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The iron abundance of the Magellanic Bridge

High-resolution HST ultra-violet spectra for five B-type stars in the Magellanic Bridge and in the Large and Small Magellanic Clouds have been analysed to estimate their iron abundances. Those for the Clouds are lower than estimates obtained from late-type stars or the optical lines in B-type stars by approximately 0.5 dex. This may be due to systematic errors possibly arising from non-LTE effects or from errors in the atomic data as similar low Fe abundances having previously been reported from the analysis of the ultra-violet spectra of Galactic early-type stars. The iron abundance estimates for all three Bridge targets appear to be significantly lower than those found for the SMC and LMC by approximately -0.5 dex and -0.8 dex respectively and these differential results should not be affected by any systematic errors present in the absolute abundance estimates. These differential iron abundance estimates are consistent with the underabundances for C, N, O, Mg and Si of approximately -1.1 dex relative to our Galaxy previously found in our Bridge targets. The implications of these very low metal abundances for the Magellanic Bridge are discussed in terms of metal deficient material being stripped from the SMC.

As H I emission and stellar condensation are strongly correlated, it is natural to suppose that star-formation may take place in these regions. Additionally, molecular clouds have been identified in the Magellanic Bridge from CO emission (Mizuno et al. 2006), which given the short lifetimes of such clouds were probably formed after the tidal encounter. Attempts to find a stellar population associated with the Stream have been largely unsuccessful (Irwin 1991). By contrast, young stellar associations have been identified in the Bridge (Irwin et al. 1985;1990;Bica and Schmitt 1995) and may reflect an episode of star formation triggered by the close encounter of the two Clouds.
The chemical composition of both the SMC and LMC have been extensively studied using both stellar targets and emission nebulae. For example the spectra of early-type stars have been used, viz, O-type supergiants (Crowther et al. 2003;Hillier et al. 2003), O-type main sequence targets , B-type supergiants Dufton et al. 2004), B-type giants (Korn et al. 2000;Lennon et al. 1999) B-type main sequence stars (Korn et al. 2002;, Hunter et al. 20042007) and A-type supergiants (Venn 2000;Venn & Pryzbilla 2003). Late-type stellar investigations have included FG-type supergiants (Russell & Dopita 1992;Spite et al. 1989;Hill et al. 1995;Andrievsky et al. 2001), Cepheids (Luck et al. 1998) and K-type supergiants (Barbuy et al. 1991;Hill 1997;1999;Gonzalez & Wallerstein 1999). Additionally there have been many H II region studies (see, for example, Kurt et al. 1999;Peimbert et al. 2000;Testor 2001;Tsamis et al. 2003). In general terms, these imply that the LMC and SMC are underabundant in metals (compared with our Galaxy) by approximately -0.3 and -0.6 dex, with nitrogen showing a greater underabundance particularly for unevolved stellar targets and H II regions.
The chemical composition of the Magellanic Bridge is more uncertain. Hambly et al. (1994) obtained optical spectra for two early-type stars (DI 1194 andDI 1388) in order to investigate whether their chemical compositions reflected those of the LMC or SMC. However, it was only possible to make marginal identifications of a few metal lines, and these implied large but uncertain metal depletions. Rolleston et al. (1999) analysed high and medium resolution spectroscopy of three other B-type bridge stars. They found an underabundance in the light metals (C, N, O, Mg, Si) of approximately -1.1 dex compared with our Galaxy. Additionally they undertook a differential analysis relative to the SMC B-type main sequence star, AV 304, and found the Bridge material to be relatively underabundant in metals by -0.6 dex. Unfortunately no iron features were observed in these optical spectra thereby preventing an abundance determination for this element. Lehner et al. (2001) have studied the interstellar ultraviolet absorption and H I emission spectra towards a young star in the Bridge. These observations also were consistent with a low metallicity (≃ −1.1 dex) compared to that of our Galaxy. Recently Lee et al. (2005) studied B-type targets in the SMC south east wing which adjoins the Bridge. These were found to have a normal SMC chemical composition, although a re-analysis of the extant Bridge observational using sophisticated non-LTE techniques confirmed the very low metal abundances found previously by Rolleston et al. The low metal abundance deduced for the Bridge material is surprising as one would expect its metallicity to reflect that of its progenitor material. A possible explanation is that the inter-cloud material could have been stripped off from either of the galaxies at a much earlier encounter (about ∼8 Gyr ago; Kobulnicky & Skillman 1997;Da Costa & Hatzidimitriou 1998), when less nucleosynthetic processing of interstellar medium of the SMC had occurred. However, this is inconsistent with the numerical simulations of, for example, Murai and Fujimoto (1980) and Gardiner and Noguchi (1996) that imply that the Magellanic Bridge was formed relatively recently and also with the presence of early-type stars, implying recent star formation.
