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The Lazy Giants: APOGEE Abundances Reveal Low Star Formation Efficiencies in the Magellanic Clouds

We report the first APOGEE metallicities and alpha-abundances measured for 3800 red giant stars spanning a large radial range of both the Large (LMC) and Small Magellanic Clouds (SMC), the largest Milky Way dwarf galaxies. Our sample is an order of magnitude larger than that of previous studies and extends to much larger radial distances. These are the first results presented that make use of the newly installed southern APOGEE instrument at the du Pont telescope at Las Campanas Observatory. Our unbiased sample of the LMC spans a large range in metallicity from [Fe/H]=-0.2 to very metal poor stars of [Fe/H]=-2.5, the most metal-poor Magellanic Clouds (MCs) stars detected to date. The LMC [alpha/Fe]-[Fe/H] distribution is very flat over a large metallicity range but rises by ~0.1 dex at the metal-rich end. We interpret this as a sign of the known recent increase in MC star formation activity and are able to reproduce the pattern with a chemical evolution model that includes a recent"starburst". This starburst phase is required to reproduce the flat alpha-abundance distributions in both the LMC and SMC. At the metal-poor end, we capture the increase of [alpha/Fe] with decreasing [Fe/H] and constrain the"alpha-knee"to [Fe/H]=-2.2 in both MCs implying a low SFE of ~0.01 Gyr^-1. Counter-intuitively, the knee is more metal-poor than that of less massive Milky Way (MW) dwarf galaxies such as Fornax or Sagittarius. One possible interpretation is that the MCs formed in a lower-density environment than the MW, a hypothesis that is consistent with the paradigm that the MCs fell into the MW potential only recently.


INTRODUCTION
Dwarf galaxies are the most abundant galaxies in the Universe, and our Milky Way (MW) hosts dozens (Drlica-Wagner et al. 2015), with dozens more likely to be found in the coming decades. These galaxies span a large range in stellar mass (∼ 10 3 M -∼ 10 9 M ; Mc-Connachie 2012) and morphologies. They also serve as important laboratories for studying the details of galaxy formation at sub-Milky Way scales, as well as the extent to which the MW was formed by the hierarchical buildup of such systems, as first suggested by Searle & Zinn (1978). While a large fraction of MW dwarf galaxies do not currently contain gas, probably due to interactions with the MW in the past (Grcevich & Putman 2009), they often exhibit complex and unique star formation histories (Weisz et al. 2014).
Our understanding of the formation and evolution of dwarf galaxies has grown significantly in the last two decades due to deep HST and large-area, ground-based imaging and multi-object spectroscopy. Despite their apparently widely varying star formation histories (SFHs; Dolphin 2002;Weisz et al. 2014), unique star formation histories, these galaxies appear to follow the wellestablished mass-metallicity relation of galaxies, regardless of whether or not they are currently forming stars (Kirby et al. 2013). The underlying cause of the massmetallicity relation is thought to be either shallower gravitational potential leading to lower metal retention (e.g., Dekel & Silk 1986), a correlation between star formation efficiency (SFE) and metallicities achieved during early star formation (e.g., Matteucci 1994;Calura et al. 2009), or an initial mass function (IMF) that increases with increasing galaxy mass (e.g., Köppen et al. 2007). While there is support in the literature for each scenario, largescale chemical abundance studies of individual stars in dwarf galaxies are required to offer important constraints on the variation in SFE, outflows, and IMF over each dwarf galaxy's lifetime.
The SFE, outflow loading factor, and IMF can be probed by analyzing the distribution of α-elements (O, Mg, Si, S, Ca, Ti) in a dwarf galaxy. These elements are primarily produced in massive stars (M > 8 M ), and are released to the interstellar medium (ISM) in Type II supernovae (SNe) explosions. The first stars that are formed are enhanced in the α-elements relative to Fe in the first 1-2 Gyr of star formation -i.e., before Type Ia SNe (which require the existence of white dwarf progenitors) begin to explode. Type Ia SNe enrich the Fe abundance of the ISM without substantially enriching the α-elements, thereby lowering the abundance of the α-elements as compared to the Fe abundance (Tinsley 1979). In the [α/Fe]-[Fe/H] abundance plane, the point at which the [α/Fe] trend begins to decrease is commonly referred to as the "knee", and the [Fe/H] where that occurs is a tracer of the early SFE of the galaxy -i.e., prior to the system reaching that metallicity. Additionally, the level of the high-α plateau can probe the IMF (e.g., McWilliam 1997) while the slope of the knee can probe the gas outflow rate (e.g., Andrews et al. 2017).
To date, the position of the "knee" has only been identified in a handful of dwarf galaxies. Based on these few cases, the [Fe/H] position of the knee appears to correlate with stellar mass, although variations have been observed (Hendricks et al. 2014). Curiously, however, the position of the α-element knee has not been measured in the two largest satellites of the Milky Way, the Large and Small Magellanic Clouds (LMC and SMC, respectively). These galaxies still contain gas, and are likely falling into the MW potential well for the first time (e.g., Besla et al. 2007Besla et al. , 2012. Both galaxies exhibit ongoing star formation, with a SFH that suggests recent, strong starbursts beginning some 2-4 Gyr ago (Smecker-Hane et al. 2002;Harris & Zaritsky 2009;Rubele et al. 2012;Weisz et al. 2013;Meschin et al. 2014), potentially due to a close encounter of the two galaxies with each other. Given a dynamical history that suggests that they have chemically evolved for the most part in near isolation, the MCs represent systems in great contrast to the MW dwarf spheroidal satellites, which are thought to have had their evolution greatly shaped by long association with the MW, which may have both incited star formation episodes through gravitational encounters and facilitated the removal of gas and metals.
