Free Access
Issue
A&A
Volume 545, September 2012
Article Number A16
Number of page(s) 22
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/201218788
Published online 29 August 2012

© ESO, 2012

1. Introduction

The combined availability of multi-wavelength data from recent and ongoing surveys is providing a wealth of information on the different phases of the interstellar medium (ISM), the stellar content and the present day star formation rates (SFRs) of nearby galaxies. Complemented with results from numerical simulations and theory, these observations contribute to our understanding of the basic process which regulates the life of a galaxy: the conversion of gas into stars. However, crucial questions remain open concerning which gas phase (on which scale) is ultimately responsible for new star formation, which tracers for the SFR are unbiased, and what is the role of very massive stars and of the environment in shaping the observed luminosity in local galaxies.

Half a century has passed since Schmidt (1959) discovered a fundamental relation between the surface density of star formation and that of the gaseous component in galaxies1, today known as the Kennicutt-Schmidt (KS) law (Schmidt 1959; Kennicutt 1989, 1998). Since then, a large number of theoretical and observational studies have addressed the origin of this correlation. Modern observations reveal a relation between the molecular gas and the star formation rate surface density (Wong & Blitz 2002; Kennicutt et al. 2007; Bigiel et al. 2008) within the optical radius where CO seems to be a reliable tracer of molecular hydrogen. While the original formulation of the KS law considered only the more extended atomic gas, the more recent results are consistent with the basic picture of star formation in giant molecular clouds. But it is unclear whether molecular hydrogen in fact drives this correlation (Krumholz et al. 2011; Glover & Clark 2012), and departures from a universal relation are still a matter of debate (Fumagalli & Gavazzi 2008; Bigiel et al. 2010; Schruba et al. 2011).

Whereas there is general consensus that high luminosity late-type galaxies display low specific star formation rates (SFR per unit stellar mass; SSFRs), as expected from downsizing (e.g. Gavazzi et al. 1996), the behavior of dwarf galaxies, whose SSFRs span a range exceeding two orders of magnitude (Lee et al. 2007), is poorly understood. In addition, the SFRs inferred from the Hα hydrogen recombination line in these systems or in the outskirts of disks, systematically underpredict estimates derived from the UV light (Meurer et al. 2009; Lee et al. 2009) to the point that doubts have been cast on the universality of the initial mass function (IMF; e.g. Meurer et al. 2009) and on the reliability of hydrogen recombination lines to trace star formation (Pflamm-Altenburg et al. 2007). However, uncertainties in the dust extinction (Boselli et al. 2009), star formation history (Weisz et al. 2011) and stochastic star formation rate (Fumagalli et al. 2011) can equally well explain the observed luminosities, even for a universal IMF.

Similarly, the role of the environment in shaping the star formation properties of galaxies is still debated (see a review by Boselli & Gavazzi 2006). While it is observed that atomic (e.g. Gavazzi et al. 2002b; Cortese & Hughes 2009; Rose et al. 2010) and, in highly perturbed systems, molecular (Vollmer et al. 2008; Fumagalli et al. 2009; Vollmer et al. 2009) gas depletion result in a low level of star formation, simulations of ram-pressure stripping have suggested different degrees of enhancement in the SFR of perturbed galaxies (e.g. Kronberger et al. 2008; Kapferer et al. 2009; Tonnesen & Bryan 2009). Furthermore, studies of the Hα morphology in galaxies within rich groups or clusters show a mix of global suppression and truncation of the Hα disks (Vogt et al. 2004; Koopmann & Kenney 2004; Fumagalli & Gavazzi 2008; Welikala et al. 2008; Rose et al. 2010). However, a definitive assessment of the relative importance of these different perturbation mechanisms is still lacking.

To address some of these open issues, we have recently completed an Hα narrow-band imaging survey of an HI line flux-selected sample of Local Supercluster (LSc) galaxies using the 2.1 m telescope of the San Pedro Martir (SPM) Observatory. Our sample includes  ~400 nearby galaxies, selected from the ongoing blind HI Arecibo Legacy Fast ALFA Survey (ALFALFA; Giovanelli et al. 2005) found in the Spring sky of the Local Supercluster, including the Virgo cluster, in the velocity window 350 < cz < 2000 km s-1. Because it represents a complete sample extacted from the ALFALFA catalog, we refer to our narrow-band imaging survey as the Hα3 dataset. Together with ancillary multifrequency data and complemented by similar surveys (Meurer et al. 2006) or with optically selected samples (James et al. 2004; Kent et al. 2008), these observations provide a complete census of the SFR in the local universe as traced by hydrogen recombination lines (see also Bothwell et al. 2009).

As the first of a series, the present paper presents the basic properties of the Hα3 dataset (Sect. 2). After a description of the observations (Sect. 3) and data reduction (Sect. 4), we present the previously unpublished Hα fluxes and equivalent widths for 235 galaxies. A summary and discussion of future prospects follows in Sect. 5. The Appendix B includes an Atlas of the images of the sampled galaxies.

Paper II of this series will contain the analysis of the integrated quantities (global SFRs) produced by the Hα3 survey and will investigate the relationships between atomic neutral gas and newly formed stars in different environments (cluster and field), morphological types (spirals and dwarfs), and over a wide range of stellar masses (~107.5 − 1011.5 M).

Paper III will contain the extension of Hα3 to the more distant Coma Supercluster (10h < RA < 16h; 24° < Dec < 28°; 3900 < cz < 9000 km s-1).

The analysis of the Hα morphology from Hα3 in both the Local and the Coma Superclusters will be carried out in Paper IV, which will address the comparison of the effective radii at Hα and r band as a function of morphological type, and the determination of other structural parameters such as the Concentration index, the Asymmetry and the Clumpiness parameters introduced by Conselice (2003). Throughout the paper we adopt H0 = 73 km s-1 Mpc-1.

2. The sample

2.1. Selection

Our sample is drawn from the 900 square degree region 11h < RA < 16h; 4° < Dec < 16°; 350 < cz < 2000 km s-1, covering the Local Supercluster, including the Virgo cluster2. This region has been fully mapped by ALFALFA; at these distances, the survey detects masses as low as 106.5−7.0 M, 7.7 times deeper than HIPASS, the HI Parkes All-Sky Survey (Meyer et al. 2004)3. A comprehensive catalogue containing 40% of the eventual ALFALFA coverage is given in Haynes et al. (2011), superseding previous ALFALFA publications (e.g. Giovanelli et al. 2007) covering the region 11h44m < RA < 14h00m; 12° < Dec < 16°, and Kent et al. (2008) for the region 11h26m < RA < 13h52m; 4° < Dec < 12°).

thumbnail Fig. 1

Bottom panel. Sky distribution of 409 HI selected galaxies observed in the present survey, 383 with FHI > 0.7 Jy km s-1 (filled circles) and 26 with  < 0.7 Jy km s-1 (big empty circles). Red symbols refer to 233 new sources observed in 2006 − 2009 whose fluxes are presented in this paper. Top panel. 68 HI targets that matches our selection criteria but that were not observed because: 8 lie too close to bright stars; 38 are either debris of ram pressure stripped gas or their associated galaxy is too faint to be seen on SDSS plates (triangles); 20 which will be consider in future runs (crosses). The two vertical broken lines mark the adopted boundaries of the Virgo cluster.

