11institutetext: European Southern Observatory, Karl-Schwarzschild Str. 2,
85748 Garching bei München, Germany
11email<EMAIL_ADDRESS>22institutetext: Department of Astronomy, University
of Geneva, Chemin Pegasi 51, 1290 Versoix, Switzerland
33institutetext: Space Telescope Science Institute, 3700 San Martin Drive,
Baltimore, MD21218, USA
44institutetext: Franco-Chilean Laboratory for Astronomy, IRL 3386, CNRS &
Dep. de Astonomía, Universidad de Chile, Santiago, Chile
55institutetext: Institut d’Astrophysique de Paris, UMR 7095, CNRS & Sorbonne
Université, 98bis bd Arago, 75014 Paris, France
66institutetext: Institute of Astronomy, Kharkiv National University, Sumska
35, Kharkiv, 61022, Ukraine
77institutetext: AURA for ESA, 3700 San Martin Drive, Space Telescope Science
Institute, Baltimore, MD 21218, USA
88institutetext: Department of Physics & Astronomy, Johns Hopkins University,
3400 N. Charles Street, Baltimore, MD 21218, USA
99institutetext: European Southern Observatory, Alonso de Córdova 3107,
Casilla 19001, Vitacura, Santiago, Chile
1010institutetext: Cosmic Dawn Center (DAWN)
1111institutetext: DTU-Space, National Space Institute, Technical University
of Denmark, Elektrovej 327, 2800 Kgs. Lyngby, Denmark
1212institutetext: Observatoire de Lyon, 9 avenue Charles André, 69561 St.
Genis Laval, France
1313institutetext: Univ Lyon, Univ Lyon1, Ens de Lyon, CNRS, Centre de
Recherche Astrophysique de Lyon (CRAL) UMR5574, F-69230 Saint-Genis-Laval,
France

#  $\alpha$-element enhancements in the Magellanic Interstellar Medium:
evidence for recent star formation

Annalisa De Cia 1122 Julia Roman-Duval 33 Christina Konstantopoulou 22
Pasquier Noterdaeme 4455 Tanita Ramburuth-Hurt 22 Anna Velichko 2266 Andrew J.
Fox 7788 Cédric Ledoux 99 Patrick Petitjean 55 Iris Jermann 2210101111 Jens-
Kristian Krogager 2212121313

( Received Month Day, yyyy; accepted Month Day, yyyy)

###### Abstract

Context.  Important questions on the chemical composition of the neutral
interstellar medium (ISM) in the Large Magellanic Cloud (LMC) and Small
Magellanic Cloud (SMC) are still open. It is usually assumed that their
metallicity is uniform and equal to that measured in hot stars and H ii
regions, but direct measurements of the neutral ISM metallicity have not been
performed until now. Deriving the metallicity from the observed metal
abundances is not straightforward because they also depend on the depletion of
metals into dust as well as nucleosynthesis effects such as $\alpha$-element
enhancement.

Aims. We aim at measuring the metallicity of the neutral ISM in the LMC and
SMC, dust depletion, and any nucleosynthesis effects.

Methods. We collect literature column densities of Ti ii, Ni ii, Cr ii, Fe ii,
Mn ii, Si ii, Cu ii, Mg ii, S ii, P ii, Zn ii, and O i in the neutral ISM
towards 32 and $22$ hot stars in the LMC and SMC. We determine dust depletion
from the relative abundances of different metals, because they deplete with
different strengths. This includes a “golden sample” of sightlines where both
Ti and other $\alpha$-elements are available. We fit linear relations to the
observed abundance patterns, so that the slopes determine the strengths of
dust depletion and the normalizations determine the metallicities. We
investigate $\alpha$-element enhancements in the gas from the deviations from
the linear fits and compare them with stars.

Results. In our golden sample we find $\alpha$-element enhancement in the
neutral ISM in most systems, on average 0.26 dex (0.35 dex) for the LMC (SMC),
and Mn under-abundance in the SMC (on average $-0.35$ dex). Measurements of Mn
ii are not available for the LMC. These are higher than for stars at similar
metallicities. We find total neutral ISM metallicities that are mostly
consistent with hot stars metallicity, on average [$M$/H]${}_{\rm tot}=-0.33$
($-0.83$), with standard deviations of 0.30 (0.30), in the LMC (respectively
the SMC). In six systems, however, we find significantly lower metallicities,
two out of 32 in the LMC (with $\sim 16$% solar) and four out of 22 in the SMC
(3 and 10% solar), two of which are in the outskirts of the SMC near the
Magellanic Bridge, a region known for having a lower metallicity.

Conclusions. The observed $\alpha$-element enhancements and Mn under-abundance
are likely due to bursts of star formation, more recently than $\sim 1$ Gyr
ago, that enriched the ISM from core-collapse supernovae. With the exception
of lines of sight towards the Magellanic Bridge, the neutral gas in the LMC
and SMC appears fairly well mixed in terms of metallicity.

###### Key Words.:

ISM: abundances – Galaxies: Magellanic Clouds – ISM: dust

##  1 Introduction

Figure 1: The location of the lines of sight in the LMC. The total
metallicities in the neutral ISM along these lines of sight are highlighted
with the gray scale. The systems with metallicities that are significantly
lower than the nominal value (deviating by $3\sigma$), are highlighted in
orange. The metallicities of other lines of sight are consistent with the
nominal value from hot stars, within the uncertainties. The background image
is from DSS2. Figure 2: Same as Fig. 1, but for the SMC.

The chemical evolution of galaxies is intimately related to the evolution of
their stars and gas (e.g. Tinsley 1980). The chemical properties of the
interstellar medium (ISM) of galaxies can be studied in great detail from the
rest-frame UV absorption lines of a plethora of metals observable in the
spectra of bright background sources, such as stars in the Milky Way, Large
Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC). Different processes
shape the observed metal abundances of the neutral ISM: the overall
metallicity, the presence of dust, the over-abundance or under-abundance of
specific elements due to stellar nucleosynthesis, for example $\alpha$-element
enhancement. Large fractions of metals are missing from the observable gas-
phase because they are incorporated in dust grains, a phenomenon called dust
depletion (Field 1974; Savage & Sembach 1996; Phillips et al. 1982; Jenkins et
al. 1986; Jenkins 2009; De Cia et al. 2016; Roman-Duval et al. 2021).

While the observed abundances of all metals naturally depends on the intrinsic
overall metallicity, dust depletion affects some elements (called refractory,
i.e. with a high condensation temperature) more heavily than others (volatile,
with a low condensation temperature). On the other hand, the (subtle) effects
of stellar nucleosynthesis can be observed for elements that have specific
nucleosynthetic history, such as those produced by core-collapse or Type Ia
supernovae (SNe). In addition, ISM ionization can also play a role, although
it is less of a concern for gas that has a high enough column density to
shield against further ionization and keep it dominated by neutral H i, i.e.
the neutral ISM (Viegas 1995). The dominant ionization species in this phase
are typically C ii, N ii, O i, Mg ii, Si ii, Fe ii, S ii, etc. Disentangling
these effects from the observed abundance patterns is not straightforward. It
is possible to determine the amount of dust depletion from the relative
abundances of metals, based on the fact that different metals deplete into
dust with different strengths, and without assuming a reference metallicity of
the ISM (De Cia et al. 2016, 2021; Konstantopoulou et al. 2022). In this way
it is possible to determine the total (dust + gas) metallicity, after the
correction for dust depletion (e.g De Cia et al. 2018, 2021).

The study of the chemical properties of the LMC and SMC are of special
interest because it is possible to study in great detail both their resolved
stellar populations and their gas, in a lower-metallicity environment than for
the Milky Way. In addition, these systems are the largest111The dynamical
masses of the LMC and SMC are $M_{\rm dyn}=1.9\times 10^{11}$ and $6.5\times
10^{9}$ $M_{\odot}$, respectively (Shipp et al. 2021; Bekki & Stanimirović
2009) gas-rich dwarf galaxies close to the Milky Way. The Magellanic Stream of
gas highlights the strong interaction between the MCs and the Milky Way (e.g.,
Fox et al. 2010; D’Onghia & Fox 2016; Lucchini et al. 2020). The MCs may have
had multiple close encounters in the past four billion years (Bekki et al.
2004). Strong gas outflows are observed around the LMC (Barger et al. 2016).
The metal abundances in the ISM of the MCs have been studied in great detail
from UV-spectroscopy, for example by Tchernyshyov et al. (2015), Jenkins &
Wallerstein (2017), Roman-Duval et al. (2021), including the diversity of
relative abundances of individual components along one line of sight (Welty et
al. 1997, 1999). These authors estimate the depletions based on the deviations
of the observed gas-phase abundances from a fixed reference metallicity (or
abundances), which is typically taken from young stars and is assumed to
represent the total dust+gas metallicity. This methodology assumes that there
are no variations in the gas metallicity and that the abundance ratios are
intrinsically solar. With this assumption, any potential variations from the
reference abundances is by construction interpreted as due to dust depletion,
without disentangling between potential effects of variations in ISM
metallicity or nucleosynthesis contribution from specific stellar population
(e.g. $\alpha$-element enhancement). This is further discussed in Sect. 4 and
5. Konstantopoulou et al. (2022) study the relative abundances in the neutral
ISM in the MCs, together with other environments, and measure the amount of
depletion based on the relative abundances of metals and the fact that
different metals have different tendencies to deplete into dust. These authors
study sequences of dust depletion on the global sample of relative abundances
in the MCs, and thus study the overall properties of the sample, without
analysing the abundance patterns of individual systems in the MCs.

The $\alpha$ elements are elements such as O, Mg, Si, S, Ca, and Ti, which are
mostly produced by $\alpha$-capture in core-collapse SNe (Nomoto et al. 2006).
On the other hand, the Fe-group elements, including Mn, are mostly produced by
Type Ia SNe (Nomoto et al. 1997). Enhancement of $\alpha$ elements and Mn
under-abundance are often observed in low-metallicity stars in the Milky Way
and nearby dwarf galaxies (e.g. McWilliam 1997; Tolstoy et al. 2009; de Boer
et al. 2014; Hill et al. 2019), and likely the result of star formation,
because core-collapse SNe explode before most Type Ia SNe (e.g. Tinsley 1979).
On the other hand, $\alpha$-element enhancement in the neutral ISM (in the
gas, rather than in the stars) are seldom observed in nearby galaxies (Cullen
et al. 2021) and in some gas-rich galaxies (Damped Lyman $\alpha$ Absorbers,
DLAs; Wolfe et al. 2005) with low metal enrichment (Dessauges-Zavadsky et al.
2002, 2006; Cooke et al. 2011; Becker et al. 2012; Ledoux et al. 2002; De Cia
et al. 2016), in the regime where the otherwise strong effects of dust
depletion are almost negligible. Konstantopoulou et al. (2022) note a
potential $\alpha$-element enhancement and Mn under-abundance in the neutral
ISM in the Magellanic Clouds (MCs), from small deviations of these systems
from the overall depletion properties observed for several other different
environments. Jenkins & Wallerstein (2017) find an underabundance of Mn in the
SMC, which they interpret as a stronger tendency of Mn to deplete into dust in
the SMC. Tchernyshyov et al. (2015), Jenkins & Wallerstein (2017), and Roman-
Duval et al. (2021) do not find $\alpha$-element enhancements in the neutral
ISM in the MCs. However, the formalism used by these authors interprets any
deviations of the observed abundances as due to dust depletion by
construction.

In this paper we adopt the so called ”relative” method to study the ISM, which
determines the depletion of the elements based on the relative abundances of
metals (De Cia et al. 2016, 2021; Konstantopoulou et al. 2022). A different
way to estimate the depletions is with the $F*$ method (Jenkins 2009; Jenkins
& Wallerstein 2017). The development of the $F*$ method enabled the key
discovery that the neutral ISM in the Milky Way has a continuum range of dust
depletion and allowed substantially more robust estimates of the strength of
the dust depletion than what was previously possible. The $F*$ method studies
the relations between the observed abundances, [$X$/H], assumes a fixed
metallicity of the gas, and no deviations due to nucleosynthesis effects (e.g.
no $\alpha$-element enhancements and Mn underabundance), and uses [$X$/H] to
trace dust depletion. If there are variations in ISM metallicity, the $F*$ can
observe them in the form of a discrepancy between the observed and expected
$N({\rm H})$. If there are deviations in the abundances [$X$/H] due to
nucleosynthesis, the $F*$ method interprets these variations as due to
depletion by construction. Thus, the current formalism of the $F*$ method is
not designed to disentangle between the effects of dust depletion,
metallicity, and nucleosynthesis effects and cannot purely determine dust
depletion in systems with nucleosynthesis effects such as $\alpha$-element
enhancements and Mn underabundance.

In this paper we study the chemical properties of the neutral ISM of the LMC
and SMC, with particular emphasis on the total (gas + dust) metallicity, dust
depletion, $\alpha$-element enhancement and Mn under-abundance in the neutral
ISM. In Sect. 2 and 3 we describe our sample and methodology, respectively. We
present and discuss our results in Sect. 4, include additional caveats in
Sect. 5, and conclude in Sect. 6.

Figure 3: Idealized illustration of different processes that can shape the ISM
abundance patterns. The observed abundances are on the $y$-axis, and the
$x$-axis represent the tendency of each element to deplete into dust grains.
a) If no dust and other processes that may cause additional deviations are at
play, the observed abundances reflect the actual metallicity of the gas. b) If
there is dust, the refractory elements show lower abundances, because they are
depleted. The more dust, the steeper the slope of the linear relation. The
$y$-intercept (at no depletion) of the solid line is the total (gas + dust)
metallicity. c) Deviations from the linear relation can be observed in the gas
for specific elements, in this example $\alpha$-element enhancement and Mn
under-abundance due to nucleosynthesis of recent core-collapse SNe. The dashed
line shows a fit to the $\alpha$-element data only. In this illustration Zn
(and other elements, e.g. P) is excluded from determination of the linear fit
and only shown here with the Fe-group elements. Any eventual deviations can be
observed in the data. d) The presence along the line of sight of a mix of two
gas components (empty circles) with different metallicities and amount of dust
can produce bending of the overall observed abundances (filled black circles)
measured over the whole line profile. The metallicity derived from the whole
line profile could be somewhere in-between the metallicities of the individual
components. If the abundances of enough metals with different refractory and
nucleosynthetic properties are observed, the effects of the different
processes (a-d) can be separated. Figure 4: Analysis of the abundance patterns
in the neutral ISM in the LMC and determination of the total metallicity and
overall strength of depletion. The variables and coefficients of the linear
relation are defined in Eqs. 1 to 5, where the $y$-intercept gives the
[M/H]tot and the slope of the relation gives the strength of depletion
[Zn/Fe]fit. In case Ti and another $\alpha$ element are constrained i.e. for
the golden sample, labelled with ’g’, the slope of the linear fit is
determined only from the $\alpha$ elements, which are marked in green, and
excluding O. The resulting fits are shown by the green dashed curves, and
their slopes are then fixed. The fit for the metallicity uses this slope and
is determined by the Fe-group elements Fe, Ni, and Cr (blue solid curves), and
excluding Zn and P from the fit. For the non-golden sample we fit linearly all
metals together, but excluding the $\alpha$ elements and Mn. The error bars
show the 1$\sigma$ uncertainties on the metal columns. The deviations from the
linear fit are mostly due to $\alpha$-element enhancement (see Sect. 4.2). The
uncertainties shown on the $y$-axis are the formal statistical errors on the
column densities. The uncertainty on $N(\mbox{H})_{\rm tot}$ is shown by the
error bar on the top left, it affects all points systematically and it is
included in the uncertainty of the [M/H]tot. Figure 5: Same as Fig. 4, but for
the SMC.

