Abstract

The ATLAS3D project is a multiwavelength survey combined with a theoretical modelling effort. The observations span from the radio to the millimetre and optical, and provide multicolour imaging, two-dimensional kinematics of the atomic (H i), molecular (CO) and ionized gas (Hβ, [O iii] and [N i]), together with the kinematics and population of the stars (Hβ, Fe5015 and Mg b), for a carefully selected, volume-limited (1.16 × 105 Mpc3) sample of 260 early-type (elliptical E and lenticular S0) galaxies (ETGs). The models include semi-analytic, N-body binary mergers and cosmological simulations of galaxy formation. Here we present the science goals for the project and introduce the galaxy sample and the selection criteria. The sample consists of nearby (D < 42 Mpc, |δ− 29°| < 35°, |b| > 15°) morphologically selected ETGs extracted from a parent sample of 871 galaxies (8 per cent E, 22 per cent S0 and 70 per cent spirals) brighter than MK < −21.5 mag (stellar mass M≳ 6 ×109 M). We analyse possible selection biases and we conclude that the parent sample is essentially complete and statistically representative of the nearby galaxy population. We present the size–luminosity relation for the spirals and ETGs and show that the ETGs in the ATLAS3D sample define a tight red sequence in a colour–magnitude diagram, with few objects in the transition from the blue cloud. We describe the strategy of the SAURON integral field observations and the extraction of the stellar kinematics with the ppxf method. We find typical 1σ errors of ΔV≈ 6 km s−1, Δσ≈ 7 km s−1, Δh3≈Δh4≈ 0.03 in the mean velocity, the velocity dispersion and Gauss–Hermite (GH) moments for galaxies with effective dispersion σe≳ 120 km s−1. For galaxies with lower σe (≈40 per cent of the sample) the GH moments are gradually penalized by ppxf towards zero to suppress the noise produced by the spectral undersampling and only V and σ can be measured. We give an overview of the characteristics of the other main data sets already available for our sample and of the ongoing modelling projects.

1 INTRODUCTION

1.1 Scientific background

Observations of high-redshift galaxies and the cosmic microwave background (Spergel et al. 2007) have revealed the Universe to be dominated by dark matter and dark energy (Riess et al. 1998; Perlmutter et al. 1999), providing a working paradigm for the formation of structure (e.g. Springel et al. 2005b). However, the mechanisms that form the luminous content of the dark matter potential (i.e. the stars and galaxies that we observe) remain the key unknowns of modern extragalactic astronomy. These processes are driven by the hydrodynamics and chemistry of the gas, combined with complex radiative feedback processes. High-redshift observations alone are not sufficient to constrain these processes, lacking spectral information and spatial resolution (Faber et al. 2007). It is therefore necessary to complement these studies with detailed analysis of nearby objects, tracing the fossil record of the formation process. Early-type (elliptical E and lenticular S0) galaxies (ETGs) are especially useful as they are old, have smaller levels of star formation and limited amount of dust, which simplifies the interpretation of the observations. Significant progress has been made in this direction in the past few decades, building on the classic observational works that still capture much of our understanding of the structure of local ETGs (e.g. Hubble 1936; Faber & Jackson 1976; Davies et al. 1983; Djorgovski & Davis 1987; Dressler et al. 1987; Bender, Burstein & Faber 1992; Kormendy & Richstone 1995).

A major step forward was brought by the era of large galaxy surveys. Thanks to the unprecedented sample size, one of the most important contributions of the Sloan Digital Sky Survey (SDSS; York et al. 2000) was to firmly establish a statistically significant bimodality in the colour distribution of local galaxies, such that they can be clearly separated in a so-called ‘blue cloud’, generally consisting of star-forming spiral galaxies, and a ‘red sequence’, mostly of non-star-forming ETGs (Strateva et al. 2001; Baldry et al. 2004). Accurately quantifying this bimodality, and the realization that it can be traced back in time to higher redshift (Bell et al. 2004; Faber et al. 2007), allowed a dramatic improvement in the detailed testing of galaxy formation scenarios.

The bimodality can only be explained with the existence of a mechanism, which suppresses episodes of intense star formation by evacuating gas from the system, resulting in a rapid transition of galaxies from the blue cloud to the red sequence (Springel, Di Matteo & Hernquist 2005a; Faber et al. 2007). Many simulation groups have reproduced the bimodality qualitatively, though with rather different assumptions for the star formation and feedback processes (Granato et al. 2004; Di Matteo, Springel & Hernquist 2005; Bower et al. 2006; Cattaneo et al. 2006; Croton et al. 2006). A generic feature of these models is that red-sequence galaxies form by dissipational ‘wet mergers’ of gas-rich blue-cloud galaxies, followed by quenching of the resulting intense star formation by rapid ejection of the gas, caused by the feedback from a central supermassive black hole, supernovae winds, by shock heating of the gas in the most massive haloes (Kereš et al. 2005; Dekel & Birnboim 2006) or gravitational gas heating (Naab et al. 2007; Khochfar & Ostriker 2008; Johansson, Naab & Ostriker 2009). The merging of the most massive blue galaxies, however, is not sufficient to explain the population of most massive red-sequence galaxies. Dissipationless ‘dry mergers’ of gas-poor, red-sequence galaxies is therefore also required, evolving galaxies along the red sequence as they increase in mass (Khochfar & Burkert 2003; Naab, Khochfar & Burkert 2006b; Hopkins et al. 2009; Khochfar & Silk 2009; Oser et al. 2010).

Both wet and dry major mergers generally produce red, bulge-dominated galaxies when feedback is included in the models. The kinematic structure of the remnants is however very different. In a major (1:1) merger between blue gas-rich galaxies, the gas tends to form a disc, so that the end result of the merger, after the gas has been removed from the system by ejection, heating or conversion to stars, will be a red stellar system dominated by rotation (Cox et al. 2006; Naab et al. 2006a; Robertson et al. 2006; Jesseit et al. 2009). In major mergers between red gas-poor galaxies, dissipationless processes dominate, resulting in a red galaxy with little or no net rotation (Barnes 1992; Hernquist 1992; Naab, Burkert & Hernquist 1999; Naab & Burkert 2003; Cox et al. 2006). Unlike major mergers, minor mergers (1:3 or less) retain more closely the structure of the progenitor, to an extent that depends on the amount of mass and gas accreted, so that the remnant of a spiral galaxy will always display significant rotation (Naab et al. 2006a; Robertson et al. 2006; Bournaud, Jog & Combes 2007; Jesseit et al. 2009). These simulations demonstrate that if galaxies assemble by mergers, the existence of the red/blue galaxies dichotomy therefore also suggests the existence of a kinematical differentiation within the red sequence between fast and slow rotating galaxies.

Various classic observational indicators of a ETGs dichotomy have been proposed in the past two decades. ETGs have been found to exhibit trends as a function of luminosity in terms of (i) their distribution on the (V/σ, ɛ) diagram, which relates the ratio of ordered V and random σ stellar motion to the galaxy ellipticity ɛ (e.g. Illingworth 1977; Binney 1978; Davies et al. 1983), (ii) their isophote shape (discy or boxy) (Bender et al. 1989; Kormendy & Bender 1996), (iii) the inner slope of their photometric profiles: cored/cuspy (Ferrarese et al. 1994; Lauer et al. 1995; Faber et al. 1997) or excess/deficit of core light (Graham 2004; Ferrarese et al. 2006; Kormendy et al. 2009). However, none of these signatures has been able to give clear evidence for a distinction between the two classes of red-sequence galaxies, primarily because they are all essentially secondary indicators of the galaxies’ internal kinematic structure.

By the application of integral field spectroscopy to a representative sample of nearby ETGs, the SAURON survey (de Zeeuw et al. 2002) has revealed the full richness of the kinematics of these objects (Emsellem et al. 2004; McDermid et al. 2006; Krajnović et al. 2008). From the two-dimensional nature of this unique data set, two distinct morphologies of stellar rotation fields are clearly evident, corresponding to the above described fast- and slow rotators. In two companion papers of that survey a global quantitative measure of this morphology was defined, termed λR, that can be used to kinematically classify these galaxies in a way that is more robust than the (V/σ, ɛ) diagram and is nearly insensitive to projection effects (Emsellem et al. 2007; Cappellari et al. 2007). λR relates directly to their formation, and is precisely reproducible in current cosmological simulations (Jesseit et al. 2009; Bois et al. 2010). This is the basic new finding we plan to exploit in the present project to improve our understanding of the structure and formation of ETGs. Additional results of the SAURON survey on ETGs include the robustness and empirical ‘calibration’ of the simple virial mass estimator to measure mass in the central parts of ETGs and a determination of their dark matter fraction (Cappellari et al. 2006). The survey found a high incidence of ionized gas in ETGs (Sarzi et al. 2006) and explained their ionization mechanism as mainly due to the evolved stellar population (Sarzi et al. 2010). It was shown that the stellar population gradients correlate well with the escape velocity, both locally within galaxies and globally among different ETGs (Scott et al. 2009). Star formation in ETGs only happens in fast rotators and follows two distinct modes: in discs or widespread (Shapiro et al. 2010), where the latter cases are in low-mass systems (Jeong et al. 2009; Kuntschner et al. 2010). Discs in fast rotators have enhanced metallicity, while kinematically distinct cores in slow rotators show no stellar population signatures (Kuntschner et al. 2006, 2010).

1.2 Goals of the project

Because of the exploratory character of the SAURON survey (de Zeeuw et al. 2002), the ETGs were selected to sample, with a relatively small number of objects, a wide range of masses, shapes and morphologies. This was done by selecting galaxies brighter than a total magnitude MB < −18 mag equally subdivided into 24 E and 24 S0. Within each E/S0 subclass the selected objects sample uniformly a grid in the (MB, ɛ) plane. Although that approach was crucial in bringing the fast/slow rotator dichotomy to light and in most of the findings mentioned in the previous section, the selection criteria impose complex biases and do not allow for a quantitative statistical comparisons of galaxy properties with simulations, which is a main goal of the ATLAS3D project. Moreover, with only 48 galaxies, the statistical uncertainties are large.

The power of the kinematic classification based on λR is to be able to study differences in the formation process along the red-sequence galaxy population. The λR parameter describes in a compact way the present status of the galaxies, however, it is essential to obtain information on the formation history and the detailed dynamical structure as well. The stellar population contains a record of the more distant history (a few Gyr). Recent gas accretion is recorded in the cold atomic gas components, generally detected on galaxy scales with radio observations of H i, while the ongoing accretion and star formation activity is traced by cold molecular gas (e.g. CO), often detected in regular discs in the central regions. For comparison with theoretical predictions one needs to observe all these quantities for a statistically significant, volume-limited sample of galaxies complete to some useful lower limit in mass. With these ideas in mind we carefully selected the ATLAS3D sample of ETGs and we systematically observed all the above quantities. The ATLAS3D data set now provides a complete inventory of the baryon budget and a detailed two-dimensional description of stellar and gaseous kinematics, together with resolved stellar population within the main body of a complete and statistically significant sample of ETGs. Our goal is to use this data set to perform archaeological cosmology by specifically answering the following questions.

  • How do slow rotators form? What are the physical processes that determine their kinematic and photometric features? What is the role of major and minor mergers in their formation history? This will be reflected in the kinematics, gas content and stellar population.

  • Why are most ETGs fast rotators? There seems to be a dominant formation mechanism that delivers galaxies with quite homogenous rotation properties. Can this be merging? Can significant major merging be excluded?

  • How is star formation in ETGs quenched? Is it different for fast- and slow-rotators ETGs? How does it depend on environment? Can we infer the quenching mechanism from the amount and distribution of the leftover gas, the presence of active galactic nuclei (AGN) or metallicity gradients? The distribution of stellar population and gas properties constitutes a stringent test for future galaxy formation models.

  • Most past studies have focused on single stellar population models of ETGs, but cosmological models predict more complex histories. Can we infer the star formation history in ETGs for detailed comparison with simulations?

  • How do counter rotating cores in massive and old ETGs form and survive to the present time? Are these relics of the very early Universe?

  • Can we link the present day properties of ETGs to results form existing and upcoming surveys at higher redshift with respect to e.g. masses, sizes, stellar populations, gas fractions, star formation? Our study will constitute a z = 0 redshift benchmark to trace the time evolution of galaxies.

The ATLAS3D sample includes all nearby ETGs observable from the northern Earth hemisphere, and for this reason we hope its homogeneous data set will ultimately constitute a legacy for future studies. We trust that our and other groups will exploit our data and sample well beyond what we had originally envisioned. Our first steps in the directions outlined above are presented in the following papers, while the other aspects will be presented in subsequent papers of this series:

  • Krajnović et al. (2011, hereafter Paper II), which describes the morphology of the kinematics and the kinematical misalignment in ETGs;

  • Emsellem et al. (2011, hereafter Paper III), which presents a census of the stellar angular momentum in the central region of ETGs;

  • Young et al. (2011, hereafter Paper IV), which quantifies the distribution of molecular gas content in ETGs;

  • Davis et al. (2011, hereafter Paper V), which studies the Tully & Fisher (1977) relation from the width of the molecular lines in ETGs;

  • Bois et al. (2011, hereafter Paper VI), which studies the formation of the fast- and slow-rotator galaxies via numerical simulations of binary mergers;

  • Cappellari et al. (2011, hereafter Paper VII), which revisits the morphology of nearby galaxies and presents the kinematic morphology–density relation;

  • Khochfar et al. (2011, hereafter Paper VIII), which studies the formation of ETGs using semi-analytic modelling.

Here in Section 2 we discuss the selection criteria for the parent sample of galaxies, from which the ATLAS3D sample of ETGs was extracted (Section 3). In Section 4 we present the SAURON observing strategy for the survey, the integral field data and the kinematic extraction, while other additional data sets and simulations from our project are listed in Section 5. We give a summary in Section 6. In the paper we assume H0 = 72 km s−1 Mpc−1.

2 THE PARENT SAMPLE

2.1 Selection criteria

Our final ATLAS3D sample will focus on ETGs only, however, before any morphological classification, we want to select all galaxies in the nearby volume above a certain total stellar mass. As we did not have dynamical information for all galaxies in the local volume at the beginning of our survey, the best proxy for mass available was the near-infrared (∼2.2 μm) Ks-band luminosity provided by the Two Micron All Sky Survey (2MASS; Skrutskie et al. 2006), which is unique for its full sky completeness and excellent photometric homogeneity. The Ks band is 5–10 times less sensitive to dust absorption than optical wavelengths and therefore can be used to select both dust-rich spirals and dust-poor ETGs to a similar mass level. Moreover the mass-to-light ratio of the stars in the near-infrared varies only about a factor ≈2, which is about three times less than at optical wavelengths (Bell & de Jong 2001; Maraston 2005), thus providing a better approximation to the stellar mass than an optical selection.

To derive luminosities from the observed apparent magnitudes we need distances. Numerous accurate determinations have been accumulated in the literature in the past few years. However, we will resort to redshift distances when a more accurate distance is not available. In addition we enforce obvious observability criteria. This leads to the following selection steps.

  • Choose a representative local volume with radius D = 42 Mpc. It approximates the redshift selection cz < 3000 km s−1 of the SAURON survey, for an adopted H0 = 72 km s−1 Mpc−1 (Dunkley et al. 2009). It makes sure that key spectral features, such as Hβ, [O iii] and Mg b, fall within the SAURON wavelength range and allows for a significant overlap with previous observations.

  • Specify the observability criterion from the William Herschel Telescope (WHT) on La Palma |δ− 29°| < 35°, where δ is the sky declination.

  • Exclude the dusty region near the Galaxy equatorial plane |b| < 15°, with b the galactic latitude.

  • Select all galaxies from the 2MASS extended source catalog (XSC; Jarrett et al. 2000) with apparent total magnitude KT < 11.6 mag (defined by the XSC parameter k_m_ext) and satisfying the observability criteria (ii) and (iii). Given the near completeness of the XSC down to KT≈ 13.5 mag, this selection is essentially complete. It ensures that all candidate galaxies brighter than an absolute total magnitude MK=KT− 5 log D− 25 =−21.5 mag are selected. This Ks-band luminosity limit roughly corresponds to a B-band selection MB≲−18 mag, for the typical BKs≈ 3.5 mag colour of ETGs, at the faint end of our selection. This criterion is thus again similar to the one in the SAURON survey and allows for a significant overlap in the samples, reducing the required observing time. This step provides a sample of ∼20 000 extended objects classified as galaxies.

  • Assign a distance to as many galaxies as possible in the selection and include in the ATLAS3D parent sample the ones with D < 42 Mpc and MK < −21.5 mag. The distance selection requires some further explanation and may introduce incompleteness biases that are discussed in the next section.