Here we present and analyse Hubble Space Telescope (HST) ultra-violet spectroscopy of three Bridge B-type stars, together with similar targets in the SMC and LMC. The observational data cover the wavelength range between approximately 1900 to 2000Å, where the spectrum is dominated by absorption lines due to iron group elements. Hence the principle aim of this analysis is to investigate whether the very low light metal abundances inferred for the Bridge material is replicated in the heavier metals.

OBSERVATIONS AND DATA REDUCTION
HST spectroscopy of the Magellanic Bridge stars have been obtained during two campaigns that utilised the GHRS and the STIS spectrographs. The former obtained spectroscopy of a Bridge target, DI 1388, in the wavelength range 1888-1930Å with a spectral resolution of approximately 14 km s −1 whilst the latter observed two Bridge targets and the LMC star, LH 10-3270 between 1888 and 1970Å with a spectral resolution of approximately 15 km s −1 .
These observations were supplemented with archive STIS observations of the SMC star, AV 304, that had the same wavelength region and spectral resolution. The observational data are summarized in Table 1 with the V-magnitudes and spectral types being taken from Azzopardi et al. (1975), Grondin et al. (1990), , , Parker et al. (1992), Garmany et al. (1987) and Rolleston et al. (1999).
For the STIS observations, multiple exposures each of approximately 3000 seconds were obtained. These were combined using the SCOMBINE procedure in IRAF, with tests indicating that the actual choice of parameters was not critical. Both the combined STIS and the GHRS spectra were input into the data reduction package DIPSO ) and cross-correlated with theoretical spectra (see Sect. 3 for details) to obtain the stellar radial velocity. These are also listed in Table 1 and are in good agreement with those found previously (Hambly et al. 1994;Rolleston et al. 2003), apart from the LMC target, LH 10-3270. Previously Rolleston et al. (2002) had found a value of 197 km s −1 , which is smaller than the mean LMC radial velocity of 261km s −1 (Luks & Rohlfs (1992) and the estimate of approximately 310 km s −1 found here. Hence this star may be a single lined spectroscopic binary. The spectra were corrected for these radial velocity shifts prior to further analysis.
It was difficult to estimate signal-to-noise (S/N) ratios due the rich aborption line spectra. We have used synthetic and the relatively narrow lined observational spectrum of AV 304 to aid the identification of suitable regions and these have been fitted by low order polynomials to yield the S/N ratios listed in Table 1. Given that as it was effectively impossible to identify true continuum regions, these values should be considered as lower limits. These estimates can be compared with those from the STIS and GHRS Exposure Time calculators which predicted S/N ratios of 25 for AV 304 and 30 for all the other targets. These predicted values are very sensitive to the adopted reddennings, which may partially explain the differences with those listed in Table 1.

DATA ANALYSIS
The analysis is based on grids of non-LTE model atmospheres that have been calculated using the codes TLUSTY and SYNSPEC (Hubeny 1988;Hubeny & Lanz 1995;Hubeny et al. 1998). Details of the methods can be found in Ryans et al. (2003), while the grids have been discussed in more detail by Dufton et al. (2004).
Briefly four grids have been generated with base metallicities corresponding to our galaxy ([ F e H ] = 7.5 dex) and with metallicities reduced by 0.3, 0.6 and 1.1 dex. These lower metallicities were chosen so as to be representative of the LMC, SMC and Bridge material. For each base metallicity, models have been calculated covering a range of effective temperature from 12 000 to 35 000 K in steps of 1000K or less and logarithmic gravities (in cm s −2 ) from 4.5 dex down to close to the Eddington limit (which will depend on the effective temperature) in steps of 0.25 dex. For each pair of effective temperatures and surface gravities, five models with microturbulences (ξt) of 0, 5, 10, 20 and 30 km s −1 were generated.
