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Appendix A: The WISE data

The NASA’s Wide-field Infrared Survey Explorer (WISE, Wright et al. 2010) is a 40 cm space telescope with a field of view of 47′. The WISE satellite made an all sky survey in four photometric bands in the near- and mid-infrared domain (3.6, 4.5, 12, and 22 μm). The survey has been done by mapping the sky with 8.8 s exposures with an average twelve exposures per position, which allowed us to reach a point source sensitivity better than 4 mJy (5σ) at the ecliptic and significantly better at the ecliptic poles because of the longer exposures. The angular resolution at 22 μm is 12 arcsec, while the pixel size of the co-added images is 1.375′′. Recently completed, the survey provides the community with fully reduced images that can be used to extract fluxes for all kinds of sources. Flux extraction within appropriate apertures is indeed required for the galaxies analysed in this work because of their extended nature. Flux densities provided by the WISE pipeline are generally underestimated in extended sources since the pipeline is optimised for point-like sources. For the purpose of this work, we retrieved the images of the whole Virgo cluster region in the 22 μm W4 band from the WISE Science Archive⁸. This band is close to the 25 μm IRAS and 24 μm Spitzer bands and can be easily used after simple corrections to quantify the attenuation in the FUV and NUV bands of GALEX using the prescription of Hao et al. (2011).

Fluxes have been extracted using exactly the same procedure adopted in Voyer et al. (2014) for the UV fluxes. Aperture photometry, indicated for extended sources such as those analysed in this work, has been done using the DS9/Funtools program Funcnts. This tool requires the use of different apertures: one centred on the emitting source encompassing the total emission and the others on the surrounding regions to estimate the sky contribution to the emission. For this purpose, we used exactly the same apertures on both the source and the sky as determined on the UV images by Voyer et al. (2014). These apertures were manually defined to include the total galaxy emission (elliptical aperture) and to avoid other emitting sources in the sky. We choose to use the same apertures as those used in the UV bands for several reasons. First of all, to avoid aperture effects in the extinction correction, the UV and infrared emitting flux must come from the same emitting regions. The shape of the on-source elliptical aperture (size and orientation) has been determined on the UV images of these extended sources to fully include the galaxy emission. Given the similar mid-infrared and UV morphology of galaxies, the same aperture is also well adapted in the 22 μm band. The on-source aperture is sufficiently large enough to encompass the total mid-infrared emission, which might be slightly more extended than the UV emission because of the higher resolution of GALEX (~5 arcsec). The sky regions have been selected on the UV images to avoid contaminating sources, such as background galaxies, nearby companions, or stars, which are rare in the UV bands at high Galactic latitudes. With the exception of stars, whose contribution in the WISE spectral domain under study is negligible, the nature of the possible emitting sources in the 22 μm band is similar to that of the UV sources. Both UV and mid-infrared images can be also contaminated by a low surface brightness, diffuse emission of Galactic cirri. The position of the sky regions around the target galaxy allows an accurate determination of the sky emission, thus minimising any systematic effect related to this diffuse component.

The DS9/Funtools program Funcnts has been run on all the extended UV detected sources catalogued in Voyer et al. (2014) (1771 objects). Counts have been transformed into flux densities (in Jy) using the prescriptions given in Wright et al. (2010) and in the Explanatory Supplement WISE Preliminary Data Release Products consistently with Ciesla et al. (2014), by using 5.2269 × 10^-5 Jy/DN. We also applied, as suggested by Jarrett et al. (2013), an aperture correction of −0.03 mag to account for the WISE absolute photometric calibration method by using PSF profile fitting. We also applied a second correction to account for a systematic difference in the calibrating “red” stars and “blue” galaxies. Jarrett et al. (2013) quantified this error for star-forming galaxies with a spectrum rising as S(ν) ~ ν^-2 and removed it by applying a systematic correction of 0.92 in the 22 μm band. We did not apply this correction to quiescent, early-type galaxies since the emission might still be dominated by the Rayleigh-Jeans tails of the stellar atmosphere of M type stars in this band. We did not apply any further colour correction, since it is negligible in the W4 WISE band (~1%; Jarrett et al. 2013). Combined with calibration uncertainties (~1.5%), the photometric uncertainty due to aperture and colour corrections on the W4 band should be of the order of ~5%. This, however, does not include the uncertainty on the total flux estimate, which is generally dominated by the uncertainty on the determination of the sky background in extended sources (Boselli et al. 2003b; Ciesla et al. 2012). The total uncertainty on the measure of the flux density is thus given by the quadratic sum of the calibration uncertainty err_WISE, on the uncertainty of the large scale sky fluctuations err_sky, and on the pixel per pixel uncertainty err_pix which might be partly correlated (Boselli et al. 2003b; Ciesla et al. 2012). Consistently with Boselli et al. (2003b) and Voyer et al. (2014), we calculate the uncertainty on the sky err_sky and on the pixel per pixel err_pix in ~10 square sky regions with randomly selected large sizes surrounding each target. These uncertainties are defined as: (A.1)and (A.2)where N_pix is the number of pixels in the galaxy aperture, STD [b_n] is the standard deviation of the values of all pixels in sky box n, and ⟨ b_n ⟩ is the average of all pixels in sky box n (Voyer et al. 2014). The total uncertainty on the extracted flux is then given by (A.3)to which the calibration uncertainty err_WISE should be added for estimating the total photometric uncertainty on the data. Given that err_sky and err_pix are the dominant source of error, we consider all galaxies with S_{22 μm}/err_tot> 1 here as detections. As in Boselli et al. (2003b) for undetected galaxies, we estimate an upper limit defined as (A.4)The WISE 22 μm flux densities of all the UV extended sources and their uncertainties are listed in Table A.1, which is arranged as follow:

