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Erratum
This article is an erratum for:
[https://doi.org/10.1051/0004-6361/201321602]

Issue
A&A
Volume 573, January 2015
Article Number C1
Number of page(s) 3
Section Extragalactic astronomy
DOI https://doi.org/10.1051/0004-6361/201321602e
Published online 23 December 2014

Erratum for: A&A 557, A95 (2013), DOI: 10.1051/0004-6361/201321602

1. Introduction

We present here the corrected results for the dust-to-stellar mass ratios versus metallicity for the two Herschel samples, the DGS and KINGFISH samples, after finding an error in the stellar masses for the DGS galaxies. We present corrected PACS upper limits for three galaxies and the correct value of the FIR luminosity of SBS0335-052. We also computed the stellar masses for KINGFISH using the same formula as for the DGS and look at β = 2.0 modified blackbody dust masses to see how this influences the new derived relation between dust-to-stellar mass ratios and metallicity. We find that when the stellar masses are consistently estimated for both samples, the observed correlation between the dust-to-stellar mass ratios and metallicity is partly due to the choice of leaving the emissivity index free in the modified blackbody fits. Using β = 2.0 to estimate the dust masses from a modified blackbody does not yield any clear dependence of the dust-to-stellar mass ratios on metallicity for these two samples.

2. PACS photometry

For three galaxies, HS 0822+3542, HS 1442+4250 and Tol 0618-402, some upper limits provided by Rémy-Ruyer et al. (2013) are slightly too low and have been updated to the following values:

  • HS 0822+3542: F70≤ 0.025 Jy and F100≤ 0.023 Jy,

  • HS 1442+4250: F100≤ 0.054 Jy, and

  • Tol0618-402: F100≤ 0.011 Jy.

None of these modifications affect the results of the paper because these galaxies are not detected in most Herschel bands, and thus have not been modelled with the modified blackbody model used in Rémy-Ruyer et al. (2013).

3. Dust-to-stellar mass ratios

The stellar masses used by Rémy-Ruyer et al. (2013) for the Dwarf Galaxy Survey (DGS), originally from Madden et al. (2013) were accidentally incorrect, and the right stellar masses for the DGS are presented now in Madden et al. (2014). We therefore present and analyse here the new plot of MBB/Mstar as a function of metallicity for the DGS and KINGFISH samples (Fig. 1, top left).

thumbnail Fig. 1

MBB/M⋆ as a function of metallicity for DGS (purple crosses) and KINGFISH (orange downward triangles). The best power-law fit is indicated as a black line. The distribution of MBB/M⋆ is indicated on the side for both samples: plain purple line for DGS and dashed orange line for KINGFISH. The errors on the metallicities are omitted for clarity. They are about 0.1 dex on average. Top left: the dust masses are from a modified blackbody fit with a free emissivity index, βobs (Rémy-Ruyer et al. 2013), and the KINGFISH stellar masses are from Skibba et al. (2011). The best fit line corresponds to log(MBB/M⋆) = (−20.5 ± 1.5) + (18.8 ± 1.6) × log(12 + log(O/H)). Top right: the dust masses are from a modified blackbody fit with a free emissivity index, βobs (Rémy-Ruyer et al. 2013), and the KINGFISH stellar masses are estimated with the formula of Eskew et al. (2012). The best fit line corresponds to log(MBB/M⋆) = (−20.2 ± 1.6) + (18.2 ± 1.7) × log(12 + log(O/H)). Bottom left: the dust masses are from a modified blackbody fit with a fixed emissivity index, β = 2.0, and the KINGFISH stellar masses are from Skibba et al. (2011). The best fit line corresponds to log(MBB/M⋆) = (−8.3 ± 1.1) + (5.9 ± 1.2) × log(12 + log(O/H)). Bottom right: the dust masses are from a modified blackbody fit with a fixed emissivity index, β = 2.0, and the KINGFISH stellar masses are estimated with the formula of Eskew et al. (2012). The best fit line corresponds to log(MBB/M⋆) = (−4.3 ± 1.2) + (0.9 ± 1.4) × log(12 + log(O/H)). This figure replaces Fig. 14 (top panel) in Rémy-Ruyer et al. (2013).