A summary of the selection criteria is given in Table 1, while some of the main characteristics of the resulting galaxy sample are given in Table 2. This is the sample of galaxies, which includes both spiral and ETGs, from which the ATLAS3D sample of ETGs will be extracted. The names and the characteristics of the resulting 871 galaxies in the ATLAS3D parent sample are given in Tables 3 (for the ETGs) and 4 (for the spirals). As the evolution of spirals and ETGs are closely related, the spirals of the parent sample are critical to properly interpret the ATLAS3D results on ETGs.

Table 1

Selection criteria for the galaxies in the ATLAS3D parent sample.

Distance: D < 42 Mpc 
Galaxies total mag: MK < −21.5 mag 
Observability: |δ− 29°| < 35° 
Galaxy zone of avoidance: |b| > 15° 
Distance: D < 42 Mpc 
Galaxies total mag: MK < −21.5 mag 
Observability: |δ− 29°| < 35° 
Galaxy zone of avoidance: |b| > 15° 
Table 2

Main characteristics of the ATLAS3D parent sample.

Survey volume: Vol = 1.16 × 105 Mpc3 
Galaxy K-band luminosity: L > 8.2 × 109 L⊙,K 
Galaxy stellar mass: M≳ 6 × 109 M 
Galaxy B-band total mag: MB≲−18.0 mag 
Galaxy SDSS r-band total mag: Mr≲−18.9 mag 
Total number of galaxies: Ngal = 871 
Spiral and irregular galaxies: NSp = 611 (70 per cent) 
S0 galaxies in ATLAS3D (T > −3.5): NS0 = 192 (22 per cent) 
E galaxies in ATLAS3D (T≤−3.5): NE = 68 (8 per cent) 
Survey volume: Vol = 1.16 × 105 Mpc3 
Galaxy K-band luminosity: L > 8.2 × 109 L⊙,K 
Galaxy stellar mass: M≳ 6 × 109 M 
Galaxy B-band total mag: MB≲−18.0 mag 
Galaxy SDSS r-band total mag: Mr≲−18.9 mag 
Total number of galaxies: Ngal = 871 
Spiral and irregular galaxies: NSp = 611 (70 per cent) 
S0 galaxies in ATLAS3D (T > −3.5): NS0 = 192 (22 per cent) 
E galaxies in ATLAS3D (T≤−3.5): NE = 68 (8 per cent) 
Table 3

The ATLAS3D sample of 260 early-type (E and S0) galaxies. A machine-readable version of this table is available (see Supporting Information).