Open with DEXTER

The goal of the Hα3 survey is to follow up with Hα imaging observations the ALFALFA targets with high S/N (typically S/N > 6.5) and good match between the survey’s two independent passes (i.e., the Code 1 sources; Giovanelli et al. 2005; Haynes et al. 2011). In addition, we limit the Hα sample to objects with HI line flux densities FHI > 0.7 Jy km s-1. At the distance of 17 Mpc adopted for the Virgo cluster, a flux density limit FHI = 0.7 Jy km s-1 corresponds to an HI mass MHI = 107.7 M.

Figure 1 presents the distribution of galaxies in the sky region under study. The bottom panel shows the 383 sources that have been observed in the Hα program. In addition, 26 sources in the Virgo cluster (large open circles) were observed although they are do not meet the strict flux density limit, i.e. FHI < 0.7 Jy km s-1. Their addition brings the total number of observed galaxies to 409.

thumbnail Fig. 2

Comparison of the observed HI mass distribution in the three subsamples (histograms) with the HI mass function of Martin et al. (2010) (black lines) and one corrected for the overdensity in the Local Supercluster (red lines).

Open with DEXTER

2.2. Completeness

The top panel of Fig. 1 shows the sky distribution of 68 ALFALFA sources that are not, for various reasons, included in the Hα3 sample. Among them, 38 (triangles) were not observed because they do not have any optical counterpart because they are either debris of ram pressure stripped gas (Kent et al. 2007) or too faint in optical light to be visible in the Sloan Digital Sky Survey (SDSS). It was thus deemed that they would have been undetected for the typical exposure time of our survey (see Sect. 4). Of the remaining, 8 galaxies (squares) are close to bright stars so that charge bleeding would have precluded the requested photometric accuracy. Finally, 20 galaxies which were missed for scheduling or equipment reasons will be observed in future runs (crosses). After accounting for these missing sources, the achieved completeness is 87% in Virgo and 82% outside, normalized to the ALFALFA catalogue. To investigate further the HI completeness of Hα3, i.e., the limiting HI mass above which Hα3 is complete, we compare in Fig. 2 the observed HI mass distribution (histograms) of the subsamples with the ALFALFA HI mass function derived by Martin et al. (2010) (black line), for the 40% ALFALFA sample. As discussed by those authors, the ALFALFA HI mass function is well represented by a Schechter function with α =  −1.33, Φ = 4.8 × 10-3 Mpc-3 dex-1, M = 109.96. The red lines show the ALFALFA HI mass function whose Φ has been normalized to the volumes sampled by Hα3, separately for Virgo and the isolated volume, to account for the overdensity in the two subsamples with respect to ALFALFA. This normalization has been done by dividing the integral of the ALFALFA HI mass function in the interval 108 − 9.75 M by the integral of the observed histogram in the same interval. The normalization coefficients are 1.96 (isolated), 2.99 (all), 6.01 (Virgo). The agreement between the red line and the histogram is quite satisfactory above log MHI = 8 M, assumed to be the HI completeness limit of Hα3. The data and the red line diverge above log MHI = 9.75 M because of cosmic variance since the number of the rare high HI mass galaxies found in Hα3 is very limited. The lack of the rare high HI mass galaxies arises both because of the well-known cluster HI deficiency and the relatively small volume sampled by Hα3. The number of “missing” objects with log MHI > 9.75 M is however only of 1 − 2 objects.

The optical completeness of Hα3 cannot be determined as accurately as for the HI mass because the optical luminosity function of the HI selected galaxies is unknown. However we empirically determine the optical completeness by deriving the cumulative distribution in 0.5 mag bins of i-band luminosity of galaxies in the three observed volumes: isolated, Virgo, all. The cumulative distribution flattens at Mi >  −15.25 (corresponding to log (Mlim/M) = 7.8). This represents the i-band completeness limit of our HI selected sample which itself is largely composed of late-type galaxies.

2.3. Ancillary data

The region covered by Hα3 coincides with that contained in the imaging and spectroscopic observations of the SDSS (DR7, Abazajian et al. 2009). However, given the proximity of the surveyed galaxies, their angular size often exceeds several arcmin, making the well-known SDSS pipeline shredding problem (Blanton et al. 2005a,b,c) particularly severe. In extreme cases, the catalogues magnitudes are sometimes wrong by several magnitudes. For this reason and the fact that fiber conflicts reduce the number of galaxies with nuclear spectra, the SDSS spectral database is not fully complete/reliable for the nearby Universe (z ≪ 0.2). To address these problems, the individual g and i band SDSS images centered on each galaxy targeted by Hα3 were downloaded from the SDSS archive. Many of the largest galaxies are cut into several pieces belonging to adjacent SDSS “tiles”. These images were downloaded individually and combined to cover a sufficient area to contain not only all the light from the target galaxy but also a suffient contribution of surrounding empty sky. The background was estimated and subtracted using the tasks MARKSKY and SKYSUB in the IRAF4 – based GALPHOT package5. The background subtracted frames were inspected individually and background objects and foreground stars were masked when found within or near the galaxies of interest. The photometry in the edited frames was obtained using QPHOT in IRAF by integrating the counts within a circular aperture (determined in the i-band image) containing all the flux. This procedure provides an accurate estimate of the total g and i magnitudes (see Table B.1). During this process, the major and minor diameters of the galaxies were crudely determined using elliptical regions adapted to the shape of galaxies (see Table B.1) using the DS9 tool.

The distance to the galaxies belonging to the Virgo cluster is computed following the prescription given by Gavazzi et al. (1999); in short, those authors adopt 17 Mpc for members of the Virgo A subcluster and for the N, S, and E clouds, 23 Mpc for members of the Virgo B (M49) substructure, and 32 Mpc for galaxies in the M and W clouds. These values are consistent with the more modern determinations obtained with the surface brightness fluctuation method using HST-ACS images by Mei et al. (2007). For all other members of the Local Supercluster, we adopt the galactocentric (GSR) distances listed in NED.

The HI mass is computed using the standard formula MHI = 2.36 × 105 × S21 × D2, where D is the distance to the source in Mpc and S21 is the integrated line flux density under the HI profile in units of Jy-km s-1 as given in the ALFALFA catalog.

The stellar mass is derived from the i band magnitude and the g − i color using the Bell’s et al. (2003) recipe: log Mstar =  −0.152 + 0.518(g − i) + log ilumM, where ilum is the i band luminosity in solar units.