In further contrast to most MW dSphs, the MCs, due to their relative proximity (d ∼ 50 kpc), are more amenable to high-resolution spectroscopy of their constituent stars. On the other hand, where the MCs present a disadvantage relative to the MW dSphs is their great angular extent, with LMC stellar populations found to a radial distance of at least ∼20 • (Muñoz et al. 2006;Majewski et al. 2009;Nidever et al. 2018;Belokurov & 14   Erkal 2019); thus previous high-resolution spectroscopic studies have been limited in both sample size and spatial coverage. Despite these limitations, previous abundance studies of the LMC have outlined its rough chemical characteristics, for example, that some of the α-abundances (Mg and O) of its stars are deficient compared to those of the MW, while other α-elements (Si, Ca and Ti) are similarly enriched to MW stars (Pompéia et al. 2008;Lapenna et al. 2012;Van der Swaelmen et al. 2013). These studies also suggest that the α-element knee of the LMC is at [Fe/H] < 1.5 dex. Further details were explored in Bekki & Tsujimoto (2012), who tried to fit the chemical abundance tracks using models that utilized the SFH of Harris & Zaritsky (2009), but the available chemical abundance data did not appear to be precise enough to resolve features in the [Mg/Fe]-[Fe/H] abundance plane that were predicted by their models. The SMC is less well studied, but the chemical abundances results of 200 stars from (Mucciarelli 2014) indicate that the [α/Fe] abundance patterns of the MCs are quite similar.
Fortunately, the Apache Point Observatory Galactic Evolution Experiment (APOGEE, Majewski et al. 2017), part of SDSS-III (Eisenstein et al. 2011) and SDSS-IV (Blanton et al. 2017), through installation of a second APOGEE spectrograph (Wilson et al. 2019) on the du Pont telescope at Las Campanas Observatory, has recently procured high-resolution, H-band spectra for already several thousand stars residing in the MCs. These observations cover much of the galaxies: out to 10 • for the LMC and 6 • for the SMC and with large azimuthal coverage for both. An advantage of these particular data is that they can be compared directly to the vast col-lection of APOGEE spectra similarly obtained and analyzed for both MW stars as well as stars in a sampling of other MW satellites, which ensures that any observed differences in properties found between galactic systems is likely to be real and not the result of systematic errors between disparate data sets.
In this paper we analyze the [α/Fe]-[Fe/H] abundance patterns of the Magellanic Clouds to understand the chemical evolution and star formation histories of these galaxies. We measure, for the first time, the metallicity location of the α-element knee in the LMC as well as an upper limit on the position of the knee for the SMC, which provides powerful constraints on the early star formation efficiencies of these galaxies. The layout of the paper is as follows: Section 2 gives an overview of the APOGEE MC fields and target selection while section 3 describes the APOGEE observations currently in hand and data reductions. In Section 4 we detail how we select bona fide MC member stars. Checks on the veracity of the southern APOGEE data are presented in Section 5. Our main results are described in Section 6 and the relevance and interpretation of our measurements are discussed in Section 7. Finally, our conclusions are summarized in Section 8.

FIELD AND TARGET SELECTION
A brief description of the APOGEE MC survey target selection is given in the SDSS-IV targeting paper (Zasowski et al. 2017), but we give more details here. The main goal of the APOGEE MC survey is to study the galactic chemical and kinematical evolution of the Magellanic Clouds with a particular focus on spatial variations. RGB stars are the majority of the stars in our MC survey. However, a large number of other stellar classes were also chosen to enable a variety of astrophysical studies: massive stars, hot main-sequence stars, asymptotic giant branch (AGB) stars, and Post-AGB stars. In addition, stars in the Olsen et al. (2011) metal-poor accreted stream were selected to help ascertain their properties and origin as were some stars that were previously studied with high-resolution spectra for calibration purposes.
To explore spatial gradients in the MCs, we picked fields that spanned a wide range of radius and position angle (see Fig. 1 and Table 1). We required a field to have approximately 50 or more MC red giant branch (RGB) stars for which S/N=100 could be obtained with exposure times of 9 hours in the LMC and 12 hours in the SMC. This produced a maximum radius of ∼9.5 • in the LMC and ∼5 • in the SMC. To aid in the chemical analysis we picked fields that also had deep ugriz photometry from the Survey of the MAgellanic Stellar History (SMASH; Nidever et al. 2017) or the Dark Energy Survey (DES; Dark Energy Survey Collaboration et al. 2016) 19 . One of the goals of SMASH is to derive accurate spatially-resolved star formation histories (SFHs) to old ages. When this information is combined with the precise APOGEE abundances, simple chemical evolution models can be robustly constrained. At the time of this writing the SMASH SFHs are still being generated; therefore, we did not use them in our current analysis.
19 LMC11 and LMC15 are not currently covered by SMASH or DES beecause of a change in the DES footprint. Deep DECam observations of those regions will be obtained in the near future by an approved program. To help target reliable Magellanic giant stars, especially blue metal-poor giants that can be heavily contaminated by MW foreground stars, we obtained Washington M , T 2 , and DDO51 imaging with the WFI camera on the MPG/ESO-2.2m telescope at La Silla. The data were reduced with the IRAF CCDRED package and photometeric parameters derived with the PHOTRED photometry pipeline (Nidever et al. 2017). Figure 2 shows an example of the (M -T 2 , M ) color magnitude diagram (CMD) and (M -T 2 , ∆[M -DDO51]) color-color diagram (Majewski et al. 2000), within which a giant star selection was generated (bottom panel).
While the Washington+DDO51 photometry was used to prune out any potential Milky Way foreground dwarfs, the selection of RGB targets otherwise used a wide (J-K s ) range to avoid producing a metallicity bias (see Fig.  3). Figure 3 shows an example of the targeting strategy for field LMC10. The bright RGB stars ("BrtRGB") for which a S/N of 100 will be obtained by the end of the survey (LMC: 12.35<H<12.8; SMC: 12.9<H<13.2) were chosen randomly. However, fainter RGB stars ("Fn-tRGB") were also selected to fill available fibers when needed; to maximize their S/N, these fainter stars were chosen in magnitude priority.
