ar X iv :a st ro -p h/ 02 09 39 6v 2 2 0 D ec 2 00 2 Mon. Not. R. Astron. Soc. 000, 1–17 (2002) Printed 19 January 2014 (MN LATEX style file v2.2) Stellar populations in local star-forming galaxies. I.–Data and modelling procedure. P. G. Pérez-González1, A. Gil de Paz,5,2,1 J. Zamorano,1 J. Gallego,1 A. Alonso-Herrero3 and A. Aragón-Salamanca4 1Departamento de Astrof́ısica, Facultad de F́ısicas, Universidad Complutense, E-28040 Madrid, Spain 2NASA/IPAC Extragalactic Database, California Institute of Technology, MS 100-22, Pasadena, CA 91125, USA 3Steward Observatory, The University of Arizona, Tucson AZ 85721, USA 4School of Physics and Astronomy, University of Nottingham, NG7 2RD, England 5current address: The Observatories of the Carnegie Institution of Washington, 813 Santa Barbara St., Pasadena, CA 91101, USA Received 19 January 2014 ABSTRACT We present an analysis of the integrated properties of the stellar populations in the Universidad Complutense de Madrid (UCM) Survey of Hα-selected galaxies. In this paper, the first of a series, we describe in detail the techniques developed to model star-forming galaxies using a mixture of stellar populations, and taking into account the observational uncertainties. We assume a recent burst of star formation superimposed on a more evolved population. The effects of the nebular continuum, line emission and dust attenuation are taken into account. We also test different model assumptions including the choice of specific evolutionary synthesis model, initial mass function, star formation scenario and the treatment of dust extinction. Quantitative tests are applied to determine how well these models fit our multi-wavelength obser- vations for the UCM sample. Our observations span the optical and near infrared, including both photometric and spectroscopic data. Our results indicate that extinc- tion plays a key role in this kind of studies, revealing that low- and high-obscured objects may require very different extinction laws and must be treated differently. We also demonstrate that the UCM Survey galaxies are best described by a short burst of star formation occurring within a quiescent galaxy, rather than by continu- ous star formation. A detailed discussion on the inferred parameters, such as the age, burst strength, metallicity, star formation rate, extinction and total stellar mass for individual objects, is presented in paper II of this series. Key words: mthods: data analysis – galaxies: photometry – galaxies: evolution – galaxies: stellar content – infrared: galaxies 1 INTRODUCTION One of the main issues in today’s Astrophysics is how present day galaxies formed and how they have evolved over time. A considerable observational effort is being made to study galaxies from the earliest possible times to the present. Our knowledge of the faint galaxy populations over the 0 < z < 5 range has experienced remarkable progress in a relatively short period of time (see the reviews by Ellis 1997 and Fer- guson et al. 2000). One of the main aims of these studies is to find the progenitors of the local galaxy population. While the majority of local galaxies seem to fit reasonably well into the Hubble sequence, this morphological classi- fication scheme breaks down at surprisingly low redshifts (z ∼ 0.3-0.5; see Abraham & van den Bergh 2002, and refer- ences therein). Moreover, new classes of distant objects have been discovered, such as Ultraluminous Infrared Galaxies, (Schmidt & Green 1983), Extremely Red Objects, (Yan et al. 2000) as well as bright UV galaxies (Lyman Break Galaxies, LBGs, Steidel et al. 1996, 1999). The luminosity of these ob- jects, both the reddest and the bluest, is mainly dominated by massive knots of newly-formed stars (starbursts), with different amounts of dust extinction. A complementary approach to understand how present- day galaxies came into being is to study in detail the proper- ties of local galaxies, and in particular their star-formation histories. In this respect, it is important to quantify the rel- ative importance of the current episode of star formation in comparison to the underlying older stellar populations. In- deed, even in high redshift objects, stars formed before the http://arxiv.org/abs/astro-ph/0209396v2 2 P. G. Pérez-González et al. currently-observed star formation episode must have been present in order to produce the observed metal and dust content. Examples of such high-z objects include SCUBA sources (Hughes et al. 1998) and LBGs (see Calzetti 2001 and references therein). Moreover, an accurate determina- tion of the total stellar mass in both local and distant galax- ies is a necessary step towards understanding their formation (see, e.g., Pettini et al. 1998, 2001). Our group is actively working on the detailed study of galaxies in the Local Uni- verse so that their properties can be compared with distant ones. The techniques developed and tested with local galax- ies will have direct application in high-z studies. The Universidad Complutense de Madrid (UCM) Sur- vey was carried out in order to perform a comprehen- sive study of star-forming galaxies in the Local Universe (Zamorano et al. 1994, 1996; see also Alonso et al. 1999). This Hα-selected galaxy sample has been extensively studied at optical and near infrared wavelengths (see next section). It has also been used to determine the local Hα luminos- ity function and star formation rate density (Gallego et al. 1995), providing a low-z benchmark for intermediate and high-z studies (see, for example, Iwamuro et al. 2000; Moor- wood et al. 2000; van der Werf et al. 2000; Tresse et al. 2001). Recently, the UCM Survey is being extended