2.4. Optical properties

For the large majority of the 224 Virgo galaxies (12h05m < RA < 12h50m; 4° < Dec < 16°; cz < 3000 km s-1; black filled circles in Fig. 1) the Hα data have been already published in previous papers (Gavazzi et al. 2002a; Boselli & Gavazzi 2002; Boselli et al. 2002; Gavazzi et al. 2002b; Gavazzi et al. 2006). Images and fluxes are publicly available via the GOLDMine web server (Gavazzi et al. 2003).

thumbnail Fig. 3

Properties of the Hα3 sample, compared to that of the entire ALFALFA catalogue (dotted lines) and the subset restricted to galaxies with optical counterparts (dashed lines). Panel a) 1σ limiting surface brightness (erg cm-2 s-1 arcsec-2) in the Hα NET images. Panel b) morphological types. Panel c) stellar masses from i-band photometry. Panel d) color (g − i) magnitude (i band) diagram (color coded by morphology: red = early, blue = disk; green = bulge + disk) (SDSS magnitudes are uncorrected for internal extinction). Hα3 is a homogeneous survey, complete down to a SFR density of 3 × 10-9 M yr-1 pc-2 (1σ) and HI masses of 108 M. This sample spans a wide range in color, morphological type, colors and stellar masses, thereby allowing a comparison of the SFR over a broad parameter space.

Open with DEXTER

Properties for the 235 unpublished sources observed in the period 2006 − 2009 (red filled circles in Fig. 1) are presented in Table B.1. Individual entries are as it follows:

  • Col. 1: AGC designation, from Hayneset al. (2011). AGC numberscoincide with UGC numbers forthose galaxies included in the UGC (Nilson1973);

  • Cols. 2 and 3: optical celestial coordinates (J2000);

  • Cols. 4 − 7: CGCG (Zwicky et al. 1968), UGC (Nilson 1973), NGC (Dreyer 1888) and IC (Dreyer 1908) designations;

  • Col. 8: morphological type, from NED or classified by the authors on the SDSS i-band images;

  • Col. 9: heliocentric velocity of the HI source, cz in km s-1 from Haynes et al. (2011);

  • Cols. 10 and 11: major and minor optical diameters from NED or measured with ellipses on SDSS i-band frames (see Sect. 2.3). These are consistent with 25th mag arcsec-1 isophotal diameters;

  • Cols. 12 and 13: i and g integrated (AB) magnitude obtained on the SDSS images (see Sect. 2.3);

  • Col. 14: adopted galactocentric (GSR) distances as given by NED (Mpc).

An overview of the sample properties is presented in Fig. 3. Panel (a) shows the limiting Hα fluxes, computed from the pixel to pixel 1σ sky fluctuation. We note that most of the galaxies lie in a quite narrow distribution (~0.15 dex), with a median Hα flux of 10 − 14.3 ± 0.15 erg cm-2 s-1, revealing that Hα3 is a rather homogeneous survey, despite the fact that observations were spread over almost one decade. At the distance of Virgo, our typical sensitivity corresponds to an unobscured SFR level of 1.3 × 10-3 M yr-1 at 1σ, computed as outlined in Sect. 4.3. Panel (b) shows the distribution of morphological types from the ALFALFA galaxy catalogue (dashed line) and from the Hα3 program. Perhaps not surprisingly, an HI selected sample is strongly biased towards spirals and irregular galaxies (Gavazzi et al. 2008) at the depth achieved by ALFALFA. Stellar properties for our sample (solid lines) and for ALFALFA galaxies (dashed lines) are presented in panel (c). Owing to the correspondence between stellar masses and HI masses (e.g. Gavazzi et al. 2008), the stellar distribution resembles the one for the gas masses, with a significant completeness down to less than 108 M (see Sect. 2.2). Galaxies in Hα3 span a wide range in color and gas fraction, allowing a statistical analysis of the star formation over a large space of parameters. In the color-magnitude diagram (d), HI selected galaxies lie almost exclusively in the blue cloud, while the red sequence (represented in the figure by the linear regression g − i =  −0.0585(Mi + 16) + 0.98; Gavazzi et al. 2010) is grossly undersampled, as evident in the color magnitude diagram (Fig. 7) of Haynes et al. (2011). To detect the low level of atomic gas present in galaxies located in the green valley or even in the red sequence, deeper HI observations are required (e.g. Catinella et al. 2010). More detailed discussions of stellar and star formation properties of the ALFALFA population overall are presented in Huang et al. (2012a) and Huang et al. (2012b).

3. Observations

Observations of HI selected galaxies from ALFALFA were completed in four runs of nine nights each, allocated from 2006 to 2009 by the Mexican Observatorio Astronómico Nacional (OAN) at the San Pedro Martir Observatory (SPM, Baja California, Mexico). Owing to the excellent weather conditions which are frequently encountered at SPM in the late Spring, we were able to observe mostly in photometric conditions: 8/9 nights in 2006, 9/9 in 2007 − 2008 and 5/9 in 2009. During these runs6, we focused on the field surrounding the Virgo cluster, since most of the ALFALFA sources in Virgo were already observed as part of a survey of optically selected galaxies started in 1999, using various telescopes: the OHP and Calar Alto 1.2 m (Boselli & Gavazzi 2002), the INT and NOT 2.5 m (Boselli et al. 2002), the ESO 3.6 m (Gavazzi et al. 2006) and the SPM 2.1 m (Gavazzi et al. 2002a,b, 2006). We point to those papers for a detailed description of the observing strategies, data reduction and values for Hα fluxes in that subsample.

As for the data acquired between 2006 and 2009 and reported here, we obtained narrow-band imaging in the Hα emission line (rest frame λ = 6562.8 Å) with the (f/7.5) Cassegrain focus imaging camera of the SPM 2.1 m telescope, equipped with a SIT3 1024 × 1024 pixels CCD detector with a pixel size of 0.31′′. The detector was used in the 1 e/ADU gain mode. The redshifted Hα line (ON-band frame) was imaged through a narrow band (λ 6603 Å, Δλ ~ 73 Å) interferometric filter, whose bandpass include also the [NII] lines. Except for two galaxies at lower velocities (cz < 300 km s-1), this filter maximizes the throughput at the galaxy redshift, as shown in Fig. 47. For each galaxy, we acquired multiple ON-band exposures with an integration time ranging from 15 to 60 min, adjusted according to seeing conditions and to source brightness. The stellar continuum subtraction was secured by means of shorter (typically 3 to 5 min) observations taken through a broad-band (λ 6231 Å, Δλ ~ 1200 Å) r-Gunn filter (OFF-band frames). While the median seeing of the San Pedro Martir site is , the final FWHM for point sources in the images is affected by poor telescope guiding and dome seeing. For these reasons, the final distribution of image seeing ranges from 1′′ to  (measured fitting a Gaussian profile to the stars), with a mean seeing of in the OFF-band images and in the longer ON-band exposures, as shown in Fig. 5.

thumbnail Fig. 4

The transmissivity of the ON-band (6603 Å) filter. Filled circles mark the transmissivity for Hα at the redshift of the target galaxies. Two galaxies with cz = 132 and 213 km s-1 have been observed on the steep shoulder of the filter transmission curve. They will not be further considered in the analysis.

Open with DEXTER

thumbnail Fig. 5

Point source FWHM measured on the final ON-band images (solid histogram) and OFF-band images (dashed histogram). Poor telescope guiding performance and dome seeing affect the image quality, making the distribution of the seeing slightly better in the shorter OFF exposures.

