Äîêóìåíò âçÿò èç êýøà ïîèñêîâîé ìàøèíû. Àäðåñ îðèãèíàëüíîãî äîêóìåíòà : http://www.arcetri.astro.it/~sperello/arXiv1402.4524.pdf Äàòà èçìåíåíèÿ: Thu Feb 20 12:25:32 2014 Äàòà èíäåêñèðîâàíèÿ: Thu Feb 27 22:32:50 2014 Êîäèðîâêà: Ïîèñêîâûå ñëîâà: ngc 3982

Mon. Not. R. Astron. Soc. 000, 000­000 (0000)

Printed 20 February 2014

A (MN L TEX style file v2.2)

PACS photometry of the Herschel Reference Survey ­ Far-infrared/sub-millimeter colours as tracers of dust prop erties in nearby galaxies

arXiv:1402.4524v1 [astro-ph.GA] 18 Feb 2014

L. H. J. J. S.
1 2

Cortese1,2, J. Fritz3, S. Bianchi4, A. Boselli5, L. Ciesla6, G. J. Bendo7, M. Boquien5,8, Roussel9, M. Baes3, V. Buat5, M. Clemens10, A. Cooray11, D. Cormier12, I. Davies13, I. De Looze3 , S. A. Eales13, C. Fuller13, L. K. Hunt4, S. Madden14, Munoz-Mateos15, C. Pappalardo4, D. Pierini16, A. R´ y-Ruyer14, M. Sauvage14, em 4 13 17 di Serego Alighieri , M. W. L. Smith , L. Spinoglio , M. Vaccari18, C. Vlahakis19

Centre for Astrophysics & Supercomputing, Swinburne University of Technology, Mail H30 - PO Box 218, Hawthorn, VIC 3122, Australia European Southern Observatory, Karl-Schwarzschild Str. 2, 85748 Garching bei Muenchen, Germany 3 Sterrenkundig Observatorium, Universiteit Gent, Krijgslaan 281 S9, 9000, Gent, Belgium 4 INAF-Osservatorio Astrofisico di Arcetri, Largo Enrico Fermi 5, 50125 Firenze, Italy 5 Laboratoire d'Astrophysique de Marseil le - LAM, Universit´e d'Aix-Marseil le & CNRS, UMR7326, 38 rue F. Joliot-Curie, F-13388 Marseiul le Cedex 13, France 6 University of Crete, Department of Physics, Heraklion, Crete, 71003, Greece 7 UK ALMA Regional Centre Node, Jodrel l Bank Centre for Astrophysics, School of Physics and Astronomy, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom 8 Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB30HA, UK 9 Institut d'Astrophysique de Paris, Universit´ Pierre et Marie Curie (UPMC), CNRS (UMR7095), 75014 Paris, France e 10 Osservatorio Astronomico di Padova, Vicolo del l'Osservatorio 5, I-35122 Padova, Italy 11 University of California, Irvine, Department of Physics & Astronomy, 4186 Frederick Reines Hal l, Irvine, CA, USA 12 Institut fur Theoretische Astrophysik, Zentrum fur Astronomie der Universit¨ Heidelberg, Albert-Ueberle Str. 2, D-69120 Heidelberg, Germany ¨ ¨ at 13 School of Physics and Astronomy, Cardiff University, The Parade, Cardiff, CF24 3AA, UK 14 Laboratoire AIM, CEA, Universit´ Paris VII, IRFU/Service d'Astrophysique, Bat. 709, 91191 Gif-sur-Yvette, France e 15 European Southern Observatory, Alonso de Cordova 3107, Vitacura, Casil la 19001, Santiago de Chile 16 Max-Planck-Institut fur extraterrestrische Physik, Giessenbachstrasse, Postfach 1312, D-85741, Garching bei Munchen, Germany ¨ ¨ 17 Istituto di Fisica del lo Spazio Interplanetario, INAF, Via Fosso del Cavaliere 100, I-00133 Roma, Italy 18 Astrophysics Group, Physics Department, University of the Western Cape, Private Bag X17, Bel lvil le 7535, Cape Town, South Africa 19 Joint ALMA Observatory/European Southern Observatory, Alonso de Cordova 3107, Vitacura, Santiago, Chile

Accepted 2014 January 21. Received 2014 January 20; in original form 2013 November 3

ABSTRACT

We present Herschel/PACS 100 and 160 µm integrated photometry for the 323 galaxies in the Herschel Reference Survey (HRS), a K-band-, volume-limited sample of galaxies in the local Universe. Once combined with the Herschel/SPIRE observations already available, these data make the HRS the largest representative sample of nearby galaxies with homogeneous coverage across the 100-500 µm wavelength range. In this paper, we take advantage of this unique dataset to investigate the properties and shape of the far-infrared/sub-millimeter spectral energy distribution in nearby galaxies. We show that, in the stellar mass range covered by the HRS (8
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Key words: galaxies: fundamental parameters ­ galaxies: ISM ­ infrared: galaxies

1

INTRODUCTION

It is now well established that approximately half of the radiative energy produced by galaxies is absorb ed by dust grains and re-emitted in the infrared regime (Hauser & Dwek 2001; Boselli et al. 2003; Dole et al. 2006; Dale et al. 2007; Burgarella et al. 2013). Thus, observations in the 10-1000 µm wavelength range provide us with a unique opp ortunity not only to quantify half of the b olometric luminosity of galaxies, but also to characterise the prop erties of cosmic dust. Moreover, since dust grains are crucial for the star formation cycle (Hollenbach & Salp eter 1971), such information can give us imp ortant insights into the physical processes regulating galaxy evolution (e.g., Dunne et al. 2011). Unfortunately, despite its paramount imp ortance, we are still missing a complete and coherent picture of dust prop erties in galaxies across the Hubble sequence, and of the exact role played by grains in regulating star formation (McKee & Krumholz 2010). Indeed, we know very little ab out the dust comp osition in galaxies outside our own Local Group (Draine & Li 2007; Compi`gne et al. 2011) and if/how it is regulated by the e physical conditions exp erienced by grains in the inter-stellar medium (ISM). Hence, our estimates of dust masses in galaxies are still highly uncertain (Finkb einer et al. 1999; Dupac et al. 2003; Gordon et al. 2010; Paradis et al. 2010; Planck Collab oration et al. 2011b ). Luckily, the last decade has seen the start of a golden age for observational far-infrared (FIR) and sub-millimeter (submm) astronomy, providing a new boost to the refinement of theoretical dust models (Meny et al. 2007; Draine & Li 2007; Hoang et al. 2010; Compi`gne et al. 2011; Steinacker et al. 2013). In pare ticular, the Spitzer (Werner et al. 2004), and more recently Herschel (Pilbratt et al. 2010) and Planck (Planck Collab oration et al. 2011a) space telescop es are finally gathering a wealth of information on the dust emission from thousands of galaxies up to z 2. Particularly imp ortant for a prop er characterisation of dust in galaxies is the radiation emitted at wavelengths >100-200 µm. In this regime, the integrated emission from galaxies originates predominantly from dust in thermal equilibrium, heated by the diffuse interstellar radiation field (ISRF), which represents the bulk of the dust mass in a galaxy (e.g., Sodroski et al. 1989; Sauvage & Thuan 1992; Calzetti et al. 1995; Walterb os & Greenawalt 1996; Bendo et al. 2010; Boquien et al. 2011; Bendo et al. 2012). Thus, by characterising the dust emission in the >100 µm wavelength domain, we have a unique opp ortunity to provide strong constraints to theoretical models, and to refine our census of the dust budget in galaxies.

The first natural step in this direction is to quantify how the shap e of the dust sp ectral energy distribution (SED) varies with galaxy prop erties across a wide range of morphological typ e, star formation activity, cold gas mass and metal content. This is necessary to determine if the amount of radiation emitted at each wavelength is simply regulated by the intensity of the ISRF resp onsible for the dust heating, or whether it retains an imprint of the chemical comp osition of the grains. Indeed, only after a careful characterisation of the physical parameters regulating the dust SED, will it b e possible to properly convert observables into physical quantities such as dust temp eratures and dust masses. Many recent works (Gordon et al. 2010; Skibba et al. 2011; Davies et al. 2012; Planck Collab oration et al. 2011b; Galametz et al. 2012; Auld et al. 2013) have shown that, ab ove 100 µm, the dust SED is very well approximated by a simple modified black-b ody (but see also Bendo et al. 2012): F = Mdust D2
0

0



B (T )

(1)

Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA. lcortese@swin.edu.au

where F is the flux density emitted at the frequency , 0 is the dust mass absorption coefficient at the frequency 0 , gives its variation as a function of frequency, D is the galaxy distance and B (T ) is the Planck function. Mounting evidence is emerging that is not the same in all galaxies (e.g., R´my-Ruyer et al. 2013), and may also vary within e galaxies (e.g., Galametz et al. 2012; Smith et al. 2012). Modified black-b odies are simple models and cannot prop erly reproduce real dust prop erties (e.g., Draine & Li 2007; Shetty et al. 2009; Bernard et al. 2010). Several dust comp onents at various temp eratures contribute to the total emission along the lines-of-sight. This implies the presence of temp erature mixing that can cause variations of the infrared slop e, and thus in the apparent emissivity index . Nevertheless, parameterization of the dust SEDs through modified black-b ody fitting is a p owerful tool to help understand variations of dust prop erties with other galaxy characteristics, esp ecially in case of sparse sampling of the FIR/sub-mm wavelength range (e.g., high-redshift galaxies Magdis et al. 2011; Symeonidis et al. 2013). Therefore, it is extremely important to determine in which cases a single modified backbody can be used, and how temperature and dust mass estimates are affected by the assumptions made on . In order to ascertain the dust prop erties of galaxies in the local Universe, and to provide new constraints to theoretical models, we have carried out the Herschel Reference Survey (HRS, Boselli et al. 2010b), a Herschel guaranteed time pro ject focused on the study of the interplay b etween dust, gas and star formation in a statistically significant sample of 300 galaxies spanning a wide range of morphologies, stellar masses (8 c 0000 RAS, MNRAS 000, 000­000


PACS photometry of the Herschel Reference Survey
Boselli et al. 2013; Hughes et al. 2013), has already allowed us to have a first glimpse at how the dust content and shap e of the dust SED vary with internal galaxy prop erties (Boselli et al. 2010a, 2012; Cortese et al. 2012b ). In particular, Boselli et al. (2010a, 2012) have shown that the slop e of the dust SED in the 200-500 µm interval decreases from 2 to 1 when moving from metal-rich to metal-p oor galaxies. However, our analyses have so far b een limited by the lack of data in the 100-200 µm wavelength range for the entire sample. Thus, in this pap er we present integrated Herschel/PACS (Poglitsch et al. 2010) 100 and 160 µm flux densities for all the HRS sample and take advantage of our multiwavelength dataset to p erform a first analysis of the prop erties of the dust SED across our entire sample. Corresp onding to the p eak of the dust SED, the 100-200 µm wavelength interval is crucial not only to prop erly quantify the shap e of the SED, but also to accurately determine the average dust temp erature and total dust mass in galaxies. These data make the HRS the largest representative sample of nearby galaxies with homogeneous coverage across the 100-500 µm wavelength range. In addition to releasing our dataset to the community, our primary goals are 1) to investigate how the shap e of the dust SED varies with internal galaxy prop erties, and 2) to determine whether the integrated dust SED of HRS galaxies can always b e reduced to a single modified black-b ody with a constant value of and, if not, what are the p ossible biases introduced by this assumption. The results of SED fitting with the dust models of Draine et al. (2007) will b e presented in a forthcoming pap er (Ciesla et al., submitted.). This pap er is organized as follows. In Sect. 2 we describ e the Herschel observations, data reduction, flux density estimates and comparison with the literature. In Sect. 3 we use the PACS and SPIRE colours to investigate how the shap e of the dust SED varies with internal galaxy prop erties. In Sec. 4, we show how the dust temp erature and mass obtained from fitting a single modified black-b ody to the Herschel data dep end on the assumptions made on . Finally, the summary and implications of our results are presented in Sec. 5. 2.2 PACS observations and data reduction

3

The Herschel/PACS 100 and 160 µm observations of HRS galaxies presented in this work have b een obtained as part of various op en-time Herschel pro jects. The vast ma jority of the data (228 out of 323 galaxies) comes from our own Herschel cycle 1 op en time prop osal (OT1 lcortese1). Each galaxy was observed in scan mode, along two p erp endicular axes, at the medium scan sp eed of 20 /sec. Two rep etitions were done in each scan direction. The size of each map was chosen to match the size of our SPIRE images (see Ciesla et al. 2012), making sure to have homogeneous coverage across the entire 100-500 µm range. Maps for additional 83 HRS galaxies have b een obtained as part of the Herschel Virgo Cluster Survey (HeViCS, Davies et al. 2010). HeViCS mapp ed the Virgo cluster with both PACS and SPIRE simultaneously at the fast scan speed of 60 /sec. The observing strategy consists of scanning each 4â4 deg2 field in two orthogonal directions, and rep eating each scan four times (Auld et al. 2013). The faster scan sp eed of the Herschel parallel mode with resp ect to the scan map mode, used for our observations, is comp ensated by the higher numb er of rep etitions p erformed in the Virgo cluster, making the two datasets highly comparable (i.e., within 30%) in terms of their final noise. PACS observations for the remaining 12 HRS galaxies have b een retrieved from the Herschel public archive, and come from various pro jects (i.e., Kennicutt et al. 2011, KPGT esturm 1, OT1 acrocker 1, OT2 emurph01 3, GT1 lspinogl 2, OT2 aalonsoh 2). All data have b een obtained in scan mode at the medium scan sp eed of 20 /sec and they reach a noise level similar or lower than our own observations. For one galaxy (HRS3) only 160 µm observations are available as the ob ject lies at the edge of the 100 µm map, making the data not suitable for accurate photometry. Thus, in summary, all 323 galaxies in the HRS have b een observed at 160 µm, whereas 100 µm data are available for 322 ob jects. All raw PACS data were processed from Level-0 to Level-1 within HIPE (v10.0.0, Ott 2010) using the calibration file v48. This pre-processing includes, among the other tasks, pixel flagging, flux density conversion and coordinate assignment. To remove the 1/f noise which, at this p oint, still dominates the timelines, the Level-1 data were fed into Scanamorphos (version 21, Roussel 2013), an IDL algorithm which p erforms an optimal correction by exploiting the redundancy in the observations of each sky pixel. No noise modelling is hence needed. The pixel size of the final maps was chosen to sample at the b est the p oint-spread-function, at the resp ective wavelengths, typical of the data taken at medium scan sp eed: 1.7 and 2.85 arcsec pixel-1 at 100 and 160 µm, resp ectively (i.e., FWHM/4). The typical pixel-bypixel noise in the map varies b etween 0.1 and 0.25 mJy pixel-1 at 160 µm and b etween 0.04 and 0.1 mJy pixel-1 at 100 µm. In order to show the data quality of the new observations presented here, in Fig. 1 we compare the PACS images for three of our targets with the RGB Sloan Digital Sky Survey (Abaza jian et al. 2009) optical and SPIRE 250 µm (Ciesla et al. 2012) images. We show an example of an early-typ e galaxy with dust lanes (HRS45, top row), late-

2 2.1

THE DATA The Herschel Reference Survey

The HRS is a volume-limited sample (i.e., 15D25 Mp c) including all late-typ e galaxies (261 Sa and later) with 2MASS (Skrutskie et al. 2006) K-band magnitude KS,tot 12 mag and all early-typ e galaxies (62 S0a and earlier) with KS,tot 8.7 mag1 . Additional selection criteria are high galactic latitude (b > +55 ) and low Galactic extinction (AB < 0.2 mag, Schlegel et al. 1998), to minimize Galactic cirrus contamination. More details on the original selection can b e found in Boselli et al. (2010b), while the most recent morphological classifications and distance estimates are presented in Cortese et al. (2012a).
1

We note that one galaxy (HRS228) had a wrong redshift reported in NED, and is in reality a background galaxy. In this work, we have included it for completeness. c 0000 RAS, MNRAS 000, 000­000


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SDSS optical
HRS45 NGC3619

PACS 100µm

PACS 160µm

SPIRE 250µm

a
HRS48 NGC3631

c

e

1'

a
HRS244/245 NGC4647/4649

b

d

1'

`

a

b

1'

Figure 1. Comparison of the quality of our PACS images with the Sloan Digital Sky Survey optical and SPIRE 250 µm images. We show three types of ob jects: an early-type with dust lanes (top row), an unperturbed late-type spiral and an un-detected elliptical and its spiral companion. The size of the PACS and SPIRE beams is shown in the bottom left corner of each panel.

typ e galaxy (HRS48, middle row) and un-detected elliptical and its spiral companion (HRS244/245, b ottom row).

