42 | 13 | 11 | 6 | – | $\rm 12.94\pm 0.39$ | $\rm 792.1\pm 105.6$ | $\rm 341.7\pm 45.3$ | $\rm 286.0\pm 37.6$ | $\rm 20.6\pm 3.2$ | $\rm 23.3\pm 2.7$ | $\rm 19.2\pm 2.5$
L14-093 | Field9 | 01:33:47.79 | +30:18:05.17 | 0.53 | 26 | 24 | 14 | – | $\rm 34.81\pm 0.67$ | $\rm 490.4\pm 20.9$ | – | $\rm 286.0\pm 10.2$ | $\rm 13.1\pm 1.6$ | $\rm 32.2\pm 1.8$ | $\rm 21.2\pm 1.5$
L14-103 | Field4 | 01:33:52.56 | +30:28:38.40 | 0.40 | 0 | 0 | 0 | – | $\rm 6.03\pm 0.19$ | $\rm 109.5\pm 19.4$ | – | $\rm 230.2\pm 32.7$ | $\rm 24.1\pm 3.1$ | $\rm 25.3\pm 3.3$ | $\rm 15.2\pm 3.3$
L14-106 | Field9 | 01:33:54.63 | +30:18:51.10 | 0.66 | 64 | 81 | 43 | – | $\rm 17.60\pm 1.30$ | $\rm 1160.6\pm 178.0$ | $\rm 330.5\pm 43.6$ | $\rm 286.0\pm 41.6$ | – | $\rm 43.9\pm 8.6$ | $\rm 22.6\pm 6.0$
L14-122 | Field2 | 01:34:00.25 | +30:39:28.90 | 0.77 | 0 | 0 | 0 | – | $\rm 34.01\pm 1.01$ | $\rm 1636.8\pm 265.7$ | $\rm 134.8\pm 26.5$ | $\rm 286.0\pm 45.8$ | $\rm 43.4\pm 3.1$ | $\rm 44.1\pm 3.4$ | $\rm 32.9\pm 3.3$
L14-125 | Field5 | 01:34:00.52 | +30:50:43.09 | 0.80 | 32 | 38 | 26 | – | $\rm 3.94\pm 0.32$ | $\rm 239.8\pm 52.7$ | $\rm 156.0\pm 33.3$ | $\rm 224.4\pm 47.5$ | $\rm 40.2\pm 9.8$ | $\rm 47.4\pm 9.5$ | $\rm 32.7\pm 7.8$
L14-133 | Field5 | 01:34:04.83 | +30:58:32.35 | 0.29 | 14 | 15 | 4 | – | $\rm 36.52\pm 0.91$ | $\rm 254.6\pm 31.1$ | – | $\rm 286.0\pm 16.9$ | $\rm 15.0\pm 3.7$ | $\rm 16.5\pm 2.4$ | $\rm 12.5\pm 2.2$
L14-148 | Field3 | 01:34:13.85 | +30:30:39.80 | 0.59 | 16 | 32 | 9 | – | $\rm 3.34\pm 0.13$ | $\rm 1164.4\pm 200.4$ | $\rm 528.2\pm 80.6$ | $\rm 286.0\pm 44.3$ | $\rm 26.6\pm 4.0$ | $\rm 30.4\pm 4.4$ | $\rm 28.2\pm 4.3$
L14-153 | Field1 | 01:34:14.55 | +30:44:36.20 | 0.68 | 0 | 0 | 0 | – | $\rm 14.32\pm 0.58$ | $\rm 578.4\pm 57.4$ | $\rm 120.4\pm 14.5$ | $\rm 286.0\pm 28.8$ | $\rm 32.1\pm 4.1$ | $\rm 41.9\pm 4.6$ | $\rm 26.4\pm 4.4$
L14-162 | Field5 | 01:34:19.45 | +30:52:48.90 | 0.57 | 24 | 30 | 14 | – | $\rm 39.41\pm 1.27$ | $\rm 243.5\pm 46.4$ | – | $\rm 286.0\pm 35.3$ | $\rm 18.9\pm 3.6$ | $\rm 34.4\pm 3.6$ | $\rm 23.1\pm 3.0$
L14-163 | Field3 | 01:34:19.68 | +30:33:41.50 | 0.38 | 24 | 20 | 9 | – | $\rm 105.05\pm 2.16$ | $\rm 294.8\pm 31.5$ | $\rm 425.9\pm 46.2$ | $\rm 286.0\pm 30.8$ | $\rm 12.1\pm 1.8$ | $\rm 21.2\pm 2.0$ | $\rm 16.6\pm 1.8$
L14-167 | Field3 | 01:34:24.08 | +30:33:24.40 | 0.48 | 0 | 0 | 0 | – | $\rm 32.59\pm 0.53$ | $\rm 328.1\pm 21.7$ | $\rm 194.6\pm 13.8$ | $\rm 286.0\pm 18.5$ | $\rm 17.5\pm 1.6$ | $\rm 26.5\pm 1.8$ | $\rm 21.0\pm 1.7$
L14-168 | Field1 | 01:34:24.48 | +30:48:58.30 | 0.41 | 0 | 0 | 0 | – | $\rm 33.21\pm 0.61$ | $\rm 109.4\pm 7.3$ | – | $\rm 286.0\pm 11.2$ | $\rm 18.3\pm 1.8$ | $\rm 24.6\pm 2.0$ | $\rm 16.6\pm 2.0$
L14-173 | Field3 | 01:34:29.77 | +30:35:08.40 | 0.53 | 16 | 22 | 9 | – | $\rm 29.22\pm 1.57$ | $\rm 513.5\pm 74.0$ | $\rm 26.9\pm 9.5$ | $\rm 286.0\pm 30.3$ | $\rm 14.1\pm 5.0$ | $\rm 27.5\pm 5.4$ | $\rm 25.9\pm 5.3$
L14-180 | Field1 | 01:34:37.40 | +30:44:11.00 | 0.41 | 0 | 0 | 0 | – | $\rm 46.33\pm 0.79$ | $\rm 132.1\pm 5.6$ | $\rm 17.0\pm 3.0$ | $\rm 286.0\pm 9.9$ | $\rm 19.3\pm 1.7$ | $\rm 24.7\pm 1.8$ | $\rm 16.4\pm 1.8$
L14-182 | Field3 | 01:34:39.69 | +30:39:17.60 | 0.60 | 34 | 35 | 21 | – | $\rm 20.38\pm 0.71$ | $\rm 448.8\pm 46.5$ | – | $\rm 286.0\pm 25.4$ | $\rm 7.9\pm 2.8$ | $\rm 34.6\pm 3.6$ | $\rm 25.1\pm 3.1$
L14-187 | Field1 | 01:34:42.68 | +30:40:51.50 | 0.48 | 0 | 0 | 0 | – | $\rm 6.65\pm 0.24$ | $\rm 222.7\pm 30.1$ | – | $\rm 286.0\pm 28.5$ | $\rm 18.7\pm 3.6$ | $\rm 24.6\pm 3.9$ | $\rm 23.1\pm 3.9$
L14-189 | Field3 | 01:34:45.40 | +30:35:35.20 | 0.89 | 52 | 56 | 47 | – | $\rm 10.18\pm 0.72$ | $\rm 1265.3\pm 181.8$ | $\rm 331.9\pm 46.8$ | $\rm 286.0\pm 43.6$ | $\rm 25.2\pm 7.8$ | $\rm 54.3\pm 8.0$ | $\rm 34.9\pm 6.3$
L14-191 | Field3 | 01:34:47.24 | +30:34:25.00 | 0.42 | 3 | 18 | 1 | – | $\rm 8.30\pm 0.39$ | $\rm 301.9\pm 48.9$ | – | $\rm 286.0\pm 25.4$ | $\rm 16.8\pm 4.8$ | $\rm 23.9\pm 5.0$ | $\rm 18.4\pm 4.5$