Initial estimates indicate that there is ∼20-40% vignetting in the outer portion of the field of view of the southern APOGEE fiber plugplates (0. fields restrict targets to a field radius of 0.8 • . This same restriction was used in the MC fields when there were enough bright targets to fill the fibers allotted to each target class for that field. Exceptions were made for bright but rare targets (e.g., Supergiants, main-sequence stars) and RGB targets in outer fields where the density is low. Note that an initial set of MC targets with a 0.8 • outer radius for all target types and fields was created and observed in the first APOGEE-2S MC observing run in October 2017. Unfortunately, with the smaller radius restriction a large fraction of intended MC RGB targets were "lost" in the lower density outer fields. For later observing runs the plates were redesigned to include the original targets in the outer radial zones and observed starting in December 2017. The target selection for each MC field proceeds as follows. All targets are selected for each class according to the criteria described in the list below. An absolute priority is given for all targets in the full list in a two step process using first the group priority (in the order listed below) and then by the priority within the group using a sorting algorithm (none, random, magnitude, or CMD-uniform). Next, a limit on the number of targets for each class that can be assigned fibers is imposed with a 50% excess as a buffer for dealing with fiber collisions and other contingencies. Targets with bright neighbors (brighter than 2 mag and within 6 ) and targets that collide with a higher priority targets within 56 (the minimum allowed fiber-to-fiber spacing; Zasowski et al. 2013) are removed. Any extra targets above the limit for that class are removed. In addition, the total number of targets for that entire field (250 for MC fields and 205 for the NGC362 and 47 Tucanae calibration cluster fields) from the low priority end of the list. Finally, the list of targets and their information as well as the selection function fraction (the number of targets picked divided by the total number in that class) are saved. Unlike the standard APOGEE observing for deep fields, where a "cohorting" scheme is utilized to allow swapping of brighter targets from field visit to field visit to increase the number of targets observed (Zasowski et al. 2013), for the MC observing the same targets are observed for the full number of epochs each field is visited. The MC target selection software is available at https://svn.sdss.org/public/ repo/apogee/apogeetarget/trunk/pro/mcs/ Details on how the 10 target classes were selected are given below (in target class priority order): 1. Supergiants: Massive Magellanic stars were selected from Neugent et al. (2012) and Bonanos et al. (2009) and combined in one catalog. Blue stars that overlap the "main-sequence" target class (see below) were removed. Generally a maximum of 20 fibers per field (but increased to ∼35 in some inner fields) were alloted for the supergiants and a limiting radius of 0.95 • was used to improve the yield. To date 144 MC supergiants have been observed.
2. Main-sequence: Young, blue main-sequence targets were selected using the cyan box in the (J-K s , H) diagram and are shown as filled cyan circles in Figure 3. Roughly 20 fibers per field were allotted for the main-sequence stars and the stars were selected with magnitude priority sorting and a limiting field radius of 0.95 • . To date 403 main-sequence stars have been observed. stream of metal-poor stream stars in the LMC that might be accreted SMC stars. A maximum of 20 fibers per field were allotted for the Olsen stream stars and these were selected with magnitude priority sorting and a limiting field radius of 0.95 • . To date 71 Olsen stream stars have been observed.
4. Post-AGB: Post-AGB stars were selected from Kamath et al. (2014Kamath et al. ( , 2015. A maximum of 10 fibers per field were allotted for the Post-AGB stars and these were selected with random priority sorting and a limiting field radius of 0.80 • . To date 20 Post-AGB stars have been observed. 5. Literature High-resolution RGB: To check our results we observed RGB stars that other groups have also studied with high-resolution spectra (Van der Swaelmen et al. 2013 and Carrera et al. in prep). A maximum of 10 fibers per field were allotted for the literature RGB stars and these were selected with magnitude priority sorting and a limiting radius of 0.80 • . The selected literature targets are shown as gray open diamonds in Figure  3. To date 24 literature RGB stars have been observed.
6. AGB-DC: The AGB targeting strategy was guided by the AGB selections in Nikolaev & Weinberg (2000) using 2MASS (Skrutskie et al. 2006) and Dell'Agli et al. (2015b,a) using Spitzer. A maximum of 15 fibers per field were allotted to dusty carbon-rich AGB stars. These targets were selected using the magenta box in the (J-K s , H) diagram using a "CMD-uniform" sampling designed to pick stars uniformly across the 2-D CMD space. These targets were also selected with a limiting field radius of 0.80 • . The 102 AGB-DC targets observed to date are shown as filled magenta circles in Figure 3.
7. AGB-C: A maximum of 15 fibers per field were allotted to carbon-rich AGB stars and the targets were selected using the orange box in the (J-K s , H) diagram with CMD-uniform sampling and a limiting field radius of 0.80 • . The AGB-C targets are shown as filled blue circles in Figure 3. To date 241 AGB-C targets have been observed.
8. AGB-O: Oxygen-rich AGB stars were assigned to a maximum of 15 fibers per field (but this was increased to ∼40 in some inner regions). These targets were selected using the yellow box in the (J-K s , H) diagram with CMD-uniform sampling and a limiting field radius of 0.80 • (except for the field SMC7 which used 0.95 • ). The AGB-O targets are shown as filled yellow circles in Figure 3, with 284 observed to date.
9. Bright RGB: The largest group of targets are the red giant branch stars, selected in two groups -"bright" and "faint" (see below). The higher priority group are those for which S/N=100 spectra will be obtained in 9/12 visits for the LMC/SMC. Targets were selected from among those that passed the Washington photometry giant star selection and that lie within the red-bounded polygonal area in the (J-K s , H) diagram. These stars span a magnitude range of 12.35<H<12.8 for the LMC and 12.9<H<13.2 for the SMC. Random sampling and a limiting field radius of 0.80 • (except for some outer fields where 0.95 • was allowed) were used for the selection. All of the unassigned fibers remaining after attempting to fill them with stars in any of the above target classes were allotted to Bright RGB stars, up to a maximum of 250. The bright RGB targets are shown as filled red circles in Fig 10. Faint RGB: Faint RGB stars were targeted if not enough bright RGB targets were available. Targets were selected from among those that passed the Washington photometry giant cut and that lie within the orange polygon in the (J-K s , H) diagram. Magnitude priority sorting and a limiting field radius of 0.80 • (except for some outer fields that used 0.95 • ) were adopted. All of the remaining fibers were allotted up to a maximum of 250. The faint RGB targets are shown as filled orange circles in Figure 3, with 2043 observed so far.
The CMDs were not dereddened for the target selection because it is challenging to calculate accurate star-by-star extinctions in the inner MCs (but see Choi et al. 2018a). However, our CMD selection polygons were made large enough to capture the relevant stellar populations even with the moderate reddening seen in the NIR. For the SMC fields the CMD selection polygons were shifted in magnitude by +0.4 mag due to the larger SMC distance compared to that of the LMC.
The selection of targets in the 30 Dor "APOGEE-2S first light" plate was focused on getting spectra for massive stars, and so used different criteria than used for the normal MC fields. A number of massive star types (e.g., Luminous Blue Variables, Wolf-Rayet, Blue Supergiant, main-sequence stars) were selected manually from existing catalogs and will be discussed in full in a subsequent paper (Stringfellow et al., in preparation). In addition, 72 RGB stars were selected from the CMD in a manner similar to that shown in Figure 3, but with a magnitude range of 12.30<H<13.0 and a less expansive blue limit of J − K s =0.9.