to higher red- shifts (Pascual et al. 2001). The present series of papers aims at determining the main properties of the stellar populations in the UCM Sur- vey galaxies, accounting both for the newly-formed stars and the underlying evolved populations. We make use of the ex- tensive multi-wavelength data available for the sample. A direct precursor of the current study was presented in Gil de Paz et al. (2000a, hereafter GdP00), where we character- ized the stellar content of a smaller subsample of 67 UCM galaxies, constraining their ages, metallicities and relative strength of the current star-formation episode. A sophisti- cated statistical technique was developed by GdP00 to com- pare measurements and model predictions. We now present results for virtually all the UCM galaxies, increasing the sample by a factor of 2.5. We have also included additional photometry in the B-band (Pérez-González et al. 2000), and use a more elaborated spectral synthesis method. The present paper will focus on the modelling technique and the observational data used to test it. We will discuss the model input parameters that best describe the observed properties of the UCM galaxies, including the initial mass function (IMF), star formation scenarios and extinction pre- scriptions. We will also study in detail how well our mod- elling techniques are able to reproduce the observations. In Pérez-González et al. (2002b, Paper II hereafter), the sec- ond paper of the series, we will present the derived properties of the UCM galaxies using these data and techniques. Pa- per II will discuss the young and newly-formed stars in the galaxies, together with the underlying population of evolved stars, the total stellar masses, etc. This paper is structured as follows: section 2 introduces the sample, the observations and the data measurements. Section 3 describes our modelling techniques, including the main features of the stellar and nebular emission models, the star formation scenarios and the extinction prescriptions. Section 4 discusses the goodness of the fits and possible cor- relations with the input data. Finally, Section 5 summarizes our conclusions. Throughout this paper we use a cosmology with H0 = 70 kms−1 Mpc−1, ΩM=0.3 and Λ=0.7. 2 DATA 2.1 The sample The UCM Survey galaxy sample contains 191 galaxies se- lected by their Hα emission at an average redshift of 0.026 (Zamorano et al. 1994, 1996; Gallego et al. 1996). Out of these galaxies, 15 were classified as active galactic nuclei (AGN, including Seyfert 1, Seyfert 2 and LINER types) by Gallego et al. (1996), and will be excluded from the present study. The rest are star-forming galaxies. Eleven of these were observed only in two photometric bands, and compar- ison with the models has not been attempted. Thus, the sample studied here contains 163 galaxies, i.e., 94% of all the star-forming galaxies in the complete UCM sample. This represents a factor of 2.5 increase over the sample studied by GdP00. The sample contains low excitation, high metallicity ob- jects (often with bright and dusty starbursts) and high ex- citation, low metallicity ones with blue star-forming knots which may sometimes dominate the optical luminosity of the whole galaxy, as in the case of Blue Compact Dwarfs— BCDs. These two global spectroscopic types will be called disk-like and HII-like galaxies, respectively. There is also a large spectrum of sizes and masses (from grand-design spi- rals to dwarfs), luminosities, emission-line equivalent widths and star formation rates (SFRs). The data required in the present work are available for 94% of the entire UCM sam- ple (excluding AGN). The galaxies studied here are thus a virtually complete sample, with no biases against any of the previously mentioned properties. The dataset used in this work comprises a great deal of observations, both photometric and spectroscopic. Most of them have already been presented in previous papers. Only near infrared (nIR) data for the whole UCM Survey has not been described before. In the next subsections we will review all these data, with special emphasis on the nIR campaigns. 2.2 Imaging 2.2.1 Optical: B- and r-bands Gunn r and Johnson B observations were obtained in several observing runs from 1989 to 2001 using 1-2 metre-class tele- scopes at the German-Spanish Observatory of Calar Alto (CAHA, Almeŕıa, Spain) and the Observatorio del Roque de los Muchachos (La Palma, Spain). The observing de- tails as well as the reduction and calibration procedures can be found in Vitores et al. (1996a,b) for the r data, and Pérez-González et al. (2000) and Pérez-González et al. (2001) for B. Briefly, the sample has average magnitudes of mB=16.1±1.1 (MB = −19.2) and mr = 15.5 ± 1.0 (Mr = −19.8), with a mean B-band effective radius of 2.8 kpc. Up to 65% of the sample galaxies are classified as Sb or later. Stellar populations in local star-forming galaxies.I.–Data and modelling procedure. 