Open with DEXTER

We derive the absolute flux levels using observations of the reference stars Feige 34 and HZ 44 from the catalogue of Massey et al. (1988), observed every  ~2 h. Repeated measurements gave  <5% differences that we assume as the 1σ photometric uncertainty8. A very small number of galaxies were imaged in transparent but not photometric conditions, and for those objects, we derive only the Hα equivalent width (EW; insensitive to the absolute flux level), but not the Hα flux.

We list information for individual galaxies in Table B.2, as follows:

  • Col. 1: AGC designation, from Hayneset al. (2011);

  • Col. 2: observing date (yy-mm-dd UT);

  • Cols. 3 and 4: duration and number of individual ON-band exposures;

  • Col. 5: average air mass during the ON-band exposures;

  • Col. 6: adopted photometric zero point;

  • Col. 7: FWHM of point sources (arcsec) in the ON-band frames, as measured on the images;

  • Cols. 8 and 9: duration and number of individual OFF-band exposures;

  • Col. 10: FWHM of point sources (arcsec) in the OFF-band frames, as measured on the images;

  • Col. 11: normalization factor n of the OFF-band frames (see next section).

4. Data reduction

4.1. Image analysis

We reduce the CCD frames following the procedure described by Gavazzi et al. (2002b), using the STSDAS and GALPHOT IRAF packages. To compensate for the spatial differences in the detector response, each image is bias subtracted and divided by the median of several flat-field exposures obtained during twilight in regions devoid of stars. When three exposures are available, we adopt a median combination of the realigned images to reject cosmic rays in the final stack. For galaxies observed in single exposures, we reject cosmic rays by direct inspection of the frames. For each frame, we subtract a mean local sky background, computed around the galaxy using the GALPHOT tasks MARKSKY and SKYFIT. Over the typical spatial scale of galaxies (50′′ − 200′′) the mean background varies by  ~10% of the sky rms per pixel. This is caused by residual patterns after flat-fielding and represents the dominant source of error in low S/N regions. Over extended objects, the inability to subtract the sky with high accuracy introduces an additional error on the final flux, of which we take proper account in computing the error budget.

4.2. Integral photometry

Due to the proximity of the two [NII] emission lines (λ 6548 − 6584 Å) to the Hα line, the flux measured in the ON-band observations refers to the combination of Hα+[NII]. While a proper correction for [NII] emission is required before the final SFR is computed, in this section we will generically refer to Hα as the total line emission flux Hα+[NII].

Fluxes and EWs of the Hα line can be recovered from narrow ON-band observations by subtracting the stellar continuum contribution estimated using OFF-band images, once these are normalized to account for the ratio of the transmissivity of the two filters and the difference in exposure time. For each galaxy, we derive the normalization coefficient n by assuming that field stars have no significant Hα emission on average and therefore they have identical continuum levels in the ON- and OFF-band frames (see however Spector et al. 2011).

Once the normalization coefficient is known, we derive the integrated Hα flux performing aperture photometry on both the OFF- and ON-band sky subtracted frames. First, we derive the integrated net counts CNET as: (1)where we define the normalized OFF-band counts with  the measured counts. The net flux and EW in the Hα line are then given by: (2)and (3)where T is the integration time (s), 10Zp is the ON-band zero point (erg cm-2 s-1) corrected for atmospheric extinction and RON(λ) is the transmissivity of the ON-filter at the wavelength of the redshifted Hα line. Finally, since the stellar continuum is estimated using a broad band r filter that includes the Hα line, a non-negligible (~10%) correction must be included (see Boselli et al. 2002; Gavazzi et al. 2006): (4)and (5)where ROFF(λ) is the transmissivity of the OFF filter.

4.3. The SFR calibration

The star formation rate is derived from the observed, integrated Hα flux (F(Hα)) after the following corrections are applied: i) Galactic extinction, ii) deblending from [NII], iii) internal extinction (Boselli et al. 2009).

  • i)

    Corrections for Galactic extinction A are computed using the color excess E(B − V) obtained from the far-IR dust map of Schlegel et al. (1998). For the broad band photometry, we assume A(R) = 2.3E(B − V) and A(I) = 1.5E(B − V) (Cardelli et al. 1989), while for the Hα fluxes we use A(Hα) = 0.6A(B) = 2.6E(B − V) (Kennicutt et al. 2008; Cardelli et al. 1989).

  • ii)

    The correction for [NII] deblending is obtained by fitting the ratio ( [NII] /Hα)ew9 vs. absolute i-band magnitude relation. This requires that AGNs (Seyfer+LINERS) are first identified (and disregarded) using the nuclear (3 arcesc) SDSS spectra and the BTP (Baldwin et al. 1981) diagnostic. For this purpose, the Balmer lines are corrected for underlying absorption by 5 Å for Hβ (Kennicutt 1992; Gavazzi et al. 2004) and by 1.3 Å for Hα (Gavazzi et al. 2011). We identify Seyferts as those galaxies which have a ratio of ( [NII] /Hα)ew > 0.5 and ( [OIII] /Hβ)ew > 3 and LINERS as those which have a ratio of ( [NII] /Hα)ew > 0.5 and ( [OIII] /Hβ)ew ≤ 3. After excluding both classes of AGNs, we perform a linear fit between the ratio ( [NII] /Hα)ew and the absolute i-band magnitude (see Fig. 6), corresponding to the well established mass-metallicity relation (Tremonti et al. 2004). We obtain a reliable fit with ( [NII] /Hα)ew =  −0.0854 × Mi − 1.326. The corrected flux is: F(HαMW;DB) = F(HαMW)/(1 + (1.34 × ( [NII] /Hα)ew)) where the measured ( [NII] /Hα)ew is used when the a drift-scan spectrum is available from GOLDMine; otherwise the ratio is obtained from the fit with Mi.

  • iii)

    The correction for internal extinction is performed using the value of AHa derived from the Balmer decrement if integrated drift-scan mode spectra are available and Hα and Hβ are both detected in emission (see an asterisk in Col. 9 of Table B.3). Alternatively, when integrated drift-scan mode spectra are unavailable, we apply an average correction as function of the B band luminosity as proposed by Lee et al. (2009): AHa = 1.971 + 0.323 × B + 0.0134 × B2 for B >  − 14, otherwise AHa = 0.10. It should be noted however that such a dependence is very poorly defined. For this reason, we give in Table B.3 both values (with and without the Lee et al. 2009, correction), and let the reader decide which value to adopt. To obtain such a correction, one must first convert the SDSS g(AB) magnitudes into Johnson B magnitudes, adopting the relation: B = g × 0.983 + 0.692 mag (taken from GOLDMine). In this case, the dust extinction-corrected flux becames: F(HαMW;DB;AA) = F(HαMW;DB) − (AHa/ − 2.5). Finally, we derive the corrected Hα luminosity: L(HαMW;DB;AA) = F(HαMW;DB;AA)  +  48  +  log ((3.0862) × 4π × D2) where D is the distance in Mpc. The star formation rate: log (SFR) = L(HαMW;DB;AA) − 41.1024 according to Kennicutt (1998).