2.3

PACS 100 and 160 µm integrated photometry

Integrated 100 and 160 µm photometry has b een p erformed following very closely the technique used by Ciesla et al. (2012) for the SPIRE data of HRS galaxies. This is crucial to prop erly combine the two datasets, and to characterise the shap e of the SED across the entire 100-500 µm wavelength range. Thus, whenever p ossible, we determined integrated flux densities within the same ap ertures adopted in Ciesla et al. (2012). The ap erture sizes are adapted to include the entire extent of the FIR emission from the galaxies, and they corresp ond to 1.4, 0.7 and 0.3 times the optical diameter for late-typ e, lenticular and elliptical galaxies, resp ectively. Only for 36 galaxies (11% of the sample) we choose different sizes than those used for SPIRE. There are three different reasons why we did so: a) For 23 galaxies (HRS6, 14, 22, 32, 67, 71, 75, 158, 209, 223, 225, 238, 243,

249, 255, 257, 261, 264, 286, 300, 315, 317, 322) the 100 and 160 µm emission is significantly less extended than the size of the ap erture used by Ciesla et al. (2012). Although this does not affect the estimate of the integrated flux density, it artificially b oosts the error associated with our measurements to values always ab ove 50%, and sometimes even higher than 100%. Thus, for these ob jects, we reduced the size of the ap erture (on average by 26%) to obtain more realistic error estimates. We note that the size chosen is still larger than the extent of the FIR emission (so that ap erture corrections are not necessary), and that the flux density estimated within these new ap ertures is consistent with the value obtained using Ciesla et al. (2012) ap ertures. b) 10 galaxies (HRS7, 68, 129, 138, 161, 174, 210, 231, 258, 308) were not spatially resolved in the SPIRE bands, and SPIRE photometry was carried out directly on the time-line data. For these cases, which are generally resolved by PACS, we chose new ap ertures which include all the emission from the target. c) For 3 galaxies (HRS4, 122, 263), the PACS maps available from the archive were slightly smaller than our

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PACS photometry of the Herschel Reference Survey
SPIRE maps. While these maps are large enough to include the entire ap erture used in Ciesla et al. (2012), no space is left to prop erly estimate the background. Thus, the ap erture has b een reduced in order to allow a more accurate background estimate, and still encompass all the emission from the galaxy. Sky background was determined in fifteen to thirty regions, dep ending on the size of the target, around the chosen ap erture. The use of various regions instead of just a circular annulus makes it easier to estimate the large scale variations in the background and to avoid background/foreground sources around the target. The mean sky value was then subtracted from each map b efore p erforming the flux density extraction. Since cirrus contamination is significantly less of an issue than in SPIRE images, we did not find necessary to p erform a more complex modelling of the background. However, as discussed b elow, the effect of any residual large scale gradient is included in our error estimates. Errors on integrated flux densities have b een estimated following the guidelines describ ed in Roussel (2013), which are consistent with what is done in Ciesla et al. (2012) for HRS SPIRE data. Briefly, there are three sources of errors that affect our measurements:
tot

5

=



2 cal

+

2 instr

+

2 sky

(2)

where cal is the flux calibration uncertainty (here assumed to b e 5%; Balog et al. 2013), instr is the instrumental noise which dep ends on the numb er of scans crossing a pixel, and is obtained by summing in quadrature the values on the error map within the chosen ap erture, and sky is the error on the sky measurement. As discussed in Roussel (2013), the sky uncertainty results from the combination of the uncorrelated error on the mean value of the sky (sky pix i.e., the pixel-topixel variation across the image), and the correlated noise due to long time-scale drift residuals resp onsible for the large scale structures present in the image background (sky mean i.e., the standard deviation of the mean value of the sky measured in different ap ertures around the galaxy; see also Boselli et al. 2003; Gil de Paz & Madore 2005). In detail,
sky

Columns 7-8: the J2000 right ascension and declination. Column 9: Morphological typ e, taken from Cortese et al. (2012a): -2=dE/dS0, 0=E-E/S0, 1=S0, 2=S0a-S0/Sa, 3=Sa, 4=Sab, 5=Sb, 6=Sb c, 7=Sc, 8=Scd, 9=Sd, 10=Sdm-Sd/Sm, 11=Sm, 12=Im, 13=Pec, 14=S/BCD, 15=Sm/BCD, 16=Im/BCD, 17=BCD. Column 10: 100 µm flux density measurement flag. Non detections=0, Detections=1, Confused (i.e., flux density estimate significantly contaminated by the presence of another ob ject)=2. For confused galaxies, flux densities should b e considered as an upp er limit to the real value. Column 11: Integrated 100 µm flux density, or upp er limit in Jy. Column 12: Total uncertainty on the 100 µm flux density measurement in Jy. Column 13: 160 µm flux density measurement flag. Column 14: Integrated 160 µm flux density, or upp er limit in Jy. Column 15: Total uncertainty on the 160 µm flux density measurement in Jy. Columns 16-18: Ma jor, minor semi-axis (in arcseconds) and p osition angle (in degrees) of the ap erture used for the photometry. Column 19: Herschel Prop osal ID. This table, as well as all the reduced PACS maps, are publicly available on the Herschel Database in Marseille (HeDaM, http://hedam.oamp.fr/ ). 2.4 Comparison with the literature

=

Nap

2 sky pix

2 + Nap

2 sky mean

(3)

where Nap is the numb er of pixels in the ap erture used to integrate the galaxy flux density. As exp ected, for the vast ma jority of our ob jects the dominant source of error is the correlated uncertainty on the large-scale structure of the background. The average total uncertainties are tot 16% and 12% at 100 and 160 µm, resp ectively. Out of the 323 galaxies observed, 282 have b een detected in b oth bands (284 at 160 µm only). This matches the HRS detection fraction in the SPIRE bands (i.e., 284 galaxies detected at 250 µm), allowing us to characterise the shap e of the FIR/sub-mm SED across the entire 100-500 µm range for almost 300 galaxies. In case of non detections, upp er limits have b een estimated as 3âtot , using the same ap ertures as in Ciesla et al. (2012). The results of our photometry are presented in Table 1. The columns are as follows: Columns 1-6: HRS (Boselli et al. 2010b ), CGCG (Zwicky et al. 1961), VCC (Binggeli et al. 1985), UGC (Nilson 1973), NGC (Dreyer 1888) and IC (Dreyer 1895) names.
c 0000 RAS, MNRAS 000, 000­000

In order to check the reliability of the PACS flux density measurements presented here, we compare our far-infrared integrated flux densities with the values presented in the literature, which are based on PACS, Spitzer/MIPS or IRAS observations. The results of these comparisons are shown in Fig. 2. The difference b etween our flux density estimates and those presented in Dale et al. (2012) is +6% (standard deviation of 2-3%), with our flux densities b eing brighter, although the numb er statistics is very small (6 galaxies in total). This difference is within the quoted uncertainties, and is mainly due to the different technique used to estimate flux densities (i.e., different background ap ertures and the use of ap erture corrections not adopted in this work). Auld et al. (2013) recently published PACS flux density measurements for all the VCC galaxies in the HeViCS footprint. A comparison b etween the flux density estimates for the 65 detected galaxies in common reveals a nice correlation between the two estimates with a standard deviation of just 12% and 7% at 100 and 160 µm, resp ectively. However, Auld et al. (2013) measurements are systematically 12% and 15% lower than ours. After various tests, we concluded that there are two main reasons for this discrepancy. First, a different flux density estimate technique. Auld et al. (2013) used ap ertures on average significantly smaller than ours (e.g., see their Fig. 3), and then applied ap erture corrections. Indeed, by using our own ap ertures on the Auld et al. (2013) dataset, we find no systematic offset with our 100 µm data, whereas at 160 µm there is still a difference of 12%. Second, a different data reduction technique. Auld et al. (2013) used the naive pro jection task photProject in HIPE


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Figure 2. Comparison between our 160 µm (left) and 100 µm (right) flux density bottom panels show the difference (this work (T.W.) -literature) in percentage for shows the comparison with literature estimates based on PACS data, while in the IRAS observations is presented. The dotted lines indicate the one-to-one relation, flux density estimates.

estimates and those presented in the literature. The each dataset. For each PACS channel, the left panel right panel the comparison with Spitzer/MIPS and and the dashed lines the average uncertainty in our

to reduce PACS images. This requires the use of a highpass filter to correct for 1/f noise, and such procedure could remove diffuse emission associated to extended objects. By using the same ap ertures on the HeViCS maps reduced with b oth photProject and Scanamorphos, we find that photProject maps provide flux densities 10% lower than those obtained with Scanamorphos, while no difference is seen at 100 µm. Thus, the remaining difference at 160 µm is due to the use of photProject instead of Scanamorphos. Indeed, as mentioned ab ove, this is likely due to the use of high-pass filtering which removes diffuse emission, much more commonly present at 160 µm than at 100 µm (see also R´my-Ruyer et al. 2013). e We also compared our measurements to those presented by Davies et al. (2012) for the 49 galaxies in common. These are based on an early HeViCS data release and are measured on ap ertures much more similar to the ones we used. Our flux density measurements agree very well with these estimates (+2±22% and +2±14% at 100 and 160 µm, resp ectively). The scatter is larger than in the case of Auld et al. (2013), but consistent with the typical uncertainty given in Davies et al. (2012). It is likely that, in this case, the different calibration b etween the two datasets compensates for the intrinsic differences between photProject and Scanamorphos, providing a set of measurements consistent with our own. Spitzer/MIPS 160 µm flux densities for 103 galaxies in the HRS have b een published by Bendo et al. (2012). In order to p erform a prop er comparison with our data, we removed those galaxies which were flagged as problematic due to incomplete coverage, or simply b eing confused with other nearby galaxies of similar surface brightness in Bendo et al. (2012). For the remaining 65 ob jects in common our flux densities are 8% brighter than those of MIPS one, with quite a large scatter (22%). This large scatter is mainly due to two galaxies (which fall outside the residual plot in Fig. 2):

HRS129, 258. A comparison b etween the PACS, SPIRE and MIPS data for these galaxies shows that the MIPS data suffer from background confusion effects, making it difficult to separate emission from the target and background sources. Moreover, the MIPS observations for these galaxies were performed in photometry mode, which produces compact maps where it is difficult to measure the background. Once these are removed from the sample, the difference b etween MIPS and PACS measurements b ecomes +10±14%. Conversely, the comparison with the Spitzer/MIPS 160 µm flux densities presented in Dale et al. (2007) for the 6 SINGS galaxies in our sample shows an average difference of 5±11%. All these values are within the 12% flux calibration uncertainty in MIPS data (Stansb erry et al. 2007). A PACSto-MIPS 160 µm flux density ratio systematically higher than 1 has also b een found by comparing pixel-by-pixel photometry of nearby galaxies (Aniano et al. 2012; Draine et al. 2013). We can thus conclude that our 160 µm PACS flux density measurements are consistent with those of Spitzer/MIPS within 20%, in agreement with the results obtained by the PACS Team (Paladini et al. 2012). Finally, we compared our PACS 100 µm flux density estimates with those presented in the IRAS Faint Source Catalogue (164 galaxies after exclusion of confused/contaminated ob jects), finding an average difference of +7±15% (see also Ali 2011). We remind the reader that, although the central wavelengths of MIPS and IRAS corresp ond to those of PACS, the bandpasses are not identical and part of the offsets shown ab ove are certainly due to the different filter resp onses of the three instruments.
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7

Figure 3. From top to bottom: 100-to-250 µm, 100-to-500 µm, 160-to-500 µm and 250-to-500 µm as a function of the 100-to-160 µm flux density ratio. The first column shows the entire HRS sample, while in the following three columns points are colour-coded according to morphological type (open circles=E+S0, filled circles=Sa and later), Hi gas fraction (open circles=log(M (HI )/M )<-1, filled circles=log(M (HI )/M )>-1) and gas phase metallicity (open circles=12+log(O/H)>8.65, filled circles=12+log(O/H)<8.65). The Pearson correlation coefficients () for the whole sample are shown in the top left corner of each panel. The solid and dashed lines represent the expected colours for a modified black body with =2 and 1, respectively. We consider a temperature range between 10 and 40 K. Typical errorbars are shown on the bottom right corner of each panel.

3

FAR-INFRARED/SUB-MILLIMETER COLOURS AS A PROXY FOR THE SHAPE OF THE DUST SED

In the last few years, several studies have shown how infrared colours can b e used as a proxy of dust prop erties (e.g., Boselli et al. 2010a, 2012; Dale et al. 2012; Bendo et al.
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2010, 2012; Galametz et al. 2010; Boquien et al. 2011; R´my-Ruyer et al. 2013). The novelty of the present work e is that, for the first time, we cover the 100-500 µm domain for a representative sample of galaxies spanning a large range in stellar mass, star formation activity, cold gas and metal content. For example, compared to the work pre-


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Table 2. The Pearson correlation coefficients () and scatter () of the best-fitting bisector linear fit for each sample shown in the colour-colour relations of Fig. 3.

Sample All Ear ly - ty pe Late - ty pe M (HI )/M < M (HI )/M > 12 + log (O/H ) 12 + log (O/H )

F100 /F160 - F100 /F250 N 282 29 253 106 169 50 112 0.84 0.88 0.83 0.84 0.84 0.95 0.86 0.05 0.09 0.05 0.04 0.06 0.02 0.06

F100 /F160 - F100 /F500 N 274 25 249 101 167 50 110 0.70 0.71 0.69 0.68 0.71 0.88 0.73 0.10 0.17 0.10 0.06 0.11 0.03 0.11

F100 /F160 - F160 /F500 N 274 25 249 101 167 50 110 0.30 0.39 0.27 0.26 0.34 0.66 0.32 0.14 0.23 0.14 0.09 0.15 0.05 0.15

F100 /F160 - F250 /F500 N 274 25 249 101 167 50 110 0.23 0.14 0.28 0.13 0.34 0.53 0.33 0.12 0.14 0.12 0.10 0.11 0.05 0.10

0.1 0.1 > 8.65 < 8.65

sented in Boselli et al. (2012), which focused on Hi-normal spiral galaxies only, this analysis takes advantage of a more complete coverage at wavelengths shorter than 250 µm, and includes the entire HRS sample detected by Herschel (282 versus 146 ob jects). Similarly, the numb er of HRS galaxies detected at all PACS and SPIRE wavelengths is significantly larger (i.e., 282 versus 195) than that of Auld et al. (2013), which focuses on Virgo cluster galaxies only. Particularly interesting is to quantify how well the shap es of the dust SED at the short and long wavelengthends correlate among each other. Indeed if, in the 100-500 µm wavelength range, the dust SED can b e well approximated by a single modified black-b ody with fixed (i.e., the variation of the dust emissivity with frequency describ ed by = 0 â ( /0 ) ), all FIR/sub-mm colours should b e strongly correlated. The SPIRE flux densities are obtained from Ciesla et al. (2012), but we applied several corrections to these flux estimates. We multiplied their values by 1.0253, 1.0250 and 1.0125 at 250, 350 and 500 µm to take into account the new SPIRE calibration (v.11), and then by 0.9097, 0.9136 and 0.8976 at 250, 350 and 500 µm, to correct for the new beam areas (Bendo et al. 2013; Herschel Space Observatory 2013). We did not make any attempt to include variations of the b eam size as a function of the shap e of the SED (Herschel Space Observatory 2013), as these are generally within the measurement errors (<10%). Moreover, such cor rection would mainly result in a systematic offset in the flux densities, whereas the relative variation b etween the SPIRE bands would b e <3% for the ranges of investigated here. Thus, we are confident that this does not affect our conclusions. In Fig. 3 we plot the 100-to-160 µm flux density ratio, which usually embraces the p eak of the dust SED, as a function of various flux density ratios (i.e., from top to b ottom: 100-to-250 µm, 100-to-500 µm, 160-to-500 µm and 250-to500 µm) sensible to the shap e of the SED at increasingly longer wavelengths2 . Similar results are found if additional colours (e.g., including the 350µm flux density) are used. It is clear that the farther away in wavelength two colours are, the weaker their correlation is, as already noted by Boselli et al. (2012). Indeed, the Pearson correlation co-

efficient () decreases from 0.8 to 0.2 when moving from the 100-to-250 µm to the 250-to-500 µm flux density ratios (see first column of Fig. 3). Intriguingly, the increase of a factor of 3 in scatter ( )3 observed when moving from the top to the third panel app ears to b e due to a population of galaxies that detaches from the main relation. To see if this is indeed the case, in Fig. 3 we highlight galaxies according to (from left to right) their morphological typ e, the ratio of their atomic cold gas (Hi) to stellar mass content and gas-phase metallicity. Hi measurements have mainly b een obtained from Haynes et al. (2011) and Springob et al. (2005), and are presented in Boselli et al. (2014)4 . Stellar masses are from Cortese et al. (2012a), and gas-phase metallicities (i.e., oxygen abundances) converted into the Pettini & Pagel (2004) O3N2 base metallicity are taken from Hughes et al. (2013). We use 12+log(O/H)=8.65 (ab ove which the stellar vs. mass metallicity relation starts flattening, Kewley & Ellison 2008) and M (HI )/M =0.1 (b elow which the stellar mass vs. Hi fraction relation is no longer linear, Cortese et al. 2011; Bothwell et al. 2009) to divide gas-rich/metal-p oor from gas-p oor/metal-rich galaxies. The Pearson correlation coefficients and scatter around the b est-fitting bisector linear fit are indicated in Table 2. Gas-rich/metal-p oor galaxies seem to b e resp onsible for the significant increase in scatter when moving from the 100-to-250 µm to the 160-to-500 µm colour-colour plots. If we consider gas-p oor/metal-rich galaxies only, the scatter in the three b ottom panels of Fig. 3 decreases by at least a factor 2. Indeed, p erforming a KolmogorovSmirnov test, we found that there is only a 4% chance that the 160-to-500 µm colour distributions of metal-p oor (12+log(O/H)<8.65) and metal-rich (12+log(O/H)>8.65) galaxies are drawn from the same p opulation, as already demonstrated by Boselli et al. (2012). We note that some galaxies do not app ear in the third and fourth column of Fig. 3. This is b ecause for some ob jects Hi and metallicity information is not available. Our findings suggest that, in the 100-500 µm regime, the shap e of the dust SED for galaxies with stellar mass
3 In order to minimize the effect of outlier galaxies, the scatter is defined as the interquartile of the distribution of perpendicular distances from the best-fitting bisector linear fit for each sample. 4 This is an up dated version of the values presented in Cortese et al. (2011, 2012b), which takes advantage of the recently published ALFALFA flux densities (Haynes et al. 2011) for a considerable fraction of the HRS footprint.

2

In order to avoid the need to apply colour corrections when comparing with model predictions, here we plot the ratio of the responsivity function-weighted flux density measurements.

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Figure 4. Same as Fig. 3, but with the predictions for two temperatures modified black-body SEDs with =2 overplotted on the data points. In each plot, isotherms for the cold (Tc =10, 15 and 20 K) and warm (Tw =20, 25 and 30K) dust components are indicated by the dotted and dashed lines, respectively. Cold-to-warm dust mass ratios are 1, 2, 5 and 10 from left to right.

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scenarios. In Fig. 3 we show the flux density ratios derived from single modified black-b odies with temp eratures ranging from 10 and 40 K and values fixed to 2 (solid line) and 1 (dashed line). In Fig. 4, we show a combination of two modified black-b odies with =2. We vary the cold dust temp erature (Tc ) from 10 to 20 K, and the warm dust temperature (Tw ) from 20 to 30 K. The four columns show different mass ratios Mcold /Mwarm increasing from 1 (left) to 10 (right).


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Figure 5. The left panel shows the distribution of reduced 2 ~ and =2 (dashed). The ratio of 2 obtained for the two cases the central and right panel, respectively. Empty circles show ~ for which at least one of the two 2 corresponds to a probabi

~ (2 ) for the best-fitting single modified black-body with =free (solid line) as a function of gas-phase metallicity and Hi gas fraction are presented in galaxies with Hi deficiency greater than 0.5. We show only those galaxies lity P 95%.