3 2.2.2 Near infrared: J- and K-bands Near infrared observations for a small subsample of 67 galax- ies were presented in GdP00. The whole sample of 191 galax- ies has now been observed in the nIR. A total number of 11 campaigns were necessary to com- plete the 191 objects. These runs were carried out from January 1996 to April 2002 in 1-2 metre-class telescopes: the 2.2m Telescope at Calar Alto Observatory (Almeŕıa, Spain), the 1m Telescope at UCO/Lick Observatory (Cali- fornia,USA) and the 2.3m Bok Telescope of the University of Arizona on Kitt Peak Observatory (Arizona, USA). Basic information on each observing run are given in Table 1. The filters used in these runs were J , K, Ks and K′. Standard reduction procedures in the nIR were applied, a description of which can be found in Aragón-Salamanca et al. (1993). Flux calibration was performed using standard stars from the lists of Elias et al. (1982); Hunt et al. (1998); Hawarden et al. (2001). For each photometric night, appropriate atmo- spheric extinction coefficients were derived and zero-points for each observing setup determined. Non-photometric data were calibrated using short exposures of the fields taken dur- ing photometric nights. The magnitudes of the 62 galaxies observed in K′ were transformed into the standard K system by applying the constant offset K′ − K=0.07 mag (Wain- scoat & Cowie 1992; Aragón-Salamanca et al. 1993). The correction from Ks to K is negligible (Persson et al. 1998). 2.3 Long-slit optical spectroscopy We use redshifts, Hα + [NII] equivalent widths (EW ), Hα/[NII] and Hα/Hβ intensity ratios, and spectroscopic types from Gallego et al. (1996). The EW (Hα + [NII]) was transformed into EW (Hα) using the observed Hα/[NII] ra- tios when available. For the 20 galaxies without measured [NII]/Hα ratios we assumed average values for the relevant spectroscopic types. Errors for the Hα equivalent width are estimated to be ≃ 20%. For 30 objects, the Hα/Hβ ratio was impossible to mea- sure due to high extinction and/or to stellar absorption lead- ing to the absence of detectable Hβ emission. In these cases, the average value of the 25% highest ratios for each spec- troscopic type has been assumed. The rationale behind this assumption is that these galaxies must have high extinctions in order to completely obliterate the Hβ emission line. The emission-line data was corrected for underlying stellar population absorption. Kurucz (1992) established that the Hα and Hβ equivalent widths are equal within a 30% uncertainty. Thus, we used a typical stellar absorption equivalent width for both Hα and Hβ of 3Å (Trager et al. 1998; González Delgado et al. 1999). Although described elsewhere (see Gallego et al. 1996 for details), we outline here the main properties of the dif- ferent spectroscopic types that will be used later in the dis- cussion and in Paper II: SBN —Starburst Nuclei— Originally defined by Balzano (1983), they show high extinction values, with very low [NII]/Hα ratios and faint [OIII]λ5007 emission. Their Hα luminosities are always higher than 108 L⊙. DANS —Dwarf Amorphous Nuclear Starburst— Intro- duced by Salzer et al. (1989), they show very similar spectro- scopic properties to SBN objects, but with Hα luminosities below 5 · 107 L⊙. HIIH —HII Hotspot— The HII Hotspot class shows similar Hα luminosities to those measured in SBN galaxies but with large [OIII]λ5007/Hβ ratios, that is, higher ionization. DHIIH —Dwarf HII Hotspot—- This is an HIIH subclass with identical spectroscopic properties but Hα luminosities lower than 5 · 107 L⊙. BCD —Blue Compact Dwarf— The lowest luminosity and highest ionization objects have been classified as Blue Com- pact Dwarf galaxies. They show in all cases Hα luminosities lower than 5 · 107 L⊙ as well as large [OIII]λ5007/Hβ and Hα/[NII]λ6584 line ratios and intense [OII]λ3727 emission. All these spectroscopic classes are usually collapsed in two main categories: disk-like and HII-like galaxies (see Guzmán et al. 1997 and Gallego 1998). The disk-like class includes SBN and DANS spectroscopic types, whereas the HII-like includes HIIH, DHIIH and BCD galaxies. 2.4 Photometry analysis Standard reduction procedures were applied to each pho- tometric dataset. The sky level was measured using ∼ 30 circular apertures of ∼ 100 pixels2 area placed at different positions around each object. The average of all the measure- ments and its standard deviation were used to determine the sky background and the related uncertainty. In order to study the integrated properties of the galax- ies, aperture photometry was obtained for each bandpass. Aiming at including the majority of the galaxy light, we used apertures with radii equal to three exponential disk scale lengths as determined in the r-band images (Vitores et al. 1996b). In the few cases when the r-band bulge-disk decomposition was not available, we used the radius of the 24 mag·arcsec2 isophote measured in the B-band (r24, Pérez- González et al. 2001). We inspected each image visually and checked that these apertures were encompassing all the de- tectable galaxy flux, and that no artifacts were disturbing the data. In a few cases we slightly decreased or increased the aperture radius in order to ensure that the measured flux was as close as possible to the total flux. The photometric apertures were centred on the peak of the galaxy light in each band. We checked that the effect of possible misalign- ments between the light peaks in the different bands was al- ways below the photometric uncertainty. We estimate that the size of this effect is always below 0.05 mag in B and r and 0.1 mag in J and K. Total K-band magnitudes were determined interac- tively as the average of the measurements inside the outer apertures where the curve of growth was flat. These fluxes were converted to absolute magnitudes and corrected for Galactic extinction using the maps published by Schlegel et al. (1998). Since the model-fitting procedure (explained in Sect. 3.5) takes into account the observational errors, we took special care in their determination. The main sources of uncertainty are photon-counting errors (described by Poisson statistics), readout noise, flat-field errors (affecting mainly the sky determination), and photometric calibration uncertainties. For a given aperture, the uncertainty due to photon-counting errors and readout noise can be written