Galaxy RA (°) Dec. (°) SBF NED-D Virgo Vhel (km s−1D (Mpc) MK (mag) AB (mag) T type log Re (arcsec) 
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) 
IC 0560 146.472656 −0.268221 1853 27.2 −22.10 0.59 −0.7 1.11 
IC 0598 153.202423 43.145546 2256 35.3 −22.60 0.06 −0.1 1.02 
IC 0676 168.165909 9.055736 1429 24.6 −22.27 0.11 −1.3 1.35 
IC 0719 175.077042 9.009861 1833 29.4 −22.70 0.22 −2.0 1.10 
IC 0782 185.404053 5.765672 2424 36.3 −22.02 0.09 2.7 1.35 
IC 1024 217.863419 3.009107 1479 24.2 −21.85 0.13 −2.0 1.05 
IC 3631 189.950195 12.973927 2822 42.0 −22.01 0.17 −1.3 1.13 
NGC 0448 18.818876 −1.626105 1908 29.5 −23.02 0.26 −2.5 1.05 
NGC 0474 20.027901 3.415270 2315 30.9 −23.91 0.15 −2.0 1.52 
NGC 0502 20.731415 9.049169 2524 35.9 −23.05 0.17 −2.0 1.07 
NGC 0509 20.850327 9.433469 2261 32.3 −21.89 0.20 −1.3 1.37 
NGC 0516 21.033607 9.551668 2437 34.7 −22.21 0.29 −1.5 1.16 
NGC 0524 21.198778 9.538793 10 2403 23.3 −24.71 0.36 −1.2 1.64 
NGC 0525 21.220442 9.703240 2139 30.7 −21.86 0.38 −2.0 1.06 
NGC 0661 26.060976 28.705988 3815 30.6 −23.19 0.30 −4.4 1.12 
NGC 0680 27.447035 21.970827 2928 37.5 −24.17 0.34 −4.0 1.16 
NGC 0770 29.806850 18.954695 2543 36.7 −22.57 0.31 −4.2 0.94 
NGC 0821 32.088123 10.994870 1718 23.4 −23.99 0.48 −4.8 1.60 
NGC 0936 36.906090 −1.156280 1429 22.4 −24.85 0.15 −1.2 1.72 
NGC 1023 40.100052 39.063251 602 11.1 −24.01 0.26 −2.7 1.68 
NGC 1121 42.663387 −1.734040 2558 35.3 −22.70 0.29 −1.8 0.87 
NGC 1222 47.236446 −2.955212 2422 33.3 −22.71 0.26 −3.0 1.10 
NGC 1248 48.202328 −5.224674 2217 30.4 −22.90 0.27 −2.0 1.20 
NGC 1266 49.003120 −2.427370 2170 29.9 −22.93 0.43 −2.1 1.31 
NGC 1289 49.707592 −1.973354 2792 38.4 −23.46 0.37 −2.1 1.26 
NGC 1665 72.071098 −5.427655 2745 37.5 −23.63 0.26 −1.8 1.50 
NGC 2481 119.307182 23.767693 2157 32.0 −23.38 0.28 0.4 1.02 
NGC 2549 124.743111 57.803108 1051 12.3 −22.43 0.28 −2.0 1.28 
NGC 2577 125.681137 22.553040 2062 30.8 −23.41 0.23 −3.0 1.15 
NGC 2592 126.783669 25.970339 1979 25.0 −22.88 0.25 −4.8 1.09 
NGC 2594 126.821609 25.878935 2362 35.1 −22.36 0.24 0.0 0.82 
NGC 2679 132.887192 30.865419 2027 31.1 −22.81 0.14 −2.0 1.35 
NGC 2685 133.894791 58.734409 875 16.7 −22.78 0.27 −1.0 1.41 
NGC 2695 133.612778 −3.067101 1833 31.5 −23.64 0.08 −2.1 1.21 
NGC 2698 133.902222 −3.183882 1900 27.1 −23.32 0.08 −1.0 1.10 
NGC 2699 133.953415 −3.127507 1868 26.2 −22.72 0.08 −5.0 1.06 
NGC 2764 137.072983 21.443447 2706 39.6 −23.19 0.17 −2.0 1.09 
NGC 2768 137.906265 60.037209 1353 21.8 −24.71 0.20 −4.4 1.80 
NGC 2778 138.101639 35.027424 2025 22.3 −22.23 0.09 −4.8 1.20 
NGC 2824 139.759277 26.269999 2758 40.7 −22.93 0.14 −2.0 0.86 
NGC 2852 140.810684 40.163879 1781 28.5 −22.18 0.06 1.0 0.85 
NGC 2859 141.077286 34.513378 1690 27.0 −24.13 0.09 −1.2 1.43 
NGC 2880 142.394241 62.490620 1554 21.3 −22.98 0.14 −2.7 1.32 
NGC 2950 145.646317 58.851219 1322 14.5 −22.93 0.07 −2.0 1.19 
NGC 2962 145.224609 5.165820 1967 34.0 −24.01 0.25 −1.1 1.39 
NGC 2974 145.638611 −3.699116 1887 20.9 −23.62 0.23 −4.2 1.58 
NGC 3032 148.034119 29.236279 1562 21.4 −22.01 0.07 −1.9 1.12 
NGC 3073 150.216843 55.618935 1173 32.8 −21.78 0.05 −2.8 1.13 
NGC 3098 150.569458 24.711092 1397 23.0 −22.72 0.16 −1.5 1.12 
NGC 3156 153.171692 3.129320 1338 21.8 −22.15 0.15 −2.5 1.24 
NGC 3182 154.887558 58.205818 2118 34.0 −23.19 0.05 0.4 1.32 
NGC 3193 154.603683 21.893978 1381 33.1 −24.63 0.11 −4.8 1.42 
NGC 3226 155.862549 19.898439 1315 22.9 −23.24 0.10 −4.8 1.49 
NGC 3230 155.933090 12.567883 2795 40.8 −24.18 0.16 −1.8 1.26 
NGC 3245 156.826523 28.507435 1326 20.3 −23.69 0.11 −2.1 1.40 
NGC 3248 156.939270 22.847170 1481 24.6 −22.43 0.09 −2.0 1.20 
NGC 3301 159.233459 21.882166 1339 22.8 −23.28 0.10 −0.4 1.30 
NGC 3377 161.926666 13.985640 10 690 10.9 −22.76 0.15 −4.8 1.55 
NGC 3379 161.956665 12.581630 15 918 10.3 −23.80 0.11 −4.8 1.60 
NGC 3384 162.070404 12.629300 10 733 11.3 −23.52 0.12 −2.7 1.51 
NGC 3400 162.689590 28.468929 1441 24.7 −21.82 0.08 0.7 1.23 
NGC 3412 162.722137 13.412142 860 11.0 −22.55 0.12 −2.0 1.49 
NGC 3414 162.817673 27.974968 1470 24.5 −23.98 0.11 −2.0 1.38 
NGC 3457 163.702591 17.621157 1148 20.1 −21.89 0.13 −5.0 1.13 
NGC 3458 164.006042 57.116970 1877 30.9 −23.12 0.04 −2.0 1.06 
NGC 3489 165.077454 13.901258 695 11.7 −22.99 0.07 −1.2 1.35 
NGC 3499 165.796280 56.221664 1535 26.4 −21.88 0.04 0.0 0.94 
NGC 3522 166.668549 20.085621 1228 25.5 −21.67 0.10 −4.9 1.01 
NGC 3530 167.168411 57.230160 1894 31.2 −22.00 0.04 0.0 0.87 
NGC 3595 168.856461 47.447147 2177 34.7 −23.28 0.09 −3.3 1.15 
NGC 3599 168.862305 18.110369 839 19.8 −22.22 0.09 −2.0 1.37 
NGC 3605 169.194260 18.017141 661 20.1 −21.83 0.09 −4.5 1.23 
NGC 3607 169.227737 18.051809 942 22.2 −24.74 0.09 −3.1 1.59 
NGC 3608 169.245697 18.148531 1226 22.3 −23.65 0.09 −4.8 1.47 
NGC 3610 169.605316 58.786247 1707 20.8 −23.69 0.04 −4.2 1.20 
NGC 3613 169.650543 57.999924 2051 28.3 −24.26 0.05 −4.7 1.42 
NGC 3619 169.840088 57.757683 1560 26.8 −23.57 0.08 −0.9 1.42 
NGC 3626 170.015808 18.356791 1486 19.5 −23.30 0.08 −1.0 1.41 
NGC 3630 170.070786 2.964170 1499 25.0 −23.16 0.18 −1.5 1.10 
NGC 3640 170.278549 3.234764 1298 26.3 −24.60 0.19 −4.9 1.49 
NGC 3641 170.286621 3.194489 1780 25.9 −21.85 0.18 −4.9 0.97 
NGC 3648 170.631195 39.876972 1970 31.9 −23.06 0.09 −2.0 1.12 
NGC 3658 170.992706 38.562424 2039 32.7 −23.45 0.09 −2.2 1.28 
NGC 3665 171.181793 38.762791 2069 33.1 −24.92 0.08 −2.1 1.49 
NGC 3674 171.610870 57.048290 2055 33.4 −23.23 0.06 −1.9 1.05 
NGC 3694 172.225571 35.413857 2243 35.2 −22.35 0.10 −5.0 1.02 
NGC 3757 174.261765 58.415649 1245 22.6 −22.15 0.06 −2.0 0.95 
NGC 3796 175.129776 60.298958 1250 22.7 −21.84 0.06 0.0 1.06 
NGC 3838 176.057205 57.948101 1308 23.5 −22.52 0.05 0.0 1.04 
NGC 3941 178.230667 36.986378 930 11.9 −23.06 0.09 −2.0 1.40 
NGC 3945 178.307190 60.675560 1281 23.2 −24.31 0.12 −1.2 1.45 
NGC 3998 179.484039 55.453564 1048 13.7 −23.33 0.07 −2.1 1.30 
NGC 4026 179.854950 50.961689 985 13.2 −23.03 0.09 −1.8 1.31 
NGC 4036 180.362045 61.895699 1385 24.6 −24.40 0.10 −2.6 1.46 
NGC 4078 181.198456 10.595537 2546 38.1 −22.99 0.11 −2.0 0.92 
NGC 4111 181.763031 43.065392 792 14.6 −23.27 0.06 −1.4 1.08 
NGC 4119 182.040176 10.378720 1656 16.5 −22.60 0.12 −1.3 1.60 
NGC 4143 182.400360 42.534218 946 15.5 −23.10 0.05 −1.9 1.39 
NGC 4150 182.640228 30.401487 208 13.4 −21.65 0.08 −2.1 1.20 
NGC 4168 183.071808 13.205354 2286 30.9 −24.03 0.16 −4.8 1.48 
NGC 4179 183.217087 1.299673 1300 16.5 −23.18 0.14 −1.9 1.30 
NGC 4191 183.459915 7.200842 2646 39.2 −23.10 0.09 −1.8 1.06 
NGC 4203 183.770935 33.197243 1087 14.7 −23.44 0.05 −2.7 1.47 
NGC 4215 183.977142 6.401132 2011 31.5 −23.43 0.07 −0.9 1.18 
NGC 4233 184.282043 7.624434 2306 33.9 −23.88 0.10 −2.0 1.19 
NGC 4249 184.497650 5.598720 2618 38.7 −21.98 0.09 −1.3 1.10 
NGC 4251 184.534607 28.175299 1066 19.1 −23.68 0.10 −1.9 1.29 
NGC 4255 184.734100 4.785923 1995 31.2 −22.99 0.09 −1.9 1.10 
NGC 4259 184.842468 5.376242 2497 37.2 −22.19 0.08 −2.0 0.89 
NGC 4261 184.846924 5.824710 2212 30.8 −25.18 0.08 −4.8 1.58 
NGC 4262 184.877426 14.877717 1375 15.4 −22.60 0.16 −2.7 1.10 
NGC 4264 184.899078 5.846804 2518 37.5 −23.00 0.08 −1.1 1.14 
NGC 4267 184.938675 12.798356 1021 15.8 −23.18 0.20 −2.7 1.58 
NGC 4268 184.946762 5.283650 2034 31.7 −23.05 0.08 −0.3 1.20 
NGC 4270 184.955978 5.463371 2331 35.2 −23.69 0.08 −2.0 1.21 
NGC 4278 185.028320 29.280619 620 15.6 −23.80 0.13 −4.8 1.50 
NGC 4281 185.089691 5.386430 2671 24.4 −24.01 0.09 −1.5 1.34 
NGC 4283 185.086609 29.310898 1056 15.3 −21.80 0.11 −4.8 1.09 
NGC 4324 185.775726 5.250488 1665 16.5 −22.61 0.10 −0.9 1.30 
NGC 4339 185.895599 6.081713 1266 16.0 −22.49 0.11 −4.7 1.48 
NGC 4340 185.897141 16.722195 933 18.4 −23.01 0.11 −1.2 1.57 
NGC 4342 185.912598 7.053936 761 16.5 −22.07 0.09 −3.4 0.82 
NGC 4346 185.866425 46.993881 832 13.9 −22.55 0.05 −2.0 1.29 
NGC 4350 185.990891 16.693356 1210 15.4 −23.13 0.12 −1.8 1.23 
NGC 4365 186.117615 7.317520 13 1243 23.3 −25.21 0.09 −4.8 1.72 
NGC 4371 186.230957 11.704288 933 17.0 −23.45 0.16 −1.3 1.47 
NGC 4374 186.265747 12.886960 13 1017 18.5 −25.12 0.18 −4.3 1.72 
NGC 4377 186.301285 14.762218 1338 17.8 −22.43 0.17 −2.6 1.13 
NGC 4379 186.311386 15.607498 1074 15.8 −22.24 0.10 −2.8 1.27 
NGC 4382 186.350220 18.191080 746 17.9 −25.13 0.13 −1.3 1.82 
NGC 4387 186.423813 12.810359 565 17.9 −22.13 0.14 −4.9 1.20 
NGC 4406 186.549225 12.945970 15 −224 16.8 −25.04 0.13 −4.8 1.97 
NGC 4417 186.710938 9.584117 828 16.0 −22.86 0.11 −1.9 1.25 
NGC 4425 186.805664 12.734803 1908 16.5 −22.09 0.13 −0.6 1.38 
NGC 4429 186.860657 11.107540 1104 16.5 −24.32 0.14 −1.1 1.62 
NGC 4434 186.902832 8.154311 1070 22.4 −22.55 0.10 −4.8 1.16 
NGC 4435 186.918762 13.079021 791 16.7 −23.83 0.13 −2.1 1.49 
NGC 4442 187.016220 9.803620 547 15.3 −23.63 0.09 −1.9 1.44 
NGC 4452 187.180417 11.755000 188 15.6 −21.88 0.13 −2.0 1.30 
NGC 4458 187.239716 13.241916 677 16.4 −21.76 0.10 −4.8 1.37 
NGC 4459 187.250107 13.978580 1192 16.1 −23.89 0.19 −1.4 1.56 
NGC 4461 187.262543 13.183857 1924 16.5 −23.08 0.10 −0.8 1.40 
NGC 4472 187.444992 8.000410 18 981 17.1 −25.78 0.10 −4.8 1.98 
NGC 4473 187.453659 13.429320 2260 15.3 −23.77 0.12 −4.7 1.43 
NGC 4474 187.473099 14.068673 1611 15.6 −22.28 0.18 −2.0 1.30 
NGC 4476 187.496170 12.348669 1968 17.6 −21.78 0.12 −3.0 1.20 
NGC 4477 187.509048 13.636443 1338 16.5 −23.75 0.14 −1.9 1.59 
NGC 4478 187.572662 12.328578 1375 17.0 −22.80 0.10 −4.8 1.20 
NGC 4483 187.669250 9.015665 906 16.7 −21.84 0.09 −1.3 1.24 
NGC 4486 187.705933 12.391100 15 1284 17.2 −25.38 0.10 −4.3 1.91 
NGC 4486A 187.740540 12.270361 758 18.3 −21.82 0.10 −5.0 0.94 
NGC 4489 187.717667 16.758696 961 15.4 −21.59 0.12 −4.8 1.42 
NGC 4494 187.850143 25.774981 1342 16.6 −24.11 0.09 −4.8 1.69 
NGC 4503 188.025803 11.176434 1334 16.5 −23.22 0.22 −1.8 1.45 
NGC 4521 188.198853 63.939293 2511 39.7 −23.92 0.08 −0.1 1.21 
NGC 4526 188.512619 7.699140 617 16.4 −24.62 0.10 −1.9 1.65 
NGC 4528 188.525269 11.321266 1378 15.8 −22.05 0.20 −2.0 1.15 
NGC 4546 188.872940 −3.793227 1057 13.7 −23.30 0.15 −2.7 1.40 
NGC 4550 188.877548 12.220955 459 15.5 −22.27 0.17 −2.1 1.19 
NGC 4551 188.908249 12.264010 1176 16.1 −22.18 0.17 −4.9 1.22 
NGC 4552 188.916183 12.556040 12 344 15.8 −24.29 0.18 −4.6 1.53 
NGC 4564 189.112473 11.439320 1155 15.8 −23.08 0.14 −4.8 1.31 
NGC 4570 189.222504 7.246663 1787 17.1 −23.48 0.09 −2.0 1.30 
NGC 4578 189.377274 9.555121 2292 16.3 −22.66 0.09 −2.0 1.51 
NGC 4596 189.983063 10.176031 1892 16.5 −23.63 0.09 −0.9 1.59 
NGC 4608 190.305374 10.155793 1850 16.5 −22.94 0.07 −1.9 1.42 
NGC 4612 190.386490 7.314782 1775 16.6 −22.55 0.11 −2.0 1.40 
NGC 4621 190.509674 11.646930 467 14.9 −24.14 0.14 −4.8 1.63 
NGC 4623 190.544601 7.676934 1807 17.4 −21.74 0.10 −1.5 1.31 
NGC 4624 191.274826 3.055684 912 16.5 −23.67 0.10 −0.6 1.64 
NGC 4636 190.707779 2.687780 11 930 14.3 −24.36 0.12 −4.8 1.95 
NGC 4638 190.697632 11.442459 1152 17.5 −23.01 0.11 −2.7 1.22 
NGC 4643 190.833893 1.978399 1333 16.5 −23.69 0.13 −0.6 1.38 
NGC 4649 190.916702 11.552610 11 1110 17.3 −25.46 0.11 −4.6 1.82 
NGC 4660 191.133209 11.190533 1087 15.0 −22.69 0.15 −4.7 1.09 
NGC 4684 191.822861 −2.727538 1560 13.1 −22.21 0.12 −1.2 1.32 
NGC 4690 191.981323 −1.655975 2765 40.2 −22.96 0.13 −3.0 1.25 
NGC 4694 192.062881 10.983624 1171 16.5 −22.15 0.17 −2.0 1.47 
NGC 4697 192.149612 −5.800850 1252 11.4 −23.93 0.13 −4.4 1.79 
NGC 4710 192.412323 15.165490 1102 16.5 −23.53 0.13 −0.9 1.48 
NGC 4733 192.778259 10.912103 925 14.5 −21.80 0.09 −3.8 1.52 
NGC 4753 193.092133 −1.199690 1163 22.9 −25.09 0.14 −1.4 1.69 
NGC 4754 193.073181 11.313660 1351 16.1 −23.64 0.14 −2.5 1.50 
NGC 4762 193.233536 11.230800 986 22.6 −24.48 0.09 −1.8 1.64 
NGC 4803 193.890289 8.240547 2645 39.4 −22.28 0.13 0.0 0.94 
NGC 5103 200.125229 43.084015 1273 23.4 −22.36 0.08 0.0 1.02 
NGC 5173 202.105301 46.591572 2424 38.4 −22.88 0.12 −4.9 1.01 
NGC 5198 202.547546 46.670830 2519 39.6 −24.10 0.10 −4.8 1.38 
NGC 5273 205.534943 35.654240 1085 16.1 −22.37 0.04 −1.9 1.57 
NGC 5308 206.751633 60.973038 1998 31.5 −24.13 0.08 −2.1 1.25 
NGC 5322 207.313339 60.190411 1780 30.3 −25.26 0.06 −4.8 1.60 
NGC 5342 207.857910 59.863014 2189 35.5 −22.61 0.05 −2.0 0.97 
NGC 5353 208.361420 40.283123 2198 35.2 −25.11 0.05 −2.1 1.30 
NGC 5355 208.439850 40.338795 2344 37.1 −22.40 0.05 −2.1 1.06 
NGC 5358 208.501801 40.277420 2412 38.0 −22.01 0.04 −0.2 1.05 
NGC 5379 208.893112 59.742825 1774 30.0 −22.08 0.08 −2.0 1.32 
NGC 5422 210.175262 55.164478 1838 30.8 −23.69 0.06 −1.5 1.33 
NGC 5473 211.180176 54.892620 2022 33.2 −24.25 0.05 −2.7 1.32 
NGC 5475 211.301437 55.741802 1671 28.6 −22.88 0.05 1.0 1.22 
NGC 5481 211.671722 50.723320 1989 25.8 −22.68 0.08 −3.9 1.35 
NGC 5485 211.797134 55.001518 1927 25.2 −23.61 0.07 −2.0 1.45 
NGC 5493 212.872421 −5.043663 2665 38.8 −24.49 0.15 −2.1 1.14 
NGC 5500 212.563522 48.546066 1914 31.7 −21.93 0.09 −4.9 1.18 
NGC 5507 213.332825 −3.148860 1851 28.5 −23.19 0.26 −2.3 1.09 
NGC 5557 214.607117 36.493690 3219 38.8 −24.87 0.03 −4.8 1.46 
NGC 5574 215.233109 3.237995 1589 23.2 −22.30 0.13 −2.8 1.13 
NGC 5576 215.265381 3.271049 1506 24.8 −24.15 0.13 −4.8 1.34 
NGC 5582 215.179703 39.693584 1430 27.7 −23.28 0.06 −4.9 1.44 
NGC 5611 216.019897 33.047501 1968 24.5 −22.20 0.05 −1.9 1.00 
NGC 5631 216.638687 56.582664 1944 27.0 −23.70 0.09 −1.9 1.32 
NGC 5638 217.418289 3.233443 1652 25.6 −23.80 0.14 −4.8 1.45 
NGC 5687 218.718201 54.475685 2143 27.2 −23.22 0.05 −3.0 1.36 
NGC 5770 223.312653 3.959721 1471 18.5 −22.15 0.17 −2.0 1.23 
NGC 5813 225.296936 1.701970 1956 31.3 −25.09 0.25 −4.8 1.76 
NGC 5831 226.029266 1.219917 1645 26.4 −23.69 0.25 −4.8 1.40 
NGC 5838 226.359467 2.099356 1341 21.8 −24.13 0.23 −2.6 1.40 
NGC 5839 226.364471 1.634633 1220 22.0 −22.53 0.23 −2.0 1.22 
NGC 5845 226.503281 1.633824 1472 25.2 −22.92 0.23 −4.9 0.80 
NGC 5846 226.621887 1.605637 1712 24.2 −25.01 0.24 −4.7 1.77 
NGC 5854 226.948853 2.568560 1663 26.2 −23.30 0.23 −1.1 1.26 
NGC 5864 227.389786 3.052741 1874 29.0 −23.62 0.19 −1.7 1.35 
NGC 5866 226.623169 55.763309 755 14.9 −24.00 0.06 −1.3 1.56 
NGC 5869 227.456055 0.469967 2065 24.9 −23.27 0.24 −2.3 1.31 
NGC 6010 238.579773 0.543033 2022 30.6 −23.53 0.45 0.4 1.16 
NGC 6014 238.989105 5.931838 2381 35.8 −22.99 0.22 −1.9 1.35 
NGC 6017 239.314529 5.998364 1788 29.0 −22.52 0.23 −5.0 0.85 
NGC 6149 246.851151 19.597290 2427 37.2 −22.60 0.30 −1.9 1.03 
NGC 6278 255.209763 23.010956 2832 42.9 −24.19 0.27 −1.9 1.22 
NGC 6547 271.291748 25.232645 2677 40.8 −23.60 0.50 −1.3 1.06 
NGC 6548 271.496826 18.587217 2208 22.4 −23.19 0.35 −1.9 1.35 
NGC 6703 281.828522 45.550648 2373 25.9 −23.85 0.37 −2.8 1.34 
NGC 6798 291.013306 53.624752 2360 37.5 −23.52 0.57 −2.0 1.23 
NGC 7280 336.614899 16.148266 1845 23.7 −22.83 0.24 −1.3 1.33 
NGC 7332 339.352173 23.798351 1197 22.4 −23.75 0.16 −1.9 1.24 
NGC 7454 345.277130 16.388371 2020 23.2 −23.00 0.33 −4.7 1.41 
NGC 7457 345.249725 30.144892 844 12.9 −22.38 0.23 −2.6 1.56 
NGC 7465 345.503967 15.964876 1960 29.3 −22.82 0.33 −1.9 0.90 
NGC 7693 353.293671 −1.292010 2502 35.4 −21.58 0.15 −1.0 1.11 
NGC 7710 353.942261 −2.880941 2407 34.0 −21.99 0.15 −1.9 0.92 
PGC 016060 72.143387 −3.867104 2764 37.8 −22.64 0.19 −0.6 1.01 
PGC 028887 149.931290 11.660812 2833 41.0 −22.26 0.17 0.0 1.08 
PGC 029321 151.463226 12.961213 2816 40.9 −21.66 0.16 0.0 0.89 
PGC 035754 173.614716 33.178913 2534 39.0 −21.90 0.11 −3.0 0.83 
PGC 042549 190.316513 −5.009177 2822 40.7 −22.71 0.11 −5.0 1.06 
PGC 044433 194.578110 13.391409 2675 40.1 −22.25 0.13 0.0 0.71 
PGC 050395 211.913544 54.794575 2322 37.2 −21.92 0.05 0.0 1.04 
PGC 051753 217.310318 44.699104 2418 38.3 −21.92 0.05 0.0 1.01 
PGC 054452 228.894180 2.248187 1918 29.5 −21.59 0.18 −2.0 1.14 
PGC 056772 240.548340 7.085953 2655 39.5 −22.06 0.19 −2.0 0.93 
PGC 058114 246.517838 2.906550 1507 23.8 −21.57 0.29 −2.0 0.97 
PGC 061468 272.360748 19.117682 2371 36.2 −21.68 0.35 0.0 1.06 
PGC 071531 352.121338 19.863962 2030 30.4 −21.74 0.53 −4.0 0.88 
PGC 170172 176.731720 −5.187745 2562 37.1 −21.89 0.08 −5.0 0.89 
UGC 03960 115.094856 23.275089 2255 33.2 −21.89 0.20 −4.9 1.24 
UGC 04551 131.024582 49.793968 1728 28.0 −22.92 0.10 −2.0 1.03 
UGC 05408 150.966095 59.436138 2998 45.8 −22.03 0.06 −3.3 0.84 
UGC 06062 164.656662 9.050468 2634 38.7 −22.82 0.13 −2.0 1.05 
UGC 06176 166.852753 21.657185 2677 40.1 −22.66 0.08 −2.0 1.03 
UGC 08876 209.241943 45.973179 2085 33.9 −22.37 0.04 −0.1 0.93 
UGC 09519 221.588028 34.370651 1631 27.6 −21.98 0.09 −1.9 0.87 
Galaxy RA (°) Dec. (°) SBF NED-D Virgo Vhel (km s−1D (Mpc) MK (mag) AB (mag) T type log Re (arcsec) 
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) 
IC 0560 146.472656 −0.268221 1853 27.2 −22.10 0.59 −0.7 1.11 
IC 0598 153.202423 43.145546 2256 35.3 −22.60 0.06 −0.1 1.02 
IC 0676 168.165909 9.055736 1429 24.6 −22.27 0.11 −1.3 1.35 
IC 0719 175.077042 9.009861 1833 29.4 −22.70 0.22 −2.0 1.10 
IC 0782 185.404053 5.765672 2424 36.3 −22.02 0.09 2.7 1.35 
IC 1024 217.863419 3.009107 1479 24.2 −21.85 0.13 −2.0 1.05 
IC 3631 189.950195 12.973927 2822 42.0 −22.01 0.17 −1.3 1.13 
NGC 0448 18.818876 −1.626105 1908 29.5 −23.02 0.26 −2.5 1.05 
NGC 0474 20.027901 3.415270 2315 30.9 −23.91 0.15 −2.0 1.52 
NGC 0502 20.731415 9.049169 2524 35.9 −23.05 0.17 −2.0 1.07 
NGC 0509 20.850327 9.433469 2261 32.3 −21.89 0.20 −1.3 1.37 
NGC 0516 21.033607 9.551668 2437 34.7 −22.21 0.29 −1.5 1.16 
NGC 0524 21.198778 9.538793 10 2403 23.3 −24.71 0.36 −1.2 1.64 
NGC 0525 21.220442 9.703240 2139 30.7 −21.86 0.38 −2.0 1.06 
NGC 0661 26.060976 28.705988 3815 30.6 −23.19 0.30 −4.4 1.12 
NGC 0680 27.447035 21.970827 2928 37.5 −24.17 0.34 −4.0 1.16 
NGC 0770 29.806850 18.954695 2543 36.7 −22.57 0.31 −4.2 0.94 
NGC 0821 32.088123 10.994870 1718 23.4 −23.99 0.48 −4.8 1.60 
NGC 0936 36.906090 −1.156280 1429 22.4 −24.85 0.15 −1.2 1.72 
NGC 1023 40.100052 39.063251 602 11.1 −24.01 0.26 −2.7 1.68 
NGC 1121 42.663387 −1.734040 2558 35.3 −22.70 0.29 −1.8 0.87 
NGC 1222 47.236446 −2.955212 2422 33.3 −22.71 0.26 −3.0 1.10 
NGC 1248 48.202328 −5.224674 2217 30.4 −22.90 0.27 −2.0 1.20 
NGC 1266 49.003120 −2.427370 2170 29.9 −22.93 0.43 −2.1 1.31 
NGC 1289 49.707592 −1.973354 2792 38.4 −23.46 0.37 −2.1 1.26 
NGC 1665 72.071098 −5.427655 2745 37.5 −23.63 0.26 −1.8 1.50 
NGC 2481 119.307182 23.767693 2157 32.0 −23.38 0.28 0.4 1.02 
NGC 2549 124.743111 57.803108 1051 12.3 −22.43 0.28 −2.0 1.28 
NGC 2577 125.681137 22.553040 2062 30.8 −23.41 0.23 −3.0 1.15 
NGC 2592 126.783669 25.970339 1979 25.0 −22.88 0.25 −4.8 1.09 
NGC 2594 126.821609 25.878935 2362 35.1 −22.36 0.24 0.0 0.82 
NGC 2679 132.887192 30.865419 2027 31.1 −22.81 0.14 −2.0 1.35 
NGC 2685 133.894791 58.734409 875 16.7 −22.78 0.27 −1.0 1.41 
NGC 2695 133.612778 −3.067101 1833 31.5 −23.64 0.08 −2.1 1.21 
NGC 2698 133.902222 −3.183882 1900 27.1 −23.32 0.08 −1.0 1.10 
NGC 2699 133.953415 −3.127507 1868 26.2 −22.72 0.08 −5.0 1.06 
NGC 2764 137.072983 21.443447 2706 39.6 −23.19 0.17 −2.0 1.09 
NGC 2768 137.906265 60.037209 1353 21.8 −24.71 0.20 −4.4 1.80 
NGC 2778 138.101639 35.027424 2025 22.3 −22.23 0.09 −4.8 1.20 
NGC 2824 139.759277 26.269999 2758 40.7 −22.93 0.14 −2.0 0.86 
NGC 2852 140.810684 40.163879 1781 28.5 −22.18 0.06 1.0 0.85 
NGC 2859 141.077286 34.513378 1690 27.0 −24.13 0.09 −1.2 1.43 
NGC 2880 142.394241 62.490620 1554 21.3 −22.98 0.14 −2.7 1.32 
NGC 2950 145.646317 58.851219 1322 14.5 −22.93 0.07 −2.0 1.19 
NGC 2962 145.224609 5.165820 1967 34.0 −24.01 0.25 −1.1 1.39 
NGC 2974 145.638611 −3.699116 1887 20.9 −23.62 0.23 −4.2 1.58 
NGC 3032 148.034119 29.236279 1562 21.4 −22.01 0.07 −1.9 1.12 
NGC 3073 150.216843 55.618935 1173 32.8 −21.78 0.05 −2.8 1.13 
NGC 3098 150.569458 24.711092 1397 23.0 −22.72 0.16 −1.5 1.12 
NGC 3156 153.171692 3.129320 1338 21.8 −22.15 0.15 −2.5 1.24 
NGC 3182 154.887558 58.205818 2118 34.0 −23.19 0.05 0.4 1.32 
NGC 3193 154.603683 21.893978 1381 33.1 −24.63 0.11 −4.8 1.42 
NGC 3226 155.862549 19.898439 1315 22.9 −23.24 0.10 −4.8 1.49 
NGC 3230 155.933090 12.567883 2795 40.8 −24.18 0.16 −1.8 1.26 
NGC 3245 156.826523 28.507435 1326 20.3 −23.69 0.11 −2.1 1.40 
NGC 3248 156.939270 22.847170 1481 24.6 −22.43 0.09 −2.0 1.20 
NGC 3301 159.233459 21.882166 1339 22.8 −23.28 0.10 −0.4 1.30 
NGC 3377 161.926666 13.985640 10 690 10.9 −22.76 0.15 −4.8 1.55 
NGC 3379 161.956665 12.581630 15 918 10.3 −23.80 0.11 −4.8 1.60 
NGC 3384 162.070404 12.629300 10 733 11.3 −23.52 0.12 −2.7 1.51 
NGC 3400 162.689590 28.468929 1441 24.7 −21.82 0.08 0.7 1.23 
NGC 3412 162.722137 13.412142 860 11.0 −22.55 0.12 −2.0 1.49 
NGC 3414 162.817673 27.974968 1470 24.5 −23.98 0.11 −2.0 1.38 
NGC 3457 163.702591 17.621157 1148 20.1 −21.89 0.13 −5.0 1.13 
NGC 3458 164.006042 57.116970 1877 30.9 −23.12 0.04 −2.0 1.06 
NGC 3489 165.077454 13.901258 695 11.7 −22.99 0.07 −1.2 1.35 
NGC 3499 165.796280 56.221664 1535 26.4 −21.88 0.04 0.0 0.94 
NGC 3522 166.668549 20.085621 1228 25.5 −21.67 0.10 −4.9 1.01 
NGC 3530 167.168411 57.230160 1894 31.2 −22.00 0.04 0.0 0.87 
NGC 3595 168.856461 47.447147 2177 34.7 −23.28 0.09 −3.3 1.15 
NGC 3599 168.862305 18.110369 839 19.8 −22.22 0.09 −2.0 1.37 
NGC 3605 169.194260 18.017141 661 20.1 −21.83 0.09 −4.5 1.23 
NGC 3607 169.227737 18.051809 942 22.2 −24.74 0.09 −3.1 1.59 
NGC 3608 169.245697 18.148531 1226 22.3 −23.65 0.09 −4.8 1.47 
NGC 3610 169.605316 58.786247 1707 20.8 −23.69 0.04 −4.2 1.20 
NGC 3613 169.650543 57.999924 2051 28.3 −24.26 0.05 −4.7 1.42 
NGC 3619 169.840088 57.757683 1560 26.8 −23.57 0.08 −0.9 1.42 
NGC 3626 170.015808 18.356791 1486 19.5 −23.30 0.08 −1.0 1.41 
NGC 3630 170.070786 2.964170 1499 25.0 −23.16 0.18 −1.5 1.10 
NGC 3640 170.278549 3.234764 1298 26.3 −24.60 0.19 −4.9 1.49 
NGC 3641 170.286621 3.194489 1780 25.9 −21.85 0.18 −4.9 0.97 
NGC 3648 170.631195 39.876972 1970 31.9 −23.06 0.09 −2.0 1.12 
NGC 3658 170.992706 38.562424 2039 32.7 −23.45 0.09 −2.2 1.28 
NGC 3665 171.181793 38.762791 2069 33.1 −24.92 0.08 −2.1 1.49 
NGC 3674 171.610870 57.048290 2055 33.4 −23.23 0.06 −1.9 1.05 
NGC 3694 172.225571 35.413857 2243 35.2 −22.35 0.10 −5.0 1.02 
NGC 3757 174.261765 58.415649 1245 22.6 −22.15 0.06 −2.0 0.95 
NGC 3796 175.129776 60.298958 1250 22.7 −21.84 0.06 0.0 1.06 
NGC 3838 176.057205 57.948101 1308 23.5 −22.52 0.05 0.0 1.04 
NGC 3941 178.230667 36.986378 930 11.9 −23.06 0.09 −2.0 1.40 
NGC 3945 178.307190 60.675560 1281 23.2 −24.31 0.12 −1.2 1.45 
NGC 3998 179.484039 55.453564 1048 13.7 −23.33 0.07 −2.1 1.30 
NGC 4026 179.854950 50.961689 985 13.2 −23.03 0.09 −1.8 1.31 
NGC 4036 180.362045 61.895699 1385 24.6 −24.40 0.10 −2.6 1.46 
NGC 4078 181.198456 10.595537 2546 38.1 −22.99 0.11 −2.0 0.92 
NGC 4111 181.763031 43.065392 792 14.6 −23.27 0.06 −1.4 1.08 
NGC 4119 182.040176 10.378720 1656 16.5 −22.60 0.12 −1.3 1.60 
NGC 4143 182.400360 42.534218 946 15.5 −23.10 0.05 −1.9 1.39 
NGC 4150 182.640228 30.401487 208 13.4 −21.65 0.08 −2.1 1.20 
NGC 4168 183.071808 13.205354 2286 30.9 −24.03 0.16 −4.8 1.48 
NGC 4179 183.217087 1.299673 1300 16.5 −23.18 0.14 −1.9 1.30 
NGC 4191 183.459915 7.200842 2646 39.2 −23.10 0.09 −1.8 1.06 
NGC 4203 183.770935 33.197243 1087 14.7 −23.44 0.05 −2.7 1.47 
NGC 4215 183.977142 6.401132 2011 31.5 −23.43 0.07 −0.9 1.18 
NGC 4233 184.282043 7.624434 2306 33.9 −23.88 0.10 −2.0 1.19 
NGC 4249 184.497650 5.598720 2618 38.7 −21.98 0.09 −1.3 1.10 
NGC 4251 184.534607 28.175299 1066 19.1 −23.68 0.10 −1.9 1.29 
NGC 4255 184.734100 4.785923 1995 31.2 −22.99 0.09 −1.9 1.10 
NGC 4259 184.842468 5.376242 2497 37.2 −22.19 0.08 −2.0 0.89 
NGC 4261 184.846924 5.824710 2212 30.8 −25.18 0.08 −4.8 1.58 
NGC 4262 184.877426 14.877717 1375 15.4 −22.60 0.16 −2.7 1.10 
NGC 4264 184.899078 5.846804 2518 37.5 −23.00 0.08 −1.1 1.14 
NGC 4267 184.938675 12.798356 1021 15.8 −23.18 0.20 −2.7 1.58 
NGC 4268 184.946762 5.283650 2034 31.7 −23.05 0.08 −0.3 1.20 
NGC 4270 184.955978 5.463371 2331 35.2 −23.69 0.08 −2.0 1.21 
NGC 4278 185.028320 29.280619 620 15.6 −23.80 0.13 −4.8 1.50 
NGC 4281 185.089691 5.386430 2671 24.4 −24.01 0.09 −1.5 1.34 
NGC 4283 185.086609 29.310898 1056 15.3 −21.80 0.11 −4.8 1.09 
NGC 4324 185.775726 5.250488 1665 16.5 −22.61 0.10 −0.9 1.30 
NGC 4339 185.895599 6.081713 1266 16.0 −22.49 0.11 −4.7 1.48 
NGC 4340 185.897141 16.722195 933 18.4 −23.01 0.11 −1.2 1.57 
NGC 4342 185.912598 7.053936 761 16.5 −22.07 0.09 −3.4 0.82 
NGC 4346 185.866425 46.993881 832 13.9 −22.55 0.05 −2.0 1.29 
NGC 4350 185.990891 16.693356 1210 15.4 −23.13 0.12 −1.8 1.23 
NGC 4365 186.117615 7.317520 13 1243 23.3 −25.21 0.09 −4.8 1.72 
NGC 4371 186.230957 11.704288 933 17.0 −23.45 0.16 −1.3 1.47 
NGC 4374 186.265747 12.886960 13 1017 18.5 −25.12 0.18 −4.3 1.72 
NGC 4377 186.301285 14.762218 1338 17.8 −22.43 0.17 −2.6 1.13 
NGC 4379 186.311386 15.607498 1074 15.8 −22.24 0.10 −2.8 1.27 
NGC 4382 186.350220 18.191080 746 17.9 −25.13 0.13 −1.3 1.82 
NGC 4387 186.423813 12.810359 565 17.9 −22.13 0.14 −4.9 1.20 
NGC 4406 186.549225 12.945970 15 −224 16.8 −25.04 0.13 −4.8 1.97 
NGC 4417 186.710938 9.584117 828 16.0 −22.86 0.11 −1.9 1.25 
NGC 4425 186.805664 12.734803 1908 16.5 −22.09 0.13 −0.6 1.38 
NGC 4429 186.860657 11.107540 1104 16.5 −24.32 0.14 −1.1 1.62 
NGC 4434 186.902832 8.154311 1070 22.4 −22.55 0.10 −4.8 1.16 
NGC 4435 186.918762 13.079021 791 16.7 −23.83 0.13 −2.1 1.49 
NGC 4442 187.016220 9.803620 547 15.3 −23.63 0.09 −1.9 1.44 
NGC 4452 187.180417 11.755000 188 15.6 −21.88 0.13 −2.0 1.30 
NGC 4458 187.239716 13.241916 677 16.4 −21.76 0.10 −4.8 1.37 
NGC 4459 187.250107 13.978580 1192 16.1 −23.89 0.19 −1.4 1.56 
NGC 4461 187.262543 13.183857 1924 16.5 −23.08 0.10 −0.8 1.40 
NGC 4472 187.444992 8.000410 18 981 17.1 −25.78 0.10 −4.8 1.98 
NGC 4473 187.453659 13.429320 2260 15.3 −23.77 0.12 −4.7 1.43 
NGC 4474 187.473099 14.068673 1611 15.6 −22.28 0.18 −2.0 1.30 
NGC 4476 187.496170 12.348669 1968 17.6 −21.78 0.12 −3.0 1.20 
NGC 4477 187.509048 13.636443 1338 16.5 −23.75 0.14 −1.9 1.59 
NGC 4478 187.572662 12.328578 1375 17.0 −22.80 0.10 −4.8 1.20 
NGC 4483 187.669250 9.015665 906 16.7 −21.84 0.09 −1.3 1.24 
NGC 4486 187.705933 12.391100 15 1284 17.2 −25.38 0.10 −4.3 1.91 
NGC 4486A 187.740540 12.270361 758 18.3 −21.82 0.10 −5.0 0.94 
NGC 4489 187.717667 16.758696 961 15.4 −21.59 0.12 −4.8 1.42 
NGC 4494 187.850143 25.774981 1342 16.6 −24.11 0.09 −4.8 1.69 
NGC 4503 188.025803 11.176434 1334 16.5 −23.22 0.22 −1.8 1.45 
NGC 4521 188.198853 63.939293 2511 39.7 −23.92 0.08 −0.1 1.21 
NGC 4526 188.512619 7.699140 617 16.4 −24.62 0.10 −1.9 1.65 
NGC 4528 188.525269 11.321266 1378 15.8 −22.05 0.20 −2.0 1.15 
NGC 4546 188.872940 −3.793227 1057 13.7 −23.30 0.15 −2.7 1.40 
NGC 4550 188.877548 12.220955 459 15.5 −22.27 0.17 −2.1 1.19 
NGC 4551 188.908249 12.264010 1176 16.1 −22.18 0.17 −4.9 1.22 
NGC 4552 188.916183 12.556040 12 344 15.8 −24.29 0.18 −4.6 1.53 
NGC 4564 189.112473 11.439320 1155 15.8 −23.08 0.14 −4.8 1.31 
NGC 4570 189.222504 7.246663 1787 17.1 −23.48 0.09 −2.0 1.30 
NGC 4578 189.377274 9.555121 2292 16.3 −22.66 0.09 −2.0 1.51 
NGC 4596 189.983063 10.176031 1892 16.5 −23.63 0.09 −0.9 1.59 
NGC 4608 190.305374 10.155793 1850 16.5 −22.94 0.07 −1.9 1.42 
NGC 4612 190.386490 7.314782 1775 16.6 −22.55 0.11 −2.0 1.40 
NGC 4621 190.509674 11.646930 467 14.9 −24.14 0.14 −4.8 1.63 
NGC 4623 190.544601 7.676934 1807 17.4 −21.74 0.10 −1.5 1.31 
NGC 4624 191.274826 3.055684 912 16.5 −23.67 0.10 −0.6 1.64 
NGC 4636 190.707779 2.687780 11 930 14.3 −24.36 0.12 −4.8 1.95 
NGC 4638 190.697632 11.442459 1152 17.5 −23.01 0.11 −2.7 1.22 
NGC 4643 190.833893 1.978399 1333 16.5 −23.69 0.13 −0.6 1.38 
NGC 4649 190.916702 11.552610 11 1110 17.3 −25.46 0.11 −4.6 1.82 
NGC 4660 191.133209 11.190533 1087 15.0 −22.69 0.15 −4.7 1.09 
NGC 4684 191.822861 −2.727538 1560 13.1 −22.21 0.12 −1.2 1.32 
NGC 4690 191.981323 −1.655975 2765 40.2 −22.96 0.13 −3.0 1.25 
NGC 4694 192.062881 10.983624 1171 16.5 −22.15 0.17 −2.0 1.47 
NGC 4697 192.149612 −5.800850 1252 11.4 −23.93 0.13 −4.4 1.79 
NGC 4710 192.412323 15.165490 1102 16.5 −23.53 0.13 −0.9 1.48 
NGC 4733 192.778259 10.912103 925 14.5 −21.80 0.09 −3.8 1.52 
NGC 4753 193.092133 −1.199690 1163 22.9 −25.09 0.14 −1.4 1.69 
NGC 4754 193.073181 11.313660 1351 16.1 −23.64 0.14 −2.5 1.50 
NGC 4762 193.233536 11.230800 986 22.6 −24.48 0.09 −1.8 1.64 
NGC 4803 193.890289 8.240547 2645 39.4 −22.28 0.13 0.0 0.94 
NGC 5103 200.125229 43.084015 1273 23.4 −22.36 0.08 0.0 1.02 
NGC 5173 202.105301 46.591572 2424 38.4 −22.88 0.12 −4.9 1.01 
NGC 5198 202.547546 46.670830 2519 39.6 −24.10 0.10 −4.8 1.38 
NGC 5273 205.534943 35.654240 1085 16.1 −22.37 0.04 −1.9 1.57 
NGC 5308 206.751633 60.973038 1998 31.5 −24.13 0.08 −2.1 1.25 
NGC 5322 207.313339 60.190411 1780 30.3 −25.26 0.06 −4.8 1.60 
NGC 5342 207.857910 59.863014 2189 35.5 −22.61 0.05 −2.0 0.97 
NGC 5353 208.361420 40.283123 2198 35.2 −25.11 0.05 −2.1 1.30 
NGC 5355 208.439850 40.338795 2344 37.1 −22.40 0.05 −2.1 1.06 
NGC 5358 208.501801 40.277420 2412 38.0 −22.01 0.04 −0.2 1.05 
NGC 5379 208.893112 59.742825 1774 30.0 −22.08 0.08 −2.0 1.32 
NGC 5422 210.175262 55.164478 1838 30.8 −23.69 0.06 −1.5 1.33 
NGC 5473 211.180176 54.892620 2022 33.2 −24.25 0.05 −2.7 1.32 
NGC 5475 211.301437 55.741802 1671 28.6 −22.88 0.05 1.0 1.22 
NGC 5481 211.671722 50.723320 1989 25.8 −22.68 0.08 −3.9 1.35 
NGC 5485 211.797134 55.001518 1927 25.2 −23.61 0.07 −2.0 1.45 
NGC 5493 212.872421 −5.043663 2665 38.8 −24.49 0.15 −2.1 1.14 
NGC 5500 212.563522 48.546066 1914 31.7 −21.93 0.09 −4.9 1.18 
NGC 5507 213.332825 −3.148860 1851 28.5 −23.19 0.26 −2.3 1.09 
NGC 5557 214.607117 36.493690 3219 38.8 −24.87 0.03 −4.8 1.46 
NGC 5574 215.233109 3.237995 1589 23.2 −22.30 0.13 −2.8 1.13 
NGC 5576 215.265381 3.271049 1506 24.8 −24.15 0.13 −4.8 1.34 
NGC 5582 215.179703 39.693584 1430 27.7 −23.28 0.06 −4.9 1.44 
NGC 5611 216.019897 33.047501 1968 24.5 −22.20 0.05 −1.9 1.00 
NGC 5631 216.638687 56.582664 1944 27.0 −23.70 0.09 −1.9 1.32 
NGC 5638 217.418289 3.233443 1652 25.6 −23.80 0.14 −4.8 1.45 
NGC 5687 218.718201 54.475685 2143 27.2 −23.22 0.05 −3.0 1.36 
NGC 5770 223.312653 3.959721 1471 18.5 −22.15 0.17 −2.0 1.23 
NGC 5813 225.296936 1.701970 1956 31.3 −25.09 0.25 −4.8 1.76 
NGC 5831 226.029266 1.219917 1645 26.4 −23.69 0.25 −4.8 1.40 
NGC 5838 226.359467 2.099356 1341 21.8 −24.13 0.23 −2.6 1.40 
NGC 5839 226.364471 1.634633 1220 22.0 −22.53 0.23 −2.0 1.22 
NGC 5845 226.503281 1.633824 1472 25.2 −22.92 0.23 −4.9 0.80 
NGC 5846 226.621887 1.605637 1712 24.2 −25.01 0.24 −4.7 1.77 
NGC 5854 226.948853 2.568560 1663 26.2 −23.30 0.23 −1.1 1.26 
NGC 5864 227.389786 3.052741 1874 29.0 −23.62 0.19 −1.7 1.35 
NGC 5866 226.623169 55.763309 755 14.9 −24.00 0.06 −1.3 1.56 
NGC 5869 227.456055 0.469967 2065 24.9 −23.27 0.24 −2.3 1.31 
NGC 6010 238.579773 0.543033 2022 30.6 −23.53 0.45 0.4 1.16 
NGC 6014 238.989105 5.931838 2381 35.8 −22.99 0.22 −1.9 1.35 
NGC 6017 239.314529 5.998364 1788 29.0 −22.52 0.23 −5.0 0.85 
NGC 6149 246.851151 19.597290 2427 37.2 −22.60 0.30 −1.9 1.03 
NGC 6278 255.209763 23.010956 2832 42.9 −24.19 0.27 −1.9 1.22 
NGC 6547 271.291748 25.232645 2677 40.8 −23.60 0.50 −1.3 1.06 
NGC 6548 271.496826 18.587217 2208 22.4 −23.19 0.35 −1.9 1.35 
NGC 6703 281.828522 45.550648 2373 25.9 −23.85 0.37 −2.8 1.34 
NGC 6798 291.013306 53.624752 2360 37.5 −23.52 0.57 −2.0 1.23 
NGC 7280 336.614899 16.148266 1845 23.7 −22.83 0.24 −1.3 1.33 
NGC 7332 339.352173 23.798351 1197 22.4 −23.75 0.16 −1.9 1.24 
NGC 7454 345.277130 16.388371 2020 23.2 −23.00 0.33 −4.7 1.41 
NGC 7457 345.249725 30.144892 844 12.9 −22.38 0.23 −2.6 1.56 
NGC 7465 345.503967 15.964876 1960 29.3 −22.82 0.33 −1.9 0.90 
NGC 7693 353.293671 −1.292010 2502 35.4 −21.58 0.15 −1.0 1.11 
NGC 7710 353.942261 −2.880941 2407 34.0 −21.99 0.15 −1.9 0.92 
PGC 016060 72.143387 −3.867104 2764 37.8 −22.64 0.19 −0.6 1.01 
PGC 028887 149.931290 11.660812 2833 41.0 −22.26 0.17 0.0 1.08 
PGC 029321 151.463226 12.961213 2816 40.9 −21.66 0.16 0.0 0.89 
PGC 035754 173.614716 33.178913 2534 39.0 −21.90 0.11 −3.0 0.83 
PGC 042549 190.316513 −5.009177 2822 40.7 −22.71 0.11 −5.0 1.06 
PGC 044433 194.578110 13.391409 2675 40.1 −22.25 0.13 0.0 0.71 
PGC 050395 211.913544 54.794575 2322 37.2 −21.92 0.05 0.0 1.04 
PGC 051753 217.310318 44.699104 2418 38.3 −21.92 0.05 0.0 1.01 
PGC 054452 228.894180 2.248187 1918 29.5 −21.59 0.18 −2.0 1.14 
PGC 056772 240.548340 7.085953 2655 39.5 −22.06 0.19 −2.0 0.93 
PGC 058114 246.517838 2.906550 1507 23.8 −21.57 0.29 −2.0 0.97 
PGC 061468 272.360748 19.117682 2371 36.2 −21.68 0.35 0.0 1.06 
PGC 071531 352.121338 19.863962 2030 30.4 −21.74 0.53 −4.0 0.88 
PGC 170172 176.731720 −5.187745 2562 37.1 −21.89 0.08 −5.0 0.89 
UGC 03960 115.094856 23.275089 2255 33.2 −21.89 0.20 −4.9 1.24 
UGC 04551 131.024582 49.793968 1728 28.0 −22.92 0.10 −2.0 1.03 
UGC 05408 150.966095 59.436138 2998 45.8 −22.03 0.06 −3.3 0.84 
UGC 06062 164.656662 9.050468 2634 38.7 −22.82 0.13 −2.0 1.05 
UGC 06176 166.852753 21.657185 2677 40.1 −22.66 0.08 −2.0 1.03 
UGC 08876 209.241943 45.973179 2085 33.9 −22.37 0.04 −0.1 0.93 
UGC 09519 221.588028 34.370651 1631 27.6 −21.98 0.09 −1.9 0.87 