It is clear that, while the temp erature is the main driver of the trends observed in each colour-colour plot, only a variation in , or an additional temp erature comp onent, can explain the increasing scatter when moving from the 100to-250 µm to 160-to-500 µm colours. Interestingly, the two temp erature comp onents scenario is able to reproduce the observed range of colours only if the warm comp onent contributes negligibly to the total dust budget of the galaxy (i.e., Mcold /Mwarm >5; Vlahakis et al. 2005). This is easy to understand if we consider the fact that, at fixed dust mass, the flux density emitted by a black-b ody in the FIR/submm wavelength range increases with temp erature. Thus, if the warm and cold comp onents have the same dust mass, the warm dust dominates the total emission, and the shap e of the SED is very close to that of a single black-b ody. Only if the cold dust comp onent dominates the mass budget, the shap e of the combined SED deviates significantly from a single black-b ody. Unfortunately, with our current data it is imp ossible to discriminate b etween a varying and a multiple temp erature comp onent scenario. Our lack of coverage b elow 100 µm makes it meaningless to p erform a two temp eratures fit, as the warm comp onent is not constrained. Thus, in the rest of this pap er we will focus on the single modified black-b ody case only, and investigate how different assumptions on can affect the interpretation of Herschel observations. A detailed comparison with the predictions of the Draine et al. (2007) dust models will b e presented in a forthcoming pap er (Ciesla et al., submitted.).

4 4.1

FITTING THE DUST SED WITH A SINGLE MODIFIED BLACK-BODY How well do colours trace the average dust temperature?

The results presented in the previous section show that FIR/sub-mm colours may not always represent a proxy for the average underlying dust temp erature. In order to investigate this issue in more detail, it is interesting to quantify how the FIR/sub-mm colours correlate with the parameters

obtained from a single modified black-b ody fitting. We assume either a constant value of =2, or keep this as a free parameter. The model functions were convolved with the PACS and SPIRE filter resp onse functions and fitted to the relative sp ectral resp onsivity function-weighted flux density measurements. Best-fit parameters and their 1 uncertainties are determined via a 2 minimisation using the Python version of the minimisation library MINUIT (James & Roos 1975). We choose =2 simply b ecause this seems to correctly reproduce the shap e of the SED for massive, metalrich spiral galaxies in the local Universe (Davies et al. 2012; Boselli et al. 2012; Draine et al. 2013). However, our results do not qualitatively change if a different (but fixed) value of is used. In the rest of the pap er, we consider only those ob jects detected in all 5 PACS/SPIRE bands, and for which ~ the reduced 2 (2 ) corresp onds to a probability P 95%: ~2 ~ i.e., dof =3 <2.6 (203 galaxies) and 2 dof =2 <3 (242 galaxies) for a fixed and variable , resp ectively. The b est-fit dust masses and temp eratures for these galaxies, as well as their distance, are provided in Table 3. This guarantees that we are not contaminated by ob jects whose FIR/submm emission is dominated by synchrotron emission (Baes et al. 2010). A comparison b etween the reduced 2 obtained for the =free and =2 cases is shown in Fig. 5. Not surprisingly, leaving free provides on average b etter fits. Moreover, as shown in the central and right panel of Fig. 5, the difference b etween the two techniques increases when moving towards metal-p oor/gas-rich systems. This is even more evident when Hi-deficient galaxies (i.e., DefHI >0.5, empty points in Fig. 5), for which the gas content is no longer a good indicator of enrichment history (Cortese & Hughes 2009; Hughes et al. 2013), are excluded ( =0.38 and 0.54 for all galaxies and Hi-normal systems only, resp ectively). In Fig. 6, we show how the FIR/sub-mm colours correlate with the b est-fit parameters obtained from our SED fitting. Not surprisingly, all SPIRE and PACS colours strongly correlate with dust temp erature if is kept fixed (we note that these results do not qualitatively change if we fix to a different value). It is also exp ected that the lowest scatter is observed for the colour spanning the largest wavelength range (i.e., the 100-to-500 µm flux density ratio), as the varic 0000 RAS, MNRAS 000, 000­000


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Figure 6. The modified black-body best-fitting parameters as a function of far-infrared/sub-millimeter colours (from left to right: 100to-160 µm, 100-to-250 µm, 100-to-500 µm and 250-to-500 µm flux density ratio). The bottom row shows the dust temperature obtained by keeping fixed to 2, while the middle and top rows show the best-fitting values for and T obtained by varying both parameters freely. The Pearson correlation coefficients are indicated in each panel. In the bottom row, the dotted lines show the expected relations between temperature and colour for a single modified black-body with =2, while the dashed line indicates the 1-to-1 relation.

ation in colour is larger, and less affected by measurement errors. More interesting is the case when is treated as a free parameter. In this case, there is a clear difference in the colours b ehaviour when crossing a of 200 µm. At shorter wavelengths, there is still a strong correlation of colour with temp erature ( 0.7), while only a very weak trend is seen with ( -0.15). Moving to longer wavelengths, the trends with temp erature b ecome weaker, and reverse for the 250to-500 µm colour ( -0.3), whereas the correlation with becomes gradually stronger. The best relation is found with the 250-to-500 µm flux density ratio ( 0.9), which app ears to b e mainly tracing variations of and not dust temp erature, as also shown in Fig. 3. These results are likely a direct consequence of the fact that the FIR/submm SED for our sample p eaks at <200 µm, and while the PACS colours trace the p eak of the dust SED, any variations in the emissivity of the grains will predominantly affect the SPIRE colours. The average value of for HRS galaxies is 1.8±0.5, a value consistent with what is found in the Milky Way and
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in other nearby galaxies (Planck Collab oration et al. 2013; Galametz et al. 2012; Boselli et al. 2012; Smith et al. 2012, 2013). An imp ortant issue affecting any modified black-b ody 2 fitting with and T as free parameters is the known anti-correlation b etween them, which is clearly shown in the right column of Fig. 6. While it is still debated whether part of this anti-correlation has a physical origin (Shetty et al. 2009; Galametz et al. 2012; Smith et al. 2012; Juvela & Ysard 2012; Juvela et al. 2013; R´my-Ruyer et al. e 2013; Tabatabaei et al. 2013), there is no doubt that it is mainly due to the 2 fitting technique (Shetty et al. 2009). Indeed, in the 2D vs. T plane, the region corresp onding to the absolute minimum of 2 dep ends on b oth quantities, giving rise to an anti-correlation b etween and T . This is clearly visible by just looking at the 2D confidence levels for any 2 modified black-b ody fit. Since in the first and third columns of Fig. 6 temp erature and show opp osite trends with colour, it is very likely that they are affected by this degeneracy. However, the significant difference in scatter b e-


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Figure 7. From top to bottom: the 250-to-500 µm flux density ratio, the best-fitting value of , the 100-to-160 µm flux density ratio, the best fitting temperature assuming =free and =2 as a function of stellar mass, stellar mass surface density (µ ), specific star formation rate (SF R/M ), Hi gas fraction (MHI /M ) and gas phase metallicity (12+log(O/H). Filled and open circles show late- and early-type galaxies, respectively. The Pearson correlation coefficients for the whole sample are shown in each panel.

tween the various relations suggests that the 100-to-160 µm colour vs. T and 250-to-500 µm colour vs. are less contaminated than the other correlations. As mentioned ab ove, this is b ecause the PACS colours mainly trace the p eak of the dust SED, whereas the SPIRE ones are mostly sensitive to variations in the dust emissivity.

4.2

The relation between dust temperature, and integrated galaxy properties

In this section we investigate further how the variation of , necessary to reproduce the observed colours of HRS galaxies in a single modified black-b ody scenario, is mirrored by a variation in galaxy prop erties. For comparison, we will also show the results obtained by keeping fixed, since we consider this an instructive exercise to illustrate how the model assumptions influence the parameters we derive. In Fig. 7, we show how the b est-fitting dust parameters, as well as the
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100-to-160 µm and 250-to-500 µm flux density ratios, are related to gas-phase metallicities, Hi gas fractions, sp ecific star formation rate (SF R/M ), stellar mass surface density 2 [µ =M /(2 R50,i ) where R50,i is the radius containing 50% of the total i-band light] and stellar mass. Star formation rates are determined by combining WISE 22µm (Ciesla et al., submitted.) and NUV photometry (Cortese et al. 2012a) using the recip es presented in Hao et al. (2011) as describ ed in Cortese (2012). By comparing the two b ottom rows of Fig. 7, it is clear that the assumptions made on significantly influence the correlations b etween temp erature and integrated galaxy prop erties. For fixed to 2, the strongest correlation is found with stellar mass surface density ( 0.45). A weak anti-correlation is visible with gas-fraction ( -0.3), while no correlation is found with sp ecific star formation rate, stellar mass or metallicity ( <0.2). Quite different re sults are obtained if is left free. In this case, the temp erature anti-correlates very weakly with µ ( -0.3), while it is strongly correlated with SF R/M (see also Clemens et al. 2013), Hi gas fraction, metallicity and stellar mass ( 0.5). Even more imp ortantly, some of the correlations show opp osite trends. For a fixed value of , the temp erature increases with metallicity and stellar mass surface densities, whereas it decreases for =free. The `reversal' of these correlations is driven exclusively by metal-p oor/gas-rich galaxies, and it is simply a consequence of the fact that, for these objects, the b est-fitting value of is significantly lower than 2. Thus, many of the correlations shown in Fig. 7 dep end on the assumptions made ab out the dust SED, and may not b e physical (Magnelli et al. 2012; Roseb oom et al. 2013). In particular, we have shown (see Fig. 6) that the 100to-160 µm and 250-to-500 µm flux density ratios are the b est proxies for T and , resp ectively. If all the trends observed in Fig. 7 are physical, we should find similar correlations when T and are replaced by the flux density ratios. However, this is not always the case. The 100-to-160 µm flux density ratio correlates only with SF R/M ( 0.5), while the 250to-500 µm ratio correlates weakly with SF R/M ( -0.2), but varies strongly with stellar mass, stellar mass surface density, Hi gas fraction and gas-phase metallicity ( 0.60.7). Thus, the T vs. Hi gas fraction and vs. SF R/M trends might b e spurious. In summary, our analysis confirms that the typical dust temp erature of a galaxies as measured from a single modified black-b ody is mainly related to sp ecific star formation rate, while varies more with the degree of metal enrichment of the ISM. As discussed in the previous section, at this stage it is imp ossible to determine whether the variation of across the HRS indicates a variation in the dust prop erties/comp osition, or it simply highlights the need of multiple temp erature comp onents for gas-rich/metal-p oor/low-mass galaxies. 4.3 Dust mass estimates

13

Figure 8. Left panel: Comparison between the dust masses obtained from a black-body SED fitting with =2 and =free. Right panel: Dust masses obtained from a black-body SED fitting with =2 as a function of those obtained using the empirical recipes of Cortese et al. (2012b), which are based on SPIRE colours only. Filled and empty circles indicate gas-rich and gaspoor galaxies, respectively (see also Fig. 3).

It is interesting to investigate how the variation of across the HRS for a single modified black-b ody affects the estimate of the dust mass reservoir. Thus, in the left panel of Fig. 8, we compare the dust masses obtained for =free and =2. Dust masses have b een calculated from Eq. 1 assuming 0 =856.5 GHz (i.e., 350 µm) and 0 =0.192 m2
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kg-1 (Draine 2003). It is evident that dust masses are significantly less affected than dust temp eratures by the assumptions made on . The average difference b etween the two measurements is 0.08 dex, with a standard deviation of 0.15 dex, which is consistent with the typical statistical error obtained from the SED fitting: 0.05 and 0.1 dex for =2 and =free. Not surprisingly, the largest difference is observed in gas-rich galaxies (filled circles, =0.14±0.14 dex), while the two techniques give consistent results for gas-p oor systems (empty circles, =-0.02±0.11 dex). This result implies that correlations involving dust masses are quite robust against the assumptions made on the shap e of the SED. Different assumptions can certainly affect the exact slop e of the dust scaling relations, but they are not able to produce the same dramatic inversion of some correlations observed for the dust temp erature (see Fig. 7). This conclusion is reinforced by the fact that the differences, already quite small, b etween the two cases might be overestimated, as we varied , by keeping fixed the value of dust opacity 0 used to determine the dust mass. As recently shown by Bianchi (2013), this is not entirely correct because the value of 0 is calibrated on a dust model with a well defined value of . Thus, if changes, 0 should change as well. Unfortunately, varying along with is far from trivial, and it is only p ossible by either having a consistent dust model for each value of , or by comparing dust mass estimates obtained from SED fitting with the ones obtained from other indep endent methods: e.g., using the amount of cold gas and metals, as prop osed by James et al. (2002). Finally, it is interesting to compare the dust masses estimated by fitting a single modified black-b ody with =2, to those obtained by using the empirical recip es develop ed by Cortese et al. (2012b), which assume =2 but are based on SPIRE data only. In this way we can quantify the b enefit provided by inclusion of the PACS data in the dust mass estimates. As shown in the right panel of Fig. 8, the two estimates show a good agreement with a mean difference of -0.07 dex and a standard deviation of 0.14 dex, lower than the typical uncertainty of 0.2 dex in the recip es by Cortese et al. (2012b). Even in this case, the largest offset


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Our findings overall reinforce the results already presented in Boselli et al. (2010a, 2012). However, it is imp ortant to note that the discovery of a clear variation in the shap e of the SED across the HRS has only b een p ossible thanks to the large wavelength coverage obtained by combining b oth PACS and SPIRE data. Indeed, with SPIRE or PACS data only, it would b e not only much more difficult to show under which conditions a simple modified black-b ody approach does not work, but it would also b e nearly impossible to quantify how model assumptions can affect the correlation of dust temp erature with star formation, galaxy structure and chemical enrichment.

(-0.12±0.11 dex) is found for gas-rich galaxies. This is a natural consequence of the fact that, for these ob jects, the shap e of the dust SED is no longer p erfectly consistent with =2. Thus, while dust mass estimates based on SPIRE colours are a reliable tool for estimating dust masses within 0.2 dex, only a complete coverage of the 100-500 µm wavelength range can provide us with accurate (within 0.1dex) dust mass estimates necessary to quantify in great detail the correlation b etween dust mass and other galaxy prop erties.

5

SUMMARY & CONCLUSIONS ACKNOWLEDGMENTS We thank an anonymous referee for his/her very useful comments and suggestions which have significantly improved this manuscript. LC thanks B. Draine for useful discussions, and B. Catinella for comments on this manuscript. We thank all the p eople involved in the construction and the launch of Herschel. The research leading to these results has received funding from the Europ ean Communitys Seventh Framework Programme (/FP7/2007-2013/) under grant agreement No 229517, and was supp orted under Australian Research Council's Discovery Pro jects funding scheme (pro ject numb er 130100664). IDL is a p ostdoctoral researcher of the FWO-Vlaanderen (Belgium). PACS has b een develop ed by a consortium of institutes led by MPE (Germany) and including UVIE (Austria); KU Leuven, CSL, IMEC (Belgium); CEA, LAM (France); MPIA (Germany); INAF-IFSI/OAA/OAP/OAT, LENS, SISSA (Italy); IAC (Spain). This development has b een supported by the funding agencies BMVIT (Austria), ESAPRODEX (Belgium), CEA/CNES (France), DLR (Germany), ASI/INAF (Italy), and CICYT/MCYT (Spain). SPIRE has b een develop ed by a consortium of institutes led by Cardiff University (UK) and including Univ. Lethbridge (Canada); NAOC (China); CEA, LAM (France); IFSI, Univ. Padua (Italy); IAC (Spain); Stockholm Observatory (Sweden); Imp erial College London, RAL, UCL-MSSL, UKATC, Univ. Sussex (UK); and Caltech, JPL, NHSC, Univ. Colorado (USA). This development has b een supp orted by national funding agencies: CSA (Canada); NAOC (China); CEA, CNES, CNRS (France); ASI (Italy); MCINN (Spain); SNSB (Sweden); STFC (UK); and NASA (USA). Part of the HRS data was accessed through the Herschel Database in Marseille (HeDaM - http://hedam.lam.fr ) op erated by CeSAM and hosted by the Lab oratoire d'Astrophysique de Marseille. We acknowledge the use of the NASA/IPAC Extragalactic Database (NED) which is op erated by the Jet Propulsion Lab oratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

In this pap er we presented PACS 100 and 160 µm integrated photometry for the Herschel Reference Survey. We have combined these data with SPIRE observations to investigate how the shap e of dust SED varies across the Hubble sequence. Being the largest representative sample of nearby galaxies with homogeneous coverage in the 100-500 µm wavelength domain, the HRS is ideal to quantify if and how dust emission varies across the local galaxy p opulation. Our main results are as follows. · The shap e of the dust SED is not well describ ed by a single modified black-b ody having just the dust temp erature as a free parameter. Instead, there is a clear need to vary the dep endence of the dust emissivity ( ) on wavelength, or to invoke multiple temp erature comp onents in order to reproduce the colours observed in our sample. This is particularly imp ortant as the HRS does not include very metal-p oor dwarf galaxies, for which we already knew that the dust SED is significantly different from the one of metal-rich, massive galaxies (Galliano et al. 2005, 2011; Engelbracht et al. 2008; Galametz et al. 2009; R´my-Ruyer et al. 2013). Our results e suggest that the difference in FIR/sub-mm colours b etween giant and dwarf galaxies (Draine & Li 2007) may not b e the result of a dramatic transition in dust prop erties, but just the consequence of the gradual variation that we observe as a function of metal and gas content. · The variation in the slop e of the dust SED strongly affects dust temp erature estimates from single modified blackbodies fits. In particular, the correlations between galaxy prop erties and dust temp eratures strongly dep end on the assumptions made on : i.e., trends can disapp ear or even reverse. Conversely, dust mass estimates are more robust, and variations in do not produce the same dramatic inversion of some correlations observed for the dust temp erature. · We confirm that the temp erature of a single modified black-b ody is mainly related to sp ecific star formation rate, while varies more with the degree of metal enrichment of the ISM. The results presented in this pap er may app ear in contradiction with several recent works showing that the dust SED is very well reproduced by a simple modified blackbody with =2 (Davies et al. 2012; Auld et al. 2013). However, all these works were focused on massive, metal-rich and relative gas-p oor galaxies, for which we also find that a constant value of provides a good fit to our data. It is when we move to the gas-rich/metal-p oor regime that the shap e of the SED starts to change (Boselli et al. 2010a, 2012; R´my-Ruyer et al. 2013). e