as: 4 P. G. Pérez-González et al. Table 1. Log of the nIR observation for the UCM sample. Telesc./Observ. Dates Chip Plate scale Conditions (1) (2) (3) (4) (5) Lick 1.0m Jan 9-14 1996 NICMOS3 256x256 0.57 3 photometric nights Lick 1.0m May 4-7 1996 NICMOS3 256x256 0.57 2 photometric nights Lick 1.0m Jun 7-9 1996 NICMOS3 256x256 0.57 photometric CAHA 2.2m Aug 4-6 1996 NICMOS3 256x256 0.63 photometric Bok 2.3m Jan 10-17 1998 NICMOS3 256x256 0.60 2 photometric nights Bok 2.3m Nov 01-07 1998 NICMOS3 256x256 0.60 photometric Bok 2.3m Mar 20-23 1999 NICMOS3 256x256 0.60 photometric Bok 2.3m Sep 27-30 1999 NICMOS3 256x256 0.60 rainy Bok 2.3m Nov 07-09 2000 NICMOS3 256x256 0.60 photometric Bok 2.3m Nov 29- Dec 01 2001 NICMOS3 256x256 0.60 1 photometric night Bok 2.3m Mar 30- Apr 01 2002 NICMOS3 256x256 0.60 photometric Table 1. Observing log for the nIR observations of the UCM Survey galaxies. Columns stand for: (1) Telescope name. (2) Date of the observation. (3) Detector used. (4) Scale of the chip in arcsec·pixel−1. (5) Weather conditions. σPoisson = √ (Cgal + ngal · Csky) · G + ngal · RON2 G (1) where Cgal is the number of counts coming from the galaxy, ngal the number of pixels inside the aperture, Csky the sky value in counts, and G and RON the gain and readout noise of the detector, measured in electrons/pixel and electrons, respectively. The error in the total flux arising from the determina- tion of the sky value is σskydet. = σsky · ngal (2) where σsky is the standard deviation of the sky measure- ments mentioned before. Expressing the previous uncertainties in magnitudes, we get ∆mimage = 1.0857 · √ ( σ2 Poisson + σ2 skydet. ) Cgal · √ Nim (3) where Nim is the number of images of the same object, rang- ing from 1 in the optical filters to 20-24 in the nIR ones. Finally, this quantity must be combined with the stan- dard deviation of the photometric calibration (σzero−point) to obtain the total error in the magnitudes: ∆mT = √ (∆mimage)2 + σ2 zero−point (4) Typical total errors are 0.04 mag in B, 0.03 mag in r and 0.09 mag in J and K. 2.5 Archival data At the time of writing, a total of 97 galaxies in our sample have been observed in J and K as part of the Two Micron All Sky Survey (2MASS; for details on the source identification and photometry procedures see Jarrett et al. 2000). When we compare our total magnitudes with the total magnitudes derived by the 2MASS team, we find that the 2MASS to- tal magnitudes are, on average, 0.07 mag fainter than ours both in J and K. The largest differences are mostly found in objects showing companions or field stars. This offset is Figure 1. Photometry comparison of the K band total magni- tudes for the UCM Survey galaxies included in the 2 Micron All Sky Survey, Second Incremental Release. probably due to differences in the determination of the to- tal magnitudes. Indeed, when we compare the magnitudes inside the same aperture in both the 2MASS images and in ours, we find that the average differences (weighted with the photometric errors) are 0.001 ± 0.052 mags in K and 0.003±0.038 mags in J . Fig. 1 shows the comparison in the K band. Among the 97 galaxies common to both samples, a total of 20 objects in J and 5 in K have not been imaged by us or our data are of poor quality. For these galaxies we have used the 2MASS images and determined aperture and total mag- nitudes following the procedures described in Section 2.4. These magnitudes will be used in our analysis. Stellar populations in local star-forming galaxies.I.–Data and modelling procedure. 5 Table 2. Photometric and spectroscopic data for the whole UCM sample. UCM name z mB mr mJ mK EW (Hα) 3dL (kpc) FHα FHβ AGal V MphT SpT MK (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) 0000+2140 0.0238 14.61±0.03 − 11.71±0.11 10.37±0.03 103±21 13.9 7.55 0.15 INTER HIIH −24.73 0003+2200 0.0224 17.19±0.02 16.30±0.04 14.65±0.15 13.53±0.08 38± 8 9.9 5.02 0.23 Sc+ DANS −21.47 0003+2215 0.0223 15.89±0.02 − − 11.36±0.03 25± 5 7.6 5.62 0.24 Sc+ SBN −23.62 0003+1955 0.0278 14.11±0.13 − − − 294±59 6.7 4.61 0.12 − Sy1 − 0005+1802 0.0187 16.40±0.13 − − 12.27±0.04 13± 3 6.4 3.62 0.12 Sb SBN −22.31 0006+2332 0.0159 14.95±0.05 − 12.69±0.05 11.90±0.06 58±12 8.4 4.58 0.31 Sb HIIH −22.37 0013+1942 0.0272 17.13±0.02 16.60±0.03 15.03±0.07 14.07±0.06 124±25 13.2 3.61 0.13 Sc+ HIIH −21.34 0014+1829 0.0182 16.50±0.03 15.91±0.04 14.66±0.15 13.65±0.18 131±26 5.7 9.80 0.16 Sa HIIH −21.53 0014+1748 0.0182 14.83±0.05 14.01±0.14 11.86±0.11 10.82±0.16 86±17 39.7 5.74 0.13 SBb SBN −23.71 0015+2212 0.0198 16.85±0.02 16.04±0.08 14.30±0.07 13.29±0.04 120±24 8.5 3.32 0.23 Sa HIIH −21.56 0017+1942 0.0260 15.91±0.02 15.38±0.07 14.01±0.08 13.09±0.07 100±20 18.7 4.37 0.17 Sc+ HIIH −22.29 0017+2148 0.0189 16.95±0.05 − 14.31±0.24 13.30±0.04 74±15 3.0 4.66 0.21 Sa HIIH −21.43 0018+2216 0.0169 16.95±0.02 16.15±0.03 14.22±0.07 13.39±0.05 15± 3 5.7 2.86 0.23 Sb DANS −21.08 0018+2218 0.0220 15.97±0.02 − 12.17±0.14 11.12±0.20 16± 3 10.8 9.39 0.22 Sb SBN −23.81 0019+2201 0.0191 16.80±0.02 15.82±0.04 13.96±0.04 12.96±0.05 33± 7 10.4 3.70 0.21 Sb DANS −21.69 0022+2049 0.0185 15.86±0.05 14.65±0.03 12.46±0.08 11.24±0.05 76±15 10.2 6.28 0.30 Sb HIIH −23.42 0023+1908 0.0251 16.83±0.05 − 14.66±0.31 13.83±0.07 121±24 3.2 4.08 0.19 Sc+ HIIH −21.39 0034+2119 0.0315 15.86±0.03 − − 11.84±0.07 19± 4 12.2 3.58 0.11 SBc+ SBN −23.91 0037+2226 0.0195 14.65±0.05 − 12.44±0.13 11.53±0.03 45± 9 7.7 4.19 0.13 SBc+ SBN −23.23 0038+2259 0.0464 16.39±0.05 15.61±0.04 13.84±0.26 12.99±0.04 21± 4 33.8 4.63 0.09 Sb SBN −23.60 0039+0054 0.0191 15.22±0.05 − − 11.93±0.07 23± 5 8.8 8.75 0.07 Sc+ SBN −22.74 0040+0257 0.0367 16.98±0.05 16.85±0.04 − 14.41±0.08 