The results of the integrated photometry as derived from the present observations are listed in Table B.3 as follows:

  • Col. 1: AGC designation, from Hayneset al. (2011);

  • Cols. 2 and 3: RA and Dec (J2000);

  • Col. 4: equivalent width of Hα + [NII] (in Å) as given in Eq. (5);

  • Col. 5: 1σ uncertainty on the Hα + [NII] equivalent width as given in Eq. (A.8);

  • Col. 6: log of Hα + [NII] (in erg cm-2 s-1) flux as given in Eq. (4);

  • Col. 7: log of 1σ uncertainty on the Hα + [NII] flux as given in Eq. (A.6);

  • Col. 8: log of SFR obtained in Sect. 4.3, without correction for internal extinction;

  • Col. 9: log of SFR10 including the correction for internal extinction using the Balmer decrement when a drift-scan spectrum is available (see *) or as proposed by Lee et al. (2009) in M yr-1;

  • Col. 10: sky quality: P = photometric (σ < 5%), T = transparent (5% < σ < 10%);

  • Col. 11: Atlas figure.

We cross correlated our catalogue with the 11 Mpc volume Hα survey by Kennicutt et al. (2008) and we found 5 galaxies in common (see Table 1). For these few, the agreement between the two sets of measurements is satisfactory.

thumbnail Fig. 6

The ratio ( [NII] /Hα)ew derived from drift-scan spectra as a function of Mi, exhibiting the variation expected for the mass-metallicity relation. Red points mark AGNs. The line indicates the linear fit to the data adopted when drift-scan spectra are unavailable.

Open with DEXTER

Table 1

Comparison between the photometry from this work and from Kennicutt et al. (2008).

An independent check of the calibration of our Hα measurements has been performed on a significant number of detections by comparing the fluxes determined in 3 arcsec nuclear apertures in our Hα images with the flux in the Hα +  [NII]  lines listed in the SDSS spectral database obtained in 3 arcsec fibres (after removing all measurements not obtained in the nuclear regions). The comparison, given in Fig. 7, shows satisfactory agreeement between the imaging and the spectral flux determinations.

The final SFRs, plotted against Mi are presented in Fig. 8. The error bars are obtained by combining in quadrature the errors on F(Hα) (see Eq. (11)) with the errors on the coefficient of absorption from the Milky Way. Errors on the extinction coefficient AHa and on the correction for deblending are not considered (see Boselli et al. 2009). The linear regression is SFR =  −0.39 ∗ Mi − 8.21, with r = 0.87, i.e. across the whole sample, the global SFR is proportional to the i band luminosity.

thumbnail Fig. 7

Comparison between the Hα +  [NII]  flux extracted in 3 arcsec aperture centered on the nucleus (from this work) and the flux in the Hα +  [NII]  lines given by SDSS in 3 arcsec fibre spectrum (for detections with SN > 2). The dashed line gives the one-to-one relation.

Open with DEXTER

thumbnail Fig. 8

The corrected SFR derived from this work (see Col. 9 of Table B.3) as a function of the absolute i band magnitude Mi.

Open with DEXTER

5. Summary and future prospects

This is the first paper of a series devoted to Hα3, the Hα narrow-band imaging survey of galaxies carryed out with the San Pedro Martir 2.1 m telescope (Mexico), selected from the ALFALFA extragalactic HI survey.

The first sample includes  ~400 targets in the Local Supercluster for the sky region 11h < RA < 16h; 4° < Dec < 16°; 350 < cz < 2000 km s-1 including the Virgo cluster.

At the distance of Virgo (17 Mpc) and given the sensitivity of ALFALFA the targets selected for the Hα follow-up contain more than 107.7 M of neutral atomic hydrogen. Hα3, complete for MHI > 108 M, provides a full census of the star formation in HI rich galaxies of the local universe over a broad range of stellar masses, from dwarf galaxies with 107.5 M up to giants with 1011.5 M. Not unexpectedly, only a handful of detections are identified with galaxies on the red sequence, while the majority are late-type, from giant spirals (Sa-Sd) to dwarf Irr-BCDs.

In this paper, we present the properties of the Hα galaxy sample, together with Hα fluxes and equivalent widths for the previously unpublished subsample observed between 2006 and 2009. The integrated Hα fluxes are corrected for galactic and internal extinction and for [NII] contamination to yield measures of the global SFR. Given the sensitivity of the present Hα observations, we detect galaxies with an unobscured SFR density above 3 × 10-9 M yr-1 pc-2 at 1σ.

The analysis of the integrated quantities (global SFR) produced by Hα3 will be carryed out in Paper II of this series (Gavazzi et al. 2012). By using hydrogen recombination lines as a tracer of recent star formation, we aim to investigate the relationships between atomic neutral gas and newly formed stars in different environments (cluster and field), morphological types (spirals and dwarfs), and over a wide range of stellar masses (~107.5 − 1011.5 M).

Paper III will contain the extension of Hα3 to the Coma supercluster (10h < RA < 16h; 24° < Dec < 28°; 3900 < cz < 9000 km s-1). Being approximately six times more distant than Virgo, galaxies selected by ALFALFA at Coma contain about 35 times higher HI mass than those at Virgo. Hence ALFALFA will be complete for  ≥109.5 M, i.e., for giant galaxies. The cost of missing completely the population of dwarf galaxies will be compensated by the fact that at cz > 5000 the shredding problem affecting the SDSS completeness is much less severe than at Virgo, hence making it possible to extract a catalogue of optically selected candidates from the SDSS database. This will allow us to investigate in detail the differences between the optical and the radio selection functions.


1

The 50th anniversary from the original Schmidt (1959) paper was celebrated during the conference SFR@50 held in Spineto in 2009.

2

The lower velocity limit is dictated by the fact that none of interferometric filters available at SPM covers the Hα line for redshift  < 350 km s-1. Furthermore some galaxies have been serendipitously observed in spite of having cz > 2000 km s-1, but they do not constitute a complete sample. In the Virgo cluster however, we extend the velocity coverage of Hα3 to 350 < cz < 3000 km s-1 in order to include its full velocity range (Gavazzi et al. 1999).

3

As introduced in Giovanelli et al. (2005) ALFALFA is a noise-limited survey rather than a flux-limited one. At any given integrated HI mass the 21 cm flux per velocity channel is inversely proportional to the width of the HI profile, thus to the galaxy inclination. The completeness and sensitivity of ALFALFA are well understood and discussed in detail in Saintonge (2007), Martin et al. (2010) and Haynes et al. (2011).

4

IRAF is the Image Analysis and Reduction Facility made available to the astronomical community by the National Optical Astronomy Observatories, which are operated by AURA, Inc., under contract with the US National Science Foundation. STSDAS is distributed by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under NASA contract NAS 5–26555.

5

GALPHOT was developed in the IRAF – STSDAS environment mainly by W. Freudling, J. Salzer, and M. P. Haynes (Haynes et al. 1999) and was further adapted by L. Cortese and S. Zibetti to handle Hα data.

6

During an unfortunate run in 2010 the SIT3 CCD broke and was substituted with an outdated Thompson detector, badly affected by fringing in the red and with a low quantum efficiency. Due to the poor weather we could observe only 2 additional galaxies that are listed at the end of the tables.

7

Two galaxies AGC4880 and AGC190160 with cz = 4971 and 4954 km s-1 respectively have been observed through a filter centered at λ 6683 Å. The will not be considered in any further analysis.