The stellar masses for KINGFISH can be found in Skibba et al. (2011) and the DGS stellar masses in Madden et al. (2014). Figure 1 (top left) shows that there is a strong decrease (slightly more than an order of magnitude) in the proportion of dust mass relative to the stellar mass with decreasing metallicity: we have a Spearman rank coefficient1ρ = 0.41. The median for the ratio Mdust,BB/M⋆ is 0.02% for DGS and 0.12% for KINGFISH. The best power-law fit gives Mdust,BB/M⋆=3.1×10-21×(12+log(O/H))18.8.\begin{equation} M_{\rm dust,BB}/M_{\star} = 3.1 \times 10^{-21} \times (12+\log({\rm O/H}))^{18.8}. \end{equation}(1)The stellar masses from the DGS are derived from the formula of Eskew et al. (2012) from the IRAC 3.6 and 4.5 μm broadband flux densities. The scatter in their relation corresponds to 1σ uncertainties for their stellar masses of ~30%, which is within the uncertainties we have for the DGS stellar masses (~50% on average). The stellar masses for KINGFISH have been derived by Skibba et al. (2011) following Zibetti et al. (2009) from optical and NIR colours. With this estimate, the KINGFISH stellar masses could be biased in the low direction by up to 40% (Zibetti et al. 2009). We perform the test by computing the KINGFISH stellar masses with the formula by Eskew et al. (2012), using the IRAC flux densities of Dale et al. (2007), and find a much weaker correlation between the dust-to-stellar mass ratio and metallicity, ρ = 0.26, and with a median Mdust,BB/M⋆ of 0.04% now for the KINGFISH sample (Fig. 1, top right).

The dust masses derived here for both samples, however, are probably lower limits of the real dust masses in many cases. In fact, we allow our βobs to go to very low values, giving lower dust masses than if we fixed it to 1.5 or even 2.0. Because we allow greater emission efficiency for the grains, we need less mass than if we were using a higher emissivity index to account for the same amount of luminosity. We perform the test by fixing the emissivity index parameter to 2.0 and find that the correlation between the dust-to-stellar mass ratios with metallicity vanishes. With β = 2.0 modified blackbody dust masses, the Spearman rank coefficient for the relation decreases to ρ = 0.22 if we are using Skibba et al. (2011) stellar masses for KINGFISH (Fig. 1 bottom left), and ρ = 2 × 10-4 if we use the KINGFISH stellar masses derived from the formula of Eskew et al. (2012) (Fig. 1 bottom right).

As a conclusion, we find that when the stellar masses are estimated consistently for both samples using the formula by Eskew et al. (2012), the observed correlation between the dust-to-stellar mass ratios and metallicity is mostly due to the choice of leaving the emissivity index free in the modified blackbody fits. When β = 2.0 is used to estimate the dust masses in the modified blackbody, no clear dependence of the dust-to-stellar mass ratios on metallicity can be observed. In a follow-up paper (Rémy-Ruyer et al., in prep.), we will obtain total dust masses from a full semi-empirical SED model, which will allow us to study this parameter in more detail.

4. Far-infrared luminosity to dust mass ratio

We also found a typo for the far-infrared (FIR) luminosity of SBS0335-052, which should be 2.0+0.14-0.12\hbox{$_{-0.12}^{+0.14}$}× 108L⊙, and not 1.2 × 107L⊙ as quoted in Table 4 of Rémy-Ruyer et al. (2013). This FIR luminosity is computed between 50 μm and 650 μm (see the definition adopted by Rémy-Ruyer et al. 2013), and we might miss some luminosity at shorter wavelengths, since the SED peaks around 30 μm in this galaxy (see Fig. A.1 in Rémy-Ruyer et al. 2013). In Fig. 2, we present the corrected point for SBS0335-052. Because this galaxy is our lowest metallicity galaxy, this new value has an influence on the derived best-fit relation. We now have a Spearman’s rank coefficient of −0.74 (−0.72 in Rémy-Ruyer et al. 2013) and the best power-law fit now gives LFIR/Mdust,BB=9.9×1030×(12+log(O/H))-30.5.\begin{equation} L_{\rm FIR}/M_{\rm dust,BB} = 9.9 \times 10^{30} \times (12+\log({\rm O/H}))^{-30.5}. \end{equation}(2)

thumbnail Fig. 2

LFIR/MBB as a function of metallicity for DGS (crosses) and KINGFISH (downward triangles). The colours code the temperature, T (Rémy-Ruyer et al. 2013). The best power-law fit line is indicated as a black line and corresponds to log(LFIR/MBB) = (31.0 ± 0.9) + (−30.5 ± 0.9) × log(12 + log(O/H)). The distribution of LFIR/MBB is indicated on the side for both samples: solid line for DGS and dashed line for KINGFISH. The errors on the metallicities are omitted for clarity. They are about 0.1 dex on average. This figure replaces Fig. 14 (bottom panel) in Rémy-Ruyer et al. (2013).