##  2 Sample

We collect a literature sample of metal column densities in the neutral ISM in
the SMC and LMC, for a total of 54 lines of sight. Tables 1 and 2 present the
targets of our LMC and SMC samples, respectively. The locations of the targets
in the LMC and SMC are shown in Figs. 1 and 2. The measurements of all the 32
LMC lines of sight in our sample are adopted from Roman-Duval et al. (2021) as
part of the METAL large HST program (Roman-Duval et al. 2019). Roman-Duval et
al. (2021) measured metal column densities using observations of hot stars
taken with the Hubble Space Telescope (HST) Cosmic Origins Spectrograph (COS;
Green et al. 2012) and the Space Telescope Imaging Spectrograph (STIS). Roman-
Duval et al. (2021) uses data collected with COS medium-resolution gratings
(G130M and G160M, with $R\sim 15,000$–$20,000$) and STIS (E140M with $R\sim
45,000$ and E230M with $R\sim 30,000$), with the exceptions of Sk-70 115 and
Sk-68 73, for which archival STIS E230H ($R\sim 114,000$) was used. The sample
of Roman-Duval et al. (2021) includes lines of sight which were previously
studied by Tchernyshyov et al. (2015), based on data from the Far Ultraviolet
Spectroscopic Explorer (FUSE; Sahnow et al. 2000) from the FUSE MC Legacy
Project archive (Blair et al. 2009). We adopt all the LMC column density
measurements from Roman-Duval et al. (2021). These authors adopt the technique
of Jenkins (1996) to correct for potential saturation of the absorption lines.
Additional information on the observations and column density measurements for
the LMC systems can be found in Roman-Duval et al. (2021). Potential
systematic differences in the measurements of column densities from data with
$R\sim 15,000$–$20,000$ or $R>30,000$ is studied by Roman-Duval et al. (2021),
who find a potential systematic underestimation of $N$(Zn) and $N$(Si) by up
to 0.3 dex in the lowest-resolution data (see their figure 23). Any potential
underestimation of $N$(Zn) does not affect our results, because Zn is not used
in this paper to estimate neither metallicities for the golden sample nor
$\alpha$-element enhancements (see Sect. 3). Any potential underestimation of
Si would also not affect our results, other than making the Si overabundances
that we observe stronger (see Sect.4.2). Roman-Duval et al. (2021) measure the
column densities of Mg ii from medium resolution COS data for BI 184, BI 253,
Sk-66 129, Sk-68 140, Sk-68 155, Sk-68 73, as well as BI 273, Sk-66 19, Sk-68
26, Sk-69 279, with the last four systems having also Ni ii measured from
medium resolution COS data. In most cases our analysis does not depend
strongly on these Ni ii and Mg ii measurements, because Fe ii and Si ii are
well measured from higher resolution STIS data. In two cases, namely BI 253
and Sk-68 73, of our most reliable golden sample (see below) the Mg ii column
density measured with lower-resolution data is the only element representing
the less-refractory $\alpha$-elements, adding some uncertainty to our ability
to constrain them. These two systems represent $\sim 8$% of our golden sample
and thus the potential saturation effects will not affect our results.

For the SMC, we use the column density measurements for $22$ lines of sight of
Jenkins & Wallerstein (2017) and Tchernyshyov et al. (2015). We adopt the
column densities for 18 out of 22 systems of Jenkins & Wallerstein (2017), who
measure them using data from STIS medium-resolution grating E140M and E230M
(with $R\sim 45,000$ and $R\sim 30,000$), similar to the LMC dataset that we
adopt from Roman-Duval et al. (2021). Jenkins & Wallerstein (2017) apply
corrections for potential saturation of the absorption lines adopting the
technique of Jenkins (1996). In addition, we include the column densities for
four systems in the SMC (namely, AzV 327, AzV 238, Sk 116, and Sk 9) from
Tchernyshyov et al. (2015), who measured them based on data taken with the COS
G185M grating ($R\sim 18,000$). Tchernyshyov et al. (2015) limit potential
saturation of the absorption lines by performing a simultaneous Voigt-profile
fit of multiple lines of the same ion. In case of strong saturation, this
technique may underestimate the column densities. However, these four lines of
sight are not part of our golden sample (see below), and thus will not
influence the results of our paper.

Konstantopoulou et al. (2022) collected column density measurements for the
MCs for the same sample222The difference in our SMC sample and that of
Konstantopoulou et al. (2022) is only for Sk 9, which is not in their sample.
and correct them for the most recent values of oscillator strength, which we
adopt here. For Mg ii, Si ii, Mn ii, Cu ii, Cr ii, and Ti ii we adopt the
oscillator strengths of Cashman et al. (2017), for Ni ii we adopt those of
Boissé & Bergeron (2019), for Zn ii those of Kisielius et al. (2015), for S ii
those of Kisielius et al. (2014), for P ii those of Kurucz (2017), and for the
other ions with no recent changes of the oscillator strengths we adopt the
values of Morton (2003). For the calculation of the (relative) abundances we
refer to the solar abundances of Asplund et al. (2021), and choosing the
photospheric or meteoritic abundances following the recommendations of Lodders
et al. (2009). A table of the solar abundances is reported in Konstantopoulou
et al. (2022).

We update the column density of Cr ii toward Sk-67 2 from $13.91\pm 0.06$
(Roman-Duval et al. 2021) to $13.0\pm 0.2$ from measurements of the Apparent
Optical Depth of the Cr ii 2062 and 2056 lines (Jenkins, private
communication), which are found in disagreement with the original measurement
based only on the Cr ii 2066 line, which is likely contaminated by other
features. The full updated analysis of the data along this line of sight will
be part of future publications from the ULLYSES project (Roman-Duval et al.
2020). This substantial change in Cr ii column density for the Sk-67 2 makes
the Cr abundance perfectly agree with the abundances of Fe and Ni (see the
study of its abundance pattern in Sect. 4).

Overall, we collect column density information for Ti ii, Ni ii, Cr ii, Fe ii,
Mn ii, Si ii, Cu ii, Mg ii, S ii, P ii, Zn ii, and O i. For both MC systems,
we adopt the column density measurements of Ti ii from Welty & Crowther
(2010). We define and build a golden sample from the systems with constrained
observations of Ti ii and at least another $\alpha$ element.

##  3 Determination of the total metallicity, overall strength of depletion,
and deviations

We determine the total (gas $+$ dust) metallicity in the LMC neutral ISM along
the different lines of sight using the “relative method” described in De Cia
et al. (2021). This method is based on the two basic facts: first, that the
total abundance $[X/{\rm H}]_{\rm tot}$ can be derived from the observed gas-
phase abundance of element $X$, $[X/{\rm H}]=\log N(X)-\log N({\rm
H})-X_{\odot}+12.$, and correcting it for the the depletion of element $X$ in
dust, $\delta_{X}$, as following: $[X/{\rm H}]_{\rm tot}=[X/{\rm
H}]-\delta_{X}$. Note that no attempt of including corrections for
nucleosynthesis effects (such as $\alpha$-element enhancement or Mn under-
abundance) is made here; however, these may become visible as deviations from
the abundance patterns that we expect from depletion effects. Second,
$\delta_{X}$ is a linear function of the overall strength of depletion, which
is described by the parameter [Zn/Fe]fit in the relative method. This
parameter is related to the observed [Zn/Fe], but is derived from the
abundances of several metals, e.g. Ti and other $\alpha$ elements when
possible, as we discuss below.

The total metallicity $[{\rm M/H}]_{\rm tot}$ and overall strength of
depletion $[{\rm Zn/Fe}]_{\rm fit}$ can then be derived with a linear fit to
the data, which are the observed gas-phase abundances of different metals and
the information on the tendency to deplete into dust for each metal ($B2_{X}$
coefficients, or refractory index), as follows:

$y=a+bx$ (1) $x=B2_{X}\mbox{,}$ (2) $\displaystyle y$ $\displaystyle=$
$\displaystyle\log N(X)-\log N({\rm H})-X_{\odot}+12-A2_{X}$
$\displaystyle\sim$ $\displaystyle[X/\mbox{H}]\mbox{,}$ $a=[{\rm M/H}]_{\rm
tot}\mbox{,}$ (4) $b=[{\rm Zn/Fe}]_{\rm fit}\mbox{.}$ (5)

We adopt the $A2_{X}$ and $B2_{X}$ coefficients of Konstantopoulou et al.
(2022), which are consistent with those of De Cia et al. (2016), but they
include 18 metals, and are based on a large collection of relative abundance
measurements for local and distant galaxies and on the most recent set of
oscillator strengths. We adopt $B2_{\rm P}=-0.26\pm 0.08$ from Konstantopoulou
et al. (2023), which is updated for the most recent oscillator strengths for P
transitions (Brown et al. 2018). The coefficients $A2_{X}$ could in fact be
omitted and assumed to be zero (which would imply zero depletion when $[{\rm
Zn/Fe}]=0$). The empirically measured values are mostly very close to zero. In
this work we include more metals for the analysis of the abundance patterns
than in De Cia et al. (2021). Uncertainties in both the $x$ and $y$ axes are
included in the calculation of the best linear fit to the abundance
patterns333For this task we make use of the IDL routine MPFITEXY, Williams et
al. (2010), which is based on the MPFIT package (Markwardt 2009).. The
uncertainties on $N(\mbox{H})_{\rm tot}$ systematically affect all the
$y$-values in a uniform way. Therefore, and unlike in De Cia et al. (2021), we
do not formally include them in the linear fit to the abundance patterns,
because the depletion (slope) does not depend on H. We include the
uncertainties on $N(\mbox{H})_{\rm tot}$ to the uncertainty of $[{\rm
M/H}]_{\rm tot}$ a posteriori, after the fit. Konstantopoulou et al. (2022)
find two different series of $B2_{X}$ values for the MCs for Ti and Mn (see
discussion in Sect. 5). We adopt the $B2_{X}$ that are derived globally for
local and distant galaxies.444Konstantopoulou et al. (2022) find two series of
$B2_{X}$ values, using or not the assumption of a constant $\alpha$-element
abundance in the MCs. The uncertainties we adopt on $B2_{X}$ do not include
the systematic uncertainty due to the two different assumptions. The global
values of $B2_{Ti}$ for the two cases are very similar. We test and discuss
the possibility of a significantly different $B2_{Ti}$ in Sect. 5.

Figure 3 visualizes how the abundance pattern in the neutral ISM is shaped by
different processes. The overall metallicity affects its normalization, i.e it
increases or decreases the abundance of all elements. The dust depletion
affects its slope, i.e. the refractory elements show lower abundances than the
volatile ones. In addition, deviations from a linear fit to the abundance
patterns can be caused by nucleosynthesis effects, such as $\alpha$-element
enhancement and Mn under-abundance. We consider this possibility by choosing
different sets of metals for the linear fits to the abundance patterns, which
we describe in more details below. Here we consider Ti, Mg, Si, S, and O as
full $\alpha$ elements, while we consider Fe, Ni, Cr in the Fe group. We treat
Mn separately, because its behaviour is somewhat opposite to the $\alpha$
elements (e.g. Kobayashi et al. 2020). The possibility of Zn and P having
intrinsic enhancement (somewhat following $\alpha$-element processes or
massive-star nucleosynthesis) is discussed in Sect. 5. Finally, another
potential cause of deviations from linear abundance patterns is the presence
of a mixture of gases with different metallicities and levels of depletion.
This may cause upturns from the linear abundance patterns, because the overall
abundance of refractory elements may arise from gas with low-metallicity and
little dust content (empty blue circles in Fig. 3, panel d), while the
abundance of the volatile elements may arise from heavily depleted gas at high
metallicities (empty magenta circles in Fig. 3, panel d). This is just an
example, and other configurations are possible. We discuss this in more
details in Sect. 4.5. The effect of the various processes on the abundance
patterns act on distinct elements differently, depending on the refractory and
nucleosynthetic properties of each element. Because of this, it is possible to
disentangle among the different processes, provided that data for a variety of
metals are available.

The choice of which metals to include in the analysis and linear fit to the
abundance patterns is vital to the outcome. We test different choices to
investigate the robustness of our results and avoid biases due to lack of data
or intrinsic variations of some of the metals (see the Appendix). The most
solid approach can be applied when several $\alpha$ and non-$\alpha$ elements
are constrained. We define our golden sample using systems where at least Ti,
another $\alpha$ element, and Fe are constrained, for a total of 10 lines of
sight towards the LMC and 14 towards the SMC. In these cases, we determine the
amount of dust ([Zn/Fe]fit555Here the slope, or strength of overall depletion,
does not depend on Fe nor Zn, but it uses the [Zn/Fe]fit notation because the
refractory index $B2_{X}$ was originally calculated from the depletion
sequences observed as a function on [Zn/Fe].) purely from the slope of the
linear fit to the abundance patterns of the $\alpha$ elements only (except O).
We then fix this slope and fit linearly the observed abundances of Fe, Ni, and
Cr (but not Mn, Zn and P) to find the total metallicity ([M/H]tot). For the
golden sample, the total metallicities are thus derived from the Fe group
abundances (free from potential $\alpha$-element enhancements or Mn
underabundance or any potential Zn and P variations), after correcting for
dust depletion. The values of [M/H]tot are indicated by the $y$-intercepts of
the solid lines at $x=0$ in the diagrams shown in Figs. 4 and 5. Zinc and
phosphorus are excluded from the determination of the linear fit to the
abundance patterns so that the results do not depend on the abundances of Zn
and P and can be used to investigate any eventual deviations of these elements
from the abundance patterns. Having constraints on Ti is crucial for this
approach, because they provide a sufficiently large dynamical range in
$B2_{X}$ for a solid determination of the slope of the abundance patterns. The
calculation of the uncertainties on [M/H]tot include both the uncertainties in
the normalization of the fit to the $\alpha$ elements (used for fixing the
slope) and the uncertainties on the normalization of the fit to the Fe-group
(with a fixed slope).