MW Disk abundances − APO
APO Trendline, α−0.035 Figure 6. A comparison of the APOGEE MW disk α abundances from APO (left) and LCO (right). The APO trendline is shown in gray and shifted by −0.035 dex in [α/Fe] in the right panel indicating that there is a slight systematic offset between the two datasets. However, the overall abundance trends are nearly identical in both panels showing the reliability of the LCO data.

OBSERVATIONS AND REDUCTIONS
For the last seven years, the original APOGEE instrument (Wilson et al. 2010(Wilson et al. , 2012(Wilson et al. , 2019 has been taking data of the northern sky using the SDSS-2.5m telescope (Gunn et al. 2006) at Apache Point Observatory. However, to allow the APOGEE-2 project to access the entire Milky Way as well as the Magellanic Clouds, a southern copy of the APOGEE instrument (APOGEE-2S; Wilson et al. 2019), was installed at the du Pont-2.5m telescope at LCO in January 2017, with first light on February 16, 2017 using the 30 Dor plate. The southern instrument is nearly identical to the northern one, with some small modifications such as a revised LN 2 tank suspension system and protections against seismic events (APOGEE-2S; Wilson et al. 2019).
Since the inaugural "first light" observations of the 30 Doradus plate, the first full season featuring Magellanic Cloud targeting began in late 2017 (with runs in November and December), and are continuing. These data were reduced through the standard APOGEE reduction pipeline (Nidever et al. 2015) and stellar parameters and abundances were obtained via the ASP-CAP pipeline García Pérez et al. 2016), which uses a library of synthetic spectra Zamora et al. (2015) convolved with a single average Line Spread Function (LSF). ASPCAP first derives stellar parameters by fitting to a 7-D synthetic spectral grid (T eff , log g , APOGEE results from the northern spectra were applied to the ASPCAP results from the southern spectra. For our analysis only stars were used that had reliable stellar parameters (no bad quality flags set). In Section §5 we perform quality checks of the stellar parameters and abundances to verify the reliability of the results from the southern spectra.

SELECTION OF MAGELLANIC CLOUD MEMBER STARS
While steps were taken to try to select as many MC RGB stars as possible (e.g., selection using the Washington photometry), it is likely that we have some MW contamination in the APOGEE MC fields, especially from MW halo stars. To refine our analysis sample from those stars that were observed, we use ASPCAP stellar parameters, radial velocity, and Gaia DR2 (Brown et al. 2018) proper motions (unavailable when the target selection was made) to select bona fide MC RGB stars. To this end we required reliable stellar parameters for all the stars from the ASPCAP pipeline and T eff <5200 K and log g < 3.4 dex. The RV and proper motion selections and are shown in Figure 4. A Gaussian-fit to the LMC RV distribution gives a mean of 254.3 km s −1 with σ V =37.7 km s −1 and we use lower/upper thresholds of 160/348 km s −1 which are roughly ±2.5σ. The same values for the SMC are mean/σ V =137.6/26.7 km s −1 with lower/upper thresholds of 71/220 km s −1 . Ellipses with the parameters, determined by eye, given in Figure 4 are used for the proper motion cuts. Of the 2842/1245 LMC/SMC stars with S/N≥20, 124/100 are pruned with the velocity cuts or 4%/8% of the samples. Figure 5 15292 15296 15300 Figure 7. The most prominent abundance features of Fe, Mg and Si in 10 example metal-poor LMC stars (black) and the best-fitting ASPCAP synthetic spectrum (red). The central wavelengths of the lines are indicated by vertical blue lines. shows the T eff -log g distribution of the final LMC and SMC RGB samples color-coded by metallicity.

QUALITY CHECKS OF APOGEE-S DATA
This work is among the first to utilize data from the Southern Hemisphere component of APOGEE-2. Therefore, we perform a number of quality checks to verify the reliability of the spectroscopic parameters.
Because this work focuses on α abundance patterns, we first ensure that the conclusions one would draw about the MW [α/Fe]-[Fe/H] abundance patterns are the same whether or not northern or southern data are used. In Figure 6, we show the [α/Fe] vs. [Fe/H] distribution for a subsample of MW stars that have similar T eff and log g distributions as the LMC stars (3700 < T eff < 4500 and log g < 1.8) for data taken from the north (left) and south (right). Because the southern survey is still largely incomplete, we also only compare similar regions of the MW disk. We only select stars that have |b| < 15 • , and for the south we select 220 • < l < 330 • , and for the north we select 30 • < l < 140 • . We find a very slight (−0.035 dex) systematic difference in [α/Fe] between the two hemispheres, but the overall trends are identical, indicating that the southern and northern APOGEE data are largely measuring α-element abundances in the same way across the Galaxy. Still, when analyzing the LMC data, we only compare the LMC to other southern data to reduce the effect this small offset may have on our interpretations.
While the bulk abundance patterns are the same for stars with −1.0 < [Fe/H] < +0.5, it is also important to verify the quality of the spectra of the most-metal poor stars of our sample as they drive our ability to measure the α-poor "knee". In Figure 7, we show the spectral features of Fe, Mg, S and Si for 10 LMC stars with −2.3 < [Fe/H] < −2.1. Figure 7 illustrates that there are plenty of measurable features in these southern spectra that are fit well by ASPCAP, and brings confidence that these are really metal-poor, α-enhanced stars. For a complete analysis of the accuracy of APOGEE abundance results for metal-poor stars, see Mészáros et al. (2013).