Note. Column (1): the name is the principal designation from LEDA, which is used as standard designation for our project. Column (2): right Ascension in degrees and decimal (J2000.0). Column (3): declination in degrees and decimals (J2000.0). As the galaxy names may not be always consistent between different catalogues, these coordinate define the galaxies of the sample. Column (4): SBF = 1 if the galaxy is in Tonry et al. (2001) and SBF = 2 if it is in Mei et al. (2007) or both. Column (5): number of redshift-independent distance determinations listed in the NED-D catalogue, excluding the ones based on kinematical scaling relations. Column (6): Virgo = 1 if the galaxies is contained within a sphere of radius R = 3.5 Mpc from the centre of the cluster assumed at coordinates RA =12h28m19s and Dec. =+12°40′ (Mould et al. 2000) and distance D = 16.5 Mpc (Mei et al. 2007). Column (7): heliocentric velocity measured from the SAURON integral field stellar kinematics (1σ error ΔVhel = 5 km s−1). Column (8): distance in Mpc; when SBF = 1 the distance comes from Tonry et al. (2001), corrected by subtracting 0.06 mag to the distance modulus (Mei et al. 2007); when SBF = 2 the distance comes from Mei et al. (2007); when SBF = 0 and NED-D > 0 the distance is the median of the NED-D values, excluding the ones based on kinematical scaling relations; when SBF = NED-D = 0 and the galaxy is in Virgo (Virgo = 1) then it is assigned the cluster distance D = 16.5 Mpc (Mei et al. 2007); otherwise D=Vcosmic/H0, with H0 = 72 km s−1 Mpc−1, where Vcosmic is the velocity derived from Vhel via the local flow field model of Mould et al. (2000) using only the Virgo attractor. Column (9): total galaxy absolute magnitude derived from the apparent magnitude KT (2MASS keyword k_m_ext) at the adopted distance D and corrected for the foreground galactic extinction: MK=KT− 5 log10D− 25 −AB/11.8, which assumes AB/AK = 11.8. Column (10): B-band foreground galactic extinction from Schlegel, Finkbeiner & Davis (1998). Column (11): morphological T type from HyperLeda. E: T≤−3.5; S0: −3.5 < T≤−0.5. This morphology was not the one used for the sample selection, but is printed in Figs 5 and 6. Column (12): projected half-light effective radius. It was derived from a combination of RC3 and 2MASS determinations, which both use growth curves, as described in Section 4.1, but it was normalized to agree on average with RC3.