In case Ti is not constrained (for the non-golden sample), we consider the fit
to all metals but excluding the $\alpha$ elements and Mn to avoid the
influence of their potential deviations. In this situation, the fits to the
abundance patterns are dominated, at the volatile-element end, by Zn and P.
This is less optimal, because some intrinsic variations due to nucleosynthesis
may be at play, see Sect. 5. Further possibilities on the choice of metals for
the analysis of the abundance patterns are discussed in the Appendix.

In the the case of Sk-67 14, where only a few metals are available, we
consider the optimal fit to all metals (a mix of $\alpha$ and non-$\alpha$
elements) and include a posteriori an additional 0.32 dex666The 0.32 dex is
chosen here to be in-between the typical values of $\alpha$-element
enhancement in the Milky Way ($\sim 0.35$ dex McWilliam 1997) and DLAs ($\sim
0.3$ dex De Cia et al. 2016). in the uncertainty on their total metallicity to
account for the paucity of data and potential nucleosynthesis effects causing
over- or underestimate of the metallicity.

Figures 4 and 5 show the determination of the total metallicity and overall
strength of depletion from the fit to the abundance patterns. Figures 16 and
15 present a comparison of the different total metallicity and overall
strength of depletion resulting from a different choice of metals in the fit
to the abundance patterns. Tables 1 and 2 list the total metallicities and
strength of dust depletion of the line of sights towards our LMC and SMC
samples, respectively.

Figure 6: Distribution of the total (dust $+$ gas) metallicities, [$M$/H]tot,
in the neutral ISM in the LMC. Larger symbols highlight the most solid
measurements, for which multiple $\alpha$ (including Ti) and non-$\alpha$
elements are available, which we define as the golden sample). Systems with
metallicities that vary significantly from the mean are highlighted with
purple circles. The mean stellar metallicity in the LMC is marked by the
horizontal dashed line. The total metallicities that we measure are integrated
along the line of sight within the LMC. In case of a chemically inhomogeneous
ISM, they may be in-between a lower and a higher metallicity, but there are
degeneracies in the potential mixes. Figure 7: Same as Fig. 4, but for the
SMC. Figure 8: Distribution of the total metallicities in the neutral ISM for
the Milky Way (from De Cia et al. 2021) and Magellanic Clouds measured in this
work (top panel, shaded regions). For each of the three environments, the
expected distribution if the ISM total metallicities would be the same as in
hot stars is shown by a Gaussian curve centred on the hot-stars metallicity
and with a $\sigma$ equal to the mean of the uncertainties in $[{\rm
M/H}]_{\rm tot}$ that we measure. The values of metallicity in the Milky Way
ISM measured by Ritchey et al. (2023) are consistent with solar metallicity,
with a standard deviation of $\sim 0.1$ dex, and are not shown in this figure.
The bottom panel shows the cumulative distribution function of the observed
total metallicities.

##  4 Results and discussion

The neutral ISM is likely complex and possibly chemically inhomogeneous (e.g.
Welty et al. 2020; De Cia et al. 2021; Ramburuth-Hurt et al. 2023). Our
understanding of its chemical properties through the study of the abundance
patterns is hindered by the several processes that shape them. In this paper
we attempt to make sense of this complexity by studying metals with different
refractory and nucleosynthetic properties, and thereby separate different
effects that play an important role in shaping the abundance patterns: the
metallicity, the dust depletion, the $\alpha$-element enhancement, and the
presence of ISM mixtures. Here we discuss our results (Sect. 4.1 to 4.5) and
their caveats (Sect. 5).

###  4.1 The neutral ISM metallicities

Figures 6 and 7 show the distribution of total metallicities in neutral ISM in
the LMC and SMC towards the lines of sight considered here. The horizontal
lines mark the nominal metallicities from measurements of hot stars, $\log
Z/Z_{\odot}=-0.3$ and $-0.7$ for the LMC and SMC, respectively (Rolleston et
al. 2002; Trundle et al. 2007; Hunter et al. 2007). We find that most of the
lines of sight have ISM metallicities which are consistent, within the
uncertainties, with the nominal values. The mean total metallicity in the
neutral ISM in our sample is $[M/\mbox{H}]_{\rm tot}=-0.33$ ($-0.83$) with
standard deviation 0.30 (0.30) for the LMC (SMC). In addition, we observe
significant variations from the nominal metallicities, with a significance
level above $3\sigma$, for two lines of sight in the LMC (namely Sk-69 279 and
Sk-67 105, none of which is in the golden sample, with [$M$/H]${}_{\rm
tot}=-0.77\pm 0.09$ and $-0.79\pm 0.08$, respectively) and for four lines of
sight in the SMC (namely AzV 26 and Sk 191, both in the golden sample, with
[$M$/H]${}_{\rm tot}=-0.98\pm 0.08$ and $-1.37\pm 0.14$, respectively, and AzV
327 and AzV 476, both not in the golden sample, with [$M$/H]${}_{\rm
tot}=-1.55\pm 0.25$ and $-1.23\pm 0.11$, respectively). These six low-
metallicity systems are highlighted in Figs. 1, 2, 6 and 7.

Figure 8 shows the distribution of the total metallicities in the neutral ISM
for the Magellanic Clouds from this work and the Milky Way measurements from
De Cia et al. (2021). The distribution of ISM total metallicities in the LMC
is overall similar to the Milky Way, while the SMC lines of sight have overall
lower total metallicities of the neutral ISM. The Gaussian curves show, for
each of the three environments, what the expected distribution of metallicity
would be if the ISM total metallicities would be the same as in hot stars and
considering the typical uncertainties of our measurements. The center of the
Gaussian curves are on the hot stars metallicities and their $\sigma$ is equal
to the mean of the uncertainties in $[{\rm M/H}]_{\rm tot}$ that we measure.
Two lines of sight toward the LMC have supersolar metallicity but with very
large uncertainties (see Fig. 6), and these are excluded from the calculation
of the Gaussian width.

Intriguingly, two of the systems with the lowest neutral ISM metallicities in
our sample, Sk 191 and AzV 476, with [$M$/H]${}_{\rm tot}=-1.37\pm 0.14$ and
$-1.23\pm 0.11$, respectively, are located in the outskirts of the main body
of the SMC, closer to the Magellanic Bridge (or inter-cloud region) and its
densest part, the SMC South East Wing (e.g. Westerlund 1990). The system with
the lowest metallicity that we measure, AzV 327, with [$M$/H]${}_{\rm
tot}=-1.55\pm 0.25$, is located in the northern outskirts of the SMC. The
positions of these stars are shown in Figure 2. The metallicity of the gas in
the Magellanic Bridge is about 10% solar (or less), from the observations of
volatile elements such as Ar and O (Lehner et al. 2008). Rolleston et al.
(1999); Dufton et al. (2008) find that B stars in the Magellanic Bridge have
$[M/H]\sim-1$, while Ramachandran et al. (2021) measure very diverse
metallicities (between $-0.3$ and $-1.4$) in O-type stars in the Magellanic
Bridge, indicating that the ISM is chemically inhomogeneous and includes low
metallicities. On the other hand, Lee et al. (2005) find that B-type stars in
the SMC South East Wing, not far from Sk 191, show metallicities that are more
similar to the main SMC body. The Magellanic Bridge is a tidally stripped
region in between the MCs, likely resulting from the interaction between the
MCs about $\sim 0.2$ Gyr ago (Gardiner & Noguchi 1996; Besla et al. 2012). In
the simulations of Bekki & Chiba (2007) gas had been transferred from the SMC
to the LMC, so that the low-metallicities in the Magellanic Bridge are
produced by the SMC halo gas, depending on a metallicity gradient. We do not
find evidence for a present-day metallicity gradient in the neutral ISM of the
MCs (Figs. 1 and 2).

The line of sight towards Sk 191 has by far the lowest observed metal
abundances with respect to the the other SMC lines of sights observed by
Jenkins & Wallerstein (2017) (see their figure 2). These authors estimate the
dust depletion from the observed metal abundances [$X$/H] and conclude that
this line of sight may have a large amount of dust depletion, comparable to
the most dusty systems in the Milky Way. However, in this interpretation the
relative abundances of S, Si, and Ti observed towards Sk 191 do not fit the
dust depletion properties known from the Milky Way, and thus Jenkins &
Wallerstein (2017) conclude that the properties of dust depletion in the SMC
must be different from the MW, specifically for Mn, Ti and Mg and possibly
other elements. To further justify their interpretation of the high depletion
towards Sk 191 Jenkins & Wallerstein (2017) resort to a marginal detection of
the weak O i 1356 line. However, as previously stated in this paper, the
formalism used by Jenkins & Wallerstein (2017) to estimate the dust depletion
does not take into account any possible variations of the ISM abundances due
to different metallicity or nucleosynthesis effects such as $\alpha$-element
enhancements. They interpret the low abundances towards Sk 191 as a pure
tracer of dust depletion, by construction of their methodology. On the other
hand, our analysis of the abundances and relative abundances allows us to
independently derive the dust depletion (from the relative abundances, which
determine the slope of the fit to the abundance patterns), the metallicity
(from the normalization of the fit to the abundance patterns) and
$\alpha$-element enhancements or Mn underabundance (from deviations to the
fit). This way, we can break the degeneracy and characterize these different
aspects. The differences between these methods are further discussed in Sect.
5. Finally, we note that the line of sight towards Sk 191 has a low dust
extinction ($E(B-V)\sim 0.1$ mag), and its environment, significantly
separated from the main SMC body, is far more similar to the Magellanic Bridge
than the dustiest regions of the Milky Way.

Another case of low observed metal abundances is for the SMC line of sight
towards Az V456 (see figure 2 of Jenkins & Wallerstein 2017), although this
system exhibits high molecular content, a relatively large dust extinction,
$E(B-V)\sim 0.33$ mag, and a Milky-Way-type extinction curve with a 2175 Å
bump. In this case, we find marginal indication of low-metallicity (Fig. 7),
consistent with the nominal SMC hot-stars metallicity. If some low metallicity
gas exists along this line of sight, it may be mixed with a higher metallicity
gas, as we discuss in Sect. 4.5. The position of AzV 456 is in the direction
of the Magellanic Bridge, but closer to the main body of the SMC with respect
to Sk 191.

In the LMC the two lines of sight with deviations in neutral ISM metallicity
from the nominal value are Sk-69 279 and Sk-67 105, which are located south of
the Tarantula Nebula and in the outskirts in the north side of the LMC,
respectively, as shown in Fig. 1. In this case, there is no apparent relation
with the Magellanic Bridge. Replenishment of gas from the SMC to the LMC (e.g.
Bekki & Chiba 2007), through the Magellanic Bridge, could be a potential
explanation for the presence of low-metallicity gas that we observe in these
two lines of sight in the LMC.

Overall, previous studies of the abundances in the MCs, such as Tchernyshyov
et al. (2015); Jenkins & Wallerstein (2017); Roman-Duval et al. (2021), do not
find variations of metallicity by construction, because they assume no
metallicity variations and any deviations of the observed abundances from
fixed references are attributed to dust depletion (see Sect. 5 for more
details). Tchernyshyov et al. (2015) do not use a single metallicity as one
fixed reference, but individual abundances of different metals as fixed
references, measured in photospheres of young stars in the MCs, and assume
that these are the total (gas+dust) abundances. They study the dust depletion
from the deviations of the observed gas-phase abundances [$X$/H] from the
reference stellar abundances. Tchernyshyov et al. (2015) observe a broad
distribution of the observed gas-phase abundances of the volatile elements
(see their figure 12), from which they cannot exclude the existence of metal-
poor gas.

Welty et al. (1997) study the line of sight towards AzV 332 (also known as Sk
108), which is included in our sample, but using high-resolution data. The
total column densities along the line of sight within the SMC are quite
similar to those we adopt here, with the exception of $N$(Ni), which is 0.4
dex lower in Welty et al. (1997). Regardless of Ni, our analysis of the
abundance patterns (Fig. 5) from the two datasets are equivalent, leading to
very similar results for the total metallicity, dust depletion, and
$\alpha$-element enhancement.

As an important warning, the total metallicities that we measure along the
whole line of sight towards each star (Fig. 6, 7, and 8) are integrated
measurements and may in fact be a combination of higher and lower
metallicities, if the ISM is not chemically homogeneous along the line of
sight. This is discussed further in Sect. 4.5. Component-by-component analysis
of metal absorption lines from high-resolution spectroscopy are rare towards
the MCs, but unveil some of the ISM complexity (e.g. Welty et al. 1997, 1999).

De Cia et al. (2021) discover large variations in the metallicity of the
neutral ISM in the Milky Way, which was generally assumed to be chemically
homogeneous and have solar metallicity. They observe regions of low
metallicities, down to 17% solar and possibly lower, and attribute these to
the infall of low-metallicity gas on the Galactic disk. The low-metallicity
gas may be distributed in pockets along the line of sight and their mass may
be small (De Cia et al. 2022). On the other hand, Ritchey et al. (2023) find
no evidence for low metallicity gas in the Milky Way. This discrepancy arises
from the different strategy in the analysis of the abundance patterns. The
results of De Cia et al. (2021) are based mostly on the study of refractory
and mildly refractory elements, which are more sensitive to less dusty and
metal-poor gas. The results of Ritchey et al. (2023) are based mostly on the
study of volatile and mildly volatile elements. The inclusion of the volatile
elements in the analysis of the abundance patterns makes it very hard to
detect the signatures of any low metallicity gas, if present along the line of
sight. This is because the determination of the volatile element abundances is
dominated by the gas of higher metallicity, hiding the possible presence of
low-metallicity gas. The methodology of Ritchey et al. (2023) is not sensitive
to the presence of low-metallicity gas because it always includes the volatile
elements in the analysis of the abundance patterns and assumes that all the
gas along the line of sight has the same metallicity (i.e. performs a linear
fit to the abundance patterns of either both volatiles and refractory
elements, or excluding the refractory ones). Overall, both De Cia et al.
(2021) and Ritchey et al. (2023) observe deviations from a linear behaviour of
the abundance patterns that are due to the complexity of the ISM medium, i.e.
differences in depletion and/or metallicity. We discuss this further in Sect.
4.5.