8

The stability of the photometry during each runs was such that we were able to detect a zero-point decrease of 0.12 dex in 4 years due to loss of reflectivity of the mirrors.

9

Hereafter, the notation ( [NII] /Hα)ew includes only the [NII]λ6584 line. A ratio of [NII]λ6548/[NII]λ6584 = 0.34 is assumed when deblending Hα from both component of [NII].

10

Among the galaxies detected under photometric conditions, the SFR is given only for objects strictly belonging to the Hα3 sample, i.e. in the interval 11h < RA < 16h; 4° < Dec < 16°; and for 350 < cz < 2000 km s-1 (outside Virgo) and 350 < cz < 3000 km s-1 (inside Virgo). For the few galaxies which do not meet those criteria but which were still observed, we give the flux and EW, but we don’t compute a SFR.

Acknowledgments

This work is dedicated to the memory of Gaby Garcia who payed with his life the passion for his work. We thank the night operators, specially Felipe Montalvo and Salvador Monrroy for their collaboration, the resident astronomers at SPM for their assistance during the observations and the mexican TAC for the generous time allocation. We acknowledge useful discussions with Luis Aguillar, Luis Carrasco, Matteo Fossati, Michael Richter and Giulia Savorgnan. We thank L. Giordano, D. Burlon, E. Farina, C. Pacifici and V. Presotto for their help during the observations and L. Cortese and S. Zibetti, F. Martinelli and I. Arosio for their support in the data reduction. We thank Shan Huang who detected a typo in one equation. The authors would like to acknowledge the work of the entire ALFALFA collaboration team in observing, flagging, and extracting the catalog of galaxies used in this work. This research has made use of the GOLDMine database (Gavazzi et al. 2003) and 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. Funding for the Sloan Digital Sky Survey (SDSS) and SDSS-II has been 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, and the Max Planck Society, and the Higher Education Funding Council for England. The SDSS Web site is http://www.sdss.org/. The SDSS is managed by the Astrophysical Research Consortium (ARC) for the Participating Institutions. The Participating Institutions are the American Museum of Natural History, Astrophysical Institute Potsdam, University of Basel, University of Cambridge, Case Western Reserve University, The University of Chicago, Drexel University, Fermilab, the Institute for Advanced Study, the Japan Participation Group, The Johns Hopkins University, the Joint Institute for Nuclear Astrophysics, the Kavli Institute for Particle Astrophysics and Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences (LAMOST), Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, Ohio State University, University of Pittsburgh, University of Portsmouth, Princeton University, the United States Naval Observatory, and the University of Washington. G.G. acknowledges financial support from italian MIUR PRIN contract 200854ECE5. R.G. and M.P.H. are supported by US NSF grants AST-0607007 and AST-1107390 and by a Brinson Foundation grant.