119±24 12.5 4.14 0.09 Sb DANS −21.64 0040+2312 0.0254 15.69±0.03 − 12.15±0.14 11.07±0.03 28± 6 12.9 8.55 0.12 Sc+ SBN −24.22 0040+0220 0.0173 17.25±0.15 16.61±0.03 15.16±0.04 14.23±0.03 77±15 4.4 3.86 0.07 Sc+ DANS −20.23 0040−0023 0.0142 13.76±0.03 − 11.15±0.10 10.35±0.07 18± 4 10.8 9.20 0.06 Sc+ LINER −23.60 0041+0134 0.0169 14.42±0.04 − − 11.46±0.08 12± 2 13.3 8.96 0.08 Sc+ SBN −22.87 0043+0245 0.0180 17.34±0.05 − − 14.30±0.08 34± 7 2.2 5.07 0.07 Sc+ HIIH −20.26 0043−0159 0.0161 13.01±0.05 − 10.79±0.01 9.70±0.07 60±12 9.8 8.03 0.09 Sc+ SBN −24.53 0044+2246 0.0253 16.06±0.15 14.90±0.08 12.54±0.07 11.47±0.05 25± 5 33.8 7.42 0.12 Sb SBN −23.78 0045+2206 0.0203 15.06±0.05 − 12.94±0.07 12.04±0.05 80±16 5.6 4.14 0.15 INTER HIIH −22.71 0047+2051 0.0577 16.98±0.05 16.14±0.03 − 13.13±0.03 73±15 20.0 4.60 0.10 Sc+ SBN −23.96 0047−0213 0.0144 15.73±0.04 14.97±0.04 13.13±0.13 12.25±0.04 40± 8 10.5 4.94 0.15 S0 DHIIH −21.94 0047+2413 0.0347 15.88±0.05 14.81±0.03 12.74±0.05 11.63±0.05 61±12 31.4 5.13 0.20 Sa SBN −24.39 0047+2414 0.0347 15.22±0.05 − 12.66±0.18 11.69±0.03 78±16 10.1 4.69 0.20 Sc+ SBN −24.28 0049−0006 0.0377 18.68±0.05 18.52±0.04 17.80±0.09 16.62±0.14 346±69 7.4 2.86 0.08 BCD BCD −19.50 0049+0017 0.0140 17.19±0.03 16.69±0.09 15.36±0.05 14.50±0.07 310±62 6.2 2.86 0.08 Sb DHIIH −19.42 0049−0045 0.0055 15.34±0.02 − 13.05±0.15 12.31±0.07 73±15 1.6 4.79 0.13 Sb HIIH −19.73 0050+0005 0.0346 16.54±0.03 16.03±0.03 − 13.68±0.07 94±19 13.1 4.50 0.08 Sa HIIH −22.31 0050+2114 0.0245 15.56±0.05 14.78±0.03 12.76±0.09 11.59±0.09 69±14 15.5 5.73 0.13 Sa SBN −23.59 0051+2430 0.0173 15.40±0.15 − 11.94±0.09 11.06±0.04 34± 7 5.7 6.12 0.15 Sa SBN −23.34 0054−0133 0.0512 16.00±0.04 − 12.99±0.13 11.80±0.07 23± 4 13.4 8.79 0.12 Sb SBN −25.02 0054+2337 0.0164 15.27±0.03 − 13.27±0.09 12.66±0.09 62±12 6.2 4.68 0.16 Sc+ HIIH −21.67 0056+0044 0.0183 16.82±0.05 16.52±0.10 15.55±0.15 14.54±0.16 399±80 17.7 3.03 0.09 Irr DHIIH −20.04 0056+0043 0.0189 16.63±0.05 16.20±0.03 − 13.88±0.07 53±11 6.8 3.81 0.09 Sb DHIIH −20.77 0119+2156 0.0583 16.66±0.29 15.46±0.10 13.31±0.05 11.93±0.04 16± 3 145.6 7.89 0.17 Sb Sy2 −25.20 0121+2137 0.0345 16.02±0.05 15.47±0.06 13.85±0.08 12.90±0.07 66±13 33.8 4.86 0.22 Sc+ SBN −23.05 0129+2109 0.0344 15.01±0.04 − 12.06±0.07 11.00±0.05 32± 6 14.4 8.41 0.19 SBc+ LINER −24.95 0134+2257 0.0353 16.03±0.05 − 12.76±0.13 11.73±0.03 26± 5 10.6 4.91 0.37 Sb SBN −24.40 0135+2242 0.0363 17.16±0.05 16.26±0.03 14.40±0.04 13.42±0.05 46± 9 14.4 6.69 0.40 S0 DANS −22.74 0138+2216 0.0591 17.71±0.03 − 14.35±0.20 13.18±0.07 10± 2 7.4 3.35 0.39 Sc+ − −24.11 0141+2220 0.0174 16.36±0.05 15.91±0.03 13.72±0.04 12.66±0.02 37± 7 9.0 4.68 0.30 Sa DANS −21.88 0142+2137 0.0362 15.35±0.05 14.25±0.05 − 11.19±0.04 29± 6 48.3 3.83 0.34 SBb Sy2 −24.98 0144+2519 0.0409 15.67±0.05 14.98±0.06 13.12±0.11 12.13±0.12 29± 6 38.2 5.66 0.42 SBc+ SBN −24.20 0147+2309 0.0194 16.88±0.05 15.99±0.04 14.56±0.05 13.62±0.06 118±24 10.8 4.34 0.32 Sa HIIH −21.05 0148+2124 0.0169 17.19±0.05 16.49±0.03 15.23±0.04 14.43±0.06 136±27 6.2 3.26 0.21 BCD BCD −20.00 0150+2032 0.0323 16.46±0.15 16.19±0.10 15.07±0.40 13.49±0.08 171±34 29.9 3.34 0.25 Sc+ HIIH −22.42 0156+2410 0.0134 15.33±0.04 14.66±0.03 13.02±0.04 12.24±0.05 40± 8 10.9 4.45 0.31 Sb DANS −21.70 0157+2413 0.0177 15.08±0.09 13.79±0.04 11.08±0.07 10.36±0.03 25± 5 30.1 5.03 0.33 Sc+ Sy2 −24.16 0157+2102 0.0106 15.01±0.04 14.58±0.03 13.01±0.04 12.31±0.05 61±12 7.6 3.89 0.29 Sb HIIH −21.10 0159+2354 0.0170 17.34±0.05 16.36±0.03 14.50±0.04 13.59±0.05 63±13 6.6 4.18 0.33 Sb HIIH −20.86 0159+2326 0.0178 16.01±0.05 14.87±0.03 12.78±0.07 11.84±0.05 28± 6 12.1 6.14 0.28 Sc+ DANS −22.82 1246+2727 0.0199 15.84±0.21 − 13.82±0.35 12.92±0.09 67±13 6.7 4.90 0.04 Irr HIIH −21.85 1247+2701 0.0231 16.76±0.09 16.12±0.03 14.49±0.03 13.69±0.05 28± 6 12.8 3.21 0.04 Sc+ DANS −21.33 6 P. G. Pérez-González et al. Table 2. continued UCM name z mB mr mJ mK EW (Hα) 3dL (kpc) FHα FHβ AGal V MphT SpT MK (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) 1248+2912 0.0217 15.09±0.17 − − 11.55±0.07 29± 6 8.0 3.99 0.06 SBb SBN −23.33 1253+2756 0.0165 16.09±0.02 15.41±0.03 13.99±0.05 13.12±0.04 114±23 6.0 2.86 0.03 Sa HIIH −21.59 1254+2740 0.0161 16.25±0.03 15.54±0.04 − − 58±12 18.5 4.28 0.04 Sa SBN − 1254+2802 0.0253 16.91±0.02 15.88±0.03 13.91±0.03 12.84±0.04 14± 3 14.7 8.78 0.04 Sc+ DANS −22.44 1255+2819 0.0273 16.10±0.12 15.33±0.03 13.63±0.05 12.66±0.05 47± 9 19.7 4.16 0.04 Sb SBN −23.10 1255+3125 0.0258 16.46±0.13 15.30±0.03 13.44±0.14 12.55±0.17 64±13 12.6 3.92 0.06 Sa HIIH −22.77 1255+2734 0.0234 16.97±0.02 16.15±0.03 − 13.33±0.06 99±20 10.6 5.44 0.04 Sc+ SBN −21.74 1256+2717 0.0273 17.93±0.13 − − 15.35±0.14 62±12 3.6 3.85 0.03 S0 DHIIH −20.04 1256+2732 0.0245 15.95±0.18 15.37±0.04 13.90±0.05 12.90±0.07 79±16 31.0 4.71 0.05 INTER SBN −22.26 1256+2701 0.0247 16.66±0.09 16.27±0.07 14.70±0.10 13.68±0.11 109±22 32.5 3.46 0.03 Sc+ HIIH −21.49 1256+2910 0.0279 16.21±0.08 15.28±0.03 13.45±0.03 12.52±0.04 25± 5 19.5 8.66 0.03 Sb SBN −23.16 1256+2823 0.0315 16.14±0.10 15.30±0.03 13.67±0.10 12.50±0.14 76±15 16.9 4.82 0.04 Sb SBN −23.35 1256+2754 0.0172 15.43±0.07 14.90±0.03 13.18±0.05 12.25±0.05 49±10 14.5 4.12 0.04 Sa SBN −22.44 1256+2722 0.0287 17.21±0.09 16.21±0.04 − 12.84±0.06 26± 5 14.3 5.10 0.04 Sc+ DANS −22.66 1257+2808 0.0171 16.38±0.02 15.66±0.03 14.26±0.32 12.91±0.29 29± 6 7.2 5.57 0.03 Sb SBN −21.48 1258+2754 0.0253 16.02±0.09 15.58±0.07 − 13.22±0.08 101±20 17.5 6.01 0.03 Sb SBN −22.06 1259+2934 0.0239 13.99±0.09 12.85±0.03 10.78±0.05 9.78±0.04 148±30 43.3 7.75 0.04 Sb Sy2 −25.37 1259+3011 0.0307 16.25±0.09 15.40±0.03 13.56±0.13 12.57±0.14 22± 4 36.5 3.50 0.04 Sa SBN −23.08 1259+2755 0.0240 15.57±0.04 