A general physical reasons for the presence of gas with lower metallicities in
galaxies could be the infall of low-metallicity, possibly near-pristine gas
(Fox & Davé 2017). While gas outflows due to galactic winds are observed in
the LMC (Lehner & Howk 2007; Lehner et al. 2009; Barger et al. 2016), it is
not clear whether infall of gas is substantial. Howk et al. (2002) and Lehner
et al. (2009) report that infall is rarely observed toward the LMC. In
general, gas infall is necessary to explain the chemical evolution of the
Milky Way (e.g. Tinsley 1980). The time scale of ISM mixing depends on the
Milky Way rotation (Edmunds 1975), and the survival of pockets of low-
metallicity gas depends on the gas masses involved (White & Audouze 1983), and
thus the gas accretion rate. De Cia et al. (2021) suggest that the observed
rate of gas accretion on the Milky Way is largely sufficient for the survival
of chemical inhomogeneities in the gas. Galactic fountains can also play an
important role for the recycling and mixing of gas and metals, so that
potentially some of the inflowing gas could be recycled rather than accreted
(e.g. Zech et al. 2008; Lehner et al. 2022; Marasco et al. 2022). It is
possible that the low-metallicity gas that we find towards some lines of sight
in the outskirts of the SMC is somehow related to the Magellanic Bridge or a
low-metallicity gas halo. The characterization of the origin of the low-
metallicity gas in the SMC is beyond the scope of this paper. On the other
hand, metallicity variations can be also due to interaction or star formation.
Variations of about 0.4 dex in metallicities of young stars (younger than 100
Myr) are observed in the Milky Way, where higher metallicities correlate with
the density of the spiral arms, and are likely produced by star formation
(Poggio et al. 2022). A young stellar population with sub-solar metallicities
is observed in the Milky Way and possibly results from a gas infall event
(Spitoni et al. 2022).

The stellar metallicities in the MCs vary, strongly depending on stellar age,
as the metal content of these galaxies build up in time and the galaxies
chemically evolve. The mean metallicities of B-Type stars are
${\rm[Fe/H]}=-0.3$ in the LMC and $-0.7$ in the SMC (Rolleston et al. 2002;
Trundle et al. 2007; Hunter et al. 2007) and they agree well with the
abundances of H ii regions (Toribio San Cipriano et al. 2017). Other studies
found somewhat lower metallicities of B stars ([Si/H] abundances between
$-0.8$ and $-0.4$ for the LMC, Korn et al. 2000). The mean metallicity of hot
late Type-O stars in the Tarantula Nebula (in clusters NGC 2060 and 2070) in
the LMC is ${\rm[Si/H]}=-0.46\pm 0.04$ (Markova et al. 2020). The youngest
(1–3 Gyr old) red giant branch (RGB) stars in the LMC have metallicities
$\mbox{[Fe/H]}\sim-0.48$ with a small dispersion $\sigma_{\rm[Fe/H]}=0.09$
(Grocholski et al. 2006). In the MCs, RGB stars younger than 3–5 Gyr in
stellar clusters have a rather flat metallicity gradient and [Fe/H] abundances
between $-0.6$ and $-0.8$ for the LMC, and between $-1.2$ and $-0.6$ for the
SMC (Parisi et al. 2009; Cioni 2009). Asymptotic giant branch stars, although
with probably older ages, show lower abundances and wider spreads, between
$-1.5<\mbox{[Fe/H]}<-1.0$ for the LMC and $-1.5<\mbox{[Fe/H]}<-0.8$ for the
SMC (Cioni 2009). The metallicities of giant stars in the youngest ($<3$ Gyr)
globular clusters spreads between $-1.2<\mbox{[Fe/H]}<0$ (Hill et al. 2000).
Cepheid stars with an age of 7–8 Gyr have metallicities between
$-0.6<\mbox{[Fe/H]}<-0.2$ in the LMC (Romaniello et al. 2022).

###  4.2 The $\alpha$-element enhancement and Mn under-abundance

Type Ia SNe produce most of the Fe-group elements, and including Mn (e.g.
Nomoto et al. 1997). On the other hand, core-collapse SNe produce many more
$\alpha$ elements with respect to Fe, and much less Mn (Nomoto et al. 2006).
As a result, $\alpha$-element enhancement and Mn under-abundance are expected
in the gas in the early phases following a burst of star formation, before SNe
Ia have the time to explode and contribute with the Fe-group elements and
consequently cancel out the $\alpha$-element enhancement and Mn under-
abundance (e.g. Tinsley 1979; Kobayashi et al. 2020; Matteucci 2021).
Consistently, $\alpha$-element enhancement and Mn under-abundance is observed
in stars in the Milky Way (e.g McWilliam 1997) as well as in nearby dwarf
galaxies (de Boer et al. 2014; Tolstoy et al. 2009; Hill et al. 2019).

We measure $\alpha$-element enhancement in the Magellanic gas that are overall
higher than in stars, compared at similar metallicities. The $\alpha$-element
enhancement in the gas was likely produced by massive stars that have exploded
as core-collapse SNe. In the golden sample we observe deviations from the
linear fits to the abundance patterns for both MCs, in the form of
$\alpha$-element enhancement. In addition, in the SMC we observe Mn under-
abundance, while for the LMC no Mn measurements are available in our dataset.
We determine the overall $\alpha$-element enhancement from the difference in
metallicity derived from the linear fit to the abundance patterns based on the
$\alpha$ elements only and the linear fit (with the same fixed slope) to the
Fe, Ni, and Cr abundances (see Figs. 4 and 5, and top panel of Fig. 16). The
$\alpha$-element enhancements are reported in Tables 1 and 2 for the golden
sample. Their values are up to 0.40 dex (0.49 dex) for the LMC (SMC), and on
average 0.26 dex (0.35), with a standard deviation of $0.08$ dex. In the SMC
golden sample we measure a mean Mn under-abundance of $-0.35$ dex, with a
standard deviation of 0.07 dex.

In Figs. 9 and 10 we present the relative abundances with respect to Fe in the
ISM in the LMC and SMC, respectively, after correcting for dust depletion,
[$X$/Fe]nucl, which are likely due to SN nucleosynthetic effects. These values
are also listed in Tables 3 and 4. These relative abundances are derived from
the residuals of the linear fits to the abundance patterns (Figs. 4 and 5).
While the observed gas-phase relative abundances, [$X$/Fe], are typically
distorted (and often dominated) by dust depletion, the values of [$X$/Fe]nucl
can be directly compared to stellar measurements. Figure 9 shows
$\alpha$-element enhancement and Mn under-abundance in the ISM of the MCs up
to high metallicities, at much higher metallicities than what is observed from
stellar observations of the MCs, and to some extent even at higher
metallicities than in the Milky Way. Figure 9 shows stellar [$X$/Fe]
measurements for the LMC bar and disc from Van der Swaelmen et al. (2013) and
Pompéia et al. (2008), based on high-resolution VLT/FLAMES spectra of field
red giant stars older than 1 Gyr. Stellar measurements from the SDSS-IV Apache
Point Observatory Galactic Evolution Experiment (APOGEE, Majewski et al. 2017)
survey for the LMC and SMC are also shown in Figs. 9 and 10 for comparison.
Nidever et al. (2020) and Hasselquist et al. (2021) measure [$\alpha$/Fe] and
[Fe/H] from high resolution spectra of a few thousands red giant stars in the
LMC and SMC, as part of APOGEE. We adopt the same target selection of
Hasselquist et al. (2021). Measurements for S and Cr from APOGEE are less
reliable.777https://www.sdss.org/dr17/irspec/abundances

The extent and occurrence of the $\alpha$-element enhancements in our samples
can be assessed from Figs. 4, 5, 9 and 10. When observed, Mn appears to be
always underabundant in our SMC sample (Fig. 10). We observe $\alpha$-element
enhancements is in all 14 systems in our SMC golden sample, and in 9 out of 10
systems in our LMC golden sample. Measuring the $\alpha$-element enhancements
outside the golden sample is not as reliable, because the fit to the abundance
pattern is determined from most elements, washing away deviations due to
potential $\alpha$-element enhancements. Overall, all the 18 SMC systems with
measurements of $\alpha$-elements show some evidence for enhancements of these
elements with respect to Fe (see Fig. 5). For the LMC, in two out of 32
systems $\alpha$-element enhancements can convincingly be excluded, namely
Sk-70 79 and Sk-67 101 (see Fig. 4). In the system toward Sk-68 52, which is
the golden sample, the absence of $\alpha$-element enhancement is hard to
establish, because it may arise from a discrepancy between the observed
abundance of Cr, which is significantly higher than the abundances of Fe and
Ni and may cause an underestimation of the $\alpha$-element enhancement. The
low [Zn/H] in this system makes this a viable explanation.

Enhancement of $\alpha$ elements and under-abundance of Mn in the MCs are also
observed by Konstantopoulou et al. (2022) from an overall study of the
depletion sequences (overall relations between the depletions and [Zn/Fe]) in
different environments. These authors consider the properties of their MC
samples as a whole and find some deviations from the general behaviour of the
depletion sequences for $\alpha$ elements and Mn of the MCs, compared to other
environments, which they interpret as evidence for $\alpha$-element
enhancement and Mn under-abundance. They do not analyse the abundance patterns
of individual systems. Here we find that $\alpha$-element enhancement and Mn
under-abundance are evident for the individual systems in the Magellanic
Clouds. Jenkins & Wallerstein (2017) also notice a deviation in depletion on
Mn for the SMC (i.e. a potentially steeper Mn depletion), which they interpret
as due to a potential affinity of Mn with different dust species. Exotic
properties of the dust depletion in the MCs that coincidentally mimic
$\alpha$-element enhancements and Mn under-abundance is an alternative
possibility to explain the deviations from the abundance patterns that we
observe. However, in that scenario the total metallicities in the gas would
have to be highly supersolar and with amount of dust higher than what is
observed even in the dustiest parts of the Milky Way (see Sect. 5). The
possibility that recent star formation (which is observed in the MCs) produces
the systematic $\alpha$-element enhancement and Mn under-abundance that we
observe in the gas is far more likely.

Figure 9: The relative abundances with respect to Fe versus the total
metallicity in the LMC ISM (orange triangles), after correcting for dust
depletion. Larger symbols highlight the golden sample. The blue circles show
the stellar measurements of field red giant stars older than 1 Gyr in the LMC
bar (dark blue) and disc (light blue) from Van der Swaelmen et al. (2013) and
Pompéia et al. (2008). The magenta points are the stellar measurements from
APOGEE in the LMC, with the selection of Hasselquist et al. (2021). The APOGEE
stellar measurements for S and Cr are less reliable. The grey dashed line
shows the average [$\alpha$/Fe] for stars in the Milky Way from McWilliam
(1997). Potential variations of [P/Fe] and [Zn/Fe] due to nucleosynthesis are
observable only in the golden sample. Figure 10: Same as Fig. 9, but for the
SMC (blue diamonds). The light-grey dashed line for [Mn/Fe] shows the average
stellar measurements from Mishenina et al. (2015).

Overall, the stellar [$\alpha$/Fe] in the MCs are lower than what is measured
in Milky Way red giants (Pompéia et al. 2008; Lapenna et al. 2012;
Chekhonadskikh 2012; Van der Swaelmen et al. 2013). The [$\alpha$/Fe] values
decrease slowly with increasing metallicity (Van der Swaelmen et al. 2013;
Hasselquist et al. 2021, see Fig. 9). The [$\alpha$/Fe] values measured in
B-Type stars in the MCs are sub-solar, around $-0.12$ (Korn et al. 2000;
Rolleston et al. 2002). The knee of the $\alpha$-element distribution with
metallicity is at $Z\sim 0.1\,Z_{\odot}$ for the Milky Way, as shown by the
dashed curves in Figs. 9 and 10. For less massive galaxies the stellar
$\alpha$-element knee is expected to be at lower metallicites (e.g. de Boer et
al. 2014). For the MCs the stellar $\alpha$-element knee is at very low
metallicity, consistently from both the APOGEE and the Van der Swaelmen et al.
(2013) data, and not visible in Figs. 9 and 10. (Nidever et al. 2020)
estimated that the $\alpha$-element knee in stars in the LMC is at [Fe/H]
$\sim-2.2$, indicating a low star formation efficiency.

In the LMC, Nidever et al. (2020) and Hasselquist et al. (2021) find a change
of trend and the stellar [$\alpha$/Fe] increases by $\sim 0.1$ dex at the
highest metallicities. These data are displayed in Figs. 9 and 10. Chemical
evolution models suggest that strong bursts of recent star formation in both
the LMC and SMC are needed to explain the observed [$\alpha$/Fe] trends with
[Fe/H] (Nidever et al. 2020; Hasselquist et al. 2021). We discuss the star
formation history of the MCs in Sec. 4.3.

Asa’d et al. (2022) measure $\alpha$-element enhancement and Mn under-
abundance in LMC stellar clusters, which are broadly consistent with the
values of Van der Swaelmen et al. (2013). Enhancement of $\alpha$ elements in
stellar clusters has also been observed in some extragalactic young clusters
(e.g. Larsen et al. 2006, 2008; Hernandez et al. 2017).

In the LMC, stellar [Ti/Fe] and [Si/Fe] are somewhat higher than [Mg/Fe] and
[O/Fe], likely because of a lower contribution of massive core-collapse SNe
(Van der Swaelmen et al. 2013). While O and Mg are produced by quiescent He
burning in very massive core-collapse SNe progenitors (Woosley & Weaver 1995),
Ti and Si are largely produced in the core-collapse SNe explosion of
intermediate-mass progenitors (e.g. Nomoto et al. 2006). Eventually, most of
the [Ti/Fe]nucl values that we measure in the ISM are similar to the values of
stellar [Ti/Fe] measured by Van der Swaelmen et al. (2013), as showed in Fig.
9. However, in the gas we observe a flat [Ti/Fe]nucl distribution with $[{\rm
M/H}]_{\rm tot}$, with enhanced [Ti/Fe]nucl at the highest metallicities as
well. Finally, the enhancements in [Ti/Fe] and [Si/Fe] that we observe exclude
the possibility that the $\alpha$-element enhancements in the ISM could be
produced by winds of massive stars before their core-collapse explosions.

