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Appendix A: Effect of metallicity assumptions on SED-fitting results

Appendix A.1: Metallicity as a free parameter

Fig. A.1 Comparison between best-fit SFR, E(B − V), and age from SED-fitting at fixed metallicity (Sect. 3) and those obtained when leaving metallicity as a free parameter. Only three objects are fitted at the right metallicity (black crosses). Ten objects are found to have an incorrect best-fit Z = Z⊙ (red), one object (green) is fit at a metallicity lower than the real one. Above each panel is the average discrepancy between the results of the two SED-fitting runs considering the whole sample (black) and the objects with Z = Z⊙ SEDs in the free metallicity run (red).

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We can exploit our sample of galaxies with measured metallicities to assess the capability of SED-fitting procedure in recovering the correct metallicity of high-redshift galaxies. We performed the fits with different SFHs and with/without nebular contribution as described in Sect. 3, but leaving metallicity as a free parameter. We found that 11 out of 14 objects are found to have an incorrect best-fit Z/Z_⊙, with seven of them being fit to Z = Z_⊙ templates and only one of them being fit at a metallicity lower than the real one. In addition, six of the sources do not have any model with the correct metallicity within a 68% confidence level from the best-fit one. In Fig. A.1 we show a comparison between the resulting best-fit age, SFR, and E(B − V) and the corresponding values found for the SED-fitting at fixed metallicity. When metallicity is not fixed we find on average lower SFRs and extinction, and larger ages. The discrepancy is higher for the objects having solar metallicity templates as best-fit. The results of this test qualitatively agree with the comparison between UV-based conversion equations and SED-fitting discussed in Sect. 3.1. However, several differences remain between SED-fitting and simplified conversion equations: the variety of SFHs used, the inclusion of nebular emissions, and the adoptedstellar population library. These differences do not allow for a straightforward comparison between this blind SED-fitting and the discussion presented in the previrous sections. This test shows that leaving metallicity as a free parameter can yield to large systematic effects in the analysis of subsolar metallicity objects.

Appendix A.2: Interpolation at the measured metallicity

Fig. A.2 Comparison between SED-fitting and UV-based extinction and SFR estimates as in Fig. 1 (stellar templates, left panels) and Fig. 2 (stellar+nebular, right panels). Each of the objects has been fitted using a customised set of templates built by linearly interpolating the available BC03 templates at its measured metallicity. For comparison, metallicities used for the results presented in Figs. 1 and 2 are indicated by different symbols (see insert in lower panels). The only significant discrepancies are found for object ID = 12341 (magenta cross).

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In principle, a thorough evaulation of the effect of metallicity on SED-fitting results requires a finer metallicity sampling than the one available in BC03. However, a finer sampling can only be based on a full treatment of the stellar models (spectra and isochrones) at each metallicity value in order to appropriately capture the contribution to the integrated SED coming from stars at different evolutionary stages. We test here the stability of the results presented in this paper through an alternative approach; namely we fit each of the objects using a customised set of templates built by linearly interpolating the available BC03 ones at its measured metallicity. As for the analysis presented in Sect. 3, we performed the SED-fitting separately for each of the adopted SFHs, both including and excluding nebular emission.

In Fig. A.2 we show, as a function of the best-fit age, the ΔE(B − V) and SFR_fit/SFR_UV99 obtained using stellar (left panels) and stellar+nebular (right panels) libraries interpolated at the measured metallicity on an object-by-object basis. The discrepancies between SED-fitting and UV-based (M99+Ma98) SFR and E(B − V) estimates are evident and are comparable to the results shown in Fig. 1 (stellar models at the nearest BC03 metallicity) and Fig. 2 (stellar+nebular).

A check on the SED-fitting results for each of the objects in the sample shows that the only significant discrepancy is found for object ID = 12341 (indicated by a magenta cross in Fig. A.2), which in the customised fit is found to have lower extinction

and SFR, and larger age. The interpretation of this discrepancy is not straightforward given the difference between the two approaches and the potential drawbacks of a linear interpolation between integrated SEDs. Nonetheless, this test demonstrates that the results discussed in the paper do not radically change when adopting a different scheme to assign subsolar metallicity templates to the objects in our sample.

Appendix B: Spectral energy distributions

We present here the spectral energy distributions of the 14 objects analysed in the paper determined considering four different analytical SFHs, and both including and excluding nebular emission (Sect. 3). In Fig. B.1 all models with P(χ²) > 32% from the best fit are shown either as light grey (models with stellar emission only) or dark grey (stellar+nebular models) curves. The best-fit UV slope is shown as a blue dashed line.

	Fig. B.1 Spectral-energy distributions of the 14 objects analysed in this paper. Light (dark) grey curves in each plot show models with P(χ2) > 32% from the best fit, considering four different SFH and fits with stellar (stellar+nebular) emission (see Sect. 3). The best-fit UV slope is shown as a blue dashed line. The bands that are not used in the SED-fitting are shown in red.
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	Fig. B.1 continued.
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