Atmospheric parameters (summarized in Table 2) for all our targets have been previously estimated from optical spectra by Rolleston et al. (1999) for the Bridge stars, Rolleston et al. (2002) for LH 10-3270 and Hunter et al. (2004) for AV 304. The first two analyses used an LTE approach based on the model atmospheres of Kurucz (1991), whilst the last was based on the non-LTE grid utilised here. However atmospheric parameters for AV 304 esti- Using a grid model with an appropriate metallicity and atmospheric parameters closest to the values listed in Table 2, we have synthesised the spectral region observed by HST for each star. As the spacing between grids points is smaller than the typical uncertainties in estimating atmospheric parameters, the adoption of the nearest grid point is unlikely to be a significant source of error. For elements (carbon, nitrogen, oxygen, magnesium and silicon) explicity included in the TLUSTY calculation, these calculations were in a non-LTE approximation. Iron was also included in the model atmosphere calculations but due to the complexity of its Grotrian diagram, individual levels were combined together into superlevels. Hence for the spectral synthesis, iron and all other elements were treated in LTE. Test calculation showed that typically 80% of the absorption in this spectral region arose from iron with over 95% being due to iron group elements -hence these are effectively LTE calculations. To fit an observed spectrum, calculations were undertaken for the set of element abundances adopted for a particular grid (see Dufton et al. 2004 for details) and with all these abundances scaled. The actual element abundances for any given star may not vary in step but as iron dominates the absorption, any differential variations in element abundances should not significantly affect these theoretical spectra.
This approach has the consequence of introducing an inconsistency between the abundances adopted in the model atmosphere and spectrum synthesis calculations. For example, for the star, AV 304, a model would be adopted from the grid with a metallicity appropriate to the SMC viz. -0.6 dex that of the Galaxy. Spectra would then be synthesised for different metallicities which might range, for example, from the Galactic composition to -1.2 dex of the Galactic composition. We have investigated the consequences of this simplification as folows. Firstly we calculated the spec-trum for an SMC model of AV 304 with atmospheric parameters, T eff =27 500, log g=3.9, ξt=5 km s −1 and with a metallicity -0.6 dex that of the Galaxy. Then we used the Galactic model with the same atmospheric parameters but scaled the metallicity in the SYNPLOT spectrum synthesis calculation in order to mimic that of the SMC. The resulting spectra were very similar with the summed equivalent widths differing by 3%. Hence we do not expect that this simplification (that has been widely used elsewhere -see, for example Kilian et al. 1994, Korn et al. 2000, will be a source of significant uncertainty. However it is possible that this approach could lead to uncertainties that depended on the wavelength region observed as the blanketing will depend on the iron abundance adopted. In turn this could affect the ionization structure and thereby the behaviour of absorption lines formed in different parts of the stellar atmosphere. As discussed in Sect. 2, it is difficult to distinguish continuum regions due to the richness of the ultra-violet absorption line spectrum. Hence we have not attempted any continuum normalisation but have instead worked directly with the flux calibrated spectra. For the observed spectra, we must first correct for the effect of interstellar extinction. We adopted values of the colour excess (summarized in Table 1) for the Bridge targets from Demers & Battinelli (1998), for LH 10-3270 from Parker et al. (1992) and for AV 304 from Azzopardi & Vigneau (1982). There is evidence that the extinction law for the Magellanic Clouds may differ from that for the Galaxy (see, for example, Seaton 1979, Howarth 1983). However given the low reddenings of our targets the use of different laws was found to have only a small effect on the absolute fluxes deduced. More importantly, because of the limited coverage of the observed spectra, the relative flux distributions, which are important for our methodology as discussed below, remain effectively unchanged when corrected for extinction. Hence uncertainties in these corrections are unlikely to seriously affect our analysis. We then rebinned our unreddened spectra to a wavelength interval of 0.1Å and to a wavelength range of 1890-1970Å for the STIS spectra and 1890-1928Å for the GHRS spectra.