If there would be any intrinsic variations of Zn or P due to nucleosynthesis,
these can be observed in our golden sample, when Zn and P are excluded from
the fit to the abundance patterns. In the golden sample, we do not observe any
enhancement in [P/Fe] in the LMC ISM (Fig. 9), unlike in the stellar
measurements of Caffau et al. (2011). Enhancement of P was also observed by
Masseron et al. (2020) for stars with peculiarly high enhancement of $\alpha$
elements. We do not confirm the relation of P nucleosynthesis with massive
stars (Cescutti et al. 2012) based on the ISM abundances measured in the MC.
We discuss the case of P and Zn further in Sect. 5.

Strong deviations in [Zn/Fe]nucl are not observed in the golden sample, as
shown in Figs. 9 and 10. We observe a potential trend of a deviation of Zn of
up to 0.2 dex at lower metallicities, and down to $-0.2$ dex at higher
metallicities. This could be consistent with the finding on stellar
measurements of Sitnova et al. (2022), but needs to be investigated further
with more data. We discuss this possibility further in Sect. 5.

Our results suggest that a burst of recent star formation may have increased
the $\alpha$ elements in the ISM. We discuss the recent bursts of star
formation observed in the MCs in Sec. 4.3. Following the most recent burst of
star formation, it is possible that the ISM could show more $\alpha$-element
enhancement than the stars produced in the same burst of star formation, while
the next generation of stars should reflect the present-day ISM (relative)
abundances. The lines of sight in our sample are selected towards hot stars,
and thus preferentially cross star-forming regions. Whether and on which time
scales the $\alpha$ elements can mix throughout the ISM, and what is the
expected chemical composition of the next generation of stars forming from
this gas depends, among other things, on the gas and metals masses involved.
This needs further investigations, which are beyond the scope of this paper.

###  4.3 Recent star formation in the Magellanic Clouds

Gas-rich dwarf irregular galaxies tend to have bursty star formation (Weisz et
al. 2014; Atek et al. 2022). Both the LMC and SMC experienced recent bursts of
star formation. Stars in the Tarantula Nebula in the LMC have ages up to $\sim
30$ Myr (De Marchi et al. 2011), with the youngest being 1 to 2 Myr old, in
the R136 group (Massey & Hunter 1998; Crowther et al. 2016; Bestenlehner et
al. 2020). The progenitor of the core-collapse SN 1987A in the LMC is likely
$\sim 12$ Myr old (Panagia et al. 2000). In both LMC and SMC there is an
increased and common population of Cepheid with an age of $\sim 200$ Myr
(Joshi & Panchal 2019). The LMC likely experienced a most intense burst of
star formation in the last 2 Gyr (Harris & Zaritsky 2009; Nidever et al. 2021;
Hasselquist et al. 2021), and possibly more recently $\sim 10$ Myr and $\sim
100$ Myr ago (Indu & Subramaniam 2011). The SMC had an increase in star-
formation rate in the last 3–5 Gyr (Harris & Zaritsky 2004; Cignoni et al.
2013; Rubele et al. 2018; Hasselquist et al. 2021), with bursts $\sim 2.5$,
$\sim 0.4$ Gyr, $\sim 60$ Myr and $\sim 10$ Myr ago (Harris & Zaritsky 2004;
Indu & Subramaniam 2011). Some of this star-formation activity is probably
related to the interaction between the LMC, SMC, and the Milky Way, which
played a role in the creation of the Magellanic Stream $\sim 1.7$ Gyr ago
(Nidever et al. 2008). A close encounter or interaction between the MCs could
have happened over the past 1-2 Gyr (Besla et al. 2012; Pardy et al. 2018;
Lucchini et al. 2021). Gas outflows are observed around the LMC (Barger et al.
2016), also suggesting a recent burst of star formation.

While there is evidence for very recent star formation in the MCs, it is not
straightforward to estimate which stellar population could be responsible for
the $\alpha$-element enhancement in the ISM that we observe, including the
timescale for the diffusion of the $\alpha$ elements in the ISM. The bursts of
star formation that produced $\alpha$-element enhancements in the Magellanic
ISM are likely more recent than $\sim 1$ Gyr, before SNe Type Ia could
contribute in rising the Fe-group elements. Further modelling is required to
assess which stellar population and masses could reproduce the current
observations of the ISM.

###  4.4 Dust, metals, and H2 molecules.

Dust is made of metals and the surface of dust grains facilitates the
formation of molecules. Here we compare the metallicity, dust depletion, and
molecular components of the ISM in local galaxies. Figure 11 shows that the
total metallicity broadly correlates with the strength of dust depletion,
albeit with a large scatter. Thus, the amount of dust in the ISM overall
depends on the metallicity of the gas. This is in consistent with a
significant amount of dust being built through grain-growth in the ISM, as
suggested for example by (De Cia et al. 2013; Dwek 2016; Mattsson et al.
2014), depending on the gas metallicity, density, and temperature. A similar
relation between [Zn/Fe] and metallicity has previously been observed in DLAs
(e.g. Ledoux et al. 2002; Noterdaeme et al. 2008; De Cia et al. 2016).888The
correlation observed in Fig. 11 cannot be produced by covariance between the
metallicity and the dust depletion, which are the resulting intercept and
slope of the linear fit to the abundance pattern. Indeed, there is a similar
correlation (with a different slope) between the observed [Zn/Fe] and [Zn/H]
in the ISM in the MCs, with a similar internal scatter. The data for the Milky
Way do not strongly follow the dust-metallicity relation, and show higher
levels of depletion than DLAs, even at comparable metallicities (including at
a fixed solar metallicity). This is possibly the result of the fact that not
only metallicity, but also density, temperature, and pressure, have an
important role in the growth of dust grains in the ISM. Dust is expected to
grow more easily in the Milky Way disk, thanks to the higher pressure and
higher density of colder gas (as also observed for molecules, e.g. Blitz &
Rosolowsky 2006), than in the more diffuse warm neutral medium probed by DLAs.

The properties of dust depletion that we find in the neutral ISM of the MCs do
not appear to be strongly correlated with the dust extinction curves. For
example, the line of sight towards AzV 456 has a Milky-Way dust extinction
curve with a 2015 Å bump, but we find no special properties of the abundance
patterns in this system, as already remarked by Sofia et al. (2006), with the
exception of a potential presence of chemically inhomogeneous gas (possibly
including a metal- and dust-rich component) along this line of sight (see
Sect. 4.5).

Figure 11: Relation between the metallicity, [M/H]tot, and the strength of
dust depletion, [Zn/Fe]fit, in the neutral ISM in the Milky Way, LMC, SMC, and
DLAs. The solid line shows a linear fit to the data, including uncertainties
on both axis, $[{\rm Zn/Fe}]_{\rm fit}=1.08+0.57\times[{\rm M/H}]_{\rm tot}$,
with uncertainties of 0.03 and 0.04 for the intercept and slope, respectively.
The dotted lines mark the region within the resulting 0.26 internal scatter of
the relation. The Milky Way data are from De Cia et al. (2021). The DLA data
are from (De Cia et al. 2018) and they show the observed [Zn/Fe].

The amount of molecules could in principle be related to the metallicity of
the ISM, or its dust content. The rate of H2 formation is thought to be
proportional to the metallicity and the square of the density of the gas
(Glover & Mac Low 2011). Among DLAs, higher levels of dust depletion are
observed in systems bearing H2 (Noterdaeme et al. 2008; Balashev et al. 2019;
Bolmer et al. 2019). Figures 12 and 13 show that the Milky Way harbours
overall higher metallicities, dust depletion, and molecular fractions,
followed by the LMC, and then the SMC. At the same level of metallicity, the
Milky Way shows a higher molecular fraction (Fig. 13) and a higher level of
dust depletion (Fig. 11) with respect to the MCs and DLAs. This is likely
because not only metallicity plays an important role for the production of
dust and molecules, but also because of the presence of cold dense gas. In
turn, the presence of cold dense gas and the molecular fraction strongly
depends on pressure more than metallicity (Blitz & Rosolowsky 2006; Balashev
et al. 2017), making the formation of H2 more favourable in the Milky Way disk
than in DLAs (Noterdaeme et al. 2015).

In our observations, the H2 molecular fraction $f_{\mbox{\mbox{H}${}_{2}${}}}$
is not clearly correlated with the metallicity (Fig. 13) nor the amount of
dust depletion (Fig. 12). Interestingly, there are systems in the SMC that
show a high molecular fraction, but low metallicity and mild levels of dust
depletion, for example Sk 143 (in the SMC) and Sk-67 105 (in the LMC). In the
case of Sk 143, both [Zn/Fe] and [Si/Ti] give strong indication that there is
only mild dust depletion in the system, despite the high fraction of H2. In
the case of Sk-67 105, the oxygen abundance strongly deviates from the
otherwise linear abundance pattern shown by Ni, Cr, Fe, Si, Mg, S, and Zn.
Both the high molecular content and the deviation to high abundances of the
most volatile elements suggest that there is actually a mix of ISM gases along
this line of sight, with potentially different metallicities and levels of
dust depletion. We discuss this possibility in more details in Sec. 4.5.
Overall, while singly ionized species such as Zn ii and Fe ii trace the warm
neutral medium, it is very likely that H2 does not form or survive in this
medium, but rather in a colder and denser phase. This would naturally explain
the lack of clear correlations in Figs. 12 and 13.

Figure 12: The relation between the strength of dust depletion in the neutral
ISM and the fraction of molecular H2. The Milky Way data are from De Cia et
al. (2021). The DLA data are from Noterdaeme et al. (2008) and (De Cia et al.
2018) and they show the observed [Zn/Fe].  Figure 13: The relation between the
total metallicity of the neutral ISM and the fraction of molecular H2. Symbols
are like in Fig. 11. The Milky Way data are from De Cia et al. (2021). The DLA
data are from Noterdaeme et al. (2008) and (De Cia et al. 2018).

###  4.5 A mixture of different ISM gas types

The ISM is a complex medium, and likely chemically inhomogeneous in its metal
and dust content. The ISM in the Milky Way has regions with different
metallicities (De Cia et al. 2021) and strengths of dust depletion (Jenkins
2009; Welty et al. 2020). Variations of metallicities (Sánchez Almeida et al.
2015; Kreckel et al. 2019; Wang et al. 2022; Chartab et al. 2022) and dust
depletion (Prochaska 2003; Dessauges-Zavadsky et al. 2006; Rodríguez et al.
2006; Wiseman et al. 2017; de Ugarte Postigo et al. 2018; Noterdaeme et al.
2017; Guber et al. 2018; Ramburuth-Hurt et al. 2023) have been observed within
external galaxies as well. It is well possible that the total line of sight
towards a star intercepts gases with different chemical properties. Indeed, De
Cia et al. (2021) suggest that this is often the case in the Milky Way, and
that the ISM may be a mix of gases with different metallicities and depletion
properties, which are averaged out when studying the overall metal absorption-
line profiles. The actual mass of the different gas components is not
straightforward to estimate (De Cia et al. 2022).

Differences in the amount of depletion and type of depletion patterns have
been observed in different groups of components in the line profiles observed
at high spectral resolution towards AzV 332 (i.e. Sk 108) within the SMC
(Welty et al. 1997), a target which is also in our sample, and SN 1987A within
the LMC (Welty et al. 1999). Variations of depletion within absorbing systems
have been observed for distant galaxies by Ramburuth-Hurt et al. (2023).
Figure 14 shows our analysis of the metal patterns of the groups of individual
component using the measurements of Welty et al. (1997), and with the same
technique of Ramburuth-Hurt et al. (2023). This technique analyses the metal
patterns in a very similar way we analyse the abundance patterns, but without
including H, so that it cannot give information on metallicities, but it
characterises the dust depletion and any deviations due to nucleosynthesis, in
particular for individual components. Component S1 carries about 90% of the
metals (as shown from the normalization of the metal patterns in Fig. 14, and
as remarked by Welty et al. 1997) and shows the strongest strength of
depletion ([Zn/Fe]fit, i.e. the slope of the metal patterns), as well as the
stronger $\alpha$-element enhancement and Mn underabundance than the other
components.

Figure 14: The metal pattern of the three main individual components observed
towards AzV 332, based on the technique of Ramburuth-Hurt et al. (2023) and
using the metal column densities measured by Welty et al. (1997). The $y$-axis
represents the equivalent metal column densities.

The presence of multiple ISM components adds one more level of complexity to
the abundance patterns that we observe. For example, there may be the
contribution of high-metallicity and highly-depleted gas superimposed to the
contribution of metal-poor, dust-free gas. This is illustrated in Fig. 3,
panel d). In this example the metal-rich gas dominates the abundances of the
volatile elements, while the metal- and dust-poor gas dominates the refractory
ones. This effect can cause deviations of the most volatile elements from the
overall linear abundance patterns in the Milky Way ISM (De Cia et al. 2021,
2022), although this is not a unique explanation. Different mixture of ISM gas
types with different properties are possible, including gas with low dust
depletion but high metallicity, as possibly the result of dust destruction.

The observations of elements more volatile than Zn is limited in our sample. A
strong deviation of the observed oxygen abundance from the abundance patterns
is observed towards Sk-67 105 in the LMC (Fig. 4), which may be a sign of a
chemically inhomogeneous ISM mix along this line of sight. However, this O i
measurement is based on the weak 1355 Å line and it is uncertain. Oxygen is
constrained also for Sk-70 79 and Sk-68 73 and in both cases is consistent
with [$M$/H]tot within the uncertainties.

For AzV 456 in the SMC, an alternative interpretation of the Ti over-abundance
could be a potential bend of the abundance pattern due to ISM mixes. While the
presence of ISM mixes might be the case also for other lines of sight, it is
not clear from the available data.

In this work, by analysing the column densities of the whole line profiles, we
have assumed that the ISM along the line of sight is chemically homogeneous.
Nevertheless, the $\alpha$-element enhancement and Mn under-abundance that we
measure often towards both the LMC and SMC cannot be possibly explained with
different ISM components, so these results hold even if the ISM turns out to
be chemically inhomogeneous.