In addition, we compare APOGEE-2S metallicities for 14 southern globular clusters with the values from Carretta et al. (2009a) in Figure 8. For each of these clusters, we select members using spatial and radial velocity cuts, and compute the reported mean [Fe/H] for each cluster and standard error on the mean from members with relatively high S/N (> 70), 3700 < T eff < 5500, and that are not flagged with poor spectra or stellar parameters. The metallicities agree fairly well even at low metallicities   Carretta et al. (2009b), using the same cuts on S/N, effective Temperature, and flags employed to compare mean globular cluster metallicity above. Again, we see good agreement in metallicity measurements down to [Fe/H] ∼ −2, below which there is evidence of a slight trend or offset in APOGEE metallcities that are too metal-poor by ∼ 0.2 dex at [Fe/H] = −2.5. The scatter in individual α-element abundance differences is fairly small, around or below 0.1 dex, although it is slightly larger in O, which is more difficult to measure from optical spectra and typically more uncertain. The scatter we find here in individual α-element abundance measurements, as well as the scatter in metallicity measurements of individual stars and the averaged cluster metallicities are all similar to what was found at higher metallicities by Jönsson et al. (2018), in their comparison of APOGEE DR14 to high-resolution optical studies. From Figure 8, we can see that there are no major trends in the individual abundance differences as a function of metallicity, although there may be small trends that differ depending on the element. Additionally, we see that O and Si in APOGEE do not appear to have any offsets compared to Carretta et al. (2009b), however, we do notice a significant ∼ 0.2 dex offset between the Mg measurements of these two studies across nearly the whole metallicity range covered. The offsets in Mg seen by Jönsson et al. (2018) were much smaller than this, although their sample is more metal-rich than here, and we do not see the same offset when comparing to other optical studies (see below), so it is unclear what the source of this offset is. Nonetheless, even if this offset is in the APOGEE Mg measurement, a roughly constant offset at all metallicities does not strongly impact our conclusions which are Comparing the APOGEE-2S metallicity and αelement abundance measurements to other studies, we find a similar scatter in the differences to what has been previously reported for APOGEE comparisons with optical measurements. We also find that there are no significant trends in the differences between APOGEE and these other surveys, except a small trend in APOGEE's metallicities at the lowest metallicities that it measures, [Fe/H] −2, such that APOGEE metallicities may be too metal-poor by ∼ 0.2 dex at [Fe/H] = −2.5. While we do see some offsets with APOGEE's α-element abundances and those from other works in the literature, the offsets are not consistently seen across the comparisons and are likely due to the differences in spectroscopic analyses between these studies. On top of this, global offsets in [α/Fe] ratios between APOGEE and other studies do not significantly impact our analysis and conclusions given that we are largely considering relative abundance ratios measured with the same APOGEE systematics, but we do note that offsets in [α/Fe] may be present when comparing results from past studies.

BACCHUS Analysis
We further check the by completing an independent stellar abundance analysis on ∼90 stars randomly selected from the LMC sample and a comparable number of stars randomly selected from Milky Way field popu-lation observed with APOGEE. The independent abundance analysis was carried out using the Brussels Automatic Code for Characterizing High accUracy Spectra (BACCHUS, Masseron et al. 2016). The current version of BACCHUS makes use of the the MARCS model atmosphere grid (Gustafsson et al. 2008), and the radiative transfer code TURBOSPECTRUM (Alvarez & Plez 1998;Plez 2012) to generate synthetic spectra. The MARCS model atmosphere grid include both carbon and α enhancements. Similar to Hawkins et al. (2016), we fix the T eff and log g stellar atmospheric parameters to the best fit values from the ASPCAP pipeline (i.e. the uncalibrated values of T eff and log g , which can be found in the FPARAM column in the ASPCAP results table. In addition to T eff and log g , we also fix the C and N values to those found in the best fit from the ASCAP pipeline. The [Fe/H] and microturblent velocity were then determine using the same procedure as in Hawkins et al. (2016). In short, microturblence was determine by ensuring no correlation between derived Fe abundance and reduced equivalent width (i.e. equivalent width divided by wavelength). The line selection for the various elements is the same as in Hawkins et al. (2016).
After fixing the T eff , log g , , which fits all of the α-elements simultaneously (keeping their relative abundances identical) in ASPCAP, is more accurate than the individual α-elements but somewhat more challenging to interpret because the relative "weight" of different α-elements changes with metallicity and T eff . Therefore, we compare the parameter-level [α/Fe] to Mg, Si, and Ca. These α-elements show the qualitatively similar abundance patterns to the parameter-level [α/Fe] although with some small differences and offsets. The general pattern seen in all four panels is that the LMC α abundances are quite flat in metallicity from [Fe/H]=−1.7 to −0.3. There is a slight increase in α at the metal-rich end most clearly seen in the parameter-level [α/Fe], [Mg/Fe], and [Si/Fe]. At the metal-poor end the α abundances increase but do not reach their maximum until the most metalpoor stars at [Fe/H]≈ −2.2. Figure 12 also shows both the S/N>40 stars (black) and S/N>70 stars separately.  The two sets of stars show nearly identical abundance patterns, and this illustrates the reliability of the individual element α abundances down to S/N=40, although perhaps slightly less so for Ca at the lowest metallicities. Now that we have verified that the parameter-level [α/Fe] values give abundance patterns consistent with those of the individual α elements and are reliable to low S/N, we will from now on use the more precise parameterlevel [α/Fe]. In Figure 13 we show the α-element abundance distribution of both the LMC and SMC in comparison to those for MW stars and other dwarf galaxies abundance data from the literature.
Both the APOGEE MC and MW stars come from the southern APOGEE instrument. While both MCs differ from the MW in that they are generally more α-poor at fixed [Fe/H], the MCs also differ from each other. We find that the LMC reaches metallicities as high as [Fe/H]≈0.0 whereas the SMC is only as metal-rich as [Fe/H] ≈ −0.5. We also appear to be lacking the most metal-poor stars in our SMC sample likely due to the (current) lower S/N in the SMC sample compared to the LMC because the stars are ∼0.4 mag fainter. However, we are able to measure the increase in [α/Fe] (with decreasing [Fe/H]) and constrain the α-knee in both the LMC and SMC to [Fe/H] ∼ −2.2. Once we obtain the rest of our observations it is likely that we will measure the knees in both MCs.
In the bottom two panels of Figure 13 we show the α abundance distributions of the MCs as compared to other spectroscopic samples. The LMC abundances from Van der Swaelmen et al. (2013) are shown as open purple diamonds. They agree with the APOGEE results at higher metallicities, but do not cover the low-metallicity region as our data. The Van der Swaelmen et al. stars do seem to contain a larger fraction of α-enhanced LMC stars than the APOGEE sample. We find that the APOGEE stars largely follow a tight sequence in [α/Fe]-[Fe/H] space, with only a few stars scattering to super-solar αelement abundance. This discrepancy could be due to the fact that the Van der Swaelmen et al. stars are at the center of the LMC, with half of their stars belonging to the bar. In our APOGEE sample, we have only a small fraction of stars that overlap spatially with the Van der Swaelmen et al., and likely have (relatively) very few bar stars. We further discuss the comparison of our APOGEE abundances of the LMC with literature values below in §6.2.