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Table 1: The PACS 100 and 160µm flux densities of the HRS. HRS 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 C GC G 123-035 124-004 94-026 94-028 94-052 154-016 154-017 154-020 154-026 183-028 124-038 124-041 183-030 124-045 65-087 94-116 95-019 155-015 184-016 184-018 155-028 155-029 184-028 184-029 125-013 184-031 184-034 155-035 95-060 95-062 267-027 95-065 95-085 95-097 267-037 155-049 155-051 38-129 66-115 67-019 96-011 96-013 96-022 96-026 291-054 96-029 156-064 268-021 39-130 96-037 96-038 268-030 67-071 96-045 96-047 291-072 96-049 96-050 67-084 268-051 292-009 186-012 268-063 292-017 292-019 186-024 268-076 186-045 268-088 0 292-042 0 269-013 269-019 269-020 269-022 13-033 VCC 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 UGC 0 5588 5617 5620 0 5662 5663 5685 5731 5738 5742 0 5753 5767 5826 5842 5887 5906 5909 5931 5958 5959 5972 5982 5995 5990 6001 6023 6026 6028 6024 6030 6077 6116 6115 6118 6128 6167 6169 6209 6267 6277 6299 6320 6330 6343 6352 6360 6368 6396 6405 6406 6420 6445 6453 6458 6460 6464 6474 6547 6575 6577 6579 6629 6640 6651 6706 0 6787 0 6860 0 6870 6918 6919 6923 6993 NGC 0 0 3226 3227 0 0 3245 3254 3277 0 3287 0 3294 3301 3338 3346 3370 3380 3381 3395 0 3414 3424 3430 3437 0 3442 3451 3454 3455 3448 3457 3485 3501 3499 3504 3512 3526 0 3547 3592 3596 3608 0 3619 3626 3629 3631 3640 3655 3659 3657 3666 3681 3684 3683 3686 3691 3692 3729 0 3755 3756 3795 3794 3813 0 0 3898 0 3945 3952 3953 3982 0 0 4030 IC 0 0 0 0 610 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2613 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2969 0 2972 0 0 0 0 0 R.A. (J.2000) hh:mm:ss.ss 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 10: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 11: 12: 17: 20: 23: 23: 26: 27: 27: 29: 32: 34: 34: 35: 36: 36: 42: 43: 47: 48: 48: 49: 51: 51: 51: 52: 52: 52: 53: 54: 54: 54: 54: 54: 00: 02: 03: 03: 04: 06: 07: 09: 14: 15: 16: 18: 19: 20: 20: 21: 21: 22: 23: 23: 24: 26: 27: 27: 27: 28: 28: 33: 36: 36: 36: 40: 40: 41: 44: 46: 49: 52: 53: 53: 53: 56: 56: 56: 00: 39. 57. 27. 30. 28. 01. 18. 19. 55. 29. 47. 42. 16. 56. 07. 38. 04. 12. 24. 50. 15. 16. 46. 11. 35. 38. 08. 20. 29. 31. 39. 48. 02. 47. 11. 11. 02. 56. 03. 55. 27. 06. 58. 17. 21. 03. 31. 02. 06. 54. 45. 55. 26. 29. 11. 31. 43. 09. 24. 49. 26. 33. 48. 06. 53. 18. 14. 25. 15. 31. 13. 40. 48. 28. 37. 49. 23. 66 13 01 58 37 16 39 92 45 82 31 07 25 04 54 91 05 17 82 11 81 23 33 41 75 34 11 86 45 07 24 63 38 32 03 21 98 63 35 94 25 21 96 24 60 80 82 85 85 62 49 57 07 80 18 85 95 41 01 34 47 37 02 84 42 65 83 96 37 27 73 63 92 10 51 43 64 Dec (J.2000) dd:mm:ss.s +22:48:35.9 +25:21:53.4 +19:53:54.7 +19:51:54.2 +20:13:41.5 +28:38:21.9 +28:30:26.6 +29:29:29.2 +28:30:42.2 +35:15:24.4 +21:38:54.0 +26:07:33.7 +37:19:28.9 +21:52:55.7 +13:44:49.2 +14:52:18.7 +17:16:25.3 +28:36:06.5 +34:42:41.1 +32:58:58.3 +27:50:54.9 +27:58:30.0 +32:54:02.7 +32:57:01.5 +22:56:02.9 +34:28:59.3 +33:54:37.3 +27:14:22.9 +17:20:38.3 +17:17:04.7 +54:18:18.8 +17:37:16.3 +14:50:29.7 +17:59:22.2 +56:13:18.2 +27:58:21.0 +28:02:12.5 +07:10:26.1 +12:03:36.2 +10:43:15.0 +17:15:36.5 +14:47:13.5 +18:08:54.9 +18:50:49.0 +57:45:27.8 +18:21:24.5 +26:57:48.2 +53:10:11.0 +03:14:05.4 +16:35:24.5 +17:49:06.8 +52:55:15.5 +11:20:32.0 +16:51:47.5 +17:01:49.0 +56:52:37.4 +17:13:26.8 +16:55:13.7 +09:24:27.5 +53:07:31.8 +58:11:29.0 +36:24:37.2 +54:17:36.8 +58:36:47.2 +56:12:07.3 +36:32:48.3 +55:02:05.9 +34:51:09.2 +56:05:03.7 -03:52:20.1 +60:40:32.0 -03:59:47.5 +52:19:36.4 +55:07:30.6 +55:37:59.5 +53:09:37.3 -01:06:00.0 Type 13 5 0 3 7 5 1 6 4 5 9 17 7 2 7 8 7 3 13 8 6 1 5 7 7 4 3 9 7 5 13 5 5 8 13 4 7 7 5 5 7 7 0 5 1 1 8 7 0 7 11 7 7 6 6 7 6 5 5 3 8 7 6 7 9 5 11 5 4 6 1 12 6 5 10 12 6 Flag100 1 1 0 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 F100 Jy 0.748 2.439 0.0 17.589 4.502 0.275 3.472 2.878 1.948 1.168 5.192 0.613 19.809 0.477 13.12 5.688 10.209 1.465 4.335 16.137 0.625 0.618 18.098 10.909 21.647 0.744 3.148 3.569 2.403 2.87 12.17 0.042 5.138 5.002 0.24 35.557 4.532 1.818 0.915 4.478 1.418 12.111 0.119 2.521 1.782 4.995 2.652 29.87 0.261 20.97 4.542 0.783 8.762 2.819 7.742 28.93 12.431 2.098 3.801 7.738 0.7 2.73 6.471 1.333 1.909 21.54 0.841 1.518 3.46 1.605 1.567 2.403 28.168 16.493 0.148 0.886 58.47 100 Jy 0.169 0.227 0.0 1.104 0.331 0.14 0.206 1.092 0.397 0.238 0.3 0.054 1.322 0.078 2.907 0.695 0.872 0.248 0.525 1.402 0.255 0.072 0.981 1.182 1.187 0.098 0.286 0.232 0.292 0.545 1.183 0.024 0.368 0.64 0.057 1.977 0.346 0.291 0.21 0.305 0.278 2.072 0.0 0.197 0.393 0.272 0.465 3.057 0.0 1.076 0.423 0.274 0.75 0.577 0.768 1.498 1.106 0.194 0.395 0.915 0.121 0.498 1.15 0.326 0.476 1.151 0.181 0.1 1.115 0.2 0.957 0.261 2.638 1.023 0.071 0.176 3.251 Flag160 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 F160 Jy 0.932 2.808 0.846 22.675 5.563 0.483 2.843 4.641 3.037 0.788 6.148 0.492 25.224 0.372 20.386 10.294 12.793 2.015 4.371 16.068 1.084 0.685 19.636 16.037 21.174 0.864 3.173 5.184 3.422 3.859 10.63 0.182 6.83 8.619 0.273 31.358 5.328 1.886 1.199 4.51 1.584 18.583 0.187 1.982 2.72 4.9 3.163 38.272 0.231 22.078 4.996 1.305 10.815 3.076 11.416 30.107 17.983 2.449 5.622 10.477 0.937 3.527 12.252 1.682 2.082 23.821 1.209 1.531 4.318 2.018 4.253 1.972 49.52 17.392 0.37 0.909 73.761 160 Jy 0.079 0.179 0.087 1.165 0.528 0.085 0.151 1.041 0.523 0.094 0.409 0.05 1.717 0.106 2.277 0.785 0.832 0.241 0.375 0.871 0.148 0.118 1.076 1.577 1.142 0.106 0.253 0.321 0.326 0.37 1.579 0.034 0.532 0.832 0.081 1.651 0.513 0.286 0.333 0.363 0.144 1.787 0.0 0.208 0.439 0.284 0.509 3.115 0.0 1.141 0.582 0.237 0.829 0.537 0.769 1.604 1.255 0.155 0.431 0.772 0.15 0.528 1.339 0.29 0.426 1.255 0.279 0.092 1.203 0.161 0.685 0.308 4.004 0.978 0.062 0.172 4.064 a arcsec 48. 47. 39. 100. 81. 62. 48. 210. 82. 56. 88. 29. 149. 35. 247. 113. 133. 71. 86. 84. 78. 40. 109. 167. 101. 58. 56. 80. 90. 100. 236. 20. 88. 167. 34. 113. 68. 83. 81. 80. 74. 171. 28. 54. 78. 59. 96. 210. 35. 76. 87. 61. 184. 94. 121. 82. 134. 53. 132. 118. 83. 133. 175. 92. 94. 94. 67. 40. 184. 61. 170. 81. 243. 98. 30. 84. 175. b arcsec 40. 45. 39. 84. 48. 22. 30. 66. 73. 43. 41. 22. 76. 35. 152. 98. 75. 57. 78. 63. 45. 36. 59. 94. 67. 35. 48. 48. 51. 62. 75. 20. 77. 52. 30. 88. 63. 45. 39. 39. 41. 163. 28. 51. 75. 54. 68. 201. 35. 53. 62. 54. 50. 75. 84. 65. 104. 42. 48. 80. 25. 58. 88. 48. 61. 46. 45. 40. 108. 51. 112. 48. 129. 86. 24. 35. 127. P.A. degree -10. 40. 15. -25. 28. -30. -3. 46. 25. 30. 20. 20. -65. 55. -80. -72. -30. 20. 55. 50. 0. 10. -70. 35. -63. 15. -2. 50. -65. 70. 65. 90. 60. 30. 20. -30. -42. 55. 0. 7. -63. 0. 0. -73. -65. -20. 65. -62. 90. 30. 55. -20. -85. -15. -55. -52. 25. 30. -85. 15. -9. -65. -1. 53. -60. 85. 60. 0. -72. -75. -15. 79. 13. 38. 90. -10. 31. Proposal ID OT1 lcortese 1 OT1 lcortese 1 GT1 lspinogl 2 GT1 lspinogl 2/OT2 aalonsoh 2 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 KPGT esturm 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 acrocker 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 acrocker 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1

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18

Table 1 ­ Continued. HRS 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 C GC G 98-019 69-024 69-027 13-046 98-037 41-031 69-036 243-044 41-041 69-058 41-042 69-088 13-104 98-108 69-101 187-029 69-104 69-107 69-110 69-112 69-119 69-123 98-130 158-060 98-144 42-015 99-015 99-014 42-032 42-033 42-037 42-038 70-024 99-024 42-044 99-027 42-045 42-047 70-031 70-029 42-053 99-029 70-034 70-035 99-030 42-063 70-039 42-068 99-036 42-070 42-072 99-038 70-045 42-079 42-080 158-099 70-048 42-083 42-089 70-057 70-058 42-093 42-092 70-061 99-044 42-095 70-068 70-067 42-098 42-099 99-049 70-071 70-072 70-076 42-104 42-105 70-082 70-080 VCC 0 0 0 0 0 0 0 0 0 0 0 66 0 92 131 0 145 152 157 167 187 213 226 0 307 341 0 355 393 404 434 449 465 483 492 497 508 517 522 524 552 559 570 576 596 613 630 648 654 656 667 685 692 697 699 0 713 731 758 759 763 787 785 792 801 827 836 849 851 859 865 873 881 912 921 938 939 944 UGC 6995 7001 7002 7021 0 7035 7048 7095 7111 7117 7116 7215 7214 7231 7255 7256 7260 7268 7275 7284 7291 7305 7315 7338 7345 7361 7366 7365 7385 7387 0 7403 7407 7412 7413 7418 7420 7422 7432 7431 7439 7442 7445 7447 7450 7451 7456 7461 7467 7465 7469 7473 7476 7474 7477 7483 7482 7488 7492 7493 7494 7498 7497 7503 7507 7513 7520 7519 7518 7522 7526 7528 7532 7538 7536 7541 7546 7542 NGC 4032 4019 4037 4045 0 0 4067 4100 4116 4124 4123 4178 4179 4192 0 4203 4206 4207 4212 4216 4222 0 4237 4251 4254 4260 0 4262 4276 0 4287 4289 4294 4298 4300 4302 4303 0 4305 4307 0 4312 4313 4316 4321 4324 4330 4339 4340 4343 0 4350 4351 0 0 4359 4356 4365 4370 4371 4374 4376 4378 4380 4383 0 4388 4390 0 0 4396 4402 4406 4413 4412 4416 0 4417 IC 0 755 0 0 0 0 0 0 0 0 0 0 0 0 3061 0 0 0 0 0 0 3094 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3259 0 0 3267 3268 0 0 0 0 0 0 0 0 0 0 0 0 0 3322 0 0 0 0 0 0 0 0 0 R.A. (J.2000) hh:mm:ss.ss 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 00: 01: 01: 02: 03: 03: 04: 06: 07: 08: 08: 12: 12: 13: 15: 15: 15: 15: 15: 15: 16: 16: 17: 18: 18: 19: 19: 19: 20: 20: 20: 21: 21: 21: 21: 21: 21: 22: 22: 22: 22: 22: 22: 22: 22: 23: 23: 23: 23: 23: 23: 23: 24: 24: 24: 24: 24: 24: 24: 24: 25: 25: 25: 25: 25: 25: 25: 25: 25: 25: 25: 26: 26: 26: 26: 26: 26: 26: 32. 10. 23. 42. 35. 40. 11. 08. 36. 09. 11. 46. 52. 48. 04. 05. 16. 30. 39. 54. 22. 56. 11. 08. 49. 22. 28. 30. 07. 17. 48. 02. 17. 32. 41. 42. 54. 01. 03. 05. 27. 31. 38. 42. 54. 06. 17. 34. 35. 38. 48. 57. 01. 05. 07. 11. 14. 28. 54. 55. 03. 18. 18. 22. 25. 42. 46. 50. 54. 58. 58. 07. 11. 32. 36. 46. 47. 50. 82 39 67 26 94 14 55 60 82 64 11 45 11 29 44 06 81 50 36 44 52 00 42 31 63 24 66 58 50 35 49 25 79 76 47 48 90 30 60 63 25 36 55 24 90 18 25 94 31 70 52 81 56 53 44 06 53 23 93 43 78 06 09 17 50 63 82 67 12 30 80 56 74 25 10 72 23 62 Dec (J.2000) dd:mm:ss.s + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 20: 14: 13: 01: 16: 02: 10: 49: 02: 10: 02: 10: 01: 14: 14: 33: 13: 09: 13: 13: 13: 13: 15: 28: 14: 06: 17: 14: 07: 04: 05: 03: 11: 14: 05: 14: 04: 05: 12: 09: 04: 15: 11: 09: 15: 05: 11: 06: 16: 06: 07: 16: 12: 07: 06: 31: 08: 07: 07: 11: 12: 05: 04: 10: 16: 07: 12: 10: 07: 03: 15: 13: 12: 12: 03: 07: 08: 09: 04: 06: 24: 58: 03: 38: 51: 34: 41: 22: 52: 51: 17: 54: 01: 11: 01: 35: 54: 08: 18: 37: 19: 10: 24: 05: 13: 52: 41: 12: 38: 43: 30: 36: 23: 35: 28: 06: 44: 02: 33: 32: 48: 19: 49: 15: 22: 04: 43: 57: 11: 41: 12: 02: 36: 31: 32: 19: 26: 42: 53: 44: 55: 01: 28: 13: 39: 27: 33: 25: 40: 06: 56: 36: 57: 55: 53: 35: 26. 16. 03. 36. 20. 28. 15. 56. 32. 43. 41. 57. 58. 01. 44. 50. 26. 05. 05. 57. 25. 31. 26. 31. 59. 55. 49. 39. 31. 05. 23. 19. 40. 22. 05. 53. 25. 00. 27. 36. 58. 16. 03. 56. 20. 01. 04. 54. 19. 14. 12. 36. 18. 28. 26. 17. 08. 03. 40. 15. 13. 28. 30. 00. 12. 00. 43. 32. 17. 47. 17. 46. 46. 39. 52. 08. 04. 03. 0 2 7 4 0 4 8 3 0 4 8 5 9 2 3 4 3 6 4 8 5 0 3 1 4 2 4 8 2 1 5 7 0 2 4 9 1 2 3 8 7 5 4 9 6 5 7 2 9 7 6 1 1 6 9 8 9 1 4 4 1 3 2 5 0 1 5 6 4 3 3 0 4 5 7 4 6 0 Type 12 5 5 3 4 3 5 6 10 1 7 10 1 4 7 1 6 8 7 5 7 5 6 1 7 3 5 1 7 9 7 8 8 7 3 7 6 4 3 5 8 4 4 6 6 1 8 0 1 5 10 1 4 8 13 7 7 0 3 1 0 12 3 5 3 8 5 6 8 9 9 5 0 4 5 8 8 1 Flag100 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 F100 Jy 2.04 0.986 1.479 15.308 1.89 0.674 1.791 23.375 6.575 1.703 12.906 10.83 1.653 28.035 1.686 2.028 3.312 7.801 20.43 18.247 3.222 1.077 10.131 1.447 111.145 0.859 0.544 0.283 2.069 1.021 1.011 2.676 6.137 14.297 1.059 17.551 102.907 1.012 1.045 4.524 1.385 6.626 4.293 5.544 87.905 1.473 3.122 0.111 0.957 4.339 0.595 0.853 2.01 0.552 1.695 1.661 1.602 0.703 3.107 2.143 1.014 1.801 1.92 3.723 12.722 5.804 18.998 2.168 2.383 2.257 3.96 18.263 2.154 3.781 6.307 3.24 2.224 0.704 100 Jy 0.223 0.192 0.57 0.97 0.293 0.137 0.191 2.26 1.5 0.293 2.2 1.126 0.0 2.497 0.23 0.348 0.404 0.45 1.226 1.559 0.323 0.067 0.529 0.0 6.099 0.125 0.0 0.0 0.504 0.143 0.167 0.347 0.495 0.758 0.149 1.098 5.799 0.095 0.0 0.534 0.287 0.487 0.454 0.322 6.335 0.397 0.66 0.0 0.0 0.267 0.115 0.114 0.309 0.19 0.259 0.504 0.289 0.0 0.198 0.0 0.074 0.195 0.534 0.391 0.736 0.429 1.033 0.348 0.221 0.363 0.53 0.974 0.0 0.552 0.405 0.376 0.417 0.0 Flag160 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 F160 Jy 2.802 1.583 2.875 17.08 1.683 0.48 2.595 30.458 9.4 1.831 14.472 15.005 2.248 45.141 2.382 2.87 5.238 8.137 25.125 33.198 5.373 1.304 14.106 1.831 141.58 1.039 0.385 0.256 2.238 1.499 1.313 3.376 7.821 22.151 1.002 30.598 118.6 1.014 1.366 7.711 1.611 8.675 7.038 8.633 123.549 2.938 6.081 0.109 1.896 6.305 1.331 0.502 2.918 1.263 1.396 2.545 2.763 0.434 3.891 2.027 0.896 2.078 3.115 7.037 11.722 8.478 19.916 3.319 2.886 3.973 6.539 26.98 0.579 4.395 6.358 4.547 2.702 0.545 160 Jy 0.442 0.428 0.68 1.267 0.158 0.109 0.179 1.966 1.357 0.266 2.443 1.774 0.0 2.893 0.199 0.42 0.536 0.444 1.338 2.559 0.362 0.079 0.736 0.0 7.52 0.113 0.0 0.0 0.466 0.115 0.132 0.391 0.501 1.142 0.139 1.62 6.85 0.086 0.0 0.477 0.269 0.606 0.533 0.506 7.21 0.336 0.82 0.0 0.0 0.35 0.109 0.123 0.29 0.136 0.158 0.371 0.274 0.0 0.22 0.0 0.067 0.25 0.833 0.498 0.674 0.449 1.193 0.346 0.191 0.552 0.826 1.385 0.356 0.543 0.416 0.465 0.448 0.0 a arcsec 78. 108. 105. 126. 58. 47. 50. 226. 160. 68. 210. 225. 91. 411. 102. 104. 206. 82. 151. 383. 144. 39. 84. 87. 258. 68. 50. 44. 88. 81. 77. 181. 166. 101. 91. 271. 277. 57. 109. 161. 79. 214. 214. 107. 330. 148. 246. 22. 86. 109. 79. 40. 84. 65. 82. 150. 136. 78. 74. 122. 40. 77. 129. 148. 109. 157. 214. 92. 91. 121. 142. 166. 130. 123. 79. 91. 103. 86. b arcsec 76. 52. 86. 93. 54. 45. 37. 75. 101. 51. 163. 79. 91. 109. 51. 85. 51. 37. 84. 91. 47. 30. 49. 87. 235. 36. 50. 44. 88. 39. 34. 37. 52. 75. 30. 59. 225. 36. 109. 47. 60. 52. 49. 46. 293. 42. 61. 22. 86. 44. 39. 40. 62. 65. 58. 49. 36. 78. 37. 122. 39. 45. 104. 74. 54. 44. 52. 76. 39. 41. 58. 49. 114. 74. 66. 85. 98. 86. P.A. degree -4. -35. 15. 5. -75. -30. 45. -17. -17. -30. -75. 30. 0. -25. -60. 0. 0. -60. 75. 19. 55. -88. -75. 0. 60. 45. 0. 0. 3. 15. 70. 1. -20. -40. 40. -3. -18. -10. 0. 25. -10. -10. -37. -70. 30. 53. 64. 0. 0. -50. 15. -0. 70. 30. 22. -75. 40. 0. 80. 0. 90. -45. -20. -25. 20. -25. 90. -55. -20. -50. -55. 90. -50. 15. 76. -35. -15. 0. Proposal ID OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 OT1 acrocker 1 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT rkennicu 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01