##  5 Caveats

It is challenging to understand the observed ISM abundance patterns,
especially when fewer metal species are observed, and measure reliable slopes
to the linear fits to the data. For the golden sample it is possible to
establish the slope purely based on the $\alpha$ elements (Ti and at least
another more volatile $\alpha$ element, either Mg, Si, or S), thereby removing
the uncertainties on the determination of the dust depletion due to different
nucleosynthesis. Moreover, for these systems, the determination of the
metallicity is based on the Fe-group elements only, and independently from P
and Zn, elements with a potentially more uncertain nucleosynthetic origin. We
discuss the main uncertainties and caveats below.

###  5.1 On the relative and $F*$ methods

Figure 2 of Jenkins & Wallerstein (2017) shows the quantity $D(X)$, which is
used by the $F*$ method to measure dust depletion. The quantity $D(X)$ is
determined from the fixed metallicity assumed for the gas and the observed
[$X$/H], which traces not only dust depletion, but potentially also
metallicity variations and alpha-element enhancements. Variations in $D(X)$
may be caused also by variations in metallicity and $\alpha$-element
enhancement. We find that $\alpha$-element enhancements, variations in ISM
metallicity, and a mild dependence of depletion on metallicity can produce a
change of slope with respect to the Milky Way of the trend of $D({\rm Ti})$
with $D({\rm Fe})$, and not for $D({\rm Si})$, an overall effect which is
mildly observed also in Fig. 2 of Jenkins & Wallerstein (2017).

The relative method (De Cia et al. 2021) determines the neutral ISM
metallicity and dust depletion as separate parameters, i.e. the normalization
and slope, where the dust depletion (slope) is purely determined from the
relative abundances. The deviations of specific elements from the linear fit
to the abundance patterns, for example $\alpha$-element overabundances and Mn
underabundance, can reveal additional nucleosynthesis effects. This is
illustrated in Fig. 3.

The difference in assumptions of the relative and $F*$ methods may in
principle lead to different interpretations. The two methods agree fairly well
in their estimations of the metallicities in the neutral ISM of the Milky Way
De Cia et al. (2021). There is an overall correlation between the refractory
indexes of the two methods, $B2_{X}$ for the relative method and $A_{X}$ for
the $F*$ method. In particular, in the formalism of the relative method Si and
Mg are found to be more volatile, and Mn more refractory than what is
estimated in the $F*$ formalism for the Milky Way. In this work we measure
with the relative method an over-abundance of Si and Mg by up to 0.4 dex, and
an under-abundance of Mn in the neutral ISM towards the MCs. If we would
assume that Si and Mg would be more refractory (more negative $B2_{X}$) and
that Mn would be more volatile (less negative $B2_{X}$) like in the $F*$
formalism for the Milky Way, than we would observe a larger enhancement of Si
and Mn, and a larger under-abundance of Mn. The values of the $F*$-method
refractory indexes $A_{\rm Mg}$ and $A_{\rm Si}$ for the SMC are higher (and
lower for $A_{\rm Mn}$) than in the Milky Way, however (Jenkins & Wallerstein
2017). Because the $F*$ method measures the depletion of metals from the
observed [$X$/H], any variation in abundances of Mg, Si, Mn, etc. are by
construction interpreted as an effect of dust depletion in the $F*$ formalism
and affect the values of $A_{X}$. Thus, it is not possible to estimate
potential $\alpha$-element enhancement in the MCs with the $F*$ method itself
and compare it with our results.

The determination of the $B2_{X}$ values in De Cia et al. (2016) and
Konstantopoulou et al. (2022) uses data from different environments, including
DLAs and the Milky Way. In DLAs $\alpha$-element enhancements (and Mn under-
abundance) are observed for systems with no dust depletion ([Zn/Fe] $\sim 0$),
and these are corrected for by assuming an $\alpha$-element distribution,
using the observed $\alpha$-element enhancements and assuming that the
position of the so-called $\alpha$-element knee is at the same metallicity as
in the Milky Way, around [M/H] $\sim-1$. The determination of the $B2_{X}$
values are little sensitive to this assumption, and instead are dominated from
the observations of dust-free DLAs and the Milky Way. Overall, the correction
for $\alpha$-element enhancements is relevant for systems with [M/H] $<-1$ (De
Cia et al. 2016; Konstantopoulou et al. 2022). In the MCs, the gas
metallicities are well above this value, and the determination of total
metallicity and $\alpha$-element enhancements is independent from the
assumptions on nucleosynthesis of De Cia et al. (2016) and Konstantopoulou et
al. (2022).

###  5.2 Zinc

Our work uses the refractory index $B2_{X}$, which relies on the observation
of [Zn/Fe] as a tracer of dust. The main issue with this is whether Zn and Fe
follow each other nucleosynthetically. To some extent, Zn could be considered
as behaving somewhat similarly to $\alpha$ elements, albeit with a small
amplitude (e.g. Duffau et al. 2017; Sitnova et al. 2022). The DLA systems are
observed down to [Zn/Fe] $\sim 0$, i.e. with no dust depletion, and these show
$\alpha$-element enhancement and Mn under-abundance of about 0.3 dex. Similar
enhancements of Zn can be excluded, but smaller effects ($<0.2$ dex) could be
at play and we discuss it further below. We further discuss the reliability of
[Zn/Fe] as a dust tracer in in more details the Appendix.

In Sect. 4.2 we mentioned a potential trend in the deviation of Zn of up to
0.2 dex at lower metallicities, and down to $-0.2$ dex at higher
metallicities, potentially due to nucleosynthesis, which is tentatively
observed in Fig. 9 for the golden sample. For the non-golden sample, the fit
to the abundance patterns and the determination of the total metallicities
relies on Zn. In case such deviations of Zn would be present in the non-golden
sample, the estimates of the total metallicities could be about 0.2 dex higher
at the high-metallicities end, and about 0.2 dex lower at the low-
metallicities end, thereby increasing the variations of total metallicities in
the neutral ISM. The total metallicities for the non-golden sample are shown
in Fig. 6 and 7.

In the case that [Zn/Fe] would have an intrinsic trend varying up to $+0.2$
dex in low-metallicity systems and down to $-0.2$ dex for high metallicity
systems, the initial determination of $B2_{X}$ (De Cia et al. 2016;
Konstantopoulou et al. 2022) could also be affected, so that all depletions
could be slightly underestimated, i.e. all $B2_{X}$ could be somewhat lower
(steeper depletion sequences). This could lead to somewhat higher total
metallicities in the analysis of the abundance patterns. On the other hand,
the estimates of depletion of the most refractory elements (e.g. Ti) towards
the most dusty lines of sight in the MW are similar between the determinations
based on [Zn/Fe] (De Cia et al. 2016; Konstantopoulou et al. 2022) and the
determinations based on the $F*$ factor (Jenkins 2009). This ensures that if
any intrinsic [Zn/Fe] trend with metallicity is present, it does not heavily
affect the absolute values of the depletions. Moreover, a global shift of all
the $B2_{X}$ values would not affect the relative abundances of the metals in
the analysis of the abundance pattern, and thus our results on the $\alpha$
element enhancements are robust.

The determination of $B2_{X}$ is based on the assumption that the depletion of
Zn, $\delta_{\rm Zn}$, is a linear function of [Zn/Fe] (De Cia et al. 2016).
The effects of varying the slope of $\delta_{\rm Zn}$ with [Zn/Fe], $B2_{\rm
Zn}$, are investigated in De Cia et al. (2021). A $B2_{\rm Zn}$ twice as steep
than the optimal value is highly unlikely, and it would produce metallicities
that are 0.3–0.4 dex higher. A slope $B2_{\rm Zn}$ that is twice as shallow
would produce metallicities 0.15–0.20 dex lower. A relation of $\delta_{\rm
Zn}$ with [Zn/Fe] that is not linear, but keeps at zero for higher values of
[Zn/Fe] and then turns steeper, like in Figure 5 of De Cia et al. (2016) would
be similar to the latter scenario, so possibly produce slightly lower dust-
corrected metallicities. Roman-Duval et al. (2022) explored this non-linear
possibility, using a different methodology.

Zinc is not considered when calculating dust depletion, metallicity, and
$\alpha$-element enhancements in the golden sample. Thus, our results do not
depend on Zn measurements and their uncertainties. For the non-golden sample,
in case of measurements based on data at lower spectral resolution, for
example for the four SMC systems from Tchernyshyov et al. (2015), we cannot
exclude hidden saturation of Zn ii lines. The abundances of Zn in these
systems are similar to the abundances of P, which is as volatile as Zn. This
possibly hints at no strong saturation effects of Zn ii, but may be a
coincidence.

###  5.3 Phosphorus

Konstantopoulou et al. (2022) find that the depletion of P is significantly
shallower than what estimated by Jenkins (2009), who find that P has a higher
tendency of depleting than Zn.

The ISM abundances that we observe in the LMC do not show any enhancement of
P. Caffau et al. (2011) observe high values (up to $\sim 0.4$ dex) of [P/Fe]
in a dozen of Galactic stars, and interpret them as P being potentially
produced through $\alpha$ capture. To reproduce these observations, Cescutti
et al. (2012) suggest that P is formed mainly in massive stars. Phosphorus is
likely not produced in core-collapse SNe (Woosley & Weaver 1995), but rather
in the late evolutionary stages of massive stars (Arnett 1996). For DLAs with
[Zn/Fe] ¡ 0.4, for which the effects of dust depletion are minimal and the
$\alpha$-element enhancements are most noticeable, Konstantopoulou et al.
(2022) observe a branch of DLAs (not all) with increased P(see their Figure
1). However, these measurements are mostly based on only one P ii absorption
line in the Ly-$\alpha$ forest, and thus potentially contaminated De Cia et
al. (2016).

###  5.4 Sulphur

Sofia et al. (2006) suggested that sulphur is a better reference than zinc for
the estimate of the depletion of silicon. Indeed [S/Si] mildly traces dust
depletion, because S and Si are both $\alpha$ elements produced by oxygen
burning in core-collapse SNe, and their depletion properties are mildly
different. We raise nevertheless a first caveat, that S has a non-negligible
depletion (e.g. Jenkins 2009; De Cia et al. 2016). Furthermore, S has been
considered a troublesome element (Jenkins 2009; Jenkins & Wallerstein 2017)
because measurements of S ii in the local group may be affected by ionization,
i.e. the contribution to the line-of-sight N(S ii) from H ii regions. While
this effect is to some extent also observed in Konstantopoulou et al. (2022),
the determination of $B2_{S}$ is determined largely by QSO DLAs, for which
such troublesome ionization effects are not at play, because the lines of
sight are not preferentially crossing through H ii regions. While we still
include S in our analysis, any strong variations due to ionization would be
observable. Jenkins & Wallerstein (2017) found that three SMC systems showed S
over-abundance, namely AzV 321, AzV 332, and Sk 190. We interpret these as a
combination of $\alpha$-element enhancement and a relatively high total
metallicity (see Fig. 5 and Table 2), while the likely ionization effects do
not seem to cause strong deviations.

###  5.5 Manganese, titanium, and peculiar depletion

Jenkins & Wallerstein (2017) find steeper depletion sequences of Mn in the SMC
than in the Milky Way. Konstantopoulou et al. (2022) find that the apparently
steeper Mn depletion sequence for the SMC may be instead the effect of a Mn
under-abundance. They also find the opposite trend for Ti (and possibly Si).
Overall, they interpret these deviations as $\alpha$-element enhancement and
Mn under-abundance, possibly due to recent core-collapse SN nucleosynthesis.
The coincidence of the Mn under-abundance and the enhancement of Ti, Si, Mg,
and S that we observe in the ISM of the MCs make the hypothesis of recent
core-collapse SNe very appealing (e.g. Kobayashi et al. 2020).

Jenkins & Wallerstein (2017) also find that the depletion of Ti in the SMC is
steeper than in the Milky Way, while the depletion of Si is rather similar in
the two environments, which is shown in their Figure 2. In that work, the
measurements of depletions are in fact the difference between the observed
abundances and the fixed reference metallicity (assumed from the metallicity
of hot stars), and these values depends as well on potential variations in
intrinsic metallicity and other effects such as $\alpha$-element enhancements.
The different behaviours of the depletion of Ti and Si observed in the SMC by
Jenkins & Wallerstein (2017) casts some doubts on whether the variations that
we observe in the abundance patterns in the MCs are actually due to
nucleosynthesis of core-collapse SNe, or whether they are due to different
dust-depletion properties in the MCs. Konstantopoulou et al. (2022) finds that
the depletion of Ti in the MCs is significantly shallower than for the Milky
Way and distant galaxies, an effect which is removed if one assumes that there
are $\alpha$-element enhancements in the gas in the MCs. We test the effects
of a different Ti depletion in the MCs on our results by assuming a shallower
depletion of Ti ($B2_{Ti}=-1.01\pm 0.13$ and $-1.11\pm 0.06$ for LMC and SMC,
respectively, Konstantopoulou et al. 2022). In this case, for our golden
sample we would estimate total metallicities in the gas that are super-solar
for most systems (between 0.3 and 3 dex for the LMC and between $-0.26$ and
1.4 dex for the SMC) as well as extremely high values of the overall strength
of dust depletion (with $1.3<{\rm[Zn/Fe]}_{\rm fit}<3.7$ for the LMC and
$1.1<{\rm[Zn/Fe]}_{\rm fit}<2.4$), much higher than what is observed in the
dustiest lines of sight in the Milky Way. In addition, this alternative
solution would imply also strong deficiencies (by more than 1 dex), of Zn and
O. The simpler solution, where the deviations from the abundance patterns are
regular $\alpha$-element enhancements and Mn under-abundance caused by recent
star formation, is far more likely.

There is a non-negligible possibility that the [$X$/Fe]nucl variations that we
observe could not be due to recent core-collapse SNe, but to a different make-
up of dust. Our targets are all hot stars, so they preferentially select star-
forming regions and molecular clouds, and almost all of them show
$\alpha$-element enhancements. The fraction of polycyclic aromatic
hydrocarbons (PAHs, composed of C and H atoms) is lower in the SMC than in the
Milky Way, and it is not uniformly distributed, being higher in molecular
clouds (Sandstrom et al. 2010). To explain this, the PAHs could be formed in
molecular clouds, or alternatively recent star formation (younger than $\sim
25$ Myr) may have destroyed the PAH in the diffuse ISM. Overall, we observe
coherent enhancement of [Si/Fe]nucl, [Ti/Fe]nucl, [S/Fe]nucl, [Mg/Fe]nucl, and
under-abundance of [Mn/Fe]nucl in the neutral ISM towards star-forming regions
the MCs, which can be all explained by the contribution from recent core-
collapse SNe. The alternative explanation of a different dust grain
composition in molecular clouds being the cause of the [$X$/Fe]nucl variations
cannot be completely excluded but is unlikely, given the consistency in these
variations. Whether not only the physical conditions, but also
$\alpha$-element enhancements or in general the ISM composition in molecular
clouds have an influence on the PAH fraction will need to be further
investigated.