14.61±0.03 13.08±0.12 11.97±0.13 44± 9 17.2 5.22 0.03 Sa SBN −23.25 1300+2907 0.0219 17.27±0.09 16.86±0.03 − 14.75±0.10 94±19 9.7 5.10 0.04 Sa HIIH −20.16 1301+2904 0.0266 15.97±0.10 15.57±0.03 14.07±0.05 13.39±0.06 69±14 16.1 3.13 0.04 Sb HIIH −22.03 1302+2853 0.0237 16.50±0.02 15.99±0.03 14.26±0.14 13.43±0.19 40± 8 10.1 4.07 0.04 Sb DHIIH −22.24 1302+3032 0.0342 16.66±0.07 − 14.85±0.45 13.95±0.07 49±10 6.2 4.09 0.04 Sa HIIH −21.97 1303+2908 0.0261 16.82±0.10 16.28±0.03 15.27±0.06 14.31±0.08 165±33 17.5 2.86 0.04 Irr HIIH −20.99 1304+2808 0.0210 16.02±0.11 15.03±0.03 13.37±0.13 12.03±0.14 24± 5 18.9 2.86 0.04 Sb SBN −22.83 1304+2830 0.0217 18.62±0.04 18.09±0.03 − 15.43±0.09 56±11 4.7 3.57 0.04 BCD DHIIH −19.45 1304+2907 0.0159 15.16±0.24 14.61±0.08 − 12.55±0.10 8± 2 28.6 8.96 0.04 Irr − −21.64 1304+2818 0.0244 15.88±0.02 15.06±0.03 13.58±0.06 12.50±0.08 80±16 18.5 2.97 0.05 Sc+ SBN −22.72 1306+2938 0.0209 15.59±0.03 15.09±0.03 13.60±0.05 12.37±0.06 100±20 10.6 3.93 0.04 SBb SBN −22.73 1306+3111 0.0168 16.44±0.02 15.54±0.03 13.85±0.08 13.11±0.07 61±12 7.1 6.52 0.04 Sc+ DANS −21.26 1307+2910 0.0187 14.25±0.03 13.22±0.05 11.59±0.35 10.33±0.29 25± 5 37.7 4.70 0.03 SBb SBN −24.22 1308+2958 0.0212 15.36±0.02 14.53±0.04 12.71±0.08 11.94±0.15 21± 4 27.1 5.63 0.04 Sc+ SBN −22.89 1308+2950 0.0242 14.91±0.13 13.90±0.04 11.83±0.11 10.77±0.18 37± 7 49.3 8.84 0.04 SBb SBN −24.36 1310+3027 0.0234 16.70±0.09 15.80±0.03 13.74±0.07 12.86±0.05 70±14 14.6 7.27 0.04 Sb DANS −22.33 1312+3040 0.0233 15.71±0.09 14.80±0.03 12.94±0.05 11.74±0.07 53±11 16.6 3.82 0.04 Sa SBN −23.36 1312+2954 0.0230 16.20±0.09 15.24±0.03 13.27±0.14 12.44±0.34 44± 9 19.4 7.07 0.04 Sc+ SBN −22.82 1313+2938 0.0380 16.93±0.09 16.56±0.03 15.45±0.06 14.67±0.07 311±62 8.9 2.86 0.03 Sa HIIH −21.74 1314+2827 0.0253 16.39±0.03 15.72±0.04 − 13.12±0.06 48±10 10.1 4.62 0.04 Sa SBN −22.30 1320+2727 0.0247 17.51±0.13 17.08±0.03 − 14.86±0.08 52±10 7.9 2.98 0.06 Sb DHIIH −20.39 1324+2926 0.0172 18.09±0.13 17.24±0.03 15.92±0.03 15.07±0.05 236±47 3.5 2.86 0.04 BCD BCD −19.49 1324+2651 0.0249 15.20±0.13 14.56±0.03 13.01±0.03 11.89±0.04 75±15 19.0 4.74 0.04 INTER SBN −23.37 1331+2900 0.0356 19.11±0.13 18.62±0.03 − 17.29±0.26 549±110 5.9 2.86 0.04 BCD BCD −18.70 1428+2727 0.0149 15.03±0.02 14.56±0.03 13.73±0.12 12.83±0.14 182±36 9.6 3.18 0.05 Irr HIIH −21.59 1429+2645 0.0328 17.89±0.03 17.12±0.03 15.61±0.06 14.70±0.07 87±17 10.3 2.89 0.06 Sb DHIIH −21.24 1430+2947 0.0290 16.53±0.11 15.92±0.03 14.47±0.06 13.57±0.09 132±26 20.9 3.69 0.06 S0 HIIH −22.01 1431+2854 0.0310 15.76±0.05 14.98±0.03 13.36±0.06 12.45±0.06 26± 5 15.3 8.60 0.06 Sb SBN −23.34 1431+2702 0.0384 17.31±0.02 16.76±0.03 15.10±0.08 14.13±0.04 134±27 8.6 3.50 0.06 Sa HIIH −22.18 1431+2947 0.0219 17.92±0.06 17.53±0.03 − 15.76±0.17 131±26 9.7 2.86 0.05 BCD BCD −19.16 1431+2814 0.0320 17.02±0.05 15.95±0.03 13.84±0.04 12.87±0.07 19± 4 16.0 8.29 0.07 Sb DANS −22.91 1432+2645 0.0307 15.40±0.03 14.60±0.03 12.88±0.13 11.78±0.18 34± 7 42.2 4.88 0.09 SBb SBN −23.87 1440+2521N 0.0315 16.85±0.02 15.85±0.03 13.69±0.32 12.63±0.28 54±11 16.7 5.30 0.11 Sb SBN −23.21 1440+2511 0.0333 16.80±0.06 15.89±0.04 14.18±0.09 12.84±0.25 23± 5 28.7 5.02 0.12 Sb SBN −23.00 1440+2521S 0.0314 17.12±0.02 16.37±0.04 14.53±0.33 13.41±0.29 83±17 13.4 3.47 0.11 Sb SBN −22.52 1442+2845 0.0110 15.53±0.02 14.85±0.03 12.97±0.10 11.90±0.09 81±16 8.2 4.82 0.07 Sb SBN −21.67 1443+2714 0.0290 16.15±0.03 15.13±0.06 13.26±0.03 11.93±0.03 102±20 12.9 7.22 0.08 Sa Sy2 −23.79 1443+2844 0.0307 15.71±0.02 14.96±0.03 13.19±0.03 12.19±0.05 74±15 23.0 7.95 0.08 SBc+ SBN −23.52 1443+2548 0.0358 15.88±0.05 15.29±0.03 13.67±0.36 12.62±0.25 57±11 20.4 5.02 0.12 Sc+ SBN −23.45 1444+2923 0.0281 16.41±0.07 15.74±0.03 14.53±0.15 13.56±0.23 22± 4 49.2 3.90 0.06 S0 DANS −21.90 1452+2754 0.0339 16.49±0.03 15.54±0.04 13.09±0.36 12.10±0.25 77±15 18.0 3.80 0.10 Sb SBN −23.90 1506+1922 0.0205 16.07±0.04 15.01±0.04 12.90±0.37 11.97±0.26 78±16 19.5 3.91 0.14 Sb HIIH −23.00 1513+2012 0.0369 16.27±0.03 15.30±0.03 13.56±0.03 12.33±0.06 109±22 14.5 4.56 0.12 Sa SBN −24.05 1537+2506N 0.0229 15.21±0.02 14.30±0.03 12.24±0.07 11.27±0.07 113±22 27.2 3.90 0.15 SBb HIIH −23.75 1537+2506S 0.0229 16.41±0.02 15.66±0.03 13.82±0.06 12.80±0.06 151±30 9.5 3.46 0.15 SBa HIIH −22.29 Stellar populations in local star-forming galaxies.I.–Data and modelling procedure. 7 Table 2. continued UCM name z mB mr mJ mK EW (Hα) 3dL (kpc) FHα FHβ AGal V MphT SpT MK (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) 1557+1423 0.0375 16.89±0.03 15.91±0.03 14.05±0.08 12.98±0.06 40± 8 16.3 3.58 0.17 Sb SBN −23.20 1612+1308 0.0114 18.66±0.02 17.75±0.03 16.88±0.06 15.97±0.18 510±102 2.5 2.89 0.16 BCD BCD −17.64 1646+2725 0.0339 18.42±0.03 17.90±0.07 16.32±0.09 15.36±0.12 214±43 11.9 3.70 0.29 Sc+ DHIIH −20.81 1647+2950 0.0290 15.59±0.03 14.88±0.03 12.97±0.32 12.11±0.29 75±15 19.4 5.25 0.16 Sc+ SBN −23.47 1647+2729 0.0366 16.07±0.11 15.37±0.03 13.45±0.08 12.35±0.05 45± 9 20.7 5.45 0.26 Sb SBN −23.76 1647+2727 0.0369 16.10±0.05 16.57±0.03 14.91±0.04 13.95±0.06 56±11 7.2 4.76 0.28 Sb SBN −22.33 1648+2855 0.0308 15.69±0.03 15.17±0.03 13.95±0.04 12.78±0.08 203±41 12.8 3.38 0.17 Sa HIIH −23.06 1653+2644 0.0346 14.88±0.03 − 11.91±0.04 10.93±0.06 6± 1 14.2 10.17 0.24 INTER SBN −25.03 1654+2812 0.0348 18.25±0.12 17.43±0.04 15.91±0.11 15.07±0.15 61±12 16.8 3.53 0.20 Sc+ DHIIH −20.98 1655+2755 0.0349 15.72±0.03 14.35±0.04 12.22±0.05 11.32±0.06 46± 9 51.5 4.55 0.21 Sc+ Sy2 −24.63 1656+2744 0.0330 17.73±0.02 16.45±0.20 14.50±0.11 13.25±0.08 69±14 12.1 4.51 0.33 Sa SBN −22.71 1657+2901 0.0317 17.32±0.02 16.62±0.03 15.00±0.06 13.68±0.06 59±12 8.7 4.29 0.14 Sb DANS −22.31 1659+2928 0.0369 15.78±0.05 