  * •

“†” Line ratios of the regions where H$\beta$ is not measured; these line
ratios are computed by estimating an H$\beta$ flux (3$\sigma$, see Duarte
Puertas et al., 2021) value and are not used in our analysis.

Table 6: Impact of the threshold $\xi$: Fraction of SNRs in the L10 and L14 samples which do not pass the given threshold. Sample | $\xi\leq 12$ | $\xi\leq 10$ | $\xi\leq 8$ | $\xi\leq 6$
---|---|---|---|---
L10 (118 SNRs) | 18% | 14% | 10% | 8%
L14 (45 SNRs) | 67% | 62% | 47% | 40%

Finally, in Fig. 34 three diagnostic plots are shown: [NII]/H$\alpha$ vs.
[OIII]/H$\beta$ (BPTO3N2), [SII]/H$\alpha$ vs. [OIII]/H$\beta$ (BPTO3S2), and
$\sigma$ vs. [SII]/H$\alpha$. In each of them, the SNR candidates have been
colour coded by their $\xi$ value; red stars for candidates with $\xi\ \geq$
12 and blue stars for those with $\xi\ <$ 12\. As in Fig. 14, in the case of
the BPTO3N2 and BPTO3S2 diagrams there is a substantial population of
candidates with low values of $\sigma$, which might be considered as older
SNRs, for which the expansion has been considerably slowed down. When
considering the [SII]/H$\alpha$ vs. $\sigma$ diagram it can be seen that the
candidates with $\xi\ <$ 12 populate the lower zone of this diagram and those
with higher values than 12 populate the upper part, as expected from Fig. 12
for Ho 12 and all HII regions in NGC6822.

Figure 34: Diagnostic diagrams (upper and center panel) and scheme of
identification (lower panel) for the sample of SNR candidates in M33. The red
and blue stars correspond to those candidates that do and do not satisfy the
condition $\xi\ \geq$12\. The dashed, continuous, and vertical dotted lines
show the Kewley et al. (2001) curve, the Kauffmann et al. (2003) demarcation,
and the limit value of [SII]/H$\alpha$=0.4, respectively.