To compare our observed and theoretical spectra, we adopted the following methodology. The theoretical spectra were first convolved with a Gaussian broadening function to allow for intrumental broadening and with a rotational broadening function with the projected rotational velocities, v sin i, being summarized in Table 2. These were taken from Hambly et al. (1994) for DI 1388, Rolleston et al. (1999) for DI 1239 and DGIK 975, Rolleston et al. (2002) for LH 10-3270 and Rolleston et al. (2003) for AV 304. Recent studies (see, for example, Dufton et al. 2006, Simón-Díaz andHerrero 2007) have shown that macroturbulence can also be important in Btype supergiants. The estimated gravities of our targets imply that they are either near to the main sequence or giants and hence that macroturbulence will not be significant. Additionally we use these projected rotationally velocity estimates to allow for the overall broadening of the line spectra and to first order its physical origin is not important. The theoretical spectra were then rebinned to the same wavelength region and interval as those of the observed spectra and scaled so that they had the same mean flux as the observed spectra, thereby making the spectra comparable without any need for rectification or normalisation. The sum of the squares of the differences between observation and theory (S) was then computed and the metallicity varied until this was minimised. These metallicity estimates (designated as ∆[ F e H ] because our ultra-violet spectra are dominated by iron group absoption lines) are summarized in Table 3.
This approach is illustrated in Figs. 1 and 2 for the LMC target, LH 10-3270 and the Bridge target, DGIK 975 chosen to cover a range of metallicities and projected rotational velocities. In the former the observed and best fitting theoretical spectra are shown, whilst in the latter, the value of S is plotted against metallicity and minima are found at metallicities (relative to Galactic) of -0.9 and -1.7 dex respectively. In general the theoretical spectra reproduce that observed but agreement for specific features is variable. The absoption line spectrum for LH 10-3270 is relatively well observed due to both its low projected rotational velocity and the relatively high metallicity of the LMC. The theoretical spectrum is in excellent agreement with the majority of absorption features well matched. This in turn provides indirect support that our uniform scaling of all the individual element abundances is acceptable.
For DGIK 975, the situation is less satisfactory with the match to individual features being far less convincing, which may be manifested in the broad minimum found in the goodness-of-fit shown in Fig. 2. Given the better agreement found for LH 10-3270, we ascribe these problems principally to the observed absorption lines being intrinsically weak and broadened by the significant stellar rotation. However part of these discrepancies may also be due to a combination of inadequacies in the atomic data (and in particular the oscillator strengths) and the neglect of non-LTE effects for the species that dominate the absorption in this spectral region.
The spectra line data used in SYNSPEC is mainly taken from the linelists of Kurucz (see, for example, 1988;. These have been updated using more recent results taken from the NIST database as discussed in for example 2007), with further information being available from the TLUSTY/SYNSPEC webpage. All the energy levels are experimental and as such the corresponding wavelengths of the transistions should be reliable. This was confirmed by comparing the our wavelengths for a sample of Fe III features with those determined experimentally (see, Sugar and Corliss, 1985 and references;Ekberg, 1993 therein) where discrepancies were typically less than 0.01Å. This would correspond to a velocity uncertainty of approximately 1 km s −1 , which is far smaller than the intrinsic width of the line due to the rotational broadening. Hence we do not believe that uncertainties in the wavelengths will be a significant source of error.
In the case of the oscillator strengths, a number of independent calculations exist apart from those of Kurucz (1991), including Toner and Hibbert (2005), Ekberg (1993), Fawcett (1989), Nahar and Pradhan (1996). Raassen and Uylings have also provided extensive listings via a web-site (http://www.science.uva.nl/pub/orth/iron/FeIII) as part of the FER-RUM consortium (Johansson et al., 2000). As discussed by Toner and Hibbert, discrepancies are typically 40%, which for a single feature would lead to an absolute abundance error of approximately 0.2 dex. However as discussed by Thompson et al. (2007), for the stronger lines the discrepancies are smaller, being typically 10% or less. Additionally as we fit a large number of features simultane-ously, the corresponding abundance error would be smaller if these discrepancies were random. The errors in differential abundances should also be smaller as errors due to uncertainties in the oscillator strengths should to first order cancel. As even for the best modern calculations, there remains differences between the theoretical oscillator strength estimates and as these new results cover only a subset of the lines incorporated in our linelists, we have decided not to attempt to update our linelist. Given the above discussion the abundance estimates (listed in Table 3) must be treated with caution. However variations in these estimates should be more reliable as they are based on a consistent and objective approach.