References

  1. Abazajian, K. N., Adelman-McCarthy, J. K., Agüeros, M. A., et al. 2009, ApJS, 182, 543 [NASA ADS] [CrossRef] [Google Scholar]
  2. Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5 [NASA ADS] [CrossRef] [Google Scholar]
  3. Bell, E. F., McIntosh, D. H., Katz, N., & Weinberg, M. D. 2003, ApJS, 149, 289 [NASA ADS] [CrossRef] [Google Scholar]
  4. Bigiel, F., Leroy, A., Walter, F., et al. 2008, AJ, 136, 2846 [NASA ADS] [CrossRef] [Google Scholar]
  5. Bigiel, F., Leroy, A., Walter, F., et al. 2010, AJ, 140, 1194 [NASA ADS] [CrossRef] [Google Scholar]
  6. Boselli, A., & Gavazzi, G. 2002, A&A, 386, 124 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Boselli, A., & Gavazzi, G. 2006, PASP, 118, 517 [NASA ADS] [CrossRef] [Google Scholar]
  8. Boselli, A., Iglesias-Páramo, J., Vílchez, J. M., & Gavazzi, G. 2002, A&A, 386, 134 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  9. Boselli, A., Boissier, S., Cortese, L., et al. 2009, ApJ, 706, 1527 [NASA ADS] [CrossRef] [Google Scholar]
  10. Bothwell, M. S., Kennicutt, R. C., & Lee, J. C. 2009, MNRAS, 400, 154 [NASA ADS] [CrossRef] [Google Scholar]
  11. Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245 [NASA ADS] [CrossRef] [Google Scholar]
  12. Catinella, B., Schiminovich, D., Kauffmann, G., et al. 2010, MNRAS, 403, 683 [NASA ADS] [CrossRef] [Google Scholar]
  13. Conselice, C. J. 2003, ApJS, 147, 1 [NASA ADS] [CrossRef] [Google Scholar]
  14. Cortese, L., & Hughes, T. M. 2009, MNRAS, 400, 1225 [NASA ADS] [CrossRef] [Google Scholar]
  15. Dreyer, J. L. E. 1888, MmRAS, 49, 1 [NASA ADS] [CrossRef] [Google Scholar]
  16. Dreyer, J. L. E. 1908, MmRAS, 59, 105 [NASA ADS] [Google Scholar]
  17. Fumagalli, M., & Gavazzi, G. 2008, A&A, 490, 571 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  18. Fumagalli, M., Krumholz, M. R., Prochaska, J. X., Gavazzi, G., & Boselli, A. 2009, ApJ, 697, 1811 [NASA ADS] [CrossRef] [Google Scholar]
  19. Fumagalli, M., da Silva, R. L., & Krumholz, M. R. 2011, ApJ, 741, L26 [NASA ADS] [CrossRef] [Google Scholar]
  20. Gavazzi, G., Pierini, D., & Boselli, A. 1996, A&A, 312, 397 [NASA ADS] [Google Scholar]
  21. Gavazzi, G., Boselli, A., Scodeggio, M., Pierini, D., & Belsole, E. 1999, MNRAS, 304, 595 [NASA ADS] [CrossRef] [Google Scholar]
  22. Gavazzi, G., Boselli, A., Pedotti, P., Gallazzi, A., & Carrasco, L. 2002a, A&A, 386, 114 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  23. Gavazzi, G., Boselli, A., Pedotti, P., Gallazzi, A., & Carrasco, L. 2002b, A&A, 396, 449 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Gavazzi, G., Boselli, A., Donati, A., Franzetti, P., & Scodeggio, M. 2003, A&A, 400, 451 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  25. Gavazzi, G., Zaccardo, A., Sanvito, G., Boselli, A., & Bonfanti, C. 2004, A&A, 417, 499 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  26. Gavazzi, G., Boselli, A., Cortese, L., et al. 2006, A&A, 446, 839 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Gavazzi, G., Giovanelli, R., Haynes, M. P., et al. 2008, A&A, 482, 43 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Gavazzi, G., Fumagalli, M., Cucciati, O., & Boselli, A. 2010, A&A, 517, A73 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  29. Gavazzi, G., Savorgnan, G., & Fumagalli, M. 2011, A&A, 534, A31 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. Gavazzi, G., Fumagalli, M., Galardo, V., et al. 2012, A&A, submitted (Paper II) [Google Scholar]
  31. Giovanelli, R., Haynes, M. P., Kent, B. R., et al. 2005, AJ, 130, 2598 [NASA ADS] [CrossRef] [Google Scholar]
  32. Giovanelli, R., Haynes, M. P., Kent, B. R., et al. 2007, AJ, 133, 2569 [NASA ADS] [CrossRef] [Google Scholar]
  33. Glover, S. C. O., & Clark, P. C. 2012, MNRAS, 421, 9 [NASA ADS] [Google Scholar]
  34. Haynes, M. P., Giovanelli, R., Salzer, J. J., et al. 1999, AJ, 117, 1668 [NASA ADS] [CrossRef] [Google Scholar]
  35. Haynes, M. P., Giovanelli, R., Martin, A. M., et al. 2011, AJ, 142, 170 [NASA ADS] [CrossRef] [Google Scholar]
  36. Huang, S., Haynes, M.P., Giovanelli, R., et al. 2012a, AJ, 143, 133 [NASA ADS] [CrossRef] [Google Scholar]
  37. Huang, S., Haynes, M. P., Giovanelli, R., & Brinchmann, J. 2012b, ApJ, submitted [Google Scholar]
  38. James, P. A., Shane, N. S., Beckman, J. E., et al. 2004, A&A, 414, 23 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  39. Kapferer, W., Sluka, C., Schindler, S., Ferrari, C., & Ziegler, B. 2009, A&A, 499, 87 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  40. Kennicutt, R. C., Jr. 1989, ApJ, 344, 685 [NASA ADS] [CrossRef] [Google Scholar]
  41. Kennicutt, R. C., Jr. 1992, ApJ, 388, 310 [NASA ADS] [CrossRef] [Google Scholar]
  42. Kennicutt, R. C., Jr. 1998, ApJ, 498, 541 [NASA ADS] [CrossRef] [Google Scholar]
  43. Kennicutt, R. C., Jr., Calzetti, D., Walter, F., et al. 2007, ApJ, 671, 333 [NASA ADS] [CrossRef] [Google Scholar]
  44. Kennicutt, R. C., Jr., Lee, J. C., Funes, S. J., et al. 2008, ApJS, 178, 247 [NASA ADS] [CrossRef] [Google Scholar]
  45. Kent, B. R., Giovanelli, R., Haynes, M. P., et al. 2008, AJ, 136, 713 [NASA ADS] [CrossRef] [Google Scholar]
  46. Koopmann, R. A., & Kenney, J. D. P. 2004, ApJ, 613, 851 [NASA ADS] [CrossRef] [Google Scholar]
  47. Kronberger, T., Kapferer, W., Ferrari, C., Unterguggenberger, S., & Schindler, S. 2008, A&A, 481, 337 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  48. Krumholz, M. R., Leroy, A. K., & McKee, C. F. 2011, ApJ, 731, 25 [NASA ADS] [CrossRef] [Google Scholar]
  49. Lee, J. C., Kennicutt, R. C., Funes, S. J., et al. 2007, ApJ, 671, L113 [NASA ADS] [CrossRef] [Google Scholar]
  50. Lee, J. C., Gil de Paz, A., Tremonti, C., et al. 2009, ApJ, 706, 599 [NASA ADS] [CrossRef] [Google Scholar]
  51. Martin, A. M., Papastergis, E., Giovanelli, R., et al. 2010, ApJ, 723, 1359 [NASA ADS] [CrossRef] [Google Scholar]
  52. Mei, S., Blakeslee, J. P., Côté, P., et al. 2007, ApJ, 655, 144 [NASA ADS] [CrossRef] [Google Scholar]
  53. Meurer, G. R., Hanish, D. J., Ferguson, H. C., et al. 2006, ApJS, 165, 307 [NASA ADS] [CrossRef] [Google Scholar]
  54. Meurer, G. R., Wong, O. I., Kim, J. H., et al. 2009, ApJ, 695, 765 [NASA ADS] [CrossRef] [Google Scholar]
  55. Meyer, M. J., Zwaan, M. A., Webster, R. L., et al. 2004, MNRAS, 350, 1195 [NASA ADS] [CrossRef] [Google Scholar]
  56. Nilson, P. 1973, Acta Universitatis Upsaliensis, Nova Acta Regiae Societatis Scientiarum Upsaliensis – Uppsala Astronomiska Observatoriums Annaler, Uppsala: Astronomiska Observatorium [Google Scholar]
  57. Pflamm-Altenburg, J., Weidner, C., & Kroupa, P. 2007, ApJ, 671, 1550 [NASA ADS] [CrossRef] [Google Scholar]
  58. Rose, J. A., Robertson, P., Miner, J., & Levy, L. 2010, AJ, 139, 765 [NASA ADS] [CrossRef] [Google Scholar]
  59. Saintonge, A. 2007, AJ, 133, 2087 [NASA ADS] [CrossRef] [Google Scholar]
  60. Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525 [NASA ADS] [CrossRef] [Google Scholar]
  61. Schmidt, M. 1959, ApJ, 129, 243 [NASA ADS] [CrossRef] [Google Scholar]
  62. Schruba, A., Leroy, A. K., Walter, F., et al. 2011, AJ, 142, 37 [NASA ADS] [CrossRef] [Google Scholar]
  63. Spector, O., Finkelman, I., & Brosch, N. 2012, MNRAS, 419, 2156 [NASA ADS] [CrossRef] [Google Scholar]
  64. Tonnesen, S., & Bryan, G. L. 2009, ApJ, 694, 789 [NASA ADS] [CrossRef] [Google Scholar]
  65. Tremonti, C. A., Heckman, T. M., Kauffmann, G., et al. 2004, ApJ, 613, 898 [NASA ADS] [CrossRef] [Google Scholar]
  66. Vogt, N. P., Haynes, M. P., Giovanelli, R., & Herter, T. 2004, AJ, 127, 3300 [NASA ADS] [CrossRef] [Google Scholar]
  67. Vollmer, B., Braine, J., Pappalardo, C., & Hily-Blant, P. 2008, A&A, 491, 455 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  68. Vollmer, B., Soida, M., Chung, A., et al. 2009, A&A, 496, 669 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  69. von der Linden, A., Wild, V., Kauffmann, G., White, S. D. M., & Weinmann, S. 2010, MNRAS, 404, 1231 [NASA ADS] [Google Scholar]
  70. Weisz, D. R., Dalcanton, J. J., Williams, B. F., et al. 2011, ApJ, 739, 5 [NASA ADS] [CrossRef] [Google Scholar]
  71. Welikala, N., Connolly, A. J., Hopkins, A. M., Scranton, R., & Conti, A. 2008, ApJ, 677, 970 [NASA ADS] [CrossRef] [Google Scholar]
  72. Wong, T., & Blitz, L. 2002, ApJ, 569, 157 [NASA ADS] [CrossRef] [Google Scholar]
  73. Zwicky, F., Herzog, E., Wild, P., Karpowicz, M., & Kowal, C. T. 1968, Catalogue of galaxies and of clusters of galaxies (Pasadena: California Institute of Technology (CIT)) [Google Scholar]

Appendix A: The error budget

As mentioned in Sect. 4.1, for extended sources, the dominant source of error in the final Hα fluxes is associated with variations of the background on scales similar to the source, which depend on the quality of the flat-fielding. We measure the background in several regions comparable with the size of the galaxies and we establish that this fluctuation is on average  ~ 10% of the sky rms on the individual pixels. This error is dominant over the Poisson statistical uncertainty on the number counts. Therefore, the total uncertainty on the ON and OFF counts is proportional to the number of pixels Npixel occupied by each galaxy, as derived from the optical major and minor axes, a and b respectively (see Gavazzi et al. 2002a): An additional source of error affecting the OFF counts derives from the uncertainty on the normalization coefficient n which we estimate to be  ~ 3%, thus: (A.3)The error on the NET counts is defined as: (A.4)The error on the Hα flux finally becomes: (A.5)

(A.6)

The second term in Eq. (A.5) accounts for the uncertainty on the photometric calibration, which we estimate to be 5%.