##  5 Conclusions

Based on spectral datacubes obtained with SITELLE, we presented a detailed
study of the optical properties of a large sample (164) of known supernova
remnants in NGC 6822 and M33, with a particular emphasis on the measurement of
their integrated properties including their velocity dispersion, $\sigma$. Our
main conclusions are the following:

  * •

Ho 12 in NGC 6822 presents an intriguing spiral shape composed of multiple
knots mixed with a more diffuse structure. Although its global morphology is
similar at all wavelengths, we find noticeable differences in the line ratios,
radial velocities and velocity dispersion from one knot to the next. We also
note clear radial trends the properties of Ho12 as well as those of the
compact and shell-shaped SNRs in M33 which set them apart from those of HII
regions.

  * •

We introduce a diagram, $\sigma$ vs. [SII]/H$\alpha$, that can be used on a
pixel-by-pixel basis for individual objects or to assess the integrated
properties of a population of emission-line regions in a given galaxy. The
shape of the pixel-to-pixel diagrams depends on the morphological type of the
supernova remnants.

  * •

M33 SNRs showing A, A2, or A3 morphological types present higher values of
$\sigma$ in the central parts, decreasing as we move towards the outer parts.
In the case of type B and C SNRs this dependence is less evident. Also, the
scatter of [SII]/H$\alpha$ at a constant $\sigma$ value is lower in the types
A2 and A3 than in the rest of the morphological types defined by Long et al.
(2010).

  * •

Given that (a) the [SII]/H$\alpha$ ratio and the velocity dispersion are
generally spatially anti-correlated in HII regions; (b) the diffuse ionized
gas shows high values of [SII]/H$\alpha$ but low values of velocity
dispersion, and (c) supernova remnants are expected to show higher values of
both [SII]/H$\alpha$ and velocity dispersion than HII regions, we defined a
parameter that combines both properties, $\xi$=([SII]/H$\alpha$)$\times\
\sigma$. This parameter can be determined on a pixel-by-pixel basis in order
to facilitate the detection of supernova remnants using maps extracted from
datacubes, or as a parameter obtained from the integrated spectrum of
emission-line regions.

  * •

While a threshold of $\xi=12$ clearly separates the sole SNR in NGC 6822 from
the large HII regions in the same galaxy, the situation is not as clear-cut in
M33, which presents a wide variety of SNR morphologies and ISM structure.
While neither the L10 SNR sample nor the new SNRs found by L14 were assembled
using a measure of the velocity dispersion, we note a significant discrepancy
between them: 82% of the L10 SNRs satisfy the $\xi=12$ threshold (and 90% with
$\xi=8$), but only a third of the additional L14 SNRs satisfy the first
threshold and half the second. These might be older objects for which the
expansion has been significantly slowed down.

  * •

As expected, the detection rate of a significant velocity dispersion ($\sigma$
> 0) in known M33 SNRs is higher (92%, or 60/65) in our SN3 datacubes with the
canonical SIGNALS spectral resolution R = 5000 (Fields 5 to 9) than it is
(82%, or 70/98) in the datacubes obtained during the proof of concept program
(Fields 1 to 4, with R = 2200 - 2900).

  * •

We will make use of the results presented in this paper to study the SNR
population in more distant galaxies of the SIGNALS survey, such as NGC 4214
(Vicens-Mouret et al., 2023).

## Acknowledgements

We are grateful to the anonymous referee for very constructive suggestions
that have helped us to improve this manuscript. Based on observations obtained
with SITELLE, a joint project of Université Laval, ABB, Université de
Montréal, and the Canada-France-Hawaii Telescope (CFHT) which is operated by
the National Research Council of Canada, the Institut National des Sciences de
l’Univers of the Centre National de la Recherche Scientifique of France, and
the University of Hawaii. The authors wish to recognize and acknowledge the
very significant cultural role that the summit of Mauna Kea has always had
within the indigenous Hawaiian community. We are most grateful to have the
opportunity to conduct observations from this mountain.

SDP acknowledges financial support from Juan de la Cierva Formación fellowship
(FJC2021-047523-I) financed by MCIN/AEI/10.13039/501100011033 and by the
European Union ‘NextGenerationEU’/PRTR, Ministerio de Economía y
Competitividad under grants PID2019-107408GB-C44, PID2020-113689GB-I00, and
PID2020-114414GB-I00, PID2022-136598NB-C32, and from Junta de Andalucía
Excellence Project P18-FR-2664 and FQM108. SDP, LD, and CR are grateful to the
Natural Sciences and Engineering Research Council of Canada, the Fonds de
Recherche du Québec, and the Canada Foundation for Innovation for funding. LRN
is grateful to the National Science foundation NSF - 2109124 and the Natural
Sciences and Engineering Research Council of Canada NSERC - RGPIN-2023-03487
for their support. This research made use of astropy, a community-developed
core python (http://www.python.org, Van Rossum & Drake, 2009) package for
Astronomy (Astropy Collaboration et al., 2013, 2018, 2022); IPython (Pérez &
Granger, 2007); Matplotlib (Hunter, 2007); NumPy (van der Walt et al., 2011);
SciPy (Virtanen et al., 2020; Gommers et al., 2024); and Pandas (McKinney,
2010).

## Data Availability

SIGNALS data are part of the public domain already. The measurements
underlying this article can be shared upon request to the first author.

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