The abundances for Fornax from Hendricks et al. (2014) (shown in blue in Figure 13) have a plateau at slightly higher metallicity than that for the LMC. The APOGEE-2S Sagittarius (Sgr) abundances (shown as red open squared in Figure 13) exhibit sub-solar αabundances that have been interpreted as being due to a top-light IMF (Hasselquist et al. 2017 The LMC α abundance distribution shows a locus of stars with very small dispersion in α (∼0.03 dex at the metal-rich end). This indicates the high precision of the APOGEE-2S abundances. In addition, this indicates the homogeneous chemical evolution of the LMC as we sample stars across a large fraction of the galaxy. However, at the metal-rich end ([Fe/H]> −1.5) there is a small fraction of stars (∼53) with high α abundances, enhanced by ∼0.2 dex relative to the bulk of the LMC stars, somewhat similar to metal-poor MW stars. We have inspected the kinematics of these stars carefully (see Fig. 14) and believe that they are bona fide LMC stars rather than metal-rich MW halo stars that contaminate the sample. Figure 14 shows the kinematics of these stars compared to the rest of the LMC stars and indicates that they are consistent with being members of the LMC. The abundances of these stars are not inconsistent with some of the Van der Swaelman et al. high-α stars. Their existence might indicate the presence of interesting star formation and chemical evolution processes. In particular, the recent results from Clarke et al. (2018) reproduce the MW α bimodality (for the first time) with a simulation that has clumpy star formation. The metal-rich, high-α LMC stars could potentially have been produced by similar clumpy star formation. Additionally, we see a rise in α abundance with metallicity in the LMC beginning at [Fe/H] = −1.0. This implies that after the turn on of Type Ia SNe in the LMC, which lowered the [α/Fe] abundance to near-solar at [Fe/H] = −1.5, the LMC may have experienced an increase in the number of Type II SNe that were able to enrich the ISM with α elements. An increase in the Type II SNe can be due to a star burst, where the LMC quickly begins to form stars at a much faster rate. We also observe a slight turnover in [α/Fe] at [Fe/H] ∼ −0.2, which could be a sign of the Type Ia SNe exploding from the stars formed at the beginning of the starburst, adding Fe to the ISM of the LMC at the exclusion of the α elements. We further explore this star burst scenario §6.3.
The SMC does not exhibit an increase of [α/Fe] with increasing [Fe/H] beyond the apparent knee position, but it does exhibit a flat pattern starting at [Fe/H] ∼ −1.5, with perhaps a slight decrease beginning at [Fe/H] ∼ −0.7. Flat α-element abundance patterns can also be indicative of a star burst, or series of star bursts, but these star bursts are not powerful enough to substantially enrich the gas already present in the α elements (e.g., Hendricks et al. 2014).
Finally, we note that our most metal-rich LMC stars are likely very young, blue loop stars. Figure 15 shows the CMD of all APOGEE-observed LMC stars (left panel). The inner fields (R<4.8 • ) are color-coded by [Fe/H] and shows that the most metal-rich stars are the bluest stars. This is counter-intuitive because metal-rich RGB stars are generally redder. The right panel shows [α/Fe]-[Fe/H] distribution of these stars (red) compared to that of the rest of the stars, and makes clear that they are the most metal-rich stars in the entire LMC sample. The properties of these stars are consistent with young and metal-rich blue loop stars that recently evolved off of the main-sequence and that are known to be present in the central regions of the LMC where active star formation is currently ongoing.

Comparison to Previous LMC Studies
Previous α-abundance studies of the LMC (e.g., Smith et al. 2000;Pompéia et al. 2008;Lapenna et al. 2012;Van der Swaelmen et al. 2013;Sakari et al. 2017) did not find the flat α-distribution or the metal-poor α-knee that we constrain in our APOGEE dataset. To further investigate this discrepancy we show in Figure 16 a comparison of the APOGEE LMC α abundances with those of Van der Swaelmen et al. (2013), in red open diamonds, and the LMC cluster abundances compiled by Sakari et al. (2017) in blue crosses. All of the abundances are consistent at the metal-rich end. In addition, the [Ca/Fe] abundances agree well between the three datasets. The APOGEE and Van der Swaelmen et al. [Mg/Fe] abundances agree within the scatter of each dataset, although the average trends are slightly different. The latter sample has no stars below [Fe/H]=−1.5 but there are metalpoor clusters that extend to [Fe/H]=−2.2 and they show an increase in α-abundance very similar to what is seen in the APOGEE data, although shifted slightly more metalrich. The [Si/Fe] abundances are the most disparate with the literature values being higher at the metal-poor end than for APOGEE. As we previously showed in Section 5, our [Si/Fe] abundances compare well to Carretta et al. (2009b) with no significant offsets seen at these metallicities (Fig. 9), but with the comparison to GALAH DR2 suggesting (Fig. 10) Figure 16 are qualitatively quite similar between the three datasets (although the APOGEE values are shifted slightly to more metal-poor end) suggesting that they are reliable.
Although APOGEE data sample more luminous (lower log g ) giants then the Van der Swaelmen et al. sample, the T eff -log g distributions overlap considerably for log g >0.7. We investigated whether the abundances of the most luminous giants could be systematically off by splitting the APOGEE sample at log g =0.7, but found only minor differences in the α-abundances of the two subsets at the metal-poor end. If anything, the less luminous giants (log g >0.7) were shifted slightly to the metalpoor end. Therefore, we suspect that the APOGEE abundances are not affected by our sampling higher up the giant branch.
Besides the effects described above, it's important to keep in mind some differences between the APOGEE and the Van der Swaelmen et al. samples. The APOGEE dataset is significantly larger (by ∼12×) and it has much more spatial coverage to larger radii, which allows us to detect more metal-poor stars. In addition, our parameter-level [α/Fe] abundances are very precise even down to S/N=40. The combination of these factors likely allows us to discern abundance features not previously seen by previous studies, especially at the metalpoor end.