The above methodology implicitly assumes that the flux calibration of the observed spectrum has been reliably performed. For example there could remain a low frequency ripple and to investigate the consequence of this we have artificially added a sine wave component with an amplitude of 1% and a period equal to the wavelength range of our data for the target, LH 3270. We then repeated the analysis and found the same abundance estimate (after rounding to the nearest 0.1 dex). Clearly larger errors would map onto larger uncertainities in the abundances but we would expect that any systematic errors in the calibration would similarly affect all our abundance estimates and hence relative values should be more reliable.
One significant discrepancy in the comparison shown in Fig. 1 is that the theoretical spectra predicts a relatively strong feature at approximately 1906.8Å. This is not apparant in the observed spectra for LH 3270 and also may be absent from that for DGIK 975 although in this case the comparison is complicated by the greater amount of rotational broadening and the intrinsic weakness of the spectrum. Investigation of the theoretical spectra indicates that this feature arises principally from an Fe III line, which has been incorporated with and oscillator strength 0.78. For this transition, Raassen and Uylings derive a smaller value of 0.41, which may at least partially account for the discrepancy. As a test, we have repeated the fitting procedure for LH10 3270 excluding this region. The goodness-of-fit was indistinquishable from that shown in Fig.  2 and lead to the same estimate of the iron abundance as listed in Table 3.
For DI 1388, the wavelength coverage of its GHRS spectrum is approximately half of that of the STIS observations and this leads to its metallicity estimate not being strictly comparable with those for the other targets. Additionally the S/N ratio of the GHRS spectrum is relatively low, whilst DI 1388 has the highest v sin i estimate. Hence the metallicity estimate for this star is particularly uncertain, although we note that from visual inspection the agreement between observation and theory appears poor for values of the metallicity, ∆[ F e H ] > −1.3 dex. Inspection of Table 2 indicates that the two SMC and LMC targets have smaller projected rotational velocities and hence their spectral lines will be narrower. In turn this could affect the comparison between iron abundances deduced in these targets and those in the Bridge. We have investigated this as follows. For these two targets we have rotationally broadened their observed spectra to a value of v sin i= 120 km s −1 , which is typical of that observed in our Bridge targets. We have then added additional Poisson noise to obtain a S/N ratio of 30 again typical of the Bridge targets. We have then repeated the analysis of these modified spectra to obtain estimates of the iron abundances. Although there are small changes in the position of the minimum obtained in the goodness-of-fit, after rounding the abundance estiamtes to the nearest 0.1 dex, we obtain the values listed in Table 3. Hence we do not believe that the differences in broadening in the observed spectra should affect es- Figure 1. Comparison of observed and theoretical spectra for two of our targets. The upper panel shows the observed (solid line) and the theoretical (dotted line) spectra for LH10 3270 and a metallicity of -0.9 dex (corresponding to the best fit between observation and theory) relative to that of the Galaxy. To aid comparison the theoretical spectrum has been shifted downwards on the y-axis. The lower panel shows the corresonding spectra for DGIK 975, a metallicity of -1.7 dex now being adopted for the theoretical calculations timates of the abundance differences between the Bridge and the Cloud targets.
We have estimated the uncertainties in our Fe abundance estimates arising from uncertainties in the adopted atmospheric parameters. We assumed errors of ±1 000 K in T eff , ±0.2 dex in log g and ±3 km s −1 in ξt, which is consistent with the error estimates discussed in the analyses summarized in Table 2. We have used a relatively simple procedure by first calculating the total equivalent width for the ultra-violet spectra region that we have analysed for our adopted stellar atmospheric parameters and our estimated iron abundances (see Tables 2 and 3 respectively). We then increased in turn each of the atmospheric parameters by its uncertainty and changed the iron abundance until we recovered the same total equivalent width. Tests comparing this methodology with that of changing each atmospheric parameter and then recalculating the goodness-of-fit between theory and observation for different Fe abundances showed that the two methods yielded similar error estimates. Our error estimates are summarized in Table 4, with values for a similar decrease in the atmospheric parameters being of similar magnitude but with an opposite sign. In general, the errors arising from uncertainties in the surface gravity appear not to be significant. Those for the microturbulence depend on the strength of the Fe absorption lines with those for the effective temperature depending on how far the effective temperature is from that (approximately 18 000 K) corresponding to the maximum in the strength of the Fe spectrum. Assuming that these errors are uncorrelated, they can be added in quadrature and these error estimates are shown the final column of the Table 4. Adopting different errors estimates for the atmospheric parameters or allowing for the correlation between the effective temperature and gravity estimates would lead to different estimates but we believe that a typical uncertainty of ±0.2 dex implied by Table 4 to be reasonable.