L. Cortese et al.

c 0000 RAS, MNRAS 000, 000­000

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Table 1 ­ Continued. HRS 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 C GC G 99-054 42-106 42-107 70-090 42-111 70-093 70-098 70-097 70-099 42-117 70-100 70-104 70-108 99-063 99-062 70-111 99-065 42-124 70-116 70-115 70-121 42-132 42-134 70-125 70-129 70-133 42-139 70-139 70-140 42-141 129-005 42-144 99-075 99-077 99-076 99-078 70-152 70-157 14-063 99-087 70-167 70-168 159-016 99-090 42-155 42-156 70-173 42-158 42-159 14-068 42-162 99-093 99-096 0 70-182 70-184 99-098 129-010 70-186 70-189 70-188 70-192 42-178 70-195 70-197 42-183 70-199 42-186 42-187 70-202 42-191 14-091 0 70-204 99-106 70-206 70-213 70-216 VCC 958 957 971 979 1002 1003 1030 1043 1047 1048 1062 1086 1091 0 1110 1118 1126 1145 1154 1158 1190 1205 1226 1231 1253 1279 1290 1316 1326 1330 0 1375 1379 1393 1401 1410 1419 1450 0 1479 1508 1516 0 1532 1535 1540 1549 1554 1555 1562 1575 1588 1615 0 1619 1632 0 0 1664 1673 1676 1690 1692 1720 1727 1730 1757 1758 1760 1778 1780 0 0 1809 1811 1813 1859 1868 UGC 7551 7549 7556 7561 7566 7568 7575 7574 7581 7579 7583 7587 7590 7595 7594 7600 7602 7609 7614 7613 7622 7627 7629 7631 7638 7645 7647 7654 7657 7656 7662 7668 7669 7676 7675 7677 7682 7695 7694 7703 7709 7711 7714 7716 7718 7721 7728 7726 7727 7732 7736 7742 7753 0 7757 7760 7768 7772 7773 7777 7776 7786 7785 7793 7796 7794 7803 7802 7804 7817 7821 7819 0 7825 7826 7828 7839 7843 NGC 4419 4420 4423 4424 4430 4429 4435 4438 4440 0 4442 4445 0 0 4450 4451 0 4457 4459 4461 4469 4470 4472 4473 4477 4478 4480 4486 4491 4492 4494 4505 4498 0 4501 4502 4506 0 4517 4516 4519 4522 4525 0 4526 4527 0 4532 4535 4536 0 4540 4548 4546 4550 4552 4561 4565 4564 4567 4568 4569 4570 4578 4579 4580 4584 0 4586 0 4591 4592 0 0 4595 4596 4606 4607 IC 0 0 0 0 0 0 0 0 0 0 0 0 0 3391 0 0 3392 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 797 0 0 0 3476 0 0 0 0 0 800 0 0 3510 0 0 0 3521 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3611 0 0 0 3631 0 0 0 0 R.A. (J.2000) hh:mm:ss.ss 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 26: 26: 27: 27: 27: 27: 27: 27: 27: 27: 28: 28: 28: 28: 28: 28: 28: 28: 29: 29: 29: 29: 29: 29: 30: 30: 30: 30: 30: 30: 31: 31: 31: 31: 31: 32: 32: 32: 32: 33: 33: 33: 33: 33: 34: 34: 34: 34: 34: 34: 34: 34: 35: 35: 35: 35: 36: 36: 36: 36: 36: 36: 36: 37: 37: 37: 38: 38: 38: 39: 39: 39: 39: 39: 39: 39: 40: 41: 56. 58. 08. 11. 26. 26. 40. 45. 53. 55. 03. 15. 18. 27. 29. 40. 43. 59. 00. 03. 28. 37. 46. 48. 02. 17. 26. 49. 57. 59. 24. 39. 39. 54. 59. 03. 10. 41. 45. 07. 30. 39. 51. 56. 03. 08. 14. 19. 20. 27. 39. 50. 26. 29. 30. 39. 08. 20. 26. 32. 34. 49. 53. 30. 43. 48. 17. 20. 28. 04. 12. 18. 22. 48. 51. 55. 57. 12. 43 48 97 59 41 56 49 59 57 39 89 94 77 28 63 55 26 01 03 01 03 78 76 87 17 42 78 42 13 74 03 21 57 76 22 35 53 88 59 56 25 66 19 66 03 50 79 33 31 13 42 87 43 51 61 88 14 78 99 71 26 80 40 55 52 40 89 82 44 14 44 74 26 02 91 94 56 41 Dec (J.2000) dd:mm:ss.s +15:02:50.7 +02:29:39.7 +05:52:48.6 +09:25:14.0 +06:15:46.0 +11:06:27.1 +13:04:44.2 +13:00:31.8 +12:17:35.6 +05:43:16.4 +09:48:13.0 +09:26:10.7 +08:43:46.1 +18:24:55.1 +17:05:05.8 +09:15:32.2 +14:59:58.2 +03:34:14.2 +13:58:42.9 +13:11:01.5 +08:44:59.7 +07:49:27.1 +08:00:01.7 +13:25:45.7 +13:38:11.2 +12:19:42.8 +04:14:47.3 +12:23:28.0 +11:29:00.8 +08:04:40.6 +25:46:29.9 +03:56:22.1 +16:51:10.1 +15:07:26.2 +14:25:13.5 +16:41:15.8 +13:25:10.6 +14:03:01.8 +00:06:54.1 +14:34:29.8 +08:39:17.1 +09:10:29.5 +30:16:39.1 +15:21:17.4 +07:41:56.9 +02:39:13.7 +11:04:17.7 +06:28:03.7 +08:11:51.9 +02:11:16.4 +07:09:36.0 +15:33:05.2 +14:29:46.8 -03:47:35.5 +12:13:15.4 +12:33:21.7 +19:19:21.4 +25:59:15.6 +11:26:21.5 +11:15:28.8 +11:14:20.0 +13:09:46.3 +07:14:48.0 +09:33:18.4 +11:49:05.5 +05:22:06.4 +13:06:35.5 +07:53:28.7 +04:19:08.8 +13:21:48.7 +06:00:44.3 -00:31:55.2 -05:39:53.3 +12:58:26.1 +15:17:52.1 +10:10:33.9 +11:54:43.6 +11:53:11.9 Type 3 6 10 3 5 1 1 5 3 10 1 4 6 8 4 6 5 5 1 1 2 3 0 0 1 0 7 0 3 3 0 11 9 7 5 8 3 12 8 4 9 8 8 7 1 6 -2 12 7 6 15 8 5 1 1 0 10 5 0 6 6 4 1 1 5 3 3 10 3 5 5 10 13 5 5 1 3 5 Flag100 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 0 1 1 0 0 1 0 1 1 1 1 1 2 1 1 1 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 0 2 2 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 F100 Jy 17.548 7.145 0.928 6.7 4.205 4.848 4.72 11.949 0.992 0.905 1.685 1.215 0.935 1.39 9.713 4.509 4.083 10.527 4.355 1.165 3.158 4.592 1.317 0.214 1.221 0.127 4.369 0.693 2.644 1.181 0.37 12.509 4.308 2.238 74.118 0.633 0.403 3.138 28.254 1.184 8.617 4.664 1.015 1.256 15.632 75.281 0.116 15.489 34.851 56.393 2.733 5.468 13.601 0.513 0.516 0.724 2.505 55.365 0.291 14.15 47.991 31.332 1.339 1.607 25.583 5.049 0.523 0.346 2.206 0.044 1.717 5.65 0.111 0.368 3.515 1.102 2.524 8.108 100 Jy 1.121 0.436 0.178 0.438 0.583 1.025 0.304 0.863 0.0 0.208 0.0 0.139 0.088 0.212 3.046 0.257 0.632 0.664 0.25 0.0 0.282 0.246 0.0 0.0 0.101 0.0 0.319 0.182 0.217 0.276 0.037 2.008 0.549 0.304 5.57 0.163 0.049 0.314 1.875 0.0 0.893 0.381 0.487 0.546 0.827 3.999 0.0 0.835 3.113 3.262 0.481 0.398 5.576 0.132 0.096 0.0 0.299 4.659 0.0 0.743 2.419 2.268 0.0 0.0 3.355 0.335 0.228 0.139 0.53 0.025 0.217 0.713 0.0 0.0 0.327 0.113 0.289 0.768 Flag160 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 0 1 1 0 0 1 0 1 1 1 1 1 2 1 1 1 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 0 2 2 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 F160 Jy 18.421 9.352 1.4 6.132 7.142 5.509 4.484 15.454 0.972 1.342 1.393 2.378 0.916 2.187 14.263 4.894 5.039 10.627 4.049 0.869 4.171 4.981 1.438 0.179 1.285 0.115 5.391 0.82 2.265 1.979 0.313 15.141 6.629 2.67 104.85 0.854 0.583 3.928 48.955 1.282 10.184 6.095 2.011 1.533 17.282 93.527 0.114 15.638 61.656 58.539 3.017 6.779 24.022 0.632 0.486 0.498 2.426 90.833 0.268 19.184 59.217 42.761 2.675 0.94 38.766 7.3 1.259 0.612 2.806 0.194 2.468 6.237 0.113 0.357 3.768 0.897 2.9 10.674 160 Jy 0.992 0.608 0.347 0.381 0.79 0.593 0.302 1.09 0.0 0.223 0.0 0.181 0.12 0.32 3.336 0.269 0.426 0.834 0.226 0.0 0.323 0.308 0.0 0.0 0.127 0.0 0.353 0.156 0.196 0.283 0.046 3.227 0.617 0.262 5.821 0.212 0.062 0.363 2.661 0.0 0.763 0.44 0.377 0.226 0.88 4.864 0.0 0.953 3.907 3.082 0.367 0.528 3.148 0.121 0.125 0.0 0.293 5.143 0.0 0.976 2.974 2.608 0.0 0.0 2.589 0.501 0.201 0.145 0.514 0.038 0.226 0.875 0.0 0.0 0.323 0.125 0.28 0.752 a arcsec 148. 86. 107. 85. 94. 169. 83. 134. 84. 78. 121. 93. 58. 64. 258. 82. 123. 95. 40. 84. 85. 77. 92. 36. 56. 22. 84. 58. 79. 82. 26. 200. 120. 71. 304. 62. 36. 95. 462. 90. 151. 170. 126. 82. 71. 246. 22. 112. 270. 304. 84. 79. 252. 57. 83. 65. 77. 596. 38. 87. 93. 259. 84. 90. 264. 83. 82. 64. 182. 25. 82. 242. 22. 46. 91. 40. 66. 164. b arcsec 58. 51. 42. 80. 90. 78. 77. 118. 84. 36. 121. 33. 37. 50. 170. 41. 49. 95. 40. 84. 48. 48. 92. 36. 44. 22. 60. 57. 39. 82. 26. 158. 64. 47. 162. 33. 29. 73. 86. 90. 109. 42. 67. 60. 68. 79. 22. 51. 232. 138. 59. 67. 210. 37. 23. 65. 63. 80. 38. 41. 53. 157. 84. 90. 205. 73. 44. 33. 49. 20. 37. 63. 22. 46. 60. 40. 57. 57. P.A. degree -47. 8. 20. -80. -60. -81. 10. 27. 0. -50. 0. -75. -5. -85. -9. -10. 40. -15. 0. 0. 85. 0. 0. 0. 35. 0. -10. -21. -32. 75. 0. 70. -55. -72. -40. 40. -75. 30. 80. 0. -28. 33. 65. -30. -17. 67. 0. -14. 0. -40. 18. -35. -30. 80. -2. 0. -70. -45. 0. 75. 33. 23. 0. 0. -80. -20. 20. 55. -65. -65. 40. -85. 0. 0. -70. 0. 33. 4. Proposal ID OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 OT2 emurph01 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 OT1 lcortese 1 KPOT jdavie01 KPOT rkennicu 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 OT1 lcortese 1 OT1 lcortese 1 KPOT jdavie01 KPOT jdavie01 KPOT jdavie01 KPOT rkennicu 1 OT1 lcortese 1 OT1 lcortese 1 KPOT rkennicu 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1 OT1 lcortese 1