Table 4

The 611 spiral galaxies in the ATLAS3D parent sample.

Galaxy RA (°) Dec. (°) SBF NED-D Virgo Vhel (km s−1D (Mpc) MK (mag) AB (mag) T type log Re (arcsec) 
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) 
IC 0065 15.230966 47.681984 2614 39.7 −23.54 0.64 4.0 1.38 
IC 0163 27.312431 20.711317 2749 39.7 −22.38 0.36 8.0 1.35 
IC 0239 39.116250 38.970000 903 15.7 −22.23 0.31 6.0 1.90 
IC 0540 142.542755 7.902529 2035 30.0 −21.89 0.26 3.5 1.08 
IC 0591 151.865479 12.274520 2839 41.2 −21.82 0.15 6.0 1.19 
IC 0610 156.618179 20.228252 1170 19.6 −21.53 0.09 3.9 1.02 
IC 0750 179.717606 42.722404 701 36.8 −24.71 0.09 2.1 1.24 
IC 0777 184.849228 28.309881 2541 39.0 −21.92 0.10 2.6 0.95 
IC 0800 188.486313 15.354542 2326 35.8 −22.20 0.16 5.2 1.56 
IC 0851 197.143127 21.049742 2615 39.8 −21.82 0.15 3.1 1.31 
Galaxy RA (°) Dec. (°) SBF NED-D Virgo Vhel (km s−1D (Mpc) MK (mag) AB (mag) T type log Re (arcsec) 
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) 
IC 0065 15.230966 47.681984 2614 39.7 −23.54 0.64 4.0 1.38 
IC 0163 27.312431 20.711317 2749 39.7 −22.38 0.36 8.0 1.35 
IC 0239 39.116250 38.970000 903 15.7 −22.23 0.31 6.0 1.90 
IC 0540 142.542755 7.902529 2035 30.0 −21.89 0.26 3.5 1.08 
IC 0591 151.865479 12.274520 2839 41.2 −21.82 0.15 6.0 1.19 
IC 0610 156.618179 20.228252 1170 19.6 −21.53 0.09 3.9 1.02 
IC 0750 179.717606 42.722404 701 36.8 −24.71 0.09 2.1 1.24 
IC 0777 184.849228 28.309881 2541 39.0 −21.92 0.10 2.6 0.95 
IC 0800 188.486313 15.354542 2326 35.8 −22.20 0.16 5.2 1.56 
IC 0851 197.143127 21.049742 2615 39.8 −21.82 0.15 3.1 1.31 

Note. The meaning of the columns is the same as in Table 3, except for column (7), which contain here the heliocentric velocity taken from NED. Only the first 10 rows are shown; the full 611 will be published electronically (see Supporting Information). Both Tables 3 and 4 are available from our project website http://purl.org/atlas3d

2.2 Sources of distances and errors

Numerous sources of distances for nearby galaxies have been accumulated over the past decades. In most cases the distances are based on redshift as provided by large redshift surveys, but a number of more accurate distances are available based on other methods (see e.g. the recent compilations of Tully et al. 2008, 2009; Karachentsev & Nasonova 2010). For the ∼20 000 2MASS galaxies with KT < 11.6 mag we tried to automatically assign the most accurate available distance according to the following order of priority.

  • Distance obtained with the surface brightness fluctuation (SBF) method for the ACS Virgo Cluster Survey (Mei et al. 2007; Blakeslee et al. 2009) (91 values). These are claimed to be accurate to about 3 per cent in distance.

  • SBF distance from ground-based observation from Tonry et al. (2001) (300 values), which have a median error of 10 per cent in distance. These have been converted to the same zero-point of Mei et al. (2007) by subtracting 0.06 mag to the distance moduli (see discussion in Blakeslee et al. 2010).

  • Distances from the NED-D compilation1 by Madore, Steer and the NED team (V3.0 June 2010, about 2000 values). The list includes accurate determinations using (1) SBF, (2) the tip of the red giant branch (TRGB), (3) Cepheids variables, with a claimed comparable accuracy of ∼10 per cent, but the list also includes various other methods like the ones based on the (4) Tully & Fisher (1977) or (5) Fundamental Plane (Djorgovski & Davis 1987; Dressler et al. 1987) relations, on the (6) luminosity of Type Ia Supernovae, or on the luminosity functions of (7) globular clusters and (8) planetary nebulae. The latter methods are expected to be accurate to better than ≲20 per cent (Tully et al. 2008). For a number of galaxies more than one independent distance was available and we adopted the median of the values.

  • When no better distance was available, for galaxies within 12° of the projected centre of the Virgo cluster (defined by the galaxy M87) with heliocentric radial velocities Vhel < 2300 km s−1, we assigned the distance of the cluster (assumed to be 16.5 Mpc from Mei et al. 2007). These distances should be accurate to ∼7 per cent, considering the intrinsic depth of the cluster. Two galaxies were later removed from Virgo as that distance implied a too high and non-physical dynamical M/L as determined in Cappellari et al. (2010).

  • Finally, if none of the above criteria was met, we assigned a distance based on the observed heliocentric radial velocities Vhel, which we converted to velocities Vcosmic characteristic of the expansion of the universe following Mould et al. (2000),2 but only including the contribution of the Virgo attractor, and assuming H0 = 72 km s−1 Mpc−1 (Dunkley et al. 2009). We repeated our sample selection using heliocentric velocities extracted from either the HyperLeda3 (Paturel et al. 2003) or NED4 data bases and obtained identical final ATLAS3D samples. We compared the Vhel of galaxies from NED and HyperLeda and found a general very good agreement in the two data bases, with a biweight rms scatter of 0.4 per cent, as expected given that in most cases the redshifts come from the same source. However in some cases significant differences exists: we found 83/5398 galaxies (1.5 per cent) with Vhel differences larger than 20 per cent. For our Vhel in the parent sample we adopted NED (2010 June), which currently includes as major sources the Center for Astrophysics Redshift Catalog (Huchra et al. 1983), the RC3 (de Vaucouleurs et al. 1991), the ZCAT compilation (Huchra et al. 1992) and the Sloan Digital Sky Survey DR7 (Abazajian et al. 2009). After obtaining our new accurate SAURON redshifts (Section 4.3) we updated the redshift-based distances and this lead to the removal of one observed galaxy. However, we retained in the sample two observed galaxies formally with D > 42 Mpc, but still inside our volume within the distance errors.

To estimate the representative errors of the redshift distances we correlated them against the direct distance estimates in the NED-D compilation. Specifically we selected the 285 galaxies in common with our sample with at least three independent distance determinations (in most cases including SBF distances), and we correlated the median of their dNED-D×H0 values against the Vcosmic (Fig. 1). We found a biweight dispersion of 24 per cent in the residuals. The minimum value in the median residual was obtained with H0 = 72 km s−1 Mpc−1, consistent with the adopted Wilkinson Microwave Anisotropy Probe estimate. Assuming a typical rms error of 10 per cent for the best set of NED-D distances, this implies an intrinsic rms error of ∼21 per cent in the redshift distances. However, a significant number of outliers exist. If we repeat the comparison for all the 692 galaxies in common, with a NED-D distance, the biweight dispersion increases to 29 per cent, which would imply a redshift error of ∼27 per cent. If we only consider the Local Group’s peculiar velocity into Virgo in the calculation of Vcosmic, the scatter increases significantly and systematic deviations appear. Including the infall of galaxies into the Virgo attractor improves the agreement. However including other attractors as done by Mould et al. (2000) does not appear to further reduce the scatter. For this reason we only included the more secure Virgo attractor contribution in our redshift distances corrections.