We have also attempted to use the value of the χ 2 associated with our comparison of the theoretical and observed spectra to estimate the uncertainty due for example to observational errors. As discussed by Avni (1976), a change of 1.0 and 2.7 in the χ 2 parameter should correspond to the 68 and 90% limits in our uncertainty. However utilisation of this procedure led to unrealistic small error estimates of less than 0.1 dex for both cases. This may reflect that some of our data points (e.g. those near the continuum) do not represent signal but tests attempting to exclude such regions again led to low error estimates. Additionally the small implied errors may be due to stochastic noise not being the dominant source of uncertainty. For example other systematic errors in the observational data or from the physical assumptions (including the adopted atomic data) may be significant. Moehler et al. (1998) in their analysis of the equivalent widths of individual iron features in the ultra-violet spectrum of PAGB stars estimated errors due to observational uncertainties of 0.05 to 0.1 dex. From inspection by eye of the quality of our fits for different Fe abundances an error of approximately ±0.2 dex would appear reasonable which is rather larger than the errors quoted by Moehler et al. (1998). However adopting a typical random error of ±0.2 dex and combining in quadrature with those due to uncertainties in the atmospheric parameters leads to an estimated error of typically ±0.3 dex. We note that this estimate does not include Table 3. Estimated iron abundances relative to that of our Galaxy (i.e. ∆[ F e H ] = 0 dex would correspond to a solar metallicity of 7.5 dex -Grevesse and Sauval 1998) for our targets deduced from the HST ultra-violet spectra. Mean light metal abundance estimates previously deduced for these targets (designated ∆[ X H ] -see text for details) are also summarized. Other estimates of the iron abundances for the LMC and SMC relative to our Galaxy are tabulated. These are from B-type supergiants by Trundle et al. (2007), A-type supergiants by Venn (2000), F-type supergiants by Andrievsky et al. (2001) and Hill (1997). The final column lists abundance studies of late-type stars, viz. Cepheids in the LMC (Luck et al. 1998) and K-type supergiants in the SMC (Gonzalez and Wallerstein 1999).

Star
Region Bridge -1.9 <-0.9 ---- Figure 2. Estimation of the metallicity for two of our targets. The upper panel shows the goodness-of-fit, S (with units of 10 −28 erg 2 cm −4 s −2Å−2 ) between the observed and theoretical spectra for LH10 3270 plotted against the metallicity adopted for the theoretical calculations. The lower panel shows the analagous results for DGIK 975 systematic errors from, for example, the assumption of local thermodynamic equilibrium in the radiative transfer calculetion and we return to this point in Sect. 4.