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20

Table 1 ­ Continued. HRS 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 C GC G 70-214 42-205 70-223 42-208 14-109 99-112 70-229 43-002 70-230 15-008 71-015 71-016 100-004 71-019 71-023 71-026 43-018 15-015 15-016 15-019 71-043 43-028 15-023 71-045 0 43-034 100-011 43-040 43-041 129-027 15-027 0 0 129-028 71-060 71-062 15-029 100-015 71-065 15-031 15-032 0 71-068 43-060 71-071 15-037 43-066 43-068 43-069 43-071 0 15-049 71-092 15-055 0 0 189-037 217-031 218-010 16-069 246-017 73-054 190-041 246-023 218-047 45-108 218-058 17-088 45-137 295-024 46-001 46-003 46-007 46-009 46-011 272-031 47-010 47-012 VCC 1869 1883 1903 1923 0 1932 1938 1939 1943 0 1972 1978 0 1987 2000 2006 0 0 0 0 2058 0 0 2070 0 0 0 0 0 0 0 0 0 0 0 2092 0 0 2095 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 UGC 7842 7850 7858 7871 7869 7875 7880 7878 7884 7895 7896 7898 7901 7902 7914 7920 7924 7926 7931 7951 7965 7961 0 7970 0 7975 7980 7982 7985 7989 7991 0 0 8005 8007 8010 8009 8014 8016 8020 8021 0 8022 0 8032 8041 8043 8045 0 8054 0 8078 8102 8121 0 0 8271 8388 8439 8443 8593 8616 8675 8711 8725 8727 8756 8790 8821 8843 8831 8838 8847 8853 8857 9036 9172 9175 NGC 4608 4612 4621 4630 4629 4634 4638 4636 4639 4643 4647 4649 4651 4654 4660 0 4665 4666 4668 4684 4689 4688 4691 4698 4697 4701 4710 0 4713 4725 0 4720 4731 4747 4746 4754 4753 4758 4762 4771 4772 4775 4779 4791 0 0 4799 0 4803 4808 0 4845 4866 4904 4941 4981 5014 5103 5145 5147 0 5248 5273 5301 5303 5300 0 5334 5348 5372 5356 5360 5363 5364 0 5486 5560 5566 IC 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3718 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3908 0 0 0 0 0 0 0 0 0 902 0 0 0 0 0 0 4338 0 0 0 958 0 0 0 0 0 0 R.A. (J.2000) hh:mm:ss.ss 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 12: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 13: 14: 14: 14: 41: 41: 42: 42: 42: 42: 42: 42: 42: 43: 43: 43: 43: 43: 44: 44: 45: 45: 45: 47: 47: 47: 48: 48: 48: 49: 49: 49: 49: 50: 50: 50: 51: 51: 51: 52: 52: 52: 52: 53: 53: 53: 53: 54: 54: 55: 55: 55: 55: 55: 56: 58: 59: 00: 04: 08: 11: 20: 25: 26: 36: 37: 42: 46: 47: 48: 50: 52: 54: 54: 54: 55: 56: 56: 56: 07: 20: 20: 13. 32. 02. 31. 32. 40. 47. 49. 52. 20. 32. 40. 42. 56. 31. 45. 05. 08. 32. 17. 45. 46. 13. 22. 35. 11. 38. 50. 57. 26. 38. 42. 01. 45. 55. 17. 22. 44. 56. 21. 29. 45. 50. 43. 44. 12. 15. 23. 33. 48. 40. 01. 27. 58. 13. 48. 31. 30. 13. 19. 01. 32. 08. 24. 44. 16. 35. 54. 11. 46. 58. 38. 07. 12. 26. 24. 05. 19. 29 76 32 15 67 96 43 87 37 14 45 01 63 58 97 99 96 59 14 52 56 46 63 92 91 56 96 19 87 61 96 78 09 96 37 56 11 04 05 27 17 70 86 97 19 68 53 62 67 94 62 19 14 67 14 74 16 08 92 71 22 07 34 61 97 04 89 46 27 01 46 75 21 00 61 97 42 95 Dec (J.2000) dd:mm:ss.s +10:09:20.9 +07:18:53.2 +11:38:48.9 +03:57:37.3 -01:21:02.4 +14:17:45.0 +11:26:32.9 +02:41:16.0 +13:15:26.9 +01:58:42.1 +11:34:57.4 +11:33:09.4 +16:23:36.2 +13:07:36.0 +11:11:25.9 +12:21:05.2 +03:03:20.5 -00:27:42.8 -00:32:05.0 -02:43:38.6 +13:45:46.1 +04:20:09.9 -03:19:57.8 +08:29:14.3 -05:48:03.1 +03:23:19.4 +15:09:55.8 +02:51:10.4 +05:18:41.1 +25:30:02.7 +01:27:52.3 -04:09:21.0 -06:23:35.0 +25:46:38.3 +12:04:58.9 +11:18:49.2 -01:11:58.9 +15:50:55.9 +11:13:50.9 +01:16:09.0 +02:10:06.0 -06:37:19.8 +09:42:35.7 +08:03:10.7 +13:14:14.2 +00:07:00.0 +02:53:47.9 +07:54:34.0 +08:14:25.8 +04:18:14.7 -07:33:46.1 +01:34:33.0 +14:10:15.8 -00:01:38.8 -05:33:05.8 -06:46:39.1 +36:16:54.9 +43:05:02.3 +43:16:02.2 +02:06:02.7 +49:57:39.0 +08:53:06.2 +35:39:15.2 +46:06:26.7 +38:18:16.4 +03:57:03.1 +42:32:29.5 -01:06:52.7 +05:13:38.8 +58:39:59.4 +05:20:01.4 +04:59:06.2 +05:15:17.2 +05:00:52.1 +04:23:48.0 +55:06:11.1 +03:59:28.4 +03:56:00.9 Type 1 1 0 12 11 8 1 0 6 2 7 0 7 8 0 5 2 7 9 1 6 8 3 4 0 8 1 9 9 4 9 13 8 8 5 1 13 12 1 9 3 9 6 17 5 9 5 12 17 8 9 4 1 8 4 6 3 4 5 10 5 6 1 6 13 7 4 7 6 5 6 13 13 6 5 11 5 4 Flag100 0 0 0 1 1 1 0 1 1 1 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 F100 Jy 2.29 0.343 0.877 5.408 0.695 11.903 0.642 0.31 6.587 0.673 17.159 0.243 17.873 41.7 0.142 0.208 2.45 99.531 1.662 2.112 12.633 3.409 23.132 3.278 1.376 6.584 13.653 1.179 11.675 25.625 0.326 2.061 8.201 3.826 11.969 3.468 8.061 3.233 12.944 4.318 1.197 10.521 4.501 0.376 1.098 1.769 3.51 0.446 0.118 15.894 16.823 22.761 0.961 6.998 5.335 12.715 4.237 0.93 12.76 6.929 2.84 59.271 1.02 9.13 5.863 5.027 0.628 5.009 1.507 4.719 3.403 0.236 5.3 18.365 0.087 1.185 4.257 7.067 100 Jy 0.0 0.0 0.0 0.703 0.179 0.702 0.0 0.07 0.759 1.005 1.265 0.0 1.553 2.59 0.0 0.045 0.0 5.076 0.424 0.176 3.503 1.426 1.206 0.908 0.131 1.499 0.771 0.335 1.373 5.416 0.136 0.243 2.776 1.103 0.675 0.0 1.914 0.449 0.0 0.802 0.235 0.813 0.433 0.095 0.472 0.755 0.251 0.094 0.0 0.959 0.883 1.473 0.31 0.774 0.983 0.947 0.276 0.0 0.763 0.585 0.302 6.469 0.342 0.952 0.378 1.139 0.104 1.236 0.52 0.292 0.489 0.105 1.69 3.444 0.019 0.135 0.395 1.771 Flag160 0 0 0 1 1 1 0 1 1 1 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 F160 Jy 1.576 0.579 0.512 6.54 0.581 13.602 0.369 0.32 7.273 3.354 24.35 0.605 22.95 55.404 0.142 0.088 2.556 113.011 1.726 1.58 18.399 3.476 20.28 4.883 0.849 7.759 15.533 2.729 12.858 49.023 1.059 2.044 12.794 6.215 13.585 2.459 11.83 4.223 10.721 7.264 3.001 10.513 4.355 0.69 1.506 4.518 3.967 0.632 0.133 19.757 17.731 27.136 1.54 9.004 9.141 16.561 3.989 0.46 12.629 8.435 3.614 76.825 0.913 13.649 6.448 7.654 0.853 8.024 1.961 3.354 5.721 0.489 7.018 30.263 0.158 1.071 6.346 12.277 160 Jy 0.0 0.0 0.0 0.611 0.234 0.771 0.0 0.066 0.849 0.916 1.408 0.0 1.833 3.425 0.0 0.025 0.0 5.791 0.4 0.125 3.807 0.613 1.095 0.894 0.132 1.956 0.92 0.355 1.079 5.139 0.099 0.148 2.873 0.992 0.765 0.0 1.406 0.449 0.0 0.829 0.295 0.865 0.403 0.134 0.275 0.564 0.239 0.093 0.0 1.077 0.908 1.842 0.27 0.949 0.965 1.065 0.321 0.0 0.731 0.571 0.288 5.363 0.103 0.834 0.385 1.211 0.169 1.589 0.535 0.374 0.553 0.114 1.311 4.249 0.026 0.135 0.518 1.435 a arcsec 103. 51. 69. 97. 50. 119. 48. 37. 134. 107. 109. 45. 164. 210. 22. 29. 108. 198. 100. 50. 246. 107. 83. 149. 40. 151. 104. 98. 134. 420. 72. 58. 278. 166. 93. 120. 203. 129. 208. 171. 118. 90. 88. 50. 116. 130. 73. 38. 22. 111. 91. 218. 197. 115. 152. 116. 64. 60. 84. 93. 94. 260. 57. 182. 65 163. 58. 175. 154. 62. 133. 83. 171. 284. 20. 45. 149. 197. b arcsec 103. 51. 69. 67. 45. 51. 48. 35. 84. 104. 91. 45. 116. 109. 22. 24. 108. 81. 52. 47. 186. 98. 74. 74. 40. 126. 61. 35. 91. 385. 26. 44. 136. 76. 52. 120. 121. 58. 208. 66. 44. 84. 77. 34. 39. 80. 39. 30. 22. 70. 44. 69. 28. 104. 82. 86. 52. 60. 75. 77. 47. 188. 56. 72. 53 108. 32. 127. 40. 58. 51. 29. 110. 184. 20. 44. 51. 103. P.A. degree 0. 0. 0. 10. 80. -24. 0. 0. -57. -45. -75. 0. 80. -52. 0. 72. 0. 44. 5. 20. -16. 35. -75. -15. 0. 40. 27. 0. -70. 35. -10. -65. 90. 30. -60. 0. -75. -20. 0. -45. -35. 50. 10. 65. -15. -23. 90. -75. 0. -53. -10. 80. 87. -35. 15. -31. -78. 0. 85. -55. -20. -40. -85. -30. 85. -40. 85. 40. -3. 40. 12. 70. -50. 30. -0. -55. -65. 35. Proposal ID O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 KPOT O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 O T1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 rkennicu 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1 lcortese 1

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Table 1 ­ Continued. HRS 312 313 314 315 316 317 318 319 320 321 322 323 C GC G 47-020 47-022 19-012 220-015 47-063 47-066 47-070 75-064 47-090 47-123 47-127 48-004 VCC 0 0 0 0 0 0 0 0 0 0 0 0 UGC 9183 9187 9215 9242 9308 9311 9328 9353 9363 9427 9436 9483 NGC 5576 5577 0 0 5638 0 5645 5669 5668 5692 5701 0 IC 0 0 0 0 0 1022 0 0 0 0 0 1048 R.A. (J.2000) hh:mm:ss.ss 14: 14: 14: 14: 14: 14: 14: 14: 14: 14: 14: 14: 21: 21: 23: 25: 29: 30: 30: 32: 33: 38: 39: 42: 03. 13. 27. 21. 40. 01. 39. 43. 24. 18. 11. 57. 68 11 12 02 39 85 35 88 34 12 06 88 Dec (J.2000) dd:mm:ss.s + + + + + + + + + + + + 03: 03: 01: 39: 03: 03: 07: 09: 04: 03: 05: 04: 16: 26: 43: 32: 14: 46: 16: 53: 27: 24: 21: 53: 15. 08. 34. 22. 00. 22. 30. 30. 01. 37. 48. 24. 6 8 7 5 2 3 3 5 6 2 8 5 Type 0 6 9 7 0 5 9 8 9 5 3 5 Flag100 0 1 1 1 0 1 1 1 1 1 1 1 F100 Jy 0.236 2.55 2.772 1.056 0.15 0.222 4.998 6.923 7.735 2.942 1.453 5.689 100 Jy 0.0 0.802 0.417 0.409 0.0 0.1 0.406 0.996 2.205 0.17 1.035 0.391 Flag160 0 1 1 1 0 1 1 1 1 1 1 1 F160 Jy 0.187 3.803 3.316 0.863 0.169 0.475 6.331 8.145 10.256 3.164 1.859 7.547 160 Jy 0.0 0.819 0.23 0.327 0.0 0.062 0.483 1.192 1.478 0.179 1.201 0.575 a arcsec 31. 154. 95. 176. 24. 34. 101. 167. 152. 50. 124. 101. b arcsec 31. 65. 63. 29. 24. 28. 63. 118. 145. 33. 120. 47. P.A. degree 0. 55. -15. 71. 0. -15. -75. 61. 17. 40. -90. -17. Proposal ID O O O O O O O O O O O O T1 T1 T1 T1 T1 T1 T1 T1 T1 T1 T1 T1 lcortes lcortes lcortes lcortes lcortes lcortes lcortes lcortes lcortes lcortes lcortes lcortes e e e e e e e e e e e e 1 1 1 1 1 1 1 1 1 1 1 1

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L. Cortese et al.

Table 3: Best-fitting dust temperatures and masses for a single modified black-body with =2 and =free.Only galaxies for which the reduced 2 corresponds to a probability P 95% are shown. HRS D Mpc 1 2 5 6 7 8 9 11 12 13 15 16 17 18 19 21 22 23 24 26 27 28 29 30 31 33 34 36 37 38 39 40 41 42 44 46 47 48 50 51 52 53 54 55 57 59 60 61 62 63 64 65 66 67 69 16. 18. 16. 18. 18. 19. 20. 18. 19. 22. 18. 18. 18. 22. 23. 16. 20. 21. 22. 22. 24. 19. 15. 15. 19. 20. 16. 21. 19. 20. 22. 22. 18. 17. 16. 21. 21. 16. 21. 18. 17. 15. 17. 16. 16. 24. 15. 17. 22. 18. 17. 19. 20. 20. 16. 79 44 71 89 77 37 21 93 89 47 57 00 30 91 29 89 20 44 64 41 77 03 73 79 63 46 14 94 61 27 24 63 61 04 01 34 53 50 43 56 20 14 77 54 51 53 14 39 44 41 33 76 97 51 73 21. 24. 22. 13. 25. 15. 21. 23. 21. 19. 19. 21. 20. 21. 20. 23. 20. 24. 21. 20. 19. 23. 21. 19. 26. 22. 18. 23. 18. 20. 23. 24. 20. 21. T K 7+1.0 -1.0 0+0.6 -0.6 4+0.4 -0.4 9+0.8 -0.8 7+0.3 -0.3 3+0.8 -0.7 8+0.9 -0.9 6+0.7 -0.7 8+0.3 -0.3 2+0.7 -0.7 7+0.4 -0.4 2+0.4 -0.4 7+0.7 -0.7 0+0.6 -0.6 4+0.9 -0.8 3+0.3 -0.3 5+0.5 -0.5 5+0.6 -0.6 4+0.3 -0.3 2+0.6 -0.6 5+0.7 -0.7 1+0.7 -0.7 3+0.4 -0.4 1+0.5 -0.5 3+0.4 -0.4 6+0.4 -0.4 3+1.0 -1.1 7+0.4 -0.4 8+0.7 -0.7 5+0.7 -0.7 3+0.6 -0.6 5+0.4 -0.4 2+0.9 -0.9 5+0.5 -0.5 9+1.3 -1.4 1+0.9 -0.9 9+0.4 -0.4 9+0.3 -0.3 6+0.4 -0.4 3+0.4 -0.4 3+0.8 -0.8 7+0.5 -0.5 7+0.9 -0.9 5+1.2 -1.2 9+0.2 -0.2 9+0.9 -0.9 0+1.2 -1.2 =2 log(M M 5. 6. 6. 6. 6. 7. 6. 5. 7. 7. 7. 7. 6. 6. 6. 7. 7. 6. 6. 6. 6. 7. 6. 7. 7. 6. 6. 6. 6. 7. 6. 6. 6. 7. =free T K 21. 21. 20. 16. 23. 20. 18. 23. 31. 22. 20. 20. 23. 21. 25. 29. 26. 24. 21. 29. 23. 23. 24. 29. 22. 21. 26. 22. 26. 24. 25. 23. 22. 30. 24. 25. 22. 22. 26. 22. 24. 21. 21. 20. 22. 21. 24. 26. 20. 23. 27. 23. 21. 5+3.8 -3.1 6+1.9 -1.6 9+1.0 -1.0 6+5.8 -4.0 9+0.8 -0.8 9+3.6 -3.2 9+2.4 -2.0 7+1.0 -1.0 9+6.0 -4.3 5+0.7 -0.7 8+2.7 -2.3 0+1.3 -1.2 6+1.4 -1.3 3+2.3 -2.0 3+2.7 -2.3 3+8.8 -5.7 1+7.4 -4.6 1+0.8 -0.8 8+1.4 -1.3 2+4.9 -3.7 3+1.9 -1.7 2+2.7 -2.3 2+3.6 -2.9 4+4.1 -3.2 7+1.4 -1.3 8+1.6 -1.5 3+1.2 -1.1 5+1.5 -1.3 2+3.2 -2.7 7+4.4 -3.5 5+1.7 -1.5 9+3.2 -2.7 7+2.4 -2.1 1+3.8 -3.0 0+1.4 -1.2 3+4.0 -3.1 0+1.9 -1.7 9+0.7 -0.7 0+2.1 -1.8 1+4.6 -3.6 3+1.5 -1.4 9+3.0 -2.6 4+1.3 -1.2 4+1.0 -0.9 2+1.8 -1.6 1+1.2 -1.1 0+3.6 -2.9 8+3.9 -3.1 1+1.6 -1.5 4+4.0 -3.3 6+6.4 -4.6 2+4.1 -3.2 5+5.1 -3.8

dust

) 2. 2. 2. 1. 2. 1. 2. 1. 1. 1. 1. 1. 1. 1. 1. 0. 1. 1. 1. 0. 2. 1. 1. 1. 1. 1. 2. 2. 1. 1. 1. 1. 1. 1. 2. 1. 1. 2. 1. 1. 1. 1. 1. 2. 1. 2. 1. 1. 1. 1. 1. 1. 1.

0+0.5 -0.5 3+0.3 -0.3 2+0.2 -0.2 4+1.0 -0.8 2+0.1 -0.1 3+0.4 -0.3 5+0.4 -0.4 6+0.1 -0.1 2+0.4 -0.3 9+0.1 -0.1 7+0.3 -0.3 9+0.2 -0.2 7+0.1 -0.1 9+0.3 -0.3 5+0.2 -0.2 8+0.5 -0.4 2+0.6 -0.6 9+0.1 -0.1 8+0.2 -0.2 9+0.3 -0.3 2+0.2 -0.2 6+0.3 -0.3 4+0.3 -0.3 3+0.3 -0.3 8+0.2 -0.2 6+0.2 -0.2 0+0.1 -0.1 0+0.2 -0.2 2+0.2 -0.2 1+0.4 -0.4 8+0.2 -0.2 4+0.3 -0.3 7+0.3 -0.3 3+0.3 -0.2 1+0.2 -0.2 3+0.3 -0.3 9+0.3 -0.3 2+0.1 -0.1 4+0.2 -0.2 8+0.5 -0.5 5+0.1 -0.1 8+0.3 -0.3 9+0.2 -0.2 1+0.1 -0.1 6+0.2 -0.2 0+0.1 -0.1 3+0.4 -0.3 0+0.3 -0.3 8+0.2 -0.2 3+0.4 -0.3 0+0.4 -0.4 2+0.4 -0.4 5+0.5 -0.5

log(M M 5. 6. 6. 6. 6. 7. 6. 6. 5. 7. 7. 7. 7. 6. 6. 5. 5. 7. 7. 6. 6. 6. 6. 6. 6. 6. 7. 6. 6. 6. 6. 6. 7. 5. 6. 6. 7. 7. 6. 6. 6. 6. 7. 7. 7. 6. 6. 6. 7. 6. 6. 6. 6.

dust

)

20. 20. 20. 20. 19. 21. 19. 18. 17. 18. 23. 17. 18.