Figure 1

Accuracy of redshift distances. Top panel: recession velocities, converted into velocities Vcosmic characteristic of the expansion of the universe, against the median of the NED-D redshift-independent distances for 291 galaxies with at least three independent determination (in most cases including SBF distances). The solid line is a one-to-one relation, while the dashed lines indicate ±24 per cent deviations. Bottom panel: same as in the top panel for 705 galaxies with at least one distance determination in NED-D.

Figure 1

Accuracy of redshift distances. Top panel: recession velocities, converted into velocities Vcosmic characteristic of the expansion of the universe, against the median of the NED-D redshift-independent distances for 291 galaxies with at least three independent determination (in most cases including SBF distances). The solid line is a one-to-one relation, while the dashed lines indicate ±24 per cent deviations. Bottom panel: same as in the top panel for 705 galaxies with at least one distance determination in NED-D.

2.3 Estimating redshift incompleteness

Not all the ∼20 000 2MASS galaxies satisfying our observability criteria and with KT < 11.6 mag have a redshift measurement. This may introduce biases in our volume-limited sample selection. Specifically 4146/14461 (29 per cent) of the galaxies in the faintest magnitude bin 10.6 < KT < 11.6 mag do not have a redshift in NED.5 The redshift completeness quickly improves for brighter apparent magnitudes, and in fact only 4 per cent of the galaxies with KT < 10.6 mag have no redshift. One way to estimate how many of these galaxies are likely to be within our selection criteria is to look at their size distribution as measured by 2MASS. In fact one expects many of the apparently faint and small galaxies to be intrinsically brighter and larger, but to appear faint and small due to the large distance.

To quantify the galaxy angular sizes we use the 2MASS XSC parameter r_k20fe, which gives the semimajor axis of the 20 mag arcsec−2 surface brightness isophote at Ks. The size distribution for the galaxies in the faintest magnitude bin, according to this size parameter is shown in the top panel of Fig. 2. As expected the distribution presents a dramatic increase in the numbers for very small objects. For comparison we show in the bottom panel the size distribution of the 2MASS galaxies which satisfy our selection criteria D < 42 Mpc and MK < −21.5 mag. The latter sample has a peak in the size distribution around r_k20fe ≈ 40 arcsec, while the number of objects sharply drops for r_k20fe ≲ 20 arcsec (only 4 per cent of the objects have sizes below that limit). This lack of apparently small objects is not due to any redshift selection criteria. In fact among all the galaxies with measured redshift, about equal numbers have size larger or smaller than r_k20fe = 20 arcsec. The apparent galaxy size is just an efficient way to select, without redshift information, galaxies unlikely to belong to our volume-limited sample.

Figure 2

Apparent size distribution of 2MASS galaxies. Top panel: the apparent size, as described by the 2MASS XSC parameter r_k20fe, for all the galaxies satisfying our observability criteria and with 10.6 < KT < 11.6. Bottom panel: same as in the top panel for the galaxies in the parent sample (D < 42 Mpc and MK < −21.5 mag).

Figure 2

Apparent size distribution of 2MASS galaxies. Top panel: the apparent size, as described by the 2MASS XSC parameter r_k20fe, for all the galaxies satisfying our observability criteria and with 10.6 < KT < 11.6. Bottom panel: same as in the top panel for the galaxies in the parent sample (D < 42 Mpc and MK < −21.5 mag).

Excluding all objects apparently smaller than r_k20fe < 20 arcsec, likely outside the limits of our local volume, we find a redshift incompleteness of 478/3383 (14 per cent) in the faintest magnitude bin. Among the galaxies that do have redshift in this set, only 68/2905 (2 per cent) satisfy the selection criteria for the parent sample (most of the others are still outside the local volume). This implies that statistically we may expect ∼11 galaxies (1 per cent of the parent sample) to be possibly missed from the parent sample due to redshift incompleteness in the faintest magnitude bin. We conclude that we can safely ignore this possible bias from any conclusion derived from the sample.

2.4 Luminosity function

The ATLAS3D parent sample was carefully selected to provide a volume-limited sample of galaxies in the nearby universe. It should be representative of the galaxy population at low redshift, apart from the unavoidable cosmic variance, due to the relatively limited size of the volume. A first test of the representativeness of our parent sample is to compare its Ks-band luminosity function against that measured from larger volumes. For this we compare in Fig. 3 the luminosity function of the parent sample against that derived from a much larger sample, at a mean redshift 〈z〉≈ 0.08, by Bell et al. (2003), using 2MASS Ks-band photometry as we do, and SDSS redshifts. It agrees well with the ones by Kochanek et al. (2001) and Cole et al. (2001). The comparison shows excellent agreement between the two luminosity functions, both in shape and normalization, and indicates that our parent sample is representative of the general galaxy population. In particular this test shows no sign of incompleteness at the faint end, in agreement with the discussion of Section 2.3.

Figure 3

Ks-band luminosity function (LF) of the ATLAS3Dparent sample of 871 galaxies (black filled circles). The LF for the spiral galaxies (green spirals) and the 260 ETGs which constitute the ATLAS3D sample (red squares) separately are also shown. The solid curve shows the Schechter (1976) function derived by Bell et al. (2003) from a fit to 6282 galaxies. It was not fitted to our data! The black numbers above the symbols indicate the total number of galaxies included in each 0.5-mag bin, while the red ones are the corresponding numbers for the ETGs of the ATLAS3D sample. There is no evidence of incompleteness down to the magnitude limit of the survey (vertical dotted line), which is ≈2.5 mag below M (vertical dashed line).

Figure 3

Ks-band luminosity function (LF) of the ATLAS3Dparent sample of 871 galaxies (black filled circles). The LF for the spiral galaxies (green spirals) and the 260 ETGs which constitute the ATLAS3D sample (red squares) separately are also shown. The solid curve shows the Schechter (1976) function derived by Bell et al. (2003) from a fit to 6282 galaxies. It was not fitted to our data! The black numbers above the symbols indicate the total number of galaxies included in each 0.5-mag bin, while the red ones are the corresponding numbers for the ETGs of the ATLAS3D sample. There is no evidence of incompleteness down to the magnitude limit of the survey (vertical dotted line), which is ≈2.5 mag below M (vertical dashed line).

2.5 Size–luminosity relations for spirals and ETGs

To illustrate the general characteristic of the galaxies in the parent sample Fig. 4 shows the K-band size–luminosity relation and the effective surface brightness Σ50≡ LK/(2πR2e) for different morphological types. This plot shows a similar distribution as the one inferred from much larger galaxy samples based on SDSS photometry, further confirming the representativeness of our sample (compare Fig. 4 with fig. 2 of van Dokkum et al. 2008). In our plot we show the fast/slow rotator classification for the 260 ETGs of the ATLAS3D sample (Paper III) together with the early spirals (Sa–Sb) and later spiral types (Sc–Irr) of the parent sample. There is a clear trend in the ReLK diagram as a function of galaxy morphology. To quantify this trend we fitted linear relations to the logarithmic coordinates assuming the same fractional errors for both axes and requiring χ2/DOF = 1. The fit was performed using the fitexy routine which is based on the algorithm by Press et al. (1992) and is part of the idl Astronomy User’s Library6 (Landsman 1993). The best-fitting power-law ReLK relations are  

1
formula
 
2
formula
 
3
formula
for fast rotators, Sa–Sb spirals and Sc or later spiral types, respectively. The slopes for the early and late spirals bracket the trend ReL0.35K found by Courteau et al. (2007). There is a clear known zone of avoidance at small sizes and large luminosities, which is also well defined in our parent sample and approximated above our luminosity limit by a double power law (cf. Lauer et al. 1995):  
4
formula
This equation defines a minimum effective radius Re, b = 0.85 kpc and a corresponding maximum effective surface brightness at a characteristic galaxy luminosity LK, b = 2.5 × 1010 L⊙, K (cf. Graham & Worley 2008). The logarithmic power slope for LKLK, b is γ=−0.15, while for LKLK, b it is β = 0.75, so that for large luminosities ReL0.75K. A sharp transition between the two regimes is set by α = 8.

Figure 4

Top panel: size–luminosity relation for the parent sample. The K-band luminosity of all the galaxies in the parent sample is plotted against the effective radius Re (Section 4.1). Red filled circles are slow rotators, blue ellipses with vertical axis are fast rotators. These 260 objects constitute the ATLAS3D sample. The green spirals represent spiral galaxies of type Sa–Sb (−0.5 < T≤ 4), while later spiral types (T > 4) are plotted as small open circles. The solid lines are the best-fitting relations described in the text. From the bottom to the top they are fit to the fast rotators ETGs, to the Sa–Sb and to the later spiral types. The red curve approximates the boundary of the zone of avoidance in the observed galaxy distribution. Bottom panel: effective surface brightness versus luminosity. The symbols and the lines are the same as in the top panel.

Figure 4

Top panel: size–luminosity relation for the parent sample. The K-band luminosity of all the galaxies in the parent sample is plotted against the effective radius Re (Section 4.1). Red filled circles are slow rotators, blue ellipses with vertical axis are fast rotators. These 260 objects constitute the ATLAS3D sample. The green spirals represent spiral galaxies of type Sa–Sb (−0.5 < T≤ 4), while later spiral types (T > 4) are plotted as small open circles. The solid lines are the best-fitting relations described in the text. From the bottom to the top they are fit to the fast rotators ETGs, to the Sa–Sb and to the later spiral types. The red curve approximates the boundary of the zone of avoidance in the observed galaxy distribution. Bottom panel: effective surface brightness versus luminosity. The symbols and the lines are the same as in the top panel.

Consistently with other larger local galaxy samples (van Dokkum et al. 2008; Trujillo et al. 2009; Taylor et al. 2010), we find no massive and superdense (LK≳ 1011 L⊙, K and Re≲ 2 kpc) ETGs in our parent sample, contrary to what is found from photometry of ETGs at redshift z≳ 1.5 (e.g. Daddi et al. 2005; Trujillo et al. 2006; Cimatti et al. 2008; van Dokkum et al. 2008). Similar ReL relations were derived by Shen et al. (2003) for early-type and late-type galaxies, defined as those having a Sersic (1968) index larger or smaller than n = 2.5, respectively. Their relation also showed a trend for late types to have larger sizes (by definition, due to the smaller n) at given luminosity (or mass) and a more shallow ReL relations, as we find using the morphological selection. A trend in the ReM relation involving colours, with red-sequence galaxies having smaller sizes, can be seen in van Dokkum et al. (2008). While a trend involving age was presented by van der Wel et al. (2009) and Shankar & Bernardi (2009), and confirmed by Valentinuzzi et al. (2010), who find smaller sizes for older objects, at given stellar mass. All these trends are consistent with our finding using fast/slow rotators ETGs, in combination with traditional morphology of spiral galaxies (see also Bernardi et al. 2010), when one considers that later galaxy types tend to be more gas rich and have a younger stellar population. However here we interpret the observed trends as due to a variation in the bulge fraction, with bulges progressively increasing (by definition) from Sd–Sc to Sb–Sa and to fast rotators ETGs (see Paper VII). A detailed study of scaling relations in our sample will be presented in a subsequent paper.

3 The ATLAS3D SAMPLE

3.1 Morphological selection

We established that the ATLAS3D parent sample is essentially complete within the selection criteria and representative of the nearby galaxy population. We also verified that its luminosity function agrees with the one derived from much larger volumes of the Universe. The ATLAS3D survey however is focused on the study of the fossil record of galaxy formation as recorded in the structure of ETGs. The ATLAS3D sample is a subset of the parent sample, consisting of all the ETGs in that sample.

The distinction between red-sequence and blue-cloud galaxies is related, but different from the early type versus spiral morphological separation. E and S0 galaxies invariably lie on the red sequence, while late-type spirals are generally on the blue cloud. However large fractions of spirals populate the red sequence as well and overlap with ETGs (Strateva et al. 2001; Conselice 2006; van den Bergh 2007; Bernardi et al. 2010). An accurate morphology is easier to obtain for nearby galaxies and it is more robust than colour to dust and inclination effects. For this reasons a morphological classification is our preferred selection criterion.

To perform the morphological selection we considered using the morphological classification provided in available catalogues like the RC3 or its ongoing evolution HyperLeda. A problem with those classifications is the possible non-homogeneity of the classification process. Moreover the classification in those catalogues was performed using photometry in a single band, often from photographic plates. Given that for the majority of the galaxies in our parent sample excellent quality multiband photometry is available from the SDSS Data Release 7 (DR7; Abazajian et al. 2009), we decided to revisit the classification of the whole parent sample using the best available imaging.

The morphological classification of a given galaxy using multicolour imaging may differ from the one obtained from photographic plates of the same object. None the less we tried as much as possible to be consistent with the currently accepted morphological criteria. We just need to separate the parent sample into two classes: ETGs and spirals. This makes our task much simpler and reproducible than a more detailed morphological classification into E, S0 and spiral subclasses Sa–Sd.

Since the introduction of the classic tuning-fork diagram by Hubble (1936), for the past half-century, essentially all authors have converged on a simple criterion to differentiate ETGs from spirals. The criterion, which defines the revised Hubble classification scheme, is outlined by Sandage (1961) in the Hubble Atlas and is based entirely on the presence of spiral arms (or dust lanes when seen edge-on): ‘the transition stages, S0 and SB0, are firmly established. In both sequences, the nebulae may be described as systems definitely later than E7 but showing no spiral structure’. This same criterion was adopted unchanged in the extension to the classification scheme by de Vaucouleurs (1959, 1963), which was applied to the widely used RC2 and RC3 catalogues (de Vaucouleurs, de Vaucouleurs & Corwin 1976; de Vaucouleurs et al. 1991) and HyperLeda (Paturel et al. 2003). Although other characteristics of galaxies change with morphological classification (e.g. the bulge/disc ratio), they are ignored in the separation between early types and spiral galaxies (see review by Sandage 1975). We adopted the same criterion here to select the ETGs belonging to the ATLAS3D sample from the parent sample.

Our morphological selection was done by visual inspection of the true-colour red–green–blue images (Lupton et al. 2004) provided by the SDSS DR7 which are available for 82 per cent of the galaxies in the parent sample. For the remaining objects we used the B-band DSS2-blue images in the Online Digitized Sky Survey.7 We revisited the classification for the galaxies without SDSS DR7 data after obtaining our own Isaac Newton Telescope (INT) imaging (Section 5.1) and this lead to the removal of a couple of galaxies from the ETGs sample. At the end of our classification we compared the agreement between our separation into early types and spirals and the one provided by the T type given by HyperLeda, which defines as ETGs (E and S0) those having T≤−0.5. We found agreement in 97 per cent of the cases, confirming the robustness and reproducibility of the morphological selection. The few disagreements with HyperLeda could all be easily explained by the high quality of the multicolour SDSS images, which allowed for a better detection of faint spiral structures. The ATLAS3D sample of 260 ETGs obtained from this selection is given in Table 3 and illustrated in Figs 5 and 6, together with the HyperLeda morphological classification as provided by their T type (E: T≤−3.5; S0: −3.5 < T≤−0.5; S0/a: −0.5 < T≤ 0.5).

Figure 5

Morphology of slow-rotators ETGs sorted by increasing λR. Postage stamps of the SDSS DR7 and INT red–green–blue composite images of slow rotators in the ATLAS3D sample. The image of each galaxy was scaled so that the plot side is equal to 10Re, where Re is the projected half-light radius given in Table 3. From left to right and from top to bottom the panels are sorted according to their specific stellar angular momentum, as measured by the parameter λR given in Paper III. The galaxy name is given at the top of each panel and the morphological classification from HyperLeda at the bottom. At this scale slow-rotator ETGs appear generally featureless except for the synchrotron jet in NGC 4486 and obvious signs of interactions in NGC 1222, NGC 3414 and NGC 5557. The only significant flat galaxy in this class is NGC 4550, while two other galaxies NGC 3796 and NGC 4528 show evidence of bar perturbations, which is typically associated to stellar discs. All these three objects contain counter-rotating stellar discs (Paper II). (This figure is better appreciated on a computer screen rather than on printed paper.) A version of Figs 5 and 6 sorted by name is available at http://purl.org/atlas3d.