14.78±0.04 12.80±0.07 11.73±0.08 154±31 71.2 4.23 0.16 SB0 Sy1 −24.36 1701+3131 0.0345 15.33±0.02 13.70±0.03 12.46±0.06 11.48±0.07 45± 9 43.7 9.89 0.10 S0 Sy1 −24.46 2238+2308 0.0236 14.86±0.05 13.98±0.03 12.10±0.07 11.05±0.06 50±10 28.7 6.42 0.20 Sa(r) SBN −24.05 2239+1959 0.0237 15.05±0.01 14.26±0.03 12.57±0.07 11.48±0.04 118±24 17.8 4.65 0.16 S0 HIIH −23.66 2249+2149 0.0462 16.03±0.02 14.81±0.03 12.53±0.04 11.71±0.05 6± 1 45.2 8.96 0.28 Sb SBN −24.88 2250+2427 0.0421 15.40±0.02 14.82±0.03 12.95±0.07 11.67±0.04 138±28 39.5 5.19 0.49 Sa SBN −24.77 2251+2352 0.0267 16.62±0.01 15.95±0.03 14.40±0.07 13.37±0.04 68±14 7.4 3.05 0.23 Sc+ DANS −22.18 2253+2219 0.0242 16.31±0.01 15.61±0.03 13.59±0.07 12.42±0.04 63±13 9.4 4.25 0.18 Sa SBN −22.82 2255+1930S 0.0192 16.20±0.01 15.66±0.03 13.80±0.07 12.75±0.04 47± 9 7.4 3.93 0.19 Sb SBN −21.97 2255+1930N 0.0189 15.92±0.01 14.83±0.03 12.84±0.07 11.68±0.04 68±14 13.6 5.30 0.19 Sb SBN −22.99 2255+1926 0.0193 17.03±0.02 16.33±0.05 14.82±0.09 13.91±0.08 34± 7 13.8 3.13 0.18 Sb HIIH −21.03 2255+1654 0.0388 16.72±0.03 15.32±0.09 13.01±0.08 11.53±0.05 27± 5 37.7 4.05 0.19 Sc+ SBN −24.70 2256+2001 0.0193 15.69±0.04 14.64±0.04 12.86±0.05 12.05±0.09 14± 3 29.6 9.60 0.14 Sc+ DANS −22.58 2257+2438 0.0345 15.57±0.05 15.82±0.08 13.51±0.05 12.08±0.05 347±69 22.5 5.21 0.51 S0 Sy1 −23.89 2257+1606 0.0339 16.49±0.13 − 13.52±0.04 12.43±0.05 21± 4 5.7 4.05 0.22 S0 SBN −23.52 2258+1920 0.0220 15.79±0.03 15.57±0.03 13.51±0.08 12.51±0.05 144±29 12.1 3.42 0.21 Sc+ DANS −22.64 2300+2015 0.0346 16.83±0.03 15.93±0.03 13.87±0.08 12.75±0.05 63±13 15.8 5.29 0.56 Sb SBN −23.33 2302+2053W 0.0328 18.04±0.06 17.12±0.05 15.37±0.08 14.34±0.06 206±41 13.1 4.47 1.15 Sb HIIH −21.67 2302+2053E 0.0328 15.85±0.05 14.58±0.03 12.81±0.08 11.64±0.05 26± 5 20.2 6.73 1.14 Sb SBN −24.39 2303+1856 0.0276 16.12±0.03 15.06±0.04 12.58±0.11 11.40±0.08 47± 9 15.3 7.95 0.42 Sa SBN −24.17 2303+1702 0.0428 17.35±0.05 16.29±0.03 14.39±0.27 13.35±0.04 44± 9 20.1 3.88 0.32 Sc+ Sy2 −23.12 2304+1640 0.0179 17.89±0.03 17.31±0.04 16.08±0.11 15.09±0.10 151±30 6.5 3.78 0.36 BCD BCD −19.57 2304+1621 0.0384 17.14±0.03 15.42±0.04 14.04±0.26 13.04±0.04 48±10 7.7 3.77 0.42 Sa DANS −23.15 2307+1947 0.0271 16.94±0.03 15.94±0.08 13.77±0.11 12.57±0.08 30± 6 10.6 3.49 0.71 Sb DANS −23.08 2310+1800 0.0363 16.89±0.03 15.83±0.03 13.55±0.11 12.32±0.08 41± 8 18.6 5.81 0.56 Sb SBN −23.93 2312+2204 0.0327 17.14±0.04 − − 13.10±0.03 47± 9 5.4 5.51 0.67 Sa SBN −22.83 2313+1841 0.0300 17.19±0.09 16.25±0.03 14.28±0.11 13.09±0.10 60±12 15.8 6.15 0.42 Sb SBN −22.59 2313+2517 0.0273 15.00±0.03 − 11.78±0.04 10.51±0.04 28± 6 12.9 6.21 0.28 Sa SBN −24.96 2315+1923 0.0385 17.55±0.03 16.98±0.03 15.50±0.06 14.65±0.07 164±33 14.9 4.62 0.23 Sb HIIH −21.54 2316+2457 0.0277 14.62±0.03 13.63±0.06 11.72±0.11 10.49±0.08 35± 7 24.6 4.85 0.34 SBa SBN −25.05 2316+2459 0.0274 16.13±0.04 15.13±0.04 12.91±0.11 11.91±0.09 33± 7 26.6 7.72 0.34 Sc+ SBN −23.58 2316+2028 0.0263 17.11±0.03 16.85±0.03 14.08±0.11 12.94±0.09 82±16 9.2 5.59 0.49 Sa DANS −22.61 2317+2356 0.0334 14.16±0.10 13.35±0.03 11.43±0.04 10.55±0.05 28± 6 36.2 8.54 0.25 Sa SBN −25.35 2319+2234 0.0364 16.80±0.05 16.55±0.03 13.98±0.11 12.85±0.08 81±16 17.6 4.85 0.20 Sb SBN −23.25 2319+2243 0.0313 15.82±0.10 14.76±0.03 12.78±0.05 11.77±0.04 34± 7 26.3 8.37 0.23 S0 SBN −23.94 2320+2428 0.0328 15.89±0.05 14.60±0.03 12.33±0.04 11.08±0.02 9± 2 28.9 9.27 0.21 Sa DANS −24.79 2321+2149 0.0374 16.66±0.04 16.02±0.03 14.28±0.11 13.30±0.08 53±11 17.9 4.20 0.22 Sc+ SBN −22.91 2321+2506 0.0331 15.79±0.04 15.33±0.04 13.70±0.05 12.73±0.06 43± 9 25.2 10.32 0.17 Sc+ SBN −23.10 2322+2218 0.0249 17.77±0.02 16.59±0.08 14.39±0.04 13.25±0.02 41± 8 10.0 5.70 0.15 Sc+ SBN −22.02 2324+2448 0.0123 13.59±0.04 12.80±0.03 10.52±0.11 9.54±0.08 9± 2 20.3 4.57 0.23 Sb SBN −24.16 2325+2318 0.0114 13.28±0.04 − − 10.55±0.04 87±17 8.7 4.21 0.14 INTER HIIH −22.93 2325+2208 0.0116 12.59±0.05 11.81±0.04 10.16±0.08 9.06±0.07 36± 7 47.4 9.43 0.16 SBc+ SBN −24.45 2326+2435 0.0174 16.61±0.02 16.03±0.03 14.61±0.06 13.77±0.09 211±42 12.5 3.66 0.33 Sb DHIIH −20.70 2327+2515N 0.0206 15.79±0.03 15.45±0.03 14.14±0.10 13.24±0.12 94±19 9.1 3.71 0.20 Sb HIIH −21.65 2327+2515S 0.0206 15.80±0.03 15.23±0.03 13.95±0.10 13.06±0.13 257±51 11.7 4.56 0.20 S0 HIIH −21.88 2329+2427 0.0200 15.92±0.05 14.68±0.03 12.62±0.05 11.51±0.03 13± 3 23.4 9.87 0.30 Sb DANS −23.23 2329+2500 0.0305 16.11±0.04 15.28±0.04 13.24±0.18 12.20±0.04 180±36 26.5 4.54 0.22 S0(r) Sy1 −23.49 2329+2512 0.0133 16.88±0.02 16.28±0.03 14.78±0.04 14.08±0.05 58±12 4.9 3.81 0.15 Sa DHIIH −19.78 2331+2214 0.0352 17.75±0.04 16.57±0.03 14.67±0.04 13.59±0.04 60±12 12.8 5.82 0.20 Sb SBN −22.38 2333+2248 0.0399 16.97±0.03 16.31±0.08 14.70±0.06 13.74±1.23 177±36 56.6 4.08 0.22 Sc+ HIIH −22.51 2333+2359 0.0395 17.20±0.04 16.02±0.03 14.03±0.14 12.79±0.03 51±10 13.3 3.45 0.26 S0a Sy1 −23.59 8 P. G. Pérez-González et al. Table 2. continued UCM name z mB mr mJ mK EW (Hα) 3dL (kpc) FHα FHβ AGal V MphT SpT MK (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) 2348+2407 0.0359 17.09±0.04 16.43±0.03 14.61±0.05 13.60±0.05 56±11 21.5 4.10 0.22 Sa SBN −22.46 2351+2321 0.0273 17.77±0.02 16.44±0.05 14.94±0.07 13.94±0.06 92±18 16.6 2.86 0.31 Sb HIIH −21.51 Table 2. Photometric and spectroscopic data for the 191 UCM Survey galaxies. Columns stand for: (1) UCM name established in Zamorano et al. (1994, 1996). (2) Redshift (Gallego et al. 1996). (3)−(6) Johnson B, Gunn r, J and K magnitudes and errors at three disk−scales measured in r. (7) Hα equivalent width (Gallego et al. 1996). (8) Disk scale (as explained in the main text) in kpc. (9) Intensity ratio between the Hα and Hβ lines corrected for stellar absorption (see text). (10) Galactic V −band extinction (Schlegel et al. 1998). (11) Morphological type (Pérez-González et al. 2001). (12) Spectroscopic type (Gallego et al. 1996). (13) Absolute K−band magnitude corrected for Galactic extinction. 