6. 6. 7. 7. 7. 6. 6. 7. 6. 6. 7. 6. 7.

93+0.07 -0.07 27+0.04 -0.04 62+0.02 -0.02 80+0.11 -0.11 26+0.01 -0.01 48+0.06 -0.06 53+0.06 -0.05 72+0.05 -0.05 57+0.02 -0.02 60+0.06 -0.05 17+0.03 -0.03 17+0.03 -0.03 61+0.05 -0.05 99+0.04 -0.04 15+0.10 -0.10 31+0.02 -0.02 50+0.03 -0.03 56+0.03 -0.03 76+0.02 -0.02 56+0.05 -0.05 71+0.06 -0.06 06+0.04 -0.04 98+0.03 -0.03 07+0.04 -0.04 33+0.02 -0.02 73+0.03 -0.03 65+0.08 -0.07 71+0.02 -0.02 56+0.05 -0.05 32+0.05 -0.05 17+0.04 -0.04 62+0.02 -0.02 83+0.06 -0.06 53+0.04 -0.04 11+0.09 -0.09 71+0.06 -0.05 05+0.03 -0.03 25+0.02 -0.02 24+0.04 -0.04 92+0.03 -0.03 21+0.06 -0.06 39+0.04 -0.04 65+0.08 -0.07 77+0.09 -0.08 33+0.01 -0.01 65+0.08 -0.08 04+0.10 -0.09

94+0.15 -0.14 36+0.07 -0.07 68+0.05 -0.04 57+0.37 -0.33 31+0.03 -0.03 11+0.18 -0.16 66+0.12 -0.12 82+0.04 -0.04 51+0.11 -0.12 54+0.03 -0.03 52+0.12 -0.12 16+0.06 -0.06 08+0.05 -0.05 59+0.10 -0.09 83+0.09 -0.09 85+0.19 -0.20 96+0.18 -0.21 28+0.03 -0.03 44+0.06 -0.06 01+0.11 -0.12 60+0.07 -0.07 44+0.10 -0.10 51+0.12 -0.12 87+0.10 -0.10 93+0.05 -0.05 95+0.07 -0.07 33+0.04 -0.04 73+0.06 -0.06 41+0.10 -0.10 37+0.14 -0.14 65+0.05 -0.05 33+0.12 -0.11 22+0.10 -0.10 97+0.08 -0.09 64+0.05 -0.05 63+0.12 -0.13 51+0.07 -0.07 31+0.03 -0.03 65+0.07 -0.07 05+0.17 -0.17 86+0.06 -0.06 63+0.13 -0.12 02+0.06 -0.06 28+0.05 -0.05 12+0.07 -0.07 92+0.06 -0.05 02+0.12 -0.12 73+0.11 -0.11 31+0.08 -0.08 36+0.15 -0.15 40+0.17 -0.17 40+0.15 -0.15 85+0.22 -0.21

Continued on the next page. . . c 0000 RAS, MNRAS 000, 000­000


PACS photometry of the Herschel Reference Survey
Table 3 ­ Continued. HRS D Mpc 70 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 91 92 93 94 95 96 97 98 99 100 102 106 107 108 109 110 111 112 113 114 115 117 118 119 120 121 122 123 124 127 128 130 131 132 133 134 136 139 23. 22. 15. 15. 18. 15. 20. 18. 21. 17. 17. 17. 17. 17. 15. 17. 17. 17. 17. 17. 17. 15. 17. 17. 17. 17. 17. 17. 17. 17. 23. 17. 23. 17. 17. 17. 23. 17. 17. 17. 23. 17. 17. 17. 23. 17. 17. 17. 23. 23. 17. 23. 23. 17. 23. 23. 23. 10 53 00 83 33 27 83 13 54 00 00 00 60 00 31 00 00 00 00 00 00 59 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 90 00 00 00 20. 24. 19. 23. 15. 18. 22. 19. 19. 17. 22. 23. 19. 21. 21. 22. 20. 19. 19. 21. 24. 22. 18. 22. T K 7+0.6 -0.6 7+1.0 -0.9 3+0.3 -0.3 9+0.4 -0.4 6+0.9 -0.9 8+1.0 -1.0 4+0.3 -0.3 8+0.5 -0.5 9+1.0 -1.0 7+1.1 -1.1 4+0.3 -0.3 4+1.0 -1.0 8+1.3 -1.4 2+0.4 -0.4 4+0.4 -0.4 8+1.1 -1.0 5+0.9 -0.9 6+0.3 -0.3 4+0.6 -0.6 0+0.8 -0.8 5+0.3 -0.3 3+0.3 -0.3 7+0.3 -0.3 5+0.4 -0.4 5+1.2 -1.2 2+0.6 -0.6 6+0.9 -0.9 4+0.8 -0.8 7+0.2 -0.2 9+0.3 -0.3 6+0.6 -0.6 2+0.4 -0.4 4+1.1 -1.1 3+0.5 -0.5 3+0.4 -0.4 4+0.2 -0.2 1+0.3 -0.3 0+0.7 -0.7 9+0.7 -0.7 4+0.3 -0.3 7+0.5 -0.5 5+0.7 -0.7 1+0.8 -0.8 8+0.7 -0.7 4+0.3 -0.3 3+0.6 -0.6 =2 log(M M 6. 6. 7. 6. 6. 6. 7. 6. 6. 6. 7. 6. 6. 6. 7. 6. 7. 7. 6. 6. 6. 7. 7. 6. ) 1. 1. 2. 2. 1. 1. 2. 1. 1. 1. 2. 1. 0. 2. 1. 1. 2. 1. 1. 2. 1. 2. 1. 2. 2. 1. 1. 2. 2. 2. 1. 1. 2. 1. 1. 2. 1. 2. 2. 1. 2. 1. 2. 2. 2. 2. 2. 1. 2. 2. 1. 2. 0. 0. 2. 2. 1. 7+0.2 -0.2 5+0.5 -0.5 2+0.2 -0.2 0+0.2 -0.2 6+0.7 -0.6 1+0.4 -0.4 2+0.1 -0.1 4+0.4 -0.4 4+0.6 -0.6 7+0.6 -0.6 0+0.1 -0.1 7+0.4 -0.4 9+0.4 -0.4 0+0.2 -0.2 8+0.1 -0.1 2+0.2 -0.2 0+0.5 -0.5 3+0.3 -0.3 1+0.1 -0.1 0+0.2 -0.2 6+0.3 -0.3 0+0.5 -0.5 0+0.2 -0.2 2+0.1 -0.1 1+0.1 -0.1 9+0.1 -0.1 4+0.2 -0.2 4+0.2 -0.2 3+0.1 -0.1 3+0.1 -0.1 7+0.5 -0.5 6+0.3 -0.3 2+0.5 -0.4 2+0.2 -0.2 4+0.2 -0.2 3+0.1 -0.1 6+0.4 -0.4 2+0.1 -0.1 0+0.1 -0.1 8+0.3 -0.3 3+0.2 -0.2 2+0.5 -0.4 6+0.3 -0.3 4+0.3 -0.3 1+0.1 -0.1 2+0.2 -0.2 0+0.3 -0.3 8+0.4 -0.3 0+0.1 -0.1 0+0.3 -0.3 7+0.3 -0.3 5+0.6 -0.5 8+0.4 -0.4 6+0.3 -0.3 3+0.4 -0.4 4+0.2 -0.2 4+0.3 -0.3 =free T K 23. 29. 18. 24. 17. 26. 21. 24. 23. 19. 22. 25. 30. 21. 23. 26. 22. 26. 24. 19. 22. 20. 23. 22. 21. 19. 22. 20. 19. 21. 22. 21. 21. 24. 25. 19. 24. 18. 23. 23. 18. 26. 19. 18. 20. 19. 19. 19. 20. 17. 22. 16. 33. 27. 19. 20. 26. 0+2.0 -1.8 5+7.5 -5.0 3+1.1 -1.0 1+1.6 -1.4 4+4.0 -3.2 2+5.0 -3.8 3+0.7 -0.7 0+3.5 -2.7 9+6.2 -4.1 3+4.2 -3.3 8+1.0 -0.9 7+4.3 -3.4 4+8.6 -5.7 0+1.3 -1.2 2+1.3 -1.2 2+3.4 -2.9 5+4.3 -3.2 3+3.8 -3.0 9+1.5 -1.4 8+1.2 -1.1 1+2.4 -2.0 9+3.6 -2.8 5+1.9 -1.7 9+0.9 -0.9 3+0.8 -0.8 1+0.8 -0.8 7+1.5 -1.3 2+1.3 -1.2 8+0.5 -0.5 0+1.0 -0.9 8+4.7 -3.6 8+2.6 -2.2 4+3.1 -2.5 5+2.2 -1.9 4+1.9 -1.7 3+0.5 -0.4 2+3.7 -2.9 7+0.5 -0.5 2+1.0 -0.9 1+2.5 -2.1 7+1.1 -1.0 7+6.2 -4.3 2+1.6 -1.4 4+1.4 -1.3 1+0.7 -0.6 9+1.1 -1.1 2+2.1 -1.9 9+2.4 -2.0 6+0.9 -0.8 8+1.7 -1.5 6+2.7 -2.3 7+2.7 -2.3 8+8.9 -5.8 1+4.9 -4.0 1+2.2 -1.9 0+1.0 -0.9 1+3.4 -2.7 log(M M 6. 6. 7. 6. 6. 5. 7. 6. 6. 6. 7. 6. 5. 6. 7. 6. 6. 7. 7. 7. 6. 6. 6. 6. 7. 7. 6. 6. 7. 8. 6. 6. 6. 6. 6. 7. 6. 7. 7. 5. 7. 6. 6. 7. 7. 8. 6. 6. 7. 6. 6. 6. 6. 6. 6. 6. 6. )

23

dust

dust

20. 19. 22.

6. 6. 6.

21. 19. 22. 21. 20. 20. 22. 20. 20. 21. 19. 18. 20. 17. 20. 19.

6. 7. 7. 6. 7. 6. 6. 6. 7. 8. 6. 6. 7. 6. 6. 6.

20. 22. 21.

6. 6. 6.

64+0.04 -0.04 31+0.06 -0.06 77+0.03 -0.03 95+0.03 -0.03 34+0.11 -0.10 19+0.08 -0.08 93+0.01 -0.01 67+0.05 -0.05 49+0.08 -0.08 84+0.09 -0.09 14+0.02 -0.02 09+0.06 -0.06 00+0.10 -0.10 40+0.03 -0.03 36+0.03 -0.03 15+0.07 -0.07 26+0.06 -0.05 81+0.03 -0.03 59+0.05 -0.05 40+0.07 -0.07 64+0.02 -0.02 31+0.02 -0.02 77+0.02 -0.02 00+0.03 -0.03 74+0.08 -0.08 40+0.05 -0.05 24+0.06 -0.06 34+0.06 -0.06 63+0.01 -0.01 91+0.02 -0.02 04+0.04 -0.05 24+0.03 -0.03 32+0.08 -0.08 82+0.04 -0.04 92+0.04 -0.04 25+0.02 -0.02 09+0.03 -0.03 67+0.05 -0.05 98+0.05 -0.05 14+0.02 -0.02 76+0.04 -0.04 52+0.05 -0.05 55+0.07 -0.07 70+0.05 -0.05 75+0.02 -0.02 59+0.04 -0.04

55+0.08 -0.08 19+0.14 -0.16 83+0.07 -0.07 94+0.05 -0.05 21+0.25 -0.22 89+0.14 -0.15 98+0.03 -0.03 49+0.12 -0.13 33+0.18 -0.20 75+0.21 -0.20 12+0.04 -0.04 02+0.12 -0.13 65+0.18 -0.18 40+0.06 -0.06 29+0.05 -0.05 86+0.11 -0.11 16+0.15 -0.15 03+0.11 -0.11 19+0.06 -0.05 80+0.06 -0.06 46+0.10 -0.10 40+0.14 -0.15 87+0.07 -0.07 69+0.04 -0.04 35+0.04 -0.04 75+0.04 -0.04 80+0.06 -0.06 09+0.06 -0.06 17+0.03 -0.03 06+0.04 -0.05 65+0.17 -0.17 29+0.10 -0.10 29+0.12 -0.11 56+0.08 -0.08 76+0.06 -0.06 43+0.02 -0.02 23+0.12 -0.12 69+0.03 -0.03 91+0.04 -0.04 99+0.09 -0.09 31+0.06 -0.06 09+0.16 -0.17 95+0.08 -0.08 01+0.07 -0.07 27+0.03 -0.03 15+0.05 -0.05 66+0.12 -0.11 93+0.12 -0.11 13+0.04 -0.04 76+0.10 -0.10 44+0.10 -0.10 69+0.17 -0.16 12+0.15 -0.17 53+0.15 -0.14 77+0.11 -0.11 84+0.05 -0.05 42+0.10 -0.10

Continued on the next page. . . c 0000 RAS, MNRAS 000, 000­000


24

L. Cortese et al.
Table 3 ­ Continued. HRS D Mpc 140 141 143 144 146 147 148 149 151 152 153 154 156 158 159 160 162 163 165 167 168 169 170 171 172 173 174 176 177 180 182 184 185 188 189 190 191 192 193 194 196 197 198 199 200 201 203 204 205 206 207 208 212 213 217 220 221 17. 23. 23. 17. 23. 17. 17. 17. 17. 17. 17. 23. 17. 23. 23. 23. 17. 17. 23. 23. 23. 24. 17. 23. 17. 17. 17. 23. 17. 17. 17. 17. 17. 17. 17. 17. 17. 17. 17. 17. 17. 17. 16. 17. 17. 17. 17. 17. 17. 17. 17. 17. 20. 17. 17. 17. 17. 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 30 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 77 00 00 00 00 00 00 00 00 00 14 61 00 00 00 T K 17.4+0.8 -0.8 18.6+0.3 -0.3 23.9+0.3 -0.3 20.1+0.4 -0.4 17.9+0.5 -0.5 21.1+0.7 -0.7 24.4+0.4 -0.4 20.6+0.5 -0.5 17.9+0.8 -0.9 23.9+0.4 -0.4 17.7+0.8 -0.9 25.2+0.5 -0.5 19.8+0.5 -0.5 25.1+0.8 -0.7 21.3+0.4 -0.4 20.4+1.0 -1.0 19.6+0.4 -0.4 21.0+0.6 -0.6 20.1+0.7 -0.7 19.9+1.1 -1.2 23.5+0.4 -0.4 22.2+0.7 -0.7 23.9+0.4 -0.4 25.9+0.3 -0.3 21.9+0.4 -0.4 22.8+0.3 -0.3 25.6+0.9 -0.9 20.6+0.3 -0.3 26.8+1.0 -0.9 19.1+0.8 -0.8 19.3+0.5 -0.5 20.8+0.6 -0.6 21.2+0.3 -0.3 21.4+1.4 -1.5 20.8+0.7 -0.6 20.3+0.5 -0.5 21.5+0.6 -0.6 20.7+0.4 -0.4 16.1+0.7 -0.7 20.8+1.6 -1.5 22.1+0.2 -0.2 19.7+0.3 -0.3 22.4+0.9 -0.9 21.0+0.3 -0.3 19.2+0.9 -0.9 21.5+0.4 -0.4 20.7+0.6 -0.6 20.8+0.3 -0.3 =2 log(M M ) 2. 2. 1. 1. 1. 1. 1. 2. 1. 2. 1. 1. 2. 0. 2. 2. 2. 2. 1. 2. 1. 1. 1. 2. 2. 2. 2. 1. 3. 1. 2. 2. 1. 1. 2. 1. 2. 1. 1. 1. 1. 1. 1. 2. 2. 1. 2. 1. 1. 2. 2. 1. 1. 2. 2. 2. 1+0.5 -0.4 3+0.3 -0.2 5+0.1 -0.1 9+0.2 -0.2 5+0.2 -0.2 6+0.2 -0.2 2+0.2 -0.2 2+0.1 -0.1 7+0.3 -0.3 3+0.2 -0.2 9+0.3 -0.2 0+0.4 -0.4 2+0.1 -0.1 9+0.5 -0.4 2+0.3 -0.3 1+0.2 -0.2 7+0.4 -0.4 1+0.3 -0.2 6+0.4 -0.4 7+0.3 -0.3 2+0.3 -0.3 8+0.3 -0.3 9+0.5 -0.5 2+0.2 -0.2 3+0.3 -0.3 2+0.2 -0.2 3+0.2 -0.2 9+0.2 -0.2 5+0.8 -0.7 7+0.1 -0.1 5+0.5 -0.5 2+0.5 -0.5 6+0.2 -0.2 8+0.2 -0.2 2+0.1 -0.1 3+0.7 -0.6 4+0.5 -0.5 4+0.2 -0.2 4+0.1 -0.1 4+0.3 -0.2 7+0.2 -0.2 6+0.4 -0.3 7+0.7 -0.6 2+0.1 -0.1 0+0.1 -0.1 5+0.1 -0.1 1+0.2 -0.2 5+0.1 -0.1 8+0.3 -0.3 0+0.2 -0.2 0+0.5 -0.4 1+0.3 -0.3 6+0.1 -0.1 3+0.2 -0.2 3+0.4 -0.3 1+0.1 -0.1 =free T K 17. 17. 23. 24. 24. 21. 24. 19. 23. 22. 21. 24. 22. 24. 23. 19. 20. 20. 23. 16. 27. 21. 20. 22. 20. 22. 20. 23. 17. 23. 22. 18. 21. 22. 20. 26. 18. 24. 21. 26. 22. 18. 22. 22. 22. 28. 19. 27. 23. 20. 19. 28. 20. 19. 19. 20. 1+2.5 -2.2 4+1.1 -1.0 3+1.2 -1.1 4+1.5 -1.3 1+1.9 -1.7 0+1.6 -1.5 1+1.9 -1.7 9+0.5 -0.5 3+3.1 -2.5 4+1.4 -1.3 2+1.8 -1.6 5+4.4 -3.4 6+1.0 -0.9 4+4.9 -3.6 6+2.0 -1.8 4+1.4 -1.3 9+2.3 -2.0 8+1.7 -1.5 5+3.8 -3.1 5+1.2 -1.1 0+4.0 -3.1 4+2.4 -2.0 8+4.4 -3.3 0+1.3 -1.2 1+2.0 -1.7 3+1.4 -1.3 0+1.2 -1.1 4+1.3 -1.1 9+3.2 -2.5 0+1.3 -1.2 7+3.7 -2.9 2+2.7 -2.3 9+1.6 -1.4 6+2.0 -1.8 1+0.9 -0.8 4+8.2 -5.3 8+2.5 -2.1 4+2.3 -2.0 3+0.9 -0.8 0+2.8 -2.3 6+1.3 -1.2 4+2.9 -2.7 8+7.6 -5.1 3+0.7 -0.6 5+0.6 -0.6 0+1.3 -1.2 2+1.1 -1.0 3+1.3 -1.2 7+3.2 -2.6 8+1.1 -1.0 0+3.4 -2.8 7+4.1 -3.3 9+0.8 -0.8 9+1.2 -1.1 0+2.0 -1.7 2+0.8 -0.8 log(M M 7. 7. 7. 7. 6. 6. 6. 7. 6. 6. 6. 6. 7. 6. 6. 7. 6. 7. 6. 6. 6. 6. 7. 6. 6. 6. 6. 6. 5. 6. 6. 6. 6. 6. 8. 5. 5. 6. 7. 6. 6. 6. 6. 7. 7. 6. 7. 7. 6. 6. 7. 6. 8. 7. 7. 6. )