Figure 5

Morphology of slow-rotators ETGs sorted by increasing λR. Postage stamps of the SDSS DR7 and INT red–green–blue composite images of slow rotators in the ATLAS3D sample. The image of each galaxy was scaled so that the plot side is equal to 10Re, where Re is the projected half-light radius given in Table 3. From left to right and from top to bottom the panels are sorted according to their specific stellar angular momentum, as measured by the parameter λR given in Paper III. The galaxy name is given at the top of each panel and the morphological classification from HyperLeda at the bottom. At this scale slow-rotator ETGs appear generally featureless except for the synchrotron jet in NGC 4486 and obvious signs of interactions in NGC 1222, NGC 3414 and NGC 5557. The only significant flat galaxy in this class is NGC 4550, while two other galaxies NGC 3796 and NGC 4528 show evidence of bar perturbations, which is typically associated to stellar discs. All these three objects contain counter-rotating stellar discs (Paper II). (This figure is better appreciated on a computer screen rather than on printed paper.) A version of Figs 5 and 6 sorted by name is available at http://purl.org/atlas3d.

Figure 6

Same as in Fig. 5 for the fast-rotators ETGs in the ATLAS3D sample, sorted by increasing λR. The first panel contains mostly round objects. Many of them are barred (Paper II), nearly face-on, S0 galaxies and often contain stellar rings (e.g. NGC 4608), while others appears face-on from the geometry of their dust. This suggests that the round shape and low λR of these objects is not intrinsic, but due to their low inclination (i = 90° being edge on). On the contrary the last panel is dominated by nearly edge-on discs, which explains their high λR.

Figure 6

Same as in Fig. 5 for the fast-rotators ETGs in the ATLAS3D sample, sorted by increasing λR. The first panel contains mostly round objects. Many of them are barred (Paper II), nearly face-on, S0 galaxies and often contain stellar rings (e.g. NGC 4608), while others appears face-on from the geometry of their dust. This suggests that the round shape and low λR of these objects is not intrinsic, but due to their low inclination (i = 90° being edge on). On the contrary the last panel is dominated by nearly edge-on discs, which explains their high λR.

3.2 Colour–magnitude diagram

The decision to select the ATLAS3D sample based on morphology instead of colour was based on (i) the broad similarity of the two criteria, (ii) the non-availability of reliable colours for the whole parent sample and (iii) the robustness of morphology, as opposed to colours, against dust extinction. Still, we expect the ATLAS3D sample to include mainly galaxies on the red sequence in a colour–magnitude diagram. This is verified in Fig. 7. The ATLAS3D sample of ETGs indeed defines a narrow colour–magnitude sequence approximated, in SDSS magnitudes, by  

5
formula
As found by previous authors there is little scatter in the relation at the high-mass end, while at the lower mass end some galaxies appear to be still in transition between the blue and red sequence (Strateva et al. 2001; Conselice 2006; van den Bergh 2007; Bernardi et al. 2010). The 31 ETGs with SDSS colour and defined as slow rotators in Paper III all lie close to the red sequence with an rms scatter of 0.13 mag from the best-fitting relation. All the deviants ETGs are classified as fast rotators in Paper III. The nature of these objects will be investigated in detail in subsequent papers of this series. Spiral galaxies span the full region of the diagram, both on the red sequence and the blue clouds, as found by previous studies.

Figure 7

ur versus Mr colour–magnitude diagram for the morphologically selected ATLAS3D parent sample with SDSS photometry. The blue ellipses with axis are fast-rotator ETGs, the red filled circles are slow-rotators ETGs, while the green spirals are spiral galaxies. The dashed line indicates the separation between red sequence and blue cloud established by Baldry et al. (2004, 2006), from a sample of 151 642 galaxies. The vertical dotted line indicates our approximate survey completeness limit in r band Mr≲−18.9 mag. The solid line is a linear robust fit to the ETGs only, minimizing the sum of the absolute residuals.

Figure 7

ur versus Mr colour–magnitude diagram for the morphologically selected ATLAS3D parent sample with SDSS photometry. The blue ellipses with axis are fast-rotator ETGs, the red filled circles are slow-rotators ETGs, while the green spirals are spiral galaxies. The dashed line indicates the separation between red sequence and blue cloud established by Baldry et al. (2004, 2006), from a sample of 151 642 galaxies. The vertical dotted line indicates our approximate survey completeness limit in r band Mr≲−18.9 mag. The solid line is a linear robust fit to the ETGs only, minimizing the sum of the absolute residuals.

4 SAURON DATA FOR THE ATLAS3D SURVEY

4.1 Observing strategy

The main aim of the SAURON (Bacon et al. 2001) observations of the ATLAS3D sample is to obtain global galaxy quantities like the specific stellar angular momentum λR, the (V/σ, ɛ) the global kinematical misalignment, the luminosity-weighted second moment σe, the stellar and total mass-to-light ratio, the mean stellar population and the ionized gas emission. To be representative of the galaxies as a whole, these quantities need to be measured at least within one projected half-light radius Re. Moreover for a given observed area, more accurate values of the kinematical quantities are obtained when the quantities are measured within ellipses instead of circles, with ellipticity given by the galaxy photometry and the position angle defined by the stellar kinematics (see appendix B of Cappellari et al. 2007). In addition, when galaxies are barred, the SAURON survey has shown that the kinematics are generally still aligned with the position angle of the galaxy photometry at large radii PAphot (Krajnović et al. 2008), which defines the position of the line-of-nodes of the disc. These requirements, which derive from our experience with the SAURON survey (de Zeeuw et al. 2002), lead to the following optimized observing strategy, which we systematically applied for the SAURON observation of the ATLAS3D sample.

  • When Re≤ 30 arcsec take a single SAURON field and orient the SAURON major axis with the large radii PAphot.

  • When Re > 30 arcsec then we take a mosaic of two SAURON fields. Given the size of the SAURON field of 33 × 41 arcsec2, the criterion of maximizing the area of the largest isophote, of axial ratio q′, enclosed within the observed field-of-view, becomes

  • if q′ < 0.55 the SAURON long axis is aligned with PAphot and the mosaic is made by matching the two SAURON pointings along the short side;

  • if q′≥ 0.55 the SAURON short axis is aligned with PAphot and the mosaic is made by matching the two SAURON pointings along the long side.

At the time of the SAURON observations the only photometry available to us for the whole sample was from 2MASS. We adopted the Re provided by the 2MASS XSC, which is determined via growth curves within elliptical apertures. Specifically, in terms of the XSC catalogs parameters, we defined  

6
formula
as the median of the three 2MASS values in the J, H and Ks band, where the factor forumla takes into account the fact that the 2MASS values are the semimajor axes of the ellipses enclosing half of the galaxy light and we want the radius of the circle with the same area. This R2MASSe was compared to the RRC3e provided by the RC3 catalogue and measured via growth curves within circular apertures. The two values correlate well, with an observed rms scatter of 0.12 dex in Re, which implies an error of about 22 per cent in each Re determination (assuming they have similar errors). However there is a general offset by a factor RRC3e≈ 1.7 R2MASSe between the two determinations (Fig. 8). The rms scatter in the RRC3eR2MASSe correlation is close to the one (0.11 dex) we obtain when comparing RRC3e to 46 values determined using growth curves in the I band for the SAURON survey (Cappellari et al. 2006; Kuntschner et al. 2006). In that case however the offset in the values is negligible (factor 0.95). We conclude that the 2MASS Re determinations have comparable accuracy to the RC3 and SAURON determination, when they are increased by a factor of 1.7 to account for the differences in the observed photometric band and in the depth of the photometry data. All three values are consistent with having a similar error of ≈22 per cent in Re. This rather large error is consistent with the findings of Chen et al. (2010) from another extensive comparison of Re values. To further improve the accuracy we adopted Re = (1.7 R2MASSe+RRC3e)/2 for the 412/871 galaxies with both 2MASS and RC3 determinations and Re = 1.7 R2MASSe when only 2MASS was available. The values of Re for the full parent sample, divided into ETGs and spirals, are given in Tables 3 and 4.

Figure 8

Testing the accuracy of Re determinations. Top panel: comparison between 1353 values of Re given by RC3 and the ones given by 2MASS (computed as described in the text), scaled by the best-fitting factor of 1.7. Bottom panel: same as in the top panel for the RC3 Re and the ones for 46 ETGs of the SAURON survey. Once corrected for systematic differences, all three Re determinations are consistent with a similar error of ≈22 per cent.

Figure 8

Testing the accuracy of Re determinations. Top panel: comparison between 1353 values of Re given by RC3 and the ones given by 2MASS (computed as described in the text), scaled by the best-fitting factor of 1.7. Bottom panel: same as in the top panel for the RC3 Re and the ones for 46 ETGs of the SAURON survey. Once corrected for systematic differences, all three Re determinations are consistent with a similar error of ≈22 per cent.

4.2 Integral field spectroscopic observations

The SAURON integral field spectrograph was first mounted at the WHT at the Observatory of El Roque des Los Muchachos on La Palma in 1999. It has been used extensively in particular in the course of the SAURON survey, but also in separate smaller efforts (e.g. Bower et al. 2004; Allard, Peletier & Knapen 2005; Dumas et al. 2007; Weijmans et al. 2010). Given that the ATLAS3D selection criteria are by design very similar to the ones in the SAURON survey, a total of 64 ETGs had been observed before the beginning of the ATLAS3D observing campaign. 49 ETGs were part of the main survey (de Zeeuw et al. 2002), out of which 47 were presented in the subsample of ETGs (Emsellem et al. 2004) and two in the early-spirals subsample (Falcón-Barroso et al. 2006). 14 ‘special’ ETGs within the ATLAS3D volume had been observed with SAURON in the course of other projects (table 3 of Cappellari et al. 2007). All these galaxies were observed before the volume phase holographic (VPH) grating came into use and were taken with an exposure time of 2 h on source, in some cases with multiple spatial pointings to cover galaxies to roughly one effective (projected half-light Re) radius. All the observations were obtained in the low spatial resolution mode in which the instrument has a field-of-view of 33 × 41 arcsec2 sampled with 0.94 arcsec2 lenslets and with a spectral resolution of 4.2 Å full width at half-maximum (FWHM; σinstr = 105 km s−1), covering the wavelength range 4800–5380 Å.

To observe the additional 196 galaxies we were allocated 38 observing nights comprising four observing runs spread over three consecutive semesters as part of a long-term project at the WHT (Table 5). The time allocation was split equally between Dutch and UK time. We had excellent weather with just 16 per cent of nights lost due to clouds, compared to a normal average for the period of around 30 per cent. This fact, combined with an efficient observing strategy allowed us to complete all observations of the ATLAS3D sample galaxies in the allocated time.

Table 5

SAURON observing runs for the ATLAS3D sample.

Run Dates Clear 
2007 April 10–23 12/14 
2007 August 13–15 3/3 
2008 January 9–15 6/7 
2008 February 27–March 11 11/14 
Run Dates Clear 
2007 April 10–23 12/14 
2007 August 13–15 3/3 
2008 January 9–15 6/7 
2008 February 27–March 11 11/14 

The optimal scheduling of the observations of the 196 galaxies, in some cases using multiple spatial pointings, was performed with a dedicated idl script which gave higher priority to the intrinsically brightest galaxies, took into account the galaxy coordinates, the need for multiple pointings, the dates of the four observing runs and the moon position and phase. The script could be easily re-run to modify the scheduling to account for time lost due to bad weather. The observations were performed with the VPH grating, which provides a resolution of 3.9 Å FWHM (σinstr = 98 km s−1), about 7 per cent better than for the SAURON survey. The adopted on-source exposure time was 1 h, split into two equal 30-min exposure dithered by a couple of arcseconds.

4.3 Data reduction and stellar kinematics extraction

The SAURON data reduction followed standard procedures and used the dedicated xsauron software developed at Centre de Recherche Astronomique de Lyon (CRAL) and was already described in Bacon et al. (2001) and Emsellem et al. (2004). However some details of our approach have been improved after the original publication of the data. For this reason we re-extracted all the stellar kinematics using the improved and completely homogeneous approach for the entire ATLAS3D data set. We describe here the minor differences with respect to what was published before.

The data were spatially binned with the adaptive Voronoi method8 of Cappellari & Copin (2003), which optimally solves the problem of preserving the maximum spatial resolution of two-dimensional data, given a constraint on the minimum signal-to-noise ratio (S/N). We adopted a target S/N = 40 for all the data used in the ATLAS3D survey, including the previous SAURON observations, which were re-extracted adopting for consistency this lower S/N instead of the S/N = 60 as originally published in Emsellem et al. (2004).

The stellar kinematics were extracted with the penalized pixel-fitting (ppxf) software8 (Cappellari & Emsellem 2004), which simultaneously fits the stellar kinematics and the optimal linear combination of spectral templates to the observed spectrum, using a maximum-likelihood approach to suppress noisy solutions. The line-of-sight velocity distribution (LOSVD) is described via the Gauss–Hermite parametrization up to h3h4 (Gerhard 1993; van der Marel & Franx 1993). We employed as stellar template an optimal linear combination of stars from the MILES library9 (Sánchez-Blázquez et al. 2006), which was separately determined for every galaxy. We did not allow the template to change in every bin to eliminate small artefacts in the kinematics due imperfections in the velocity alignment of the MILES stars. A resolution of 2.56 Å FWHM was adopted for the stars. We adjusted the penalty in ppxf to a value λ = 0.5, optimized for the adopted S/N. Following the ppxf documentation we determined the optimal λ by requiring the maximum bias in the Gauss–Hermite parameters h3 and h4 to be equal to rms/3, where the rms is the scatter of the measurements obtained from a Monte Carlo simulations with the adopted S/N = 40 and a well resolved stellar dispersion σ≳ 180 km s−1 (Fig. 9). In a handful of cases we could not reach the required S/N without employing excessively large Voronoi bins. In those cases we further reduced the target S/N. For those galaxies we correspondingly adapted the penalty in ppxf according to the empirical relation of Fig. 10. For usage in cases where we need to approximate the stellar velocity second moments and not the full LOSVD – e.g. to fit models based on the Jeans (1922) equations or measure λR or V/σ– we separately extracted the kinematics assuming a simple Gaussian LOSVD. In that case the ppxf penalty is ignored. In all cases the errors on the kinematics were determined via bootstrapping (Efron & Tibshirani 1993), by randomly resampling the ppxf fit residuals of the best fit and repeating the kinematic fit for 100 realizations, with a zero penalty (see section 3.4 of Cappellari & Emsellem 2004). The homogeneous set of integral field SAURON kinematics introduced in this paper, together with the stellar population parameters, the characteristics of the ionized gas and the entire data cubes for the full ATLAS3D sample will be made available via the project web page10 at the end of our project.

Figure 9

Testing penalization in ppxf. We simulated spectra with the S/N = 40 of our data and an LOSVD with h3 = 0.1, h4 = 0.1 and σ in the range between 30 and 300 km s−1. We extracted the kinematics with ppxf and a penalty λ = 0.5. The lines in the top two panels show the 50th (median, solid line), 16th and 84th percentiles (1σ errors, dotted lines) of the differences between the measured values and the input values of the mean velocity Vin and the velocity dispersion σin. The bottom panels show the same lines for the recovered values of h3 and h4, compared to the input values (dashed line). The h3 and h4 parameters can only be recovered when σin≳ 100 km s−1. Typical statistical errors in the kinematics parameter for σin≈ 200 km s−1 are 6 km s−1, 7 km s−1, 0.03 and 0.03 for V, σ, h3 and h4, respectively.

Figure 9

Testing penalization in ppxf. We simulated spectra with the S/N = 40 of our data and an LOSVD with h3 = 0.1, h4 = 0.1 and σ in the range between 30 and 300 km s−1. We extracted the kinematics with ppxf and a penalty λ = 0.5. The lines in the top two panels show the 50th (median, solid line), 16th and 84th percentiles (1σ errors, dotted lines) of the differences between the measured values and the input values of the mean velocity Vin and the velocity dispersion σin. The bottom panels show the same lines for the recovered values of h3 and h4, compared to the input values (dashed line). The h3 and h4 parameters can only be recovered when σin≳ 100 km s−1. Typical statistical errors in the kinematics parameter for σin≈ 200 km s−1 are 6 km s−1, 7 km s−1, 0.03 and 0.03 for V, σ, h3 and h4, respectively.

Figure 10

Relation between the S/N of the SAURON spectrum and the optimal penalty parameter λ (keyword BIAS) in ppxf. The solid line is the polynomial BIAS = 0.15 + 0.0107 S/N − 0.00004 (S/N)2.

Figure 10

Relation between the S/N of the SAURON spectrum and the optimal penalty parameter λ (keyword BIAS) in ppxf. The solid line is the polynomial BIAS = 0.15 + 0.0107 S/N − 0.00004 (S/N)2.