###  5.6 Caveats due to possible ISM heterogeneity

Several processes shape the observed abundance patterns, as illustrated in
Fig. 3. It is necessary to observe several metals and with different
nucleosynthetic and refractory properties to be able to properly disentangle
these. The level of uncertainty is higher whenever only a few metals are
observed. It is possible to discriminate $\alpha$-element enhancement and Mn
under-abundance from the effects of ISM mixing. This is because ISM mixing can
mimic abundance deviations of the most refractory (e.g. Ti) or the most
volatile elements (e.g. O). But ISM mixing cannot selectively reproduce
deviations of specific elements in the middle range of the refractory index,
such as Si, Mg, and Mn, like $\alpha$-element enhancements instead do.

##  6 Conclusions

In this paper we study the abundance patterns in the neutral ISM towards 32
and $22$ hot stars in the LMC and SMC, respectively, and characterise (and
correct for) the depletion of metals into dust grains in these systems. For
the first time, we measure the total (gas + metals) metallicities of the
neutral ISM, as well as dust-corrected [$X$/Fe]nucl in the gas that can be
compared with stellar values, in particular $\alpha$-element enhancements.

We find enhancement of $\alpha$ elements (Ti, Si, Mg, and S) in the systems of
our golden sample in both MCs and Mn under-abundance in the golden sample for
the SMC (where Mn measurements are available), based on the deviations from
the linear fits to their abundance patterns, i.e. after correcting for dust
depletion. We observe these $\alpha$-element enhancements and Mn under-
abundance at all metallicities, including at the high-metallicity end. The
average $\alpha$-element enhancements in the ISM are of 0.26 dex (0.35 dex)
for the LMC (SMC), with a standard deviation of 0.08 for both MCs. The average
Mn under-abundance for the SMC is $-0.35$ dex, with a standard deviation of
0.07. This suggests that a recent burst of star formation has enriched in
$\alpha$ elements (and impoverished in Mn relatively to Fe) the neutral ISM of
these elements, i.e. from the nucleosynthesis contribution of core-collapse
SNe, before the onset of Type Ia SNe ($\sim 1$ Gyr). This effect is partly
observed in the stars in the MCs as well, although to a lesser extent, hinting
to a delay in chemical enrichment between the gas and the stars. Evidence for
recent star formation is also found from independent studies on gas outflows,
stellar ages, and stellar evolution observations and models, and possibly
triggered by the interaction between the SMC, LMC, and the Milky Way.

We measure the total metallicities in the neutral ISM in the LMC and SMC, and
find that most values are consistent, within the uncertainties, with the
nominal reference metallicities from OB stars and H ii regions ($\log
Z/Z_{\odot}=-0.3$ and $-0.7$ for the LMC and SMC, respectively). The average
dust-corrected metallicity in the neutral ISM is $[M/\mbox{H}]_{\rm
tot}=-0.33$ ($-0.83$) with standard deviation 0.30 (0.30) for the LMC (SMC).

In six systems we measure a significantly lower metallicity than nominal, two
in the LMC (Sk-67 105 and Sk-69 279) with $\sim 16$% solar and four in the SMC
(AzV 327, Sk 191, AzV 476, and AzV 26) with metallicities spanning between $3$
and $10$% solar. Three of the SMC lines of sight with low-metallicity gas are
located in the SMC outskirts, two of which in the direction of the Magellanic
Bridge, a region previously known to have low-metallicity gas and stars (e.g.
Lehner et al. 2008; Ramachandran et al. 2021). Thus, with the exception of
lines of sight towards the Magellanic Bridge, the neutral gas in the LMC and
SMC appears fairly well mixed in terms of metallicity. The neutral ISM
metallicity distribution in the LMC is similar to the Milky Way, while the SMC
lines of sight have overall lower metallicities.

To probe the existence of low-metallicity gas in the ISM it is necessary to
either exclude the volatile metals from the analysis of the abundance patterns
(e.g. De Cia et al. 2021) or model the abundance patterns with at least two
components, one driven by the refractory metals that can be sensitive to the
metal-poor gas, and one driven by the volatile metals that are mostly
sensitive to the metal-rich gas. Indeed, the abundances of refractory elements
are very low in dusty and metal-rich gas, but are higher dust-poor and/or
metal-poor gas. On the other hand, the abundances of volatile metals are
always higher for gas that is more-metal-rich. Studies of abundance patterns
that systematically include the volatile metals in a single fit to the
abundance patterns, even when non-linear deviations are evident (e.g Ritchey
et al. 2023) are not sensitive to the presence of low-metallicity gas, but are
instead dominated by metal-rich gas.

We find that the overall strength of dust depletion, [Zn/Fe]fit, varies within
each MC, and overall correlates with the total metallicity. Comparing
different environments, at similar metallicities, the Milky Way shows higher
levels of dust depletion and molecular fractions than the LMC, and then
progressively the SMC and DLAs. This suggests that not only metallicity plays
an important role for the formation of dust and molecules (e.g., Petitjean et
al. 2006), but probably also density, temperature and pressure (Noterdaeme et
al. 2015), so a higher fraction of cold dense gas, like in the case of the
Milky Way disk. We find no obvious trend of the molecular fraction with either
the total metallicity or the overall strength of dust depletion. The lack of
this correlation is probably due to the complexity of the ISM, having a mix of
warm, cold, and molecular medium, as well as chemical inhomogeneities along
the line of sight. Indeed, the presence of some low-metallicity and low-
depletion gas along the line of sight can lower the total metallicity and dust
depletion that we measure in the warm ISM, but does not affect the molecular
gas which is mostly confined in a colder and denser gas phase.

Studying the chemical properties of the neutral ISM based on the relative
abundances of metals (i.e. the relative method) allows the simultaneous
characterization of dust depletion, metallicity and nucleosynthesis effects
such as $\alpha$-element enhancements and Mn underabundance. Characterising
the chemical properties of the neutral ISM in the SMC and LMC and eventually
linking them to the chemical properties of stars that form from this gas is
important for a more complete understanding of their chemical evolution. This
study makes one important step forward in this direction.

###### Acknowledgements.

We thank the anonymous referee for an insightful and constructive report,
which sharpened and further enriched this paper. We thank Edward Jenkins for
the stimulating and profound discussions which helped improving the paper
substantially. We thank Eline Tolstoy, Corinne Charbonnel, Nikos Prantzos,
Yves Revaz, Pascale Jablonka, Nicolas Lehner, Guido De Marchi, Søren Larsen,
Sviatoslav Borisov, and Kirill Tchernyshyov for insightful conversations and
useful suggestions, and Mathieu Van der Swaelmen for sharing the LMC stellar
data with us. A.D.C., A.V., C.K., I.J., J.K. K., and T.R.H. acknowledge
support by the Swiss National Science Foundation under grant 185692 funding
the ”Interstellar One” project. This research has made use of ESASky (Baines
et al. 2017; Giordano et al. 2018), developed by the ESAC Science Data Centre
(ESDC) team and maintained alongside other ESA science mission’s archives at
ESA’s European Space Astronomy Centre (ESAC, Madrid, Spain).