Fig. A.1 Comparison of the 22 μm WISE flux densities determined in this work with those measured at 25 μm by IRAS for 119 detected galaxies in common. The solid line shows the 1:1 relation, while the dotted line is the expected relation once the WISE data are corrected by a factor of 1.22, as indicated by Ciesla et al. (2014) to take the shift in the photometric bands into account. Filled dots indicates late-type galaxies, empty-symbols early-types.

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• Column 1: Galaxy name, from NED.

• Columns 2 and 3: right ascension (J2000) and declination of the aperture used to extract the 22 μm WISE flux density.

• Columns 4–6: major and minor axis radii (in arcsec) and position angle (measured in degrees from north clockwise) of the adopted aperture.

• Column 7: flag indicating whether a galaxy is detected (1) or undetected (0).

• Column 8: 22 μm WISE flux density and error err_tot as defined in Eq. (9) in mJy.

To check the quality of these WISE data, we compare them to those already available in the literature in similar photometric bands. We first use a compilation of 25 μm IRAS data taken from different sources in the literature, which is available for 119 galaxies of the sample (Boselli et al. 2010). The comparison of the two sets of data is shown in Fig. A.1. Figure A.1 shows that the WISE and IRAS sets of data are fairly consistent for flux densities S_IRAS(25 μm) ≳ 400 mJy. Below this threshold, which roughly corresponds to the detection limit of IRAS in the 25 μm band, the WISE flux densities are systematically smaller than the IRAS one, thereby suggesting that these IRAS values are probably spurious detections. By comparing 24 μm MIPS Spitzer data to 22 μm WISE data for the HRS, Ciesla et al. (2014) found a systematic shift in the two sets of data of a factor 1.22 that they imputed to the slightly different spectral range covered by the two instruments. Figure A.1 shows that the same systematic shift can explain the observed difference in the IRAS and WISE data.

	Fig. A.2 Comparison of the 22 μm WISE flux densities for 138 HRS galaxies included in our sample. Filled dots indicates late-type galaxies, empty-symbols early-types. The solid line shows the 1:1 relation.
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Figure A.2 shows the comparison of the 22 μm WISE flux densities determined in this work with those recently published by Ciesla et al. (2014) for the HRS galaxies in common (138 detected objects). Figure A.2 shows that our set of data is perfectly consistent with the one of Ciesla et al. (2014). The mean Ciesla et al. (2014) to this work flux density ratio S_HRS/S_T.W. for the 138 detected galaxies in common is S_HRS/S_T.W. = 1.01 ± 0.63. The dispersion significantly drops when we limit the comparison to late-type systems (S_HRS/S_T.W. = 0.99 ± 0.10; 105 objects), which are the galaxies where the WISE data are crucial for an accurate dust extinction correction, while it is higher in early-type systems (S_HRS/S_T.W. = 1.06 ± 1.30; 33 objects). This systematic difference in early-type galaxies, where the 22 μm WISE emission might still be dominated by the stellar emission and is thus limited to the innermost brightest regions, is due to the reason that while here we keep the same aperture than the one used to integrate the UV emission, in Ciesla et al. (2014) the apertures are manually adapted to encompass the total infrared emission on the WISE images and thus minimise the uncertainties due to the sky fluctuations. The procedure adopted in Ciesla et al. (2014) for early-type systems, thus, should give more accurate results. We recall that the 22 μm flux densities of early-type galaxies are not used for the dust attenuation correction of the UV and optical photometric data. They are reported here just for completeness.

Table A.2 gives the cumulative and differential detection rate in the 22 μm band in different bins of stellar mass for the whole sample of Virgo galaxies and separately for early- and late-type galaxies. The overall detection rate of late-type galaxies, where 22 μm flux densities are necessary for an accurate extinction correction, is fairly good (~70%) although it drops to 38% in the lowest stellar mass bin.