Our conclusions for the variation in the LFIR/Mdust,BB ratios between the DGS and KINGFISH sample as presented in Rémy-Ruyer et al. (2013) are not affected.

1

The Spearman rank coefficient, ρ, indicates how well the relationship between X and Y can be described by a monotonic function: monotonically increasing: ρ> 0, or monotonically decreasing: ρ< 0. For our number of sources (≥100), a Spearman rank coefficient ≥0.30 (or ≤–0.30) is the sign of a significant correlation between X and Y (i.e., the probability that the two variables are monotonically correlated is ≥99.9%).

References

  1. Dale, D. A., Gil de Paz, A., Gordon, K. D., et al. 2007, ApJ, 655, 863 [NASA ADS] [CrossRef] [Google Scholar]
  2. Eskew, M., Zaritsky, D., & Meidt, S. 2012, AJ, 143, 139 [NASA ADS] [CrossRef] [Google Scholar]
  3. Madden, S. C., Rémy-Ruyer, A., Galametz, M., et al. 2013, PASP, 125, 600 [NASA ADS] [CrossRef] [Google Scholar]
  4. Madden, S. C., Rémy-Ruyer, A., Galametz, M., et al. 2014, PASP, 126, 1079 [CrossRef] [Google Scholar]
  5. Rémy-Ruyer, A., Madden, S. C., Galliano, F., et al. 2013, A&A, 557, A95 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Skibba, R. A., Engelbracht, C. W., Dale, D., et al. 2011, ApJ, 738, 89 [NASA ADS] [CrossRef] [Google Scholar]
  7. Zibetti, S., Charlot, S., & Rix, H.-W. 2009, MNRAS, 400, 1181 [NASA ADS] [CrossRef] [Google Scholar]

© ESO, 2014

All Figures

thumbnail Fig. 1

MBB/M⋆ as a function of metallicity for DGS (purple crosses) and KINGFISH (orange downward triangles). The best power-law fit is indicated as a black line. The distribution of MBB/M⋆ is indicated on the side for both samples: plain purple line for DGS and dashed orange line for KINGFISH. The errors on the metallicities are omitted for clarity. They are about 0.1 dex on average. Top left: the dust masses are from a modified blackbody fit with a free emissivity index, βobs (Rémy-Ruyer et al. 2013), and the KINGFISH stellar masses are from Skibba et al. (2011). The best fit line corresponds to log(MBB/M⋆) = (−20.5 ± 1.5) + (18.8 ± 1.6) × log(12 + log(O/H)). Top right: the dust masses are from a modified blackbody fit with a free emissivity index, βobs (Rémy-Ruyer et al. 2013), and the KINGFISH stellar masses are estimated with the formula of Eskew et al. (2012). The best fit line corresponds to log(MBB/M⋆) = (−20.2 ± 1.6) + (18.2 ± 1.7) × log(12 + log(O/H)). Bottom left: the dust masses are from a modified blackbody fit with a fixed emissivity index, β = 2.0, and the KINGFISH stellar masses are from Skibba et al. (2011). The best fit line corresponds to log(MBB/M⋆) = (−8.3 ± 1.1) + (5.9 ± 1.2) × log(12 + log(O/H)). Bottom right: the dust masses are from a modified blackbody fit with a fixed emissivity index, β = 2.0, and the KINGFISH stellar masses are estimated with the formula of Eskew et al. (2012). The best fit line corresponds to log(MBB/M⋆) = (−4.3 ± 1.2) + (0.9 ± 1.4) × log(12 + log(O/H)). This figure replaces Fig. 14 (top panel) in Rémy-Ruyer et al. (2013).
In the text
thumbnail Fig. 2

LFIR/MBB as a function of metallicity for DGS (crosses) and KINGFISH (downward triangles). The colours code the temperature, T (Rémy-Ruyer et al. 2013). The best power-law fit line is indicated as a black line and corresponds to log(LFIR/MBB) = (31.0 ± 0.9) + (−30.5 ± 0.9) × log(12 + log(O/H)). The distribution of LFIR/MBB is indicated on the side for both samples: solid line for DGS and dashed line for KINGFISH. The errors on the metallicities are omitted for clarity. They are about 0.1 dex on average. This figure replaces Fig. 14 (bottom panel) in Rémy-Ruyer et al. (2013).
In the text

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