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Table 1: Sample of lines of sight towards the LMC and chemical properties of their neutral ISM. The [$\alpha$/Fe]nucl is the average $\alpha$-element enhancement, reported only for the golden sample.[1] Roman-Duval et al. (2021). The metal column densities have been corrected for the latest oscillator strengths, following Konstantopoulou et al. (2022). $N$(Ti) are taken from Welty & Crowther (2010). ID | RA | Dec | $\log N({\rm H})_{\rm tot}$ | [Zn/Fe] | $\log f_{\rm H_{2}}$ | Ref. | [Zn/Fe]fit | [M/H]tot | [$\alpha$/Fe]nucl
---|---|---|---|---|---|---|---|---|---
BI 173 | 05:27:09.94 | -69:07:56.46 | $21.25\pm 0.05$ | $0.83\pm 0.05$ | $-5.31$ | [1] | $0.75\pm 0.05$ | $-0.50\pm 0.07$ | –
BI 184 | 05:30:30.66 | -71:02:31.60 | $21.15\pm 0.04$ | $0.73\pm 0.08$ | $-1.20$ | [1] | $0.70\pm 0.08$ | $-0.38\pm 0.10$ | –
BI 237 | 05:36:14.63 | -67:39:19.18 | $21.65\pm 0.03$ | $0.98\pm 0.07$ | $-1.30$ | [1] | $1.07\pm 0.10$ | $-0.50\pm 0.12$ | $0.29\pm 0.16$
BI 253 | 05:37:34.46 | -69:01:10.20 | $21.68\pm 0.03$ | $0.83\pm 0.04$ | $-1.62$ | [1] | $0.91\pm 0.12$ | $-0.53\pm 0.16$ | $0.28\pm 0.22$
PGMW 3120 | 04:56:46.81 | -66:24:46.72 | $21.48\pm 0.03$ | $0.97\pm 0.08$ | $-2.88$ | [1] | $0.91\pm 0.07$ | $-0.50\pm 0.09$ | –
PGMW 3223 | 04:57:00.86 | -66:24:25.12 | $21.40\pm 0.06$ | $1.03\pm 0.06$ | $-2.41$ | [1] | $1.05\pm 0.07$ | $-0.30\pm 0.10$ | –
Sk-65 22 | 05:01:23.07 | -65:52:33.40 | $20.66\pm 0.03$ | $0.83\pm 0.06$ | $-5.43$ | [1] | $0.80\pm 0.06$ | $-0.17\pm 0.07$ | –
Sk-66 172 | 05:37:05.39 | -66:21:35.18 | $21.27\pm 0.03$ | $1.11\pm 0.06$ | $-2.76$ | [1] | $1.07\pm 0.07$ | $-0.49\pm 0.08$ | –
Sk-66 19 | 04:55:53.95 | -66:24:59.35 | $21.87\pm 0.07$ | $1.25\pm 0.13$ | $-1.37$ | [1] | $1.27\pm 0.13$ | $-0.41\pm 0.16$ | –
Sk-66 35 | 04:57:04.44 | -66:34:38.45 | $20.85\pm 0.04$ | $0.84\pm 0.14$ | $-1.25$ | [1] | $0.98\pm 0.13$ | $-0.05\pm 0.14$ | –
Sk-67 101 | 05:25:56.22 | -67:30:28.67 | $20.20\pm 0.04$ | $0.68\pm 0.13$ | – | [1] | $0.67\pm 0.13$ | $0.10\pm 0.15$ | –
Sk-67 105 | 05:26:06.19 | -67:10:56.79 | $21.26\pm 0.04$ | $0.86\pm 0.07$ | $-1.83$ | [1] | $0.86\pm 0.08$ | $-0.77\pm 0.09$ | –
Sk-67 14 | 04:54:31.89 | -67:15:24.58 | $20.24\pm 0.06$ | $0.00\pm 0.00$ | $-4.93$ | [1] | $1.01\pm 0.10$ | $0.47\pm 0.44$ | –
Sk-67 191 | 05:33:34.03 | -67:30:19.72 | $20.78\pm 0.03$ | $0.52\pm 0.20$ | – | [1] | $0.54\pm 0.21$ | $-0.49\pm 0.23$ | –
Sk-67 2 | 04:47:04.45 | -67:06:53.12 | $21.46\pm 0.12$ | $1.15\pm 0.11$ | $-0.21$ | [1] | $0.98\pm 0.12$ | $-0.82\pm 0.19$ | $0.29\pm 0.26$
Sk-67 211 | 05:35:13.91 | -67:33:27.51 | $20.81\pm 0.04$ | $0.73\pm 0.06$ | – | [1] | $0.90\pm 0.07$ | $-0.06\pm 0.09$ | $0.25\pm 0.12$
Sk-67 5 | 04:50:18.92 | -67:39:38.10 | $21.04\pm 0.04$ | $1.00\pm 0.05$ | $-1.28$ | [1] | $0.92\pm 0.06$ | $-0.46\pm 0.09$ | $0.40\pm 0.11$
Sk-68 129 | 05:36:26.77 | -68:57:31.90 | $21.62\pm 0.14$ | $1.33\pm 0.14$ | $-1.12$ | [1] | $1.27\pm 0.15$ | $-0.13\pm 0.20$ | –
Sk-68 135 | 05:37:49.11 | -68:55:01.69 | $21.48\pm 0.02$ | $1.04\pm 0.07$ | $-1.31$ | [1] | $0.83\pm 0.14$ | $-0.51\pm 0.18$ | $0.28\pm 0.25$
Sk-68 140 | 05:38:57.18 | -68:56:53.10 | $21.51\pm 0.11$ | $1.16\pm 0.10$ | $-1.10$ | [1] | $1.07\pm 0.11$ | $-0.14\pm 0.16$ | –
Sk-68 155 | 05:42:54.93 | -68:56:54.50 | $21.47\pm 0.09$ | $1.06\pm 0.05$ | $-1.18$ | [1] | $1.00\pm 0.06$ | $-0.12\pm 0.11$ | –
Sk-68 26 | 05:01:32.25 | -68:10:42.93 | $21.65\pm 0.06$ | $1.05\pm 0.15$ | $-0.97$ | [1] | $0.94\pm 0.15$ | $-0.77\pm 0.17$ | –
Sk-68 52 | 05:07:20.42 | -68:32:08.59 | $21.31\pm 0.06$ | $0.43\pm 0.12$ | $-1.54$ | [1] | $0.86\pm 0.06$ | $-0.27\pm 0.09$ | $0.09\pm 0.13$
Sk-68 73 | 05:22:59.78 | -68:01:46.62 | $21.68\pm 0.02$ | $1.24\pm 0.12$ | $-1.29$ | [1] | $1.25\pm 0.16$ | $-0.18\pm 0.21$ | $0.26\pm 0.30$
Sk-69 104 | 05:18:59.50 | -69:12:54.82 | $19.57\pm 0.68$ | $1.06\pm 0.27$ | – | [1] | $1.06\pm 0.29$ | $0.40\pm 0.73$ | –
Sk-69 175 | 05:31:25.52 | -69:05:38.59 | $20.64\pm 0.03$ | $0.38\pm 0.12$ | – | [1] | $0.42\pm 0.12$ | $-0.55\pm 0.13$ | –
Sk-69 246 | 05:38:53.38 | -69:02:00.93 | $21.48\pm 0.02$ | $0.80\pm 0.04$ | $-1.47$ | [1] | $0.88\pm 0.09$ | $-0.40\pm 0.11$ | $0.18\pm 0.15$
Sk-69 279 | 04:54:14.26 | -69:15:13.35 | $21.63\pm 0.05$ | $0.76\pm 0.06$ | $-1.02$ | [1] | $0.65\pm 0.06$ | $-0.79\pm 0.08$ | –
Sk-70 115 | 05:48:49.65 | -70:03:57.82 | $21.18\pm 0.08$ | $0.67\pm 0.05$ | $-0.94$ | [1] | $0.72\pm 0.08$ | $-0.30\pm 0.12$ | $0.25\pm 0.16$
Sk-70 79 | 05:06:37.26 | -70:29:24.16 | $21.34\pm 0.04$ | $1.51\pm 0.09$ | $-0.78$ | [1] | $1.57\pm 0.11$ | $-0.08\pm 0.13$ | –
Sk-71 45 | 05:31:15.65 | -71:04:09.69 | $21.11\pm 0.03$ | $0.81\pm 0.06$ | $-2.18$ | [1] | $0.77\pm 0.06$ | $-0.26\pm 0.07$ | –
Sk-71 50 | 05:40:43.19 | -71:29:00.65 | $21.24\pm 0.05$ | $0.55\pm 0.05$ | $-0.81$ | [1] | $0.59\pm 0.05$ | $-0.44\pm 0.07$ | –
Table 2: Same as Table 1, but for the SMC. [2] Jenkins & Wallerstein (2017); [3] Tchernyshyov et al. (2015). The metal column densities have been corrected for the latest oscillator strengths, following Konstantopoulou et al. (2022). $N$(Ti) are taken from Welty & Crowther (2010). ID | RA | Dec | $\log N({\rm H})_{\rm tot}$ | [Zn/Fe] | $\log f_{\rm H_{2}}$ | Ref. | [Zn/Fe]fit | [M/H]tot | [$\alpha$/Fe]nucl
---|---|---|---|---|---|---|---|---|---
AzV 18 | 00:47:12.22 | -73:06:33.11 | $22.06\pm 0.02$ | $0.91\pm 0.09$ | $-1.40$ | [2] | $0.98\pm 0.10$ | $-0.66\pm 0.13$ | $0.38\pm 0.18$
AzV 26 | 00:47:50.05 | -73:08:21.05 | $21.77\pm 0.04$ | $0.60\pm 0.05$ | $-0.84$ | [2] | $0.57\pm 0.06$ | $-0.98\pm 0.08$ | $0.22\pm 0.11$
AzV 47 | 00:48:51.49 | -73:25:58.54 | $21.32\pm 0.04$ | $0.57\pm 0.07$ | $-2.48$ | [2] | $0.54\pm 0.07$ | $-0.73\pm 0.08$ | $0.28\pm 0.12$
AzV 78 | 00:50:38.39 | -73:28:18.26 | $21.70\pm 0.06$ | $0.00\pm 0.00$ | $-2.76$ | [2] | $0.62\pm 0.12$ | $-0.82\pm 0.17$ | $0.24\pm 0.24$
AzV 80 | 00:50:43.81 | -72:47:41.55 | $21.83\pm 0.02$ | $0.69\pm 0.06$ | $-1.45$ | [2] | $0.84\pm 0.11$ | $-0.81\pm 0.15$ | $0.35\pm 0.21$
AzV 95 | 00:51:21.60 | -72:44:14.88 | $21.50\pm 0.04$ | $0.57\pm 0.07$ | $-1.80$ | [2] | $0.59\pm 0.07$ | $-0.83\pm 0.09$ | $0.30\pm 0.12$
AzV 104 | 00:51:38.43 | -72:48:06.08 | $21.46\pm 0.06$ | $0.51\pm 0.16$ | $-1.93$ | [2] | $0.58\pm 0.16$ | $-0.92\pm 0.19$ | –
AzV 207 | 00:58:33.19 | -71:55:46.72 | $21.44\pm 0.06$ | $0.83\pm 0.06$ | $-1.74$ | [2] | $0.98\pm 0.27$ | $-0.45\pm 0.35$ | $0.29\pm 0.50$
AzV 216 | 00:58:59.14 | -72:44:34.13 | $21.64\pm 0.03$ | $0.72\pm 0.08$ | $-2.56$ | [2] | $0.73\pm 0.08$ | $-0.77\pm 0.09$ | –
AzV 229 | 00:59:26.58 | -72:09:53.93 | $21.06\pm 0.04$ | $0.62\pm 0.08$ | $-5.10$ | [2] | $0.75\pm 0.07$ | $-0.61\pm 0.08$ | $0.36\pm 0.12$
AzV 242 | 01:00:06.88 | -72:13:57.37 | $21.32\pm 0.04$ | $1.16\pm 0.18$ | $-3.81$ | [2] | $0.85\pm 0.06$ | $-0.62\pm 0.09$ | $0.37\pm 0.11$
AzV 321 | 01:02:57.08 | -72:08:09.11 | $20.70\pm 0.08$ | $0.90\pm 0.11$ | $-5.96$ | [2] | $0.87\pm 0.07$ | $-0.37\pm 0.12$ | $0.38\pm 0.16$
AzV 332 | 01:03:25.23 | -72:06:43.86 | $20.54\pm 0.16$ | $0.56\pm 0.06$ | $-5.74$ | [2] | $0.54\pm 0.06$ | $-0.47\pm 0.17$ | –
AzV 388 | 01:05:39.53 | -72:29:26.94 | $21.19\pm 0.04$ | $0.99\pm 0.07$ | $-1.49$ | [2] | $1.07\pm 0.10$ | $-0.55\pm 0.12$ | $0.43\pm 0.16$
AzV 456 | 01:10:55.76 | -72:42:56.22 | $21.43\pm 0.07$ | $1.36\pm 0.09$ | $-0.20$ | [2] | $0.95\pm 0.17$ | $-1.09\pm 0.24$ | $0.41\pm 0.33$
AzV 476 | 01:13:42.45 | -73:17:29.52 | $21.95\pm 0.08$ | $0.81\pm 0.17$ | $-0.70$ | [2] | $0.58\pm 0.08$ | $-1.23\pm 0.11$ | –
Sk 190 | 01:31:27.98 | -73:22:14.22 | $20.62\pm 0.04$ | $0.00\pm 0.00$ | $-2.90$ | [2] | $0.74\pm 0.10$ | $-0.55\pm 0.12$ | $0.50\pm 0.17$
Sk 191 | 01:41:42.07 | -73:50:38.18 | $21.62\pm 0.04$ | $0.00\pm 0.00$ | $-0.67$ | [2] | $1.12\pm 0.11$ | $-1.37\pm 0.14$ | $0.40\pm 0.19$
AzV 238 | 00:59:55.51 | -72:13:37.78 | $21.41\pm 0.21$ | $0.89\pm 0.04$ | $-5.16$ | [3] | $0.81\pm 0.06$ | $-0.89\pm 0.22$ | –
AzV 327 | 01:03:10.55 | -72:02:14.33 | $21.62\pm 0.22$ | $0.83\pm 0.19$ | $-6.53$ | [3] | $0.68\pm 0.13$ | $-1.55\pm 0.25$ | –
Sk 9 | 00:46:32.63 | -73:06:05.56 | $21.76\pm 0.21$ | $2.17\pm 2.10$ | $-4.43$ | [3] | $0.67\pm 0.05$ | $-0.96\pm 0.21$ | –
Sk 116 | 01:04:55.74 | -72:46:48.15 | $21.57\pm 0.21$ | $0.54\pm 0.04$ | $-2.74$ | [3] | $0.51\pm 0.03$ | $-1.00\pm 0.21$ | –
Table 3: The [$X$/Fe]nucl due to nucleosynthesis, after correction for dust-depletion, in the LMC neutral ISM. These values are shown in Fig. 9. ID | [Mg/Fe]nucl | [Si/Fe]nucl | [Cr/Fe]nucl | [Ni/Fe]nucl | [Zn/Fe]nucl | [Ti/Fe]nucl | [O/Fe]nucl | [S/Fe]nucl | [Cu/Fe]nucl | [P/Fe]nucl
---|---|---|---|---|---|---|---|---|---|---
BI 173 | $0.21\pm 0.12$ | $0.32\pm 0.21$ | $0.07\pm 0.08$ | $-0.06\pm 0.08$ | $0.08\pm 0.07$ | – | – | $0.34\pm 0.08$ | $0.19\pm 0.23$ | $-0.34\pm 0.09$
BI 184 | $0.19\pm 0.11$ | $0.14\pm 0.19$ | $0.02\pm 0.15$ | $0.05\pm 0.16$ | $0.03\pm 0.11$ | – | – | – | – | –
BI 237 | $0.33\pm 0.11$ | $0.09\pm 0.17$ | $0.04\pm 0.16$ | $-0.02\pm 0.15$ | $-0.09\pm 0.11$ | $0.31\pm 0.16$ | – | – | – | –
BI 253 | $0.28\pm 0.16$ | – | $0.02\pm 0.19$ | $-0.06\pm 0.19$ | $-0.08\pm 0.12$ | $0.27\pm 0.21$ | – | – | – | –
PGMW 3120 | $0.13\pm 0.15$ | $0.24\pm 0.27$ | $0.08\pm 0.13$ | $0.01\pm 0.12$ | $0.06\pm 0.10$ | – | – | – | – | –
PGMW 3223 | $0.17\pm 0.13$ | $0.13\pm 0.18$ | $0.05\pm 0.12$ | $-0.08\pm 0.10$ | $-0.02\pm 0.08$ | – | – | – | – | –
Sk-65 22 | – | $0.29\pm 0.14$ | $0.01\pm 0.12$ | $-0.04\pm 0.11$ | $0.03\pm 0.08$ | – | – | $0.52\pm 0.13$ | – | $-0.12\pm 0.10$
Sk-66 172 | $0.27\pm 0.16$ | – | $0.04\pm 0.14$ | $0.03\pm 0.18$ | $0.04\pm 0.09$ | – | – | $0.30\pm 0.17$ | – | $-0.02\pm 0.12$
Sk-66 19 | $0.32\pm 0.21$ | – | $0.10\pm 0.22$ | $-0.08\pm 0.19$ | $-0.01\pm 0.17$ | – | – | – | – | –
Sk-66 35 | $0.18\pm 0.19$ | $0.27\pm 0.20$ | – | $-0.10\pm 0.21$ | $-0.14\pm 0.19$ | – | – | $0.33\pm 0.18$ | $0.25\pm 0.25$ | –
Sk-67 101 | – | $0.06\pm 0.20$ | $0.06\pm 0.24$ | $-0.06\pm 0.24$ | $0.01\pm 0.20$ | – | – | $0.15\pm 0.16$ | – | –
Sk-67 105 | $0.36\pm 0.21$ | $0.04\pm 0.11$ | $-0.01\pm 0.13$ | $0.01\pm 0.14$ | $-0.00\pm 0.10$ | – | $1.21\pm 0.21$ | $0.27\pm 0.11$ | – | –
Sk-67 14 | – | $-0.19\pm 0.16$ | – | $0.08\pm 0.17$ | – | – | – | $0.07\pm 0.12$ | – | –
Sk-67 191 | $0.17\pm 0.33$ | $0.33\pm 0.31$ | $-0.00\pm 0.38$ | $-0.05\pm 0.37$ | $-0.03\pm 0.32$ | – | – | $0.52\pm 0.27$ | – | –
Sk-67 2 | $0.33\pm 0.19$ | – | $-0.11\pm 0.28$ | $-0.14\pm 0.25$ | $0.17\pm 0.16$ | $0.25\pm 0.21$ | – | $0.20\pm 0.21$ | – | –
Sk-67 211 | $-0.02\pm 0.14$ | $0.32\pm 0.21$ | $-0.00\pm 0.12$ | $0.02\pm 0.11$ | $-0.17\pm 0.09$ | $0.27\pm 0.11$ | – | $0.31\pm 0.09$ | – | $-0.12\pm 0.49$
Sk-67 5 | $0.35\pm 0.11$ | $0.43\pm 0.08$ | $0.03\pm 0.12$ | $-0.14\pm 0.12$ | $0.08\pm 0.07$ | $0.37\pm 0.10$ | – | $0.36\pm 0.08$ | – | $-0.14\pm 0.10$
Sk-68 129 | $0.30\pm 0.17$ | – | $0.04\pm 0.23$ | – | $0.07\pm 0.20$ | – | – | – | – | –
Sk-68 135 | $0.28\pm 0.20$ | – | $0.09\pm 0.23$ | $-0.07\pm 0.22$ | $0.21\pm 0.16$ | $0.29\pm 0.25$ | – | – | – | $-0.18\pm 0.17$
Sk-68 140 | $0.23\pm 0.22$ | $0.23\pm 0.27$ | $0.09\pm 0.18$ | $0.09\pm 0.18$ | $0.09\pm 0.14$ | – | – | – | – | –
Sk-68 155 | $0.26\pm 0.09$ | $0.02\pm 0.14$ | $0.04\pm 0.09$ | $0.02\pm 0.12$ | $0.06\pm 0.07$ | – | – | – | – | –
Sk-68 26 | $0.42\pm 0.19$ | – | $0.26\pm 0.26$ | $0.09\pm 0.23$ | $0.11\pm 0.21$ | – | – | – | – | –
Sk-68 52 | $-0.05\pm 0.15$ | $-0.10\pm 0.15$ | $0.16\pm 0.10$ | $-0.05\pm 0.11$ | $-0.43\pm 0.14$ | $0.24\pm 0.10$ | – | $0.27\pm 0.08$ | – | –
Sk-68 73 | $0.26\pm 0.22$ | – | $0.04\pm 0.26$ | $-0.01\pm 0.24$ | $-0.01\pm 0.20$ | $0.32\pm 0.28$ | $0.14\pm 0.21$ | – | $-0.04\pm 0.22$ | –
Sk-69 104 | – | $0.43\pm 0.40$ | – | – | $0.00\pm 0.42$ | – | – | $0.01\pm 0.36$ | – | –