Appendix B: The stellar mass determination

The standard recipes such as those proposed by Bell & de Jong (2001), Bell et al. (2003), Zibetti et al. (2009), and Boselli et al. (2009) to estimate the stellar mass of galaxies using a combination of a stellar luminosity with an optical or near-infrared colour index have been calibrated using different population synthesis models and initial mass functions (IMF) and assume different realistic star-formation histories. These star-formation histories are generally assumed to reproduce the smooth evolution of unperturbed objects of different luminosity and morphological type. They are thus not ideally defined to reproduce the evolution of strongly perturbed galaxies in high-density environments, such as those analysed in this work. Indeed, the removal of the atomic and molecular gas content for a ram pressure stripping event is very rapid in cluster galaxies and is thus able to quench the activity of star formation on very short timescales. Thus, the standard recipes for determining the total stellar mass proposed in the literature might not be optimised for perturbed galaxies, such as those analysed in this work. Their adoption can induce systematic effects in the analysed sample. To quantify these effects, we plot the relationship between the i-band mass-to-light ratio and the g − i colour index for galaxies of different stellar mass in Fig. B.1 as predicted by our multizone chemo-spectrophotometric models of galaxy evolution and those predicted by the prescription of Zibetti et al. (2009). Figure B.1 shows a tight correlation between the two variables for unperturbed galaxies using either our evolutionary models or the predictions of Zibetti et al. (2009), although this last gives a steeper relation. The observed difference in the two relations for unperturbed galaxies comes from the use of different population synthesis models, the adoption of different IMF, and star-formation histories of the target galaxies (e.g. Courteau et al. 2014). In this comparison, the main difference is that our model concerns disk galaxies while Zibetti et al. (2009) is a fit to the M/L-colour diagram obtained for a set of models which include a very large variety of star-formation histories (not only adapted to star forming galaxies). The Zibetti et al. fit is thus an average of “active” galaxies (similar to our bluest models in the absence of interaction) and of “passive” galaxies (similar to our reddest models in which the interaction has reduced the star-formation activity).

Fig. B.1 Relationship between the stellar mass-to-i-band luminosity ratio and the g − i colour index, as predicted by the calibration of Zibetti et al. (2009) (green solid line), and our models of galaxy evolution for unperturbed galaxies of different rotational velocity and fixed spin parameter (λ = 0.05; red open symbols), as well as for galaxies undergoing a ram pressure stripping event (blue symbols).

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Figure B.1 also shows that the relationship between M_star/L(i) and g − i significantly changes in perturbed galaxies. This is obvious, since the colour of a galaxy significantly changes becoming redder once the galaxy has abruptly stopped its star-formation activity, as indeed indicated by our models (Boselli et al. 2006; 2008a). If the i-band luminosity is barely affected after a ram pressure stripping event, the colour can significantly change on relatively short timescales. The adoption of a unique relation using standard recipes based on stellar luminosities and colours might thus induce strong systematic biases in the stellar mass determination. It would be more appropriate to use a standard spectral energy distribution fitting code, provided that realistic truncated star-formation histories, such as those observed in our sample can be easily reproduced. To effectively constrain the star-formation history of galaxies, however, a full coverage of the UV-to-far-infrared spectral energy distribution is necessary. This, unfortunately, is still quite prohibitive in the nearby universe for samples, such as the one analysed in this work, which span a wide range in luminosity (from giant to dwarfs) and morphological type (from ellipticals to irregulars). Furthermore, the star-formation history of the target galaxies, which is the topic of the present work, is an unknown variable, while not all fitting codes are tuned for such a purpose⁹. We thus decided to estimate stellar masses using a standard recipe and to quantify the uncertainty and any possible systematic effects on the derived M_star by comparing the prediction of our evolutionary models with the mass-to-light ratio vs. colour relations

proposed in the literature. This is done in Fig. B.2, where the i-band stellar mass-to-light ratio predicted by the Zibetti et al. (2009) prescription is plotted vs. the optical g − i colour and compared to the predictions of our multizone chemo-spectrophotometric models.

Fig. B.2 Upper panel: relationship between the stellar mass estimated using the Zibetti et al. (2009) mass-to-light colour dependent calibration and the real stellar mass of galaxies in our models of galaxy evolution for unperturbed (red symbols) and ram pressure stripped objects (blue symbols). The dotted line gives the 1:1 relation, while the dashed lines shows a variation of 0.2 dex (this value is typical of the global uncertainties affecting mass determinations due to the choice of the IMF). Lower panel: logarithmic difference between the stellar mass estimated using the Zibetti et al. (2009) mass-to-light colour dependent calibration and the stellar mass from our models for unperturbed (red symbols) and ram pressure stripped objects (blue symbols) is plotted vs. the stellar mass of the model galaxies.

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In unperturbed galaxies, Fig. B.2 shows that the prescription of Zibetti et al. (2009) compared to our models underpredicts the stellar mass of galaxies by a factor of ~0.3–0.1 dex (larger values are for dwarf systems), while it overpredicts the mass in perturbed, gas deficient objects where the star-formation activity is rapidly quenched after a ram pressure stripping event. In these objects, however, the overprediction is just by ~0.1 dex irrespective of stellar mass. Although important, Fig. B.2 shows that the systematic effect in the determination of the stellar mass using the recipe of Zibetti et al. (2009) is relatively small compared to the dynamic range in the stellar mass sampled in this work. We thus decided to use the Zibetti et al. (2009) relation, since it gives an “average” value for unperturbed and perturbed objects. Figure B.2 can be used to quantify the systematic effect on stellar mass for different galaxies.

© ESO, 2014