As discussed in detail in Cappellari & Emsellem (2004) and illustrated in Fig. 9, the SAURON spectroscopic data allow the extraction of the full stellar LOSVD, including the Gauss–Hermite parameters, only for observed velocity dispersions σ≳ 120 km s−1. Below this value the h3 and h4 start becoming unconstrained by the data, due to the spectral undersampling and for this reason the ppxf method automatically and gradually penalizes them towards zero to keep the noise on the mean velocity V and velocity dispersion σ under control. As the minimum S/N of our data is defined by our Voronoi binning criterion, the level of bias depends only on σ as illustrated in the Monte Carlo simulation of Fig. 9. This effect is also illustrated for ATLAS3D data in Fig. 11, for a small set of galaxies with a range of luminosity-weighed σe within 1Re (defined as in Cappellari et al. 2006). The figure shows the range of data quality for the stellar kinematical data for the ATLAS3D survey. At high σe the data have a quality which is comparable to the one for the SAURON survey presented in Emsellem et al. (2004). The shorter exposure time of the ATLAS3D survey is in part compensated by the use of the VPH grating and in part by the adoption of larger Voronoi bins. However at σe≲ 120 km s−1 there is not enough information in the data to constrain h3 and h4. Contrary to the SAURON survey the volume-limited ATLAS3D survey is dominated by the more common low-luminosity galaxies, which also tend to have low dispersion. In practice we find that ≈40 per cent of the galaxies in the sample have σe≲ 120 km s−1 and for those objects we can only recover reliable V and σ values. Although the kinematics are not sufficient to constrain general dynamical models for the full sample, they still provide very reliable global values of specific angular momenta and galaxy masses for all galaxies (e.g. Cappellari et al. 2010).

Figure 11

Quality of the SAURON stellar kinematics in the ATLAS3D survey. Each column from left to right shows the Voronoi binned kinematic moments extracted via ppxf from the SAURON data: mean velocity, V, velocity dispersion, σ, and higher Gauss–Hermite moments, h3 and h4. From top to bottom the data for seven newly observed fast rotators in the ATLAS3D sample are sorted according to the luminosity-weighted dispersion σe within 1Re. Below σe≲ 120 km s−1 the data have insufficient information to constrain the full LOSVD and the Gauss–Hermite moments are automatically and gradually suppressed by ppxf towards zero to reduce the noise in V and σ, which can still be reliably recovered. About 40 per cent of the galaxies in the sample have σe≲ 120 km s−1.

Figure 11

Quality of the SAURON stellar kinematics in the ATLAS3D survey. Each column from left to right shows the Voronoi binned kinematic moments extracted via ppxf from the SAURON data: mean velocity, V, velocity dispersion, σ, and higher Gauss–Hermite moments, h3 and h4. From top to bottom the data for seven newly observed fast rotators in the ATLAS3D sample are sorted according to the luminosity-weighted dispersion σe within 1Re. Below σe≲ 120 km s−1 the data have insufficient information to constrain the full LOSVD and the Gauss–Hermite moments are automatically and gradually suppressed by ppxf towards zero to reduce the noise in V and σ, which can still be reliably recovered. About 40 per cent of the galaxies in the sample have σe≲ 120 km s−1.

We also used the SAURON stellar kinematic to measure extremely robust heliocentric recession velocities Vhel for all galaxies in the sample. Repeated determinations indicate a 1σ accuracy ΔVhel≈ 5 km s−1. The values were derived from the integral field stellar kinematics by finding the value which needs to be subtracted from the observed velocity field to best fit a bi-antisymmetric version of the velocity field.11 This technique does not suffer from the uncertainties due to the slit centring, which affects spectroscopic surveys, or from the possibility of the gas not being associated to the galaxy, which affects H i determinations. The observed velocities were converted into velocities Vhel relative to the barycentre of the Solar system via the idl routine baryvel, which implements the algorithm by Stumpff (1980) and is part of the idl Astronomy User’s Library (Landsman 1993). The measured Vhel values are given in Table 3.

5 ADDITIONAL ATLAS3D DATA AND SIMULATIONS

5.1 H i, CO and optical observations

Apart from the SAURON integral field spectroscopic observations presented in detail in Section 4, the ATLAS3D survey includes other multiwavelength observations obtained with different instruments and facilities. These data sets will be presented in subsequent papers, however, a summary of the main ones is presented in Table 6, and more information are given below.

Table 6

Multiwavelength ATLAS3D data.

Instrument Tracer/band/res. Number of objects Selection Reference Time allocation 
WSRT H i@21 cm 170 δ > 10° Serra et al. (in preparation) 1212 h 
IRAM 30-m 12 CO J = 1–0 and 2–1 259 All Paper IV 211 h 
CARMA 12 CO J = 1–0 32 f > 19 Jy km s−1 Alatalo et al. (in preparation) 467 h 
INT + SDSS u, g, r, i, z 35 + 225 All Scott et al. (in preparation) + Abazajian et al. (2009) 5 n 
SAURON 480–538 nm; R = 1300 260 All This paper 38 n 
Instrument Tracer/band/res. Number of objects Selection Reference Time allocation 
WSRT H i@21 cm 170 δ > 10° Serra et al. (in preparation) 1212 h 
IRAM 30-m 12 CO J = 1–0 and 2–1 259 All Paper IV 211 h 
CARMA 12 CO J = 1–0 32 f > 19 Jy km s−1 Alatalo et al. (in preparation) 467 h 
INT + SDSS u, g, r, i, z 35 + 225 All Scott et al. (in preparation) + Abazajian et al. (2009) 5 n 
SAURON 480–538 nm; R = 1300 260 All This paper 38 n 

  • Hiinterferometry. We have observed the H i properties of all galaxies in the ATLAS3D sample above δ = 10° (due to the telescope latitude). This subsample includes 170 galaxies – 43 inside and 127 outside the Virgo cluster. We observed all galaxies outside Virgo, and galaxies inside Virgo detected by the Alfalfa survey (Giovanelli et al. 2005), with the Westerbork Synthesis Radio Telescope (WSRT). Some of the galaxies were observed with the WSRT as part of previous studies (Morganti et al. 2006; Józsa et al. 2009; Oosterloo et al. 2010). The integration time for all galaxies observed with the WSRT is 12 h, providing H i cubes at a resolution of ∼30 arcsec and 16 km s−1 over a field of view of ∼1 deg2 and a velocity range of ∼4000 km s−1. We detect H i gas down to a column density of a few times 1019 cm−2. The upper limits on M(H i) derived from these data ranges between 106 and a few times 107 M depending on galaxy distance. This is typically about five times lower than upper limits derived from Alfalfa spectra. These observations and a discussion of the H i properties will be presented in Serra et al. (in preparation). Interesting objects, like extended discs, have been followed-up for deeper H i observations.

  • CO single dish. All of the ATLAS3D galaxies have been searched for 12CO J = 1–0 and 2–1 emission with the IRAM 30-m telescope, including 204 new observations with the remainder collected from the recent literature. The data consist of a single pointing at the galaxy centre, covering a bandwidth of 1300 km s−1 centred on the optical velocity. The rms noise levels of the 1–0 spectra are 3 mK (T*A) or better after binning to 31 km s−1 channels, so that the 3σ upper limit for a sum over a 300 km s−1 linewidth corresponds to a H2 mass ∼1 × 107 M for the most nearby sample members and ∼1 × 108 M for the most distant members. A detailed description of the observations and the corresponding measurements is presented in Paper IV.

  • CO interferometry. The brighter CO detections have been, observed in the 1–0 line with the BIMA, Plateau de Bure, and CARMA millimeter interferometers in order to map the distribution and kinematics of the molecular gas. These observations are designed to provide the molecular surface densities and angular momenta for 80 per cent of all of the molecular gas found in the ATLAS3D sample, typically at resolutions of 5 arcsec. Some additional data at higher and lower resolutions are obtained as necessary to probe the structure of the gas and recover the bulk of the emission detected in the single dish data. On-source integration times range from 4 to 20 h and are also adjusted as necessary for high-quality detections. A detailed description of the observations and the corresponding measurements is presented in Alatalo et al. (in preparation).

  • INT optical imaging. Observations with the Wide-Field Camera (WFC) at the 2.5-m INT were carried out to obtain u, g, r, i and z-band imaging for galaxies not observed by the SDSS. Images were taken through the five filters for 55 galaxies from the ATLAS3D sample. Integration times were typically 60 to 160 s reaching sensitivities comparable or deeper than the SDSS. Galaxies already observed by SDSS were observed in the runs as a cross-check in general and to bring the INT imaging on to the same photometric system as SDSS in particular. The images have been reduced and calibrated using the Astro-WISE system (Valentijn et al. 2007). A detailed description of the observations and the corresponding measurements is presented in Scott et al. (in preparation).

  • Targeted follow-ups. We are also obtaining data for targeted subsets of the sample: deep optical images of ATLAS3D galaxies were obtained with the MegaCam camera installed on the Canada–France–Hawaii Telescope. This imaging part of the project aims to reach surface brightness limits as low as 28.5 mag arcsec2 in the g band. Reaching such values allows to disclose very faint, diffuse structures in the outskirts of the ETGs, such as shells and tidal tails, that tell about their past mass accretion history. We have also started an observing campaign to obtain stellar kinematics and absorption line strengths out to large radii (3–5 Re) with integral field units (IFUs; e.g. SAURON, VIRUS-P) for a number of ATLAS3D galaxies. Following the methods outlined in Weijmans et al. (2009) we will construct dynamical models to trace the halo mass profiles. We primarily target galaxies that have been detected in H i to have a regularly rotating disc and ring, so that the H i kinematics can be added to the dynamical modelling.

5.2 Numerical simulations

The ATLAS3D project includes a theoretical effort to interpret the observations using models of galaxy formation. We are attacking the problem via three parallel approaches as described below.

  • Binary mergers. An extensive set of ‘idealized’ (i.e. without the cosmological context) numerical simulations is being conducted. These simulations have been made at an unmatched resolution (softening length of 58 pc and a total number of particles of 1.2 × 107) with the goal to better understand the role of mergers in the formation and evolution of galaxies of the red sequence and to understand in details the physical processes involved during a merger (e.g. the formation of the kinematically decoupled components, the energy and angular momentum exchanges). These simulations are also a powerful tool to perform direct comparisons with observations such as e.g. the morphology via the ellipticity, the kinematics via λR, the redistribution of the gas at large scales, the metallicity gradients and the Mg bVesc relation (Davies, Sadler & Peletier 1993; Scott et al. 2009). The detailed description of the simulations and their associated results are presented in Bois et al. (2010) and Paper VI. Other idealized simulations of ATLAS3D galaxies are performed with the ramses high-resolution grid-based hydrodynamical code (Teyssier 2002). Following the technique developed in Bournaud et al. (2010), we model the dynamics of atomic and molecular gas discs in ETGs with parsec-scale resolution, based on accurate mass models extracted from the ATLAS3D data. These models aim at understanding the dynamics, stability and star formation activity of the interstellar medium in ETGs.

  • Semi-analytic modelling. In a second strand of simulations we address the formation of elliptical galaxies within a large-scale cosmological setting using a semi-analytic modelling (SAM) approach. Using the knowledge gained from idealized high-resolution simulations of mergers and the formation of a limited number of cosmologically simulated ETGs we test formation scenarios within our SAM making full use of the completeness of the ATLAS3D sample. The SAM we use is an extension of earlier work by Khochfar & Burkert (2005) and Khochfar & Silk (2006). Within the SAM we follow the individual history of a large statistical sample of galaxies to the present day, taking into account their merging history and physical processes related to e.g. gas cooling or star formation. In addition the SAM is used to make predictions on the evolution of these classes of ETGs that can be tested with future observations (Paper VIII).

  • Cosmological simulations. We will also make use of high-resolution simulations of individual galaxies in a full cosmological context (i.e. Naab et al. 2007; Naab, Johansson & Ostriker 2009) to investigate the physical processes setting the present day kinematical properties of ETGs. We will use a new sample of simulations (Oser et al. 2010) covering the full mass range of the ATLAS3D galaxies. From these simulated galaxies we will construct two-dimensional kinematical maps (Jesseit et al. 2007) to compare directly to the ATLAS3D observations. The use of cosmological simulations is advantageous as we can link the present day properties to the evolutionary history embedded in the favoured cosmology. We will also be able to investigate the influence of the merging history, dark matter and various feedback mechanisms on kinematic properties and the stellar populations.

6 SUMMARY

We described the motivation and goals of the ATLAS3D project, which aims at constraining models of galaxy formation by obtaining two-dimensional observations of the distribution and kinematics of the atomic (H i), molecular (CO) and ionized gas, together with the stellar population and kinematics, for a volume-limited nearly mass-selected (Ks band) sample of ETGs.

We defined the selection criteria for the volume-limited (1.16 × 105 Mpc3) parent sample of 871 galaxies with D < 42 Mpc and MK < −21.5 mag, satisfying our observability criteria, and investigated possible selection biases, especially due to redshift incompleteness. We found that incompleteness cannot amount to more than a couple of per cent, making the sample essentially complete and representative of the nearby population. We additionally tested the representativeness of the sample by comparing its Ks-band luminosity function with the one derived from a much larger sample (Bell et al. 2003) and found a very good agreement. We described the morphological selection used to extract the 260 ETGs of the ATLAS3D sample from the parent sample and showed that the ETGs define a narrow red sequence, on a colour–magnitude diagram, with few objects in transition from the blue cloud. We presented the size–luminosity relation for the ATLAS3D sample and the full parent sample to illustrate the general characteristic of our galaxies.

We described the strategy for the SAURON integral field observations, the data reduction, the extraction of the stellar kinematics and their typical errors. We gave an overview of the additional data set already available for our sample, which include interferometric observations of the atomic gas as traced by H i, single dish and interferometric observations of molecular gas as traced by the CO lines and multiband optical photometry. We summarized the ongoing semi-analytic modelling and the cosmological and binary-merger N-body simulations we are performing to interpret our observations.

This is the first paper of a series devoted to our understanding of the formation of ETGs. Key additional elements are provided by the kinematics, ages and chemical composition of the stars in the galaxies, the presence of cold atomic or molecular gas, the photometric profiles and the dynamical masses, as a function of environment. The observations for the ATLAS3D sample will be compared against the model predictions to test formation scenarios and to tune the model parameter. This will be the topic of future papers of this series. The ATLAS3D project aims to constitute a zero redshift baseline, against which one can investigate the evolution of galaxy global parameters with redshift, to trace galaxy evolution back in time. Future studies should extend this effort to more dense environment than can be explored in the nearby universe, and to increasingly higher redshifts to explore the time evolution of the structure of ETGs.

2
Corrected as described in the corresponding erratum.
5
The situation will change in the near future when the 2MASS Redshift Survey will become available, which is already complete down to Ks = 11.25 (Crook et al. 2007) and ultimately aims for a redshift completeness down to Ks = 13.0 (Huchra et al. 2005).
9
Available from http://miles.iac.es/
11
This was performed with the idl routine fit_kinematics_pa described in appendix C of Krajnović et al. (2006) and available at http://purl.org/cappellari/idl

We thank to the anonymous referee for a useful report. MC acknowledges support from a STFC Advanced Fellowship PP/D005574/1 and a Royal Society University Research Fellowship. This work was supported by the rolling grants ‘Astrophysics at Oxford’ PP/E001114/1 and ST/H002456/1 and visitors grants PPA/V/S/2002/00553, PP/E001564/1 and ST/H504862/1 from the UK Research Councils. RLD acknowledges travel and computer grants from Christ Church, Oxford and support from the Royal Society in the form of a Wolfson Merit Award 502011.K502/jd. RLD also acknowledges the support of the ESO Visitor Programme that funded a 3-month stay in 2010. SK acknowledges support from the Royal Society Joint Projects Grant JP0869822. RMM is supported by the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., on behalf of the international Gemini partnership of Argentina, Australia, Brazil, Canada, Chile, the United Kingdom and the United States of America. TN and MBo acknowledge support from the DFG Cluster of Excellence ‘Origin and Structure of the Universe’. MS acknowledges support from a STFC Advanced Fellowship ST/F009186/1. NS and TAD acknowledge support from an STFC studentship. The authors acknowledge financial support from ESO. We acknowledge the usage in ppxf of the mpfit routine by Markwardt (2009). The SAURON observations were obtained at the WHT, operated by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias. We are grateful to the ING staff for their excellent support and creativity in quickly solving technical problem during the SAURON runs. We are grateful to Jesús Falcon-Barroso for useful discussions and help with the observations. MC is grateful to the NED staff for prompt support. This research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. We acknowledge the usage of the HyperLeda data base (http://leda.univ-lyon1.fr). Funding for the SDSS and SDSS-II was provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the US Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society and the Higher Education Funding Council for England. The SDSS was managed by the Astrophysical Research Consortium for the Participating Institutions. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation.

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