Similarly, for the EWs, we compute the final error as: In conclusion this error budget results from several components (photometric accuracy, flat fielding), even if a systematic uncertainty on the normalization factor, as derived from the measurement of foreground stars, is the dominant source of error (Spector et al. 2011).

Appendix B: The Atlas

Images of the OFF and NET frames of galaxies with Hα observations presented in this work are given separately for 102 galaxies with substantial Hα structure in Fig. B.1; for 84 marginal detections (<2σ) or with unresolved/complex Hα emission in Fig. B.2. For the 47 remaining galaxies with no Hα emission, the OFF-band images are shown in Fig. B.3. Galaxies are labeled with their celestial coordinates. A 1 arcmin bar is given.

Table B.1

Basic data for the 235 target galaxies.

Table B.2

Hα observational specifications of the 235 target galaxies.

Table B.3

Integrated Hα photometric parameters of the 235 target galaxies.

thumbnail Fig. B.1

Atlas of 102 galaxies with substantial Hα structure, identified by their celestial coordinates. The OFF-band (left panel) and the NET frame (right panel) are given (2 objects per line). A 1 arcmin bar is given on all images.

Open with DEXTER

thumbnail Fig. B.2

Atlas of 84 marginal detections (<2σ) or with complex unresolved Hα emission, identified by their celestial coordinates (2 objects per line). The OFF-band (left panel), the NET frame (right panel) are given. A 1 arcmin bar is given on all images

Open with DEXTER

thumbnail Fig. B.3

Atlas of 47 galaxies with no Hα emission, identified by their celestial coordinates (4 objects per line). The OFF-band images are given with a 1 arcmin bar.

Open with DEXTER

Online material (Figures of Appendix B)

PDF files of Figures B.1 to B.3

Fig. B.1

(Access here)

Fig. B.2

(Access here)

Fig. B.3

(Access here)

All Tables

Table 1

Comparison between the photometry from this work and from Kennicutt et al. (2008).

Table B.1

Basic data for the 235 target galaxies.

Table B.2

Hα observational specifications of the 235 target galaxies.

Table B.3

Integrated Hα photometric parameters of the 235 target galaxies.

All Figures

thumbnail Fig. 1

Bottom panel. Sky distribution of 409 HI selected galaxies observed in the present survey, 383 with FHI > 0.7 Jy km s-1 (filled circles) and 26 with  < 0.7 Jy km s-1 (big empty circles). Red symbols refer to 233 new sources observed in 2006 − 2009 whose fluxes are presented in this paper. Top panel. 68 HI targets that matches our selection criteria but that were not observed because: 8 lie too close to bright stars; 38 are either debris of ram pressure stripped gas or their associated galaxy is too faint to be seen on SDSS plates (triangles); 20 which will be consider in future runs (crosses). The two vertical broken lines mark the adopted boundaries of the Virgo cluster.

Open with DEXTER
In the text
thumbnail Fig. 2

Comparison of the observed HI mass distribution in the three subsamples (histograms) with the HI mass function of Martin et al. (2010) (black lines) and one corrected for the overdensity in the Local Supercluster (red lines).

Open with DEXTER
In the text
thumbnail Fig. 3

Properties of the Hα3 sample, compared to that of the entire ALFALFA catalogue (dotted lines) and the subset restricted to galaxies with optical counterparts (dashed lines). Panel a) 1σ limiting surface brightness (erg cm-2 s-1 arcsec-2) in the Hα NET images. Panel b) morphological types. Panel c) stellar masses from i-band photometry. Panel d) color (g − i) magnitude (i band) diagram (color coded by morphology: red = early, blue = disk; green = bulge + disk) (SDSS magnitudes are uncorrected for internal extinction). Hα3 is a homogeneous survey, complete down to a SFR density of 3 × 10-9 M yr-1 pc-2 (1σ) and HI masses of 108 M. This sample spans a wide range in color, morphological type, colors and stellar masses, thereby allowing a comparison of the SFR over a broad parameter space.

Open with DEXTER
In the text
thumbnail Fig. 4

The transmissivity of the ON-band (6603 Å) filter. Filled circles mark the transmissivity for Hα at the redshift of the target galaxies. Two galaxies with cz = 132 and 213 km s-1 have been observed on the steep shoulder of the filter transmission curve. They will not be further considered in the analysis.

Open with DEXTER
In the text
thumbnail Fig. 5

Point source FWHM measured on the final ON-band images (solid histogram) and OFF-band images (dashed histogram). Poor telescope guiding performance and dome seeing affect the image quality, making the distribution of the seeing slightly better in the shorter OFF exposures.

Open with DEXTER
In the text
thumbnail Fig. 6

The ratio ( [NII] /Hα)ew derived from drift-scan spectra as a function of Mi, exhibiting the variation expected for the mass-metallicity relation. Red points mark AGNs. The line indicates the linear fit to the data adopted when drift-scan spectra are unavailable.

Open with DEXTER
In the text
thumbnail Fig. 7

Comparison between the Hα +  [NII]  flux extracted in 3 arcsec aperture centered on the nucleus (from this work) and the flux in the Hα +  [NII]  lines given by SDSS in 3 arcsec fibre spectrum (for detections with SN > 2). The dashed line gives the one-to-one relation.

Open with DEXTER
In the text
thumbnail Fig. 8

The corrected SFR derived from this work (see Col. 9 of Table B.3) as a function of the absolute i band magnitude Mi.

Open with DEXTER
In the text
thumbnail Fig. B.1

Atlas of 102 galaxies with substantial Hα structure, identified by their celestial coordinates. The OFF-band (left panel) and the NET frame (right panel) are given (2 objects per line). A 1 arcmin bar is given on all images.

Open with DEXTER
In the text
thumbnail Fig. B.2

Atlas of 84 marginal detections (<2σ) or with complex unresolved Hα emission, identified by their celestial coordinates (2 objects per line). The OFF-band (left panel), the NET frame (right panel) are given. A 1 arcmin bar is given on all images

Open with DEXTER
In the text
thumbnail Fig. B.3

Atlas of 47 galaxies with no Hα emission, identified by their celestial coordinates (4 objects per line). The OFF-band images are given with a 1 arcmin bar.

Open with DEXTER
In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.