DISCUSSION
In Table 3, we also summarize for our targets, the mean differential abundance (designated ∆[ X H ]) for all reliably observed elements Table 4. Uncertainties in our estimated iron abundances due to uncertainties in the atmospheric parameters. For each star, the effective temperature, logarithmic gravity and microturbulence have been increased by 1 000 K, 0.2 dex and 3 km s −1 respectively and the change of iron abundance required to obtain the best agreement between theory and observation was estimated; see text for further details. Also shown is the estimated errors assuming that these errors can be added in quadrature. from carbon to sulphur with the exception of nitrogen. This is because analysis of H II region (see, for example, Kurt et al. 1999;Peimbert et al. 2000;Testor 2001;Tsamis et al. 2003) and stellar spectra (see, for example, Korn et al. 2002; indicate that nitrogen has anomalously low differential abundances in the Magellanic system. The sources of these light element abundances are: LH 10-3270 (Rolleston et al. 2002); AV 304 Hunter et al. 2004); DKIK 975 and DI 1239 (Rolleston et al. 1999) and DI 1388 (Hambly et al. 1994). In this Table, we also summarize iron abundances estimated for some representative analyses of other stellar targets: SMC and LMC B-type supergiants (Trundle et al. 2007); SMC A-type supergiants (Venn 2000); F-type supergiants (Andrievsky et al. 2001;Hill 1997); LMC Cepheids (Luck et al. 1998) and SMC K-type supergiants (Gonzalez & Wallerstein 1999). A comparison of our iron abundances deduced from ultraviolet spectra with those obtained for other stellar targets shows that the former are lower by 0.5-0.6 dex for both the SMC and LMC. This would appear to be the case even when we compare the analyses of isolated optical Fe III lines of B-type stars with our ultra-violet spectra (which are again dominated by Fe III lines), although unfortunately there are no stars in common between the analyses. Studies of the ultra-violet spectra of other hot stars have also found relatively low iron abundances, as discussed by Thompson et al. (2007). For example, Grigsby et al. (1998) analysed the iron lines between 1800 and 2500Å in the spectrum of the B3 V star ι Her. They found an underabundance of -0.47 dex relative to the sun assuming a zero microturbulence. As pointed out by Grib-sby et al., an increase in the microturbulence would decrease their estimates and hence the actual underabundance estimated from the ultra-violet spectrum could be larger. From their results, we can deduce an abundance estimate from the Fe III lines that lie in the wavelength region (1888 to 1978Å) that we have considered. This again implies that iron is underabundant by 0.4 dex or more (depending on the microturbulence adopted) compared with the solar value (Meyer 1985;Anders and Grevesse 1989;Grevesse and Sauval 1998). By contrast, analyses of the optical Fe III spectrum in ι Her (Kodeira and Scholz 1970;Peters and Aller 1970;Peters and Polidan 1985;Pintado and Adelman 1985) have led to values that are close to solar.

Star
Hot post-asymptotic-giant branch (PAGB) stars have also been found with relatively low iron abundances as discussed by Moehler (2001). Napiwotzki et al. (1994) analysed optical and ultra-violet spectra of the field star BD+33 • 2642 and found underabundances (relative to solar) of approximately 1.0 dex for C, N, O, Mg, Si but a larger underabundance of 2.0 dex for Fe. The latter was found from analysis of Fe III lines in the same spectral region as considered here. Napiwotzki et al. showed that such an abundance pattern could be understood by a seperation of gas and dust as proposed for cooler PAGB stars (see, for example, Mathis and Lamers 2002). Moehler et al. (1998) analysed ultra-violet and optical spectra of two PAGB stars, ROA 5701 and Barnard 29, in globular clusters with the main aim of determining their iron abundance. From the ultra-violet spectra, they determined iron abundances that for Barnard 29 was 0.5 dex lower than that found for the cooler giant stars in M 13 and for ROA 5701 was lower than the range of abundances found in ω Cen. Moehler et al. again interpreted these observations as due to a gas/dust separation in the atmospheres of the PAGB stars. Recently Thompson et al. (2007) have reanalysed the spectroscopy for these stars. From the ultraviolet spectra they find iron abundances using the spectra synthesis technique used here that are similar to those estimated by Moehler et al. However they also tentatively identified Fe III lines in their optical spectra. These implied higher iron abundances that agree well with those found from the red giants in M 13 and with the range of iron abundances found from the red giants in ω Cen (Origlia et al. 2003).
In summary analyses of the ultraviolet Fe III spectrum of Btype stars around 1900Å have consistently yielded relatively low iron abundances. For the highly evolved objects, this may reflect real physical effects but in others there appears to be differences between abundance estimates from the optical and ultra-violet spectra and for the younger massive stars inconsistencies with the iron abundance that would be expected. Indeed our results for the SMC and LMC targets and those discussed above for ι Her would imply that a systematic increase in the iron abundances deduced from the ultra-violet spectra of approximately 0.5 dex would appear appropriate. The cause of this systematic offset could be in the theoretical modelling and in particular in the use of an LTE approximation in the spectral synthesis or in the adopted oscillator strengths. Additionally if the ionic linelists are incomplete, the presence of a large number of weak unresolved lines would act as a pseudo-continuous opacity. In turn this could lead to the strengths of lines or blends in our theoretical spectra being too strong, thereby leading to our abundance estimates being too small.