dust

dust

7.01+0.08 -0.07 7.39+0.03 -0.03 7.07+0.02 -0.02 6.87+0.03 -0.03 6.92+0.04 -0.04 6.68+0.05 -0.05 6.54+0.02 -0.02 6.72+0.04 -0.04 7.13+0.08 -0.07 7.05+0.02 -0.02 6.86+0.08 -0.08 6.75+0.03 -0.03 7.24+0.03 -0.03 6.35+0.06 -0.06 7.19+0.03 -0.04 6.44+0.07 -0.07 6.76+0.04 -0.04 6.35+0.05 -0.05 6.73+0.05 -0.05 7.29+0.08 -0.08 6.76+0.02 -0.02 6.63+0.04 -0.04 6.82+0.02 -0.02 6.23+0.01 -0.01 6.81+0.03 -0.03 6.57+0.02 -0.02 5.72+0.06 -0.07 6.82+0.02 -0.02 5.94+0.06 -0.06 6.53+0.07 -0.06 7.00+0.03 -0.03 6.50+0.04 -0.04 8.02+0.02 -0.02 5.88+0.10 -0.10 5.80+0.06 -0.06 6.71+0.04 -0.04 7.00+0.04 -0.04 6.84+0.03 -0.03 6.91+0.07 -0.07 6.25+0.11 -0.12 7.88+0.01 -0.01 7.91+0.03 -0.03 6.39+0.06 -0.05 6.88+0.02 -0.02 7.59+0.07 -0.06 7.59+0.03 -0.03 7.64+0.05 -0.05 6.89+0.02 -0.02

03+0.17 -0.15 45+0.07 -0.06 17+0.05 -0.05 05+0.05 -0.05 71+0.07 -0.07 76+0.08 -0.07 82+0.07 -0.07 47+0.03 -0.02 60+0.11 -0.11 61+0.05 -0.05 69+0.08 -0.08 84+0.14 -0.15 10+0.04 -0.04 56+0.15 -0.16 80+0.06 -0.06 26+0.07 -0.07 48+0.09 -0.09 21+0.08 -0.08 32+0.13 -0.13 93+0.08 -0.08 15+0.11 -0.11 68+0.10 -0.10 25+0.20 -0.20 81+0.05 -0.05 72+0.10 -0.09 88+0.06 -0.06 90+0.06 -0.06 55+0.05 -0.05 96+0.12 -0.13 72+0.05 -0.05 05+0.11 -0.12 58+0.15 -0.14 88+0.07 -0.07 43+0.08 -0.08 08+0.04 -0.04 71+0.19 -0.21 88+0.11 -0.11 54+0.08 -0.08 88+0.04 -0.04 84+0.08 -0.08 76+0.05 -0.05 75+0.19 -0.16 16+0.27 -0.26 07+0.03 -0.03 86+0.02 -0.02 87+0.04 -0.04 93+0.06 -0.06 50+0.04 -0.04 35+0.11 -0.11 89+0.05 -0.05 61+0.19 -0.18 37+0.10 -0.10 17+0.04 -0.04 66+0.06 -0.06 72+0.10 -0.10 92+0.04 -0.04

Continued on the next page. . . c 0000 RAS, MNRAS 000, 000­000


PACS photometry of the Herschel Reference Survey
Table 3 ­ Continued. HRS D Mpc 222 223 224 226 227 230 231 232 233 237 238 239 242 243 244 246 247 252 254 255 257 258 259 260 261 262 263 264 265 266 267 268 270 271 273 274 275 276 277 279 280 281 285 286 287 288 289 290 292 293 294 295 296 297 298 299 300 17. 17. 17. 17. 15. 17. 17. 17. 17. 17. 15. 17. 17. 17. 17. 17. 17. 23. 17. 17. 17. 17. 17. 17. 16. 17. 17. 18. 21. 21. 16. 17. 17. 17. 17. 17. 22. 17. 17. 17. 17. 17. 17. 17. 17. 15. 23. 16. 17. 15. 22. 16. 15. 21. 20. 16. 19. 00 00 00 00 27 00 00 00 00 00 94 00 00 00 00 00 00 13 00 00 00 73 00 00 54 00 27 17 49 30 84 00 70 00 00 00 37 00 00 00 00 00 00 00 00 91 97 23 50 60 97 46 20 54 27 73 34 21. 16. 19. 20. 21. 26. 22. 22. 21. 21. 22. 21. 16. 21. 18. 20. 17. 16. 31. 23. 17. 21. 18. 16. 23. 17. 18. 21. 18. 17. 21. 22. 16. 22. 20. 22. 16. 21. 19. 21. 25. 24. 20. 21. 22. 24. 18. 19. T K 0+1.3 -1.3 8+1.2 -1.2 2+0.9 -0.9 5+0.5 -0.6 2+0.5 -0.5 1+0.8 -0.8 4+0.6 -0.6 0+0.5 -0.5 9+0.6 -0.6 4+1.7 -1.8 7+0.3 -0.3 2+0.6 -0.6 4+1.0 -0.9 0+0.4 -0.4 0+1.4 -1.4 3+1.0 -1.0 1+1.3 -1.2 9+0.8 -0.8 2+1.1 -1.1 0+0.3 -0.3 3+0.7 -0.7 8+0.6 -0.6 2+0.7 -0.7 7+0.6 -0.6 2+0.7 -0.7 5+1.2 -1.2 7+0.9 -0.9 2+0.9 -0.9 9+0.6 -0.6 3+0.4 -0.4 5+0.6 -0.6 0+1.4 -1.3 8+0.8 -0.8 3+0.4 -0.4 0+0.8 -0.8 5+0.3 -0.3 7+1.3 -1.2 2+0.5 -0.5 2+0.5 -0.5 7+0.4 -0.4 1+0.5 -0.5 4+0.4 -0.4 1+0.5 -0.5 8+0.5 -0.5 6+1.8 -1.7 4+0.4 -0.4 4+0.9 -0.9 5+0.8 -0.8 =2 log(M M 6. 6. 6. 6. 6. 5. 6. 6. 6. 5. 7. 6. 7. 7. 6. 7. 6. 7. 5. 7. 6. 7. 8. 6. 6. 7. 6. 7. 7. 6. 6. 5. 7. 6. 5. 7. 6. 6. 7. 7. 6. 6. 6. 7. 5. 6. 7. 6. ) 2. 1. 2. 1. 0. 1. 2. 2. 2. 2. 0. 2. 1. 2. 2. 1. 1. 1. 2. 0. 1. 2. 1. 2. 1. 1. 1. 1. 1. 1. 1. 1. 2. 1. 1. 2. 1. 1. 2. 1. 1. 2. 2. 0. 1. 2. 1. 2. 2. 1. 1. 2. 0. 1. 2. 1. 1. 5+0.8 -0.7 2+0.7 -0.6 0+0.5 -0.5 7+0.2 -0.2 7+0.2 -0.2 7+0.2 -0.2 2+0.4 -0.4 2+0.4 -0.3 2+0.2 -0.2 0+0.3 -0.3 7+0.7 -0.7 1+0.1 -0.1 4+0.3 -0.3 7+0.8 -0.6 2+0.1 -0.1 8+0.2 -0.2 8+0.1 -0.1 0+0.4 -0.3 1+0.4 -0.4 6+0.6 -0.5 8+0.5 -0.5 1+0.3 -0.3 0+0.3 -0.3 0+0.1 -0.1 9+0.4 -0.4 6+0.2 -0.2 7+0.4 -0.4 6+0.4 -0.3 9+0.3 -0.3 1+0.4 -0.4 5+0.3 -0.3 8+0.1 -0.1 1+0.4 -0.4 3+0.2 -0.2 8+0.3 -0.3 1+0.3 -0.3 5+0.2 -0.2 6+0.2 -0.2 9+1.4 -1.1 2+0.4 -0.3 9+0.2 -0.2 2+0.5 -0.4 0+0.1 -0.1 8+0.8 -0.7 7+0.2 -0.2 0+0.2 -0.2 8+0.1 -0.1 1+0.3 -0.2 1+0.1 -0.1 6+0.1 -0.1 5+0.2 -0.2 0+0.2 -0.2 9+0.5 -0.5 6+0.1 -0.1 1+0.2 -0.1 4+0.4 -0.3 6+0.5 -0.5 =free T K 18.3+4.2 -3.2 21.2+6.3 -4.4 19.5+3.4 -2.8 22.2+1.9 -1.7 29.9+3.8 -3.1 23.1+1.9 -1.7 24.8+3.5 -2.9 20.9+2.3 -2.0 20.8+1.5 -1.3 21.6+2.0 -1.8 +26 36.1-10.7 .3 22.2+0.8 -0.8 25.6+3.0 -2.5 13.5+2.9 -2.6 20.6+0.7 -0.7 22.6+1.4 -1.3 22.6+0.8 -0.8 27.6+5.9 -4.5 19.6+3.0 -2.5 . 32.7+1826 -9. 18.2+3.2 -2.7 29.6+4.3 -3.4 29.7+6.0 -4.5 23.3+1.0 -0.9 18.0+2.3 -2.0 24.8+2.2 -1.9 19.9+2.7 -2.3 19.1+2.5 -2.1 23.7+2.5 -2.1 25.0+5.4 -4.1 23.1+3.2 -2.8 24.6+0.9 -0.8 20.4+2.9 -2.4 24.3+2.6 -2.2 20.0+2.0 -1.8 17.0+1.3 -1.2 27.1+2.0 -1.7 24.7+2.3 -2.0 17.6+5.6 -3.9 22.1+3.5 -2.9 23.2+1.3 -1.2 19.0+2.7 -2.3 22.4+0.9 -0.9 23.9+9.2 -5.6 23.3+1.6 -1.5 19.1+1.6 -1.4 22.8+1.1 -1.0 24.5+2.1 -1.8 23.8+1.1 -1.1 24.3+1.4 -1.3 23.7+1.7 -1.5 21.9+1.3 -1.2 +20 38.0-10.3 .0 22.4+1.3 -1.2 +1.3 23.3-1.2 22.7+3.3 -2.7 21.6+4.0 -3.0 log(M M 6. 6. 6. 6. 6. 6. 5. 6. 6. 6. 5. 7. 6. 7. 7. 7. 7. 6. 7. 6. 7. 5. 6. 7. 6. 6. 7. 6. 6. 7. 6. 6. 7. 6. 7. 6. 7. 6. 5. 6. 6. 6. 7. 6. 6. 7. 7. 6. 6. 6. 6. 7. 5. 7. 6. 6. 6. )

25

dust

dust

01+0.10 -0.09 32+0.12 -0.11 72+0.07 -0.07 45+0.04 -0.04 64+0.04 -0.04 61+0.04 -0.04 38+0.04 -0.04 94+0.03 -0.03 77+0.04 -0.04 81+0.12 -0.12 01+0.02 -0.02 90+0.04 -0.04 13+0.09 -0.08 39+0.03 -0.03 87+0.11 -0.10 37+0.07 -0.07 99+0.11 -0.11 25+0.08 -0.08 35+0.04 -0.04 03+0.02 -0.02 83+0.07 -0.06 07+0.04 -0.04 02+0.07 -0.07 55+0.06 -0.06 38+0.04 -0.04 66+0.09 -0.09 99+0.06 -0.06 11+0.06 -0.06 11+0.05 -0.05 90+0.04 -0.04 69+0.04 -0.04 64+0.11 -0.11 08+0.07 -0.07 51+0.02 -0.02 95+0.06 -0.06 31+0.02 -0.02 75+0.15 -0.16 95+0.03 -0.03 11+0.04 -0.04 45+0.02 -0.02 25+0.03 -0.03 87+0.02 -0.02 94+0.03 -0.03 80+0.03 -0.03 76+0.11 -0.11 68+0.02 -0.02 16+0.07 -0.07 26+0.07 -0.07

14+0.21 -0.20 07+0.26 -0.25 71+0.17 -0.16 38+0.08 -0.08 62+0.09 -0.10 56+0.07 -0.07 65+0.09 -0.09 44+0.09 -0.10 99+0.07 -0.07 78+0.08 -0.08 40+0.27 -0.37 03+0.04 -0.04 74+0.09 -0.09 38+0.34 -0.26 34+0.04 -0.04 32+0.06 -0.06 66+0.03 -0.03 47+0.16 -0.16 41+0.15 -0.14 36+0.30 -0.33 17+0.20 -0.18 38+0.08 -0.09 66+0.14 -0.14 02+0.04 -0.04 79+0.14 -0.13 97+0.07 -0.07 94+0.13 -0.13 41+0.13 -0.13 36+0.08 -0.08 29+0.18 -0.18 77+0.13 -0.12 93+0.03 -0.03 14+0.14 -0.14 66+0.09 -0.09 05+0.10 -0.09 92+0.09 -0.09 02+0.06 -0.06 57+0.08 -0.08 83+0.25 -0.25 79+0.15 -0.14 48+0.05 -0.05 00+0.14 -0.13 32+0.04 -0.04 41+0.27 -0.28 86+0.06 -0.06 11+0.09 -0.09 41+0.04 -0.04 27+0.06 -0.06 89+0.04 -0.04 73+0.05 -0.05 80+0.06 -0.06 80+0.06 -0.06 38+0.23 -0.28 36+0.05 -0.05 72+0.05 -0.05 97+0.12 -0.12 17+0.15 -0.16

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26

L. Cortese et al.
Table 3 ­ Continued. HRS D Mpc 301 302 303 304 305 306 307 309 310 311 313 314 315 317 318 319 320 321 322 323 19. 20. 24. 19. 16. 16. 17. 19. 24. 21. 21. 19. 20. 24. 19. 19. 22. 22. 21. 23. 71 61 53 57 73 23 74 76 54 31 29 84 57 51 57 54 61 59 50 43 17. 15. 26. 19. 18. 23. 19. 21. 19. 16. 20. 17. T K 4+0.9 -1.0 6+1.1 -1.0 8+0.6 -0.6 1+0.4 -0.4 2+1.3 -1.3 2+1.5 -1.5 1+0.7 -0.7 3+0.5 -0.5 1+0.7 -0.7 9+0.8 -0.8 7+2.7 -2.8 4+1.0 -0.9 5+0.4 -0.4 4+1.4 -1.3 =2 log(M M 7. 7. 6. 7. 5. 6. 7. 7. 7. 7. 6. 6. ) 1. 1. 2. 2. 2. 2. 1. 1. 2. 2. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1+0.4 -0.3 0+0.4 -0.3 1+0.3 -0.2 0+0.2 -0.2 2+1.0 -0.8 6+0.7 -0.6 6+0.3 -0.3 0+0.2 -0.2 3+0.3 -0.3 0+0.3 -0.3 5+0.3 -0.3 0+0.2 -0.2 8+0.8 -0.7 4+0.2 -0.2 1+0.3 -0.3 1+0.3 -0.3 9+0.2 -0.2 7+1.5 -0.9 7+0.1 -0.1 =free T K 24. 25. 26. 19. 17. 19. 21. 28. 19. 19. 20. 27. 18. 25. 26. 25. 24. 16. 22. 1+4.1 -3.2 0+5.5 -4.4 3+2.5 -2.1 2+1.2 -1.2 5+5.0 -3.7 4+4.0 -3.1 5+2.2 -2.0 4+3.4 -2.8 9+1.6 -1.5 4+2.2 -2.0 5+2.9 -2.7 6+3.4 -2.8 7+4.8 -3.6 1+1.9 -1.7 3+3.4 -2.8 2+4.0 -3.4 6+1.4 -1.3 0+6.6 -5.8 8+0.9 -0.9 log(M M 7. 6. 6. 7. 6. 6. 7. 6. 7. 7. 7. 6. 6. 6. 6. 7. 6. 7. 7. )

dust

dust

23. 14.

6. 7.

43+0.08 -0.07 07+0.09 -0.09 49+0.03 -0.03 10+0.03 -0.03 98+0.13 -0.13 61+0.08 -0.08 71+0.05 -0.05 07+0.04 -0.04 50+0.05 -0.05 27+0.06 -0.06 24+0.21 -0.19 42+0.10 -0.10 55+0.02 -0.02 51+0.15 -0.15 -

10+0.15 -0.15 57+0.19 -0.17 51+0.07 -0.07 09+0.07 -0.07 03+0.29 -0.27 77+0.19 -0.18 60+0.10 -0.09 11+0.09 -0.09 13+0.07 -0.07 49+0.12 -0.11 06+0.15 -0.13 57+0.09 -0.09 34+0.26 -0.23 80+0.06 -0.06 98+0.10 -0.11 27+0.14 -0.13 51+0.04 -0.05 38+0.70 -0.39 11+0.04 -0.04

c 0000 RAS, MNRAS 000, 000­000