2.6 Summary of available data Table 2 contains all the data described in this section. It includes object names, redshifts, magnitudes, and errors in the four photometric bands, together with Hα equivalent widths and uncertainties, radii of the apertures used in the photometric measurements, Hα/Hβ intensity ratios, Galac- tic extinction values in the V band, morphological and spec- troscopic types and total absolute K magnitudes. Before attempting the comparison with the models, the BrJK magnitudes listed in Table 2 were corrected for Galactic extinction using the maps of Schlegel et al. (1998) and the extinction curve of Cardelli et al. (1989). We also applied k-corrections given by Fioc & Rocca-Volmerange (1999) for BJK and Fukugita et al. (1995) for Gunn-r, tak- ing into account the morphological types. The k-corrections applied are, in any case, small because of the low redshifts of the galaxies in the sample (z < 0.045). The k-corrections are (in absolute value) smaller than 0.22 in B, 0.04 in r, 0.03 in J and 0.13 in K. Note that the nIR k-corrections are negative. 3 MODELS 3.1 Underlying stellar population In our models, we have assumed that our observational data (B−r, r−J , and J−K colours, and EW (Hα)) can be repro- duced by an underlying stellar population with colours and mass-to-light ratios in the K-band (M/LK hereafter) similar to those of typical spiral and lenticular galaxies of the same morphological type on top of which a recent burst of star for- mation is superimposed. This assumption represents a sig- nificant improvement with respect to GdP00 where the same underlying population colours and M/LK were assumed for the entire sample. We have also considered typical values for the EW of the Hα emission-line in ‘normal’ spirals (Davidge 1992; Kennicutt 1983). This fact means that our modelling will refer to the properties of a recent star formation event which takes place in excess of what is typical in a normal spiral or lenticular galaxy. In Table 3 we give the typical B− r (Fukugita et al. 1995), r−J , and J −K colours (Fioc & Rocca-Volmerange 1999), EW (Hα), and M/LK for each morphological type. The M/LK values have been derived separately for each galaxy type and IMF using a relation between the B − r color and the M/LK (see Bell & de Jong 2000, 2001) for the Bruzual & Charlot (private communi- cation; BC99 hereafter) exponential star formation models with different τ parameters, a formation age of 12Gyr, and a mean attenuation in the V -band of τV,ISM = 0.5 mag. With regard to the Blue Compact Dwarf galaxies there is a significant lack of studies providing information about the optical and nIR properties of their underlying stellar population. Despite of the recent efforts, both at optical (Cairós et al. 2001) and nIR wavelengths (Doublier et al. 2001), very few objects have been studied simultaneously within the wavelength range defined by the B and K bands. A noteworthy exception is the work of Gil de Paz et al. (2000b,c) on the BCD galaxy Mrk 86 where deep surface photometry was obtained in all BV RJHK bands. It is im- portant to note that this galaxy is a prototype of the iE BCDs (Loose & Thuan 1985), the most numerous BCD sub- class (Papaderos et al. 1996; Cairós et al. 2001). Moreover, the B −R and J −K colours of the underlying stellar pop- ulation in Mrk 86 (B −R=1.2; J −K=1.1; see Table 3) are very similar to the average values derived by Cairós et al. (2001), B − R=1.1, and Doublier et al. (2001), J − K=1.0. The standard deviations of these mean values are 0.2 mag in both cases. Although there are no galaxies in our sample morpho- logically classified as ellipticals, we also give the typical colours of this type for the sake of completeness. These un- derlying population colours are quite similar to our mea- surements in the outer parts of some randomly selected test galaxies (Pérez-González et al. 2002a). Because the detection limit in EW (Hα) for the UCM Survey is about 20 Å (Gallego et al. 1995), even late-type spirals galaxies in the sample must have, or have recently had, enhanced star formation compared to their ‘relaxed’ counterparts in order to have been detected in the UCM Survey photographic plates. The primary goal of this paper will be the characterization of this star formation activity. 3.2 Recent star formation In order to reproduce the observational properties of the sample we have generated a complete set of models that as- sume a recent/ongoing episode of star formation that takes place in galaxies with the underlying stellar population de- scribed above. For the stellar continuum of the newly-formed Stellar populations in local star-forming galaxies.I.–Data and modelling procedure. 9 Table 3. Assumed properties of the underlying stellar popula- tions. Type1 (B − r)2 (r − J)3 (J − K)4 EW 5 M/LK (Å) SALP6 SCA7 MSCA8 E 1.15 1.90 0.91 0 1.24 0.65 0.55 S0 0.98 2.03 0.94 -2 1.01 0.57 0.43 Sa 0.92 1.92 1.01 0 0.95 0.54 0.40 Sb 0.69 2.07 1.01 8 0.73 0.45 0.30 Sc+ 0.61 1.91 0.93 15 0.67 0.42 0.27 Irr 0.61 1.62 0.93 18 0.67 0.42 0.27 BCD 0.83 1.77 1.06 -2 0.86 0.51 0.36 Table 3. Main properties of the underlying population assumed in our models as a function of Hubble type (column 1). B − r, r − J , J − K colours (columns 2,3 and 4), Hα equivalent width (column 5; minus sign means absorption) and mass-to-light ratio in the K-band for different IMFs (Salpeter, Scalo and Miller-Scalo in columns