Given the uncertainties, in the absolute iron abundances deduced from the HST spectra, we have instead chosen to take a differential approach. For example, we find a difference between in the iron abundance of our SMC and LMC target of -0.3 dex which is in excellent agreement with those found from the optical spectra of BAF-type and late-type stars in the Magellanic Clouds (see Ta-ble 3). More importantly all three Magellanic Bridge targets appear to have very low iron abundances and in particularly values that are lower than the SMC iron abundance by between -0.4 to -0.7 dex. These differences are larger than the error estimates discussed in Sect. 3 and although it is possible that these have been underestimated, the similarity in the iron underabundance found for all three Bridge targets is striking. Additionally as we have adopted a differential approach, any systematic errors should have been minimised.
Such an iron underabundance is consistent with those for the lighter metals (listed in Table 3) and with the analysis discussed in Rolleston et al. (1999) who estimated a mean light metal underabundance for the Bridge material of -0.60±0.18 dex with respect to the SMC. Additionally Lehner et al. (2001), from an analysis of the interstellar absorption lines seen in the spectra of a background object, also found evidence for low metal abundances in the Magellanic Bridge gas. Therefore in the discussion that follows, we will assume that the material in the Magellanic Bridge is underabundant in metals by factors of approximately -0.5 and -0.8 dex compared with the SMC and LMC respectively.
As discussed in the introduction, both observational (e.g. Irwin et al. 1985;1990;) and theoretical (e.g. Gardiner and Noguchi 1996;Sawa et al. 1999) studies imply that the Bridge was formed during a close encounter between the Magellanic Clouds approximately 200 million years ago. This scenario has been supported by more recent investigations, with for example Nishiyama et al. (2007) tentatively identifying pre-main sequence Herbig Ae/Be stars in the Magellanic Bridge. Additionally the recent photometric investigation of Harris (2007) failed to identify an older stellar population implying that the material stripped from the Magellanic Clouds was effectively a pure gas.
Of particular relevance to the metal abundances found in the Magellanic Bridge are the recent numerical simulations of Bekki and Chiba (2005;2007). These follow the evolution and star formation history of the Magellanic System over the last 800 million years using chemodynamical simulations with both Clouds being modeled as self-gravitating barred and disk systems. A mean metal abundance for the Bridge (relative to our Galaxy) of -0.8 dex is predicted, compared with -0.6 dex adopted for the cental regions of the SMC. This underabundance arises from the Bridge material primarily originating from the outer regions of the SMC with the simulations incorporating a negative metallicity gradient. As pointed out by Bekki and Chiba (2007), this is qualitatively consistent with the Bridge light element underabundances found by Rolleston et al. (1999) and summarized in Table 3. However as for our iron abundance estimates of the three bridge stars, there remains a significant quantitative discrepancy of approximately 0.3 dex. Bekki and Chiba (2007) predicted a range of metallicity in Bridge stars with a mean value of -0.8 dex but with approximately three percent of stars having values −0.9 dex. Our three targets are spatially well separated across the Magellanic Bridge (see Figure 3 of Rolleston et al. 1999) and hence it would be highly improbable that they could all be from the lower metallicity part of this distribution. We therefore conclude that a plausible explanation for the very low light metal and iron abundances found in the Magellanic Bridge is that the corresponding material was stripped from the outer regions of the SMC approximately 200 million years ago. However observational abundance estimates and theoretical predictions still differ by 0.3 dex.

CONCLUSIONS
We have presented HST ultra-violet spectroscopy of five targets in the Magellanic Clouds and Bridge. These data have been analysed using grids of non-LTE models atmospheres with the spectral synthesis being predominantly undertaken in an LTE approximation to deduce metallicities (which will be dominated by the iron abundances). The principal results can be summarized as follows: (i) Iron abundances estimated from the ultra-violet spectra of SMC and LMC targets are typically -0.5 dex lower than those derived by other methods. This is consistent with results found from previous studies of Galactic objects.
(ii) The iron abundance estimates for the three bridge targets are -0.5 and -0.8 dex lower than those for the SMC and LMC respectively. This is consistent with the underabundance in light metals of -1.1 dex found for the Bridge material with respect to our Galaxy.
(iii) These metal abundances are in qualitative agreement with numerical simulations which imply that most of the Bridge material has been stripped from the outer layers of the SMC. However there remain significant quantitative differences between the observed estimates and those predicted by the simulations.