Chemical Evolution Model
Using this large sample of MC stars with precise chemical abundances we can begin to detect signatures of their detailed chemical evolution and start to unravel their SFHs. To do so, we use chemical evolution models to assist in interpreting the LMC α-element abundance pattern. To produce the chemical evolution models used here, we use the flexCE 20 code (Andrews et al. 2017), which is a one-zone, open-box, chemical evolution modeling program, utilizing nucleosynthetic yields for corecollapse SNe from Chieffi & Limongi (2004) and Limongi & Chieffi (2006), Type Ia SNe from Iwamoto et al. (1999), and AGB stars from Karakas (2010). To match the observed chemical abundance patterns in the MCs the flexible chemical evolution modeling from flexCE allows us to vary several parameters pertaining to star formation, such as the initial gas mass, inflow rate and time dependence, the outflow mass-loading parameter (η), and SFE. Because the present SMC sample is limited to relatively lower S/N, we focus here on the chemical evolution modeling of the LMC and leave the SMC for future work when the continuing APOGEE-2S observations improve the S/N of the SMC stars.
Fiducial chemical evolution models with parameters like SFE that are constant over time typically have difficulty in fitting the flat or increasing α-element abundance patterns over ∼1 dex in metallicity, as seen in the LMC at metallicities [Fe/H] −1.5. So we first attempt to generate models that can match the LMC [α/Fe]-[Fe/H] abundance pattern at lower metallicities, from −2.5 < [Fe/H] < −1.2. The parameters we adopt for the chemical evolution models that are held constant are: • Initial gas mass, M gas, i = 2 × 10 9 M ; • Inflow rate according to a delayed tau model (t e −t/τ ), with a mass normalization of M 1 = 6 × 10 10 M , and an inflow time scale of τ 1 = 2 Gyr; • Outflow mass-loading factor η = 10; • Fiducial IMF (Kroupa;Kroupa 2001)  This initial mass and mass normalization is about onetenth (modified slightly to alter the ratio of initial gas mass to the inflow mass) of the fiducial model parameters used by Andrews et al. (2017) to model the MW. We use a delayed tau model for its exponential decline in inflow rate at late times, but does not turn on inflow immediately and reaches a maximum later and is motivated by cosmological hydrodynamical simulations (Simha et al. 2014, although as found by this study and discussed below, this inflow rate with a constant SFE cannot alone reproduce the necessary SFH of late star forming galaxies like the MCs). A shorter inflow timescale helps produce a slightly steeper [α/Fe] slope, but we do not use to short of a timescale so that the peak inflow happens after a few billion years. We use a outflow mass loading factor of 10, which also steepens the [α/Fe] slope and is roughly consistent with values found in simulations showing that MW mass galaxies have η of order unity, whearas SMCmass galaxies have η ∼ 10−20 (e.g., Hopkins et al. 2013). We then alter the remaining parameter, the SFE, to generate a series of models whose SFE varies from 0.005 Gyr −1 to 0.03 Gyr −1 , as shown in Figure 17. Comparing to the observed abundance trend in the LMC, we find that the model with SFE = 0.01 Gyr −1 returns the lowest χ 2 for the data in the range −2.5 < [Fe/H] < −1.2.
Despite the fit to the metal-poor stars, most of these models barely enrich to [Fe/H] ∼ −1.0, and none reproduce the flat or increasing α-element abundance pattern seen in the LMC at higher metallicities. An increasing αelement abundance pattern at these metallicities is, however, not entirely unexpected. Bekki & Tsujimoto (2012) modeled the LMC α-element abundance patterns using a variety of SFHs, including models where the LMC underwent a burst of SFH starting about 2 Gyr ago, which produces a bump in [Mg/Fe] ratios as a function of metallicity owing to an increased contribution of core-collapse SNe for a relatively short duration that gives way once again to a dominating Fe contribution from Type Ia SNe.  Figure 18. Comparison of our best-fitting galactic one-zone chemical "starburst" evolution model with a recent starburst. (Top) The α abundances for the LMC (black dots) with a trendline (gray) and chemical evolution model (red). (Middle) The metallicity distribution function of the data (black) and model (red). The model matches the shape of the data well but is slightly too metal-poor by−0.15 dex. (Bottom) The star formation history of the chemical evolution model indicating the rapid increase in the star formation rate from ∼0.24×10 −10 M yr −1 pc −2 for the first ∼10 Gyr to 2.1×10 −10 M yr −1 pc −2 (an increase of ∼8.75×) at the peak of the "starburst" over the last couple Gyrs.
jimoto (2012) were not entirely conclusive that this was the best SFH model, they were consistent with producing MW 6x10 10 LMC 2e10 9 SMC 5x10 8 Sgr 2x10 6 (4x10 8 ) For 2x10 7 Scl 2x10 6 Figure 19. A comparison of the α-element abundance patterns of various Local Group galaxies. The MW, LMC, SMC and Sgr trendlines come from APOGEE-2S data while that for Fornax is from Hendricks et al. (2014) and that for Sculptor is from (Kirby et al. 2010 To modify our best-fit model in flexCE to simulate a starburst in the LMC's chemical evolution history, we alter the SFE to be time dependent, allowing for bursts of star formation that could be triggered by events such as interactions with the SMC, without requiring an infall of gas (which could also be triggered by an interaction with the SMC). We model a burst or increase in star formation by adding a Gaussian shaped increase in SFE on top of the constant SFE already in the models (see bottom panel of Fig. 18). By varying the time of the burst, its duration, and its strength, we find that we can not only reach higher metallicities than constant SFE models, but can also produce the increase and subsequent decrease in [α/Fe] seen in the abundance pattern of the LMC at metallicities [Fe/H] −1.0. Our best burst model, shown in Figure 18, uses essentially the same parameters as the best-fit model to the metal-poor end of the LMC abundance distribution given above except with a slightly modified base SFE i = 0.0125 Gyr −1 that later undergoes an increase following a Gaussian form with a duration of σ τ = 1.5 Gyr, peaking at µ τ = 15.25 Gyr with a 6× increase in SFE (i.e., SFE peak = 0.35 Gyr −1 ). Because the peak of the SFE is outside the model run time of 13 Gyr, the actual peak SFR occurs around 12.25 Gyr because the gas available for star formation depletes more rapidly during the starburst.
Altogether, this best model produces a SFH with a low and slow SFR for the majority of LMC's history, which produces the low metallicity end of the LMC's chemical abundance patterns, which is kickstarted within the past 2-3 Gyr with a recent burst of star formation producing the high metallicity population of the LMC. Looking at the α-element abundance pattern of our burst model, we can see that the model passes through the low-metallicity end of the LMC abundance distribution, although there is a large scatter that is likely due to a combination of higher uncertainties in metal-poor stars and their intrinsic scatter. This model also reproduces the rise and slight turnover seen in the [α/Fe] ratio at metallicities [Fe/H] −1 that were difficult to reproduce with constant SFE models. By binning the model in metallicity and normalizing by the surviving population of stars at each time step, we can also compare the expected metallicity distribution function (MDF) of the chemical evolution model to the observed MDF (normalized by the number of stars in our LMC sample with S/N > 50). In general, the shape of the model MDF is similar to the observed MDF, although it is shifted to lower metallicities by ∼0.15 dex. This shift could suggest that a chemical evolution model with a slightly higher base SFE may be more appropriate, although higher SFEs were slightly less preferred when fitting the LMC abundance profiles.
Qualitatively, this old and slow SFH with a recent burst in the past few Gyr is similar to the SFH's found by photometric studies (e.g., Meschin et al. 2014). However, the presence of stars with low α-element abundances even at metallicities of [Fe/H] ∼ −1.5 and an increasing [α/Fe] abundance pattern with decreasing metallicity seem to imply a relatively slower early SFH than found by the photometric studies, which are more limited in their metallicity discrimination. However, this discrepancy should be revisited when more metal-poor stars are included in LMC chemical evolution analyses. Regardless of the specific SFE at low metallicities, the fact that metallicities above [Fe/H] ∼ −1 in the model are produced within the burst of star formation within the last 2-3 Gyr of the model, implies that the majority of stars we have observed in the LMC using APOGEE have been formed within the past 2-3 Gyr. While an age analysis is beyond the scope of this paper, we do find that the most metal-rich stars in our sample are likely blue loop stars as shown in Figure 15. If so, this would imply that their masses are ∼ 3 M , which supports that the metal-rich stars are rather young.

DISCUSSION
Compared to many other MW dwarf galaxies, the αknees of the MCs (as measured by APOGEE) are more metal-poor. This is shown in Figure 19 where we compare the [α/Fe]-[Fe/H] trendlines of other galaxies in the literature to our MC trendlines. We do not actually measure the metal-poor knee in Sgr but other studies have measured the knee at [Fe/H]≈ −1.3 (e.g., de Boer et al. 2014). We find that the LMC knee is almost as metalpoor as that of Sculptor, but the LMC is a factor of ∼1000 more massive in stellar mass.
There is some discussion in the literature that the position of the knee correlates with the mass of the galaxy. This was summarized in Hendricks et al. (2014), and they found that Fornax potentially had a knee position that was too metal-poor for its mass. In Figure 20 we replicate the knee [Fe/H]-M v plot from Hendricks et al., adding to it our measurements for the MCs. We find that the MCs fall way off this trend, having knee positions that are uncharacteristically metal-poor for their luminosities.
So why are the MCs so "lazy" early-on in their evolution? One major difference between the MCs and the rest of the dwarf galaxies in Figure 20 is the environment in which they formed and evolved. The MCs are likely falling into the MW gravitational potential well for the first time (e.g., Besla et al. 2007Besla et al. , 2012, and have presumably been forming stars in isolation for roughly 10 Gyr. If the other galaxies with more metal-rich αelement knees fell into the MW potential well early on in their formation, it is possible they have artificially high SFE from tidal interactions with the MW and/or experienced enhanced star formation during ram pressure stripping. Gallart et al. (2015) derived precise star formation histories from deep HST imaging of LG dwarf galaxies and found that the early star formation rate of the dwarf galaxies depended on the density of their environment with "slow" dwarfs forming in relatively isolated regions. In this context, the slow early star formation of the MCs adds even more support to the hypothesis that the MCs fell into the MW potential only recently.
However, as discussed in §6.3, it is not possible for the LMC to enrich its gas to the level seen today with the SFE responsible for the metal-poor knee. We argue that the observed bump in [α/Fe] is indicative of a large star burst some 2-3 Gyr ago (e.g., Harris & Zaritsky 2009), which is then responsible for enriching the galaxy from [Fe/H] = −1.0 to [Fe/H]≈0.0. Without the recent starburst, likely created by a close interaction with the SMC (e.g., Harris & Zaritsky 2009;Besla et al. 2012), the LMC chemical abundances patterns and MDF would be substantially different than we see today. While we do not observe increasing [α/Fe] with increasing [Fe/H] beyond the knee in any of the other galaxies, we do observe a flat [α/Fe] with increasing [Fe/H] for the SMC, Sgr, and Fornax (from Hendricks et al. 2014). A flat [α/Fe] abundance pattern can be produced with a weak star burst (or star bursts), that enrich the ISM with metals, but are weak enough such that there is no substantial [α/Fe] enhancement. Hendricks et al. (2014) found that they were able to recreate the Fornax α-element abundance patterns by using a chemical evolution model with three distinct star bursts that varied in SFE, but were all more efficient than the initial star burst. There is a thread of work in the literature that finds evidence for a recent merger in Fornax from spatial and kinematical substructure (e.g., Coleman et al. 2004;Yozin & Bekki 2012;del Pino et al. 2015), which could be responsible for causing these starbursts. In the case of the MCs, the starbursts were likely spurned by a close interaction between the MCs some 2-3 Gyr ago. Evidence for such an interaction is motivated by cotemporal starbursts, dynamical simulations, and studies of Magellanic stellar substructures (e.g., Harris & Zaritsky 2009;Besla et al. 2012Besla et al. , 2016Choi et al. 2018a,b;Belokurov et al. 2018).

SUMMARY
We have obtained 3800 high-resolution H-band spectra of stars in the Large and Small Magellanic Clouds (MCs) using the new southern APOGEE instrument on the du Pont telescope at Las Campanas Observatory. This sizable stellar sample covers a large radial and azimuthal range of the MCs. The stars cover a large metallicity range (−2.5<[Fe/H]< −0.2) and the α distributions reveal important insights into the chemical evolution of the MCs, among them: Our main conclusions are: 2. There is an increase of ∼0.1 dex in [α/Fe] at the metal-rich end with a small decrease for the youngest and most metal-rich LMC stars. This behavior can be explained by a recent increase in star formation activity in the MCs. Our one-zone chemical evolution models are able to reproduce this αabundance "bump" with such a recent starburst. This feature in the star formation history is vital to reproducing the bump and metal-rich distribution of the MCs.
3. We constrain the position of the "α-knee" to be at [Fe/H] −2.2 for both the LMC and the SMC. Chemical evolution models fitted to the abundances of the metal-poor stars in the LMC find a low star formation efficiency of ≈0.01 Gyr −1 with a gas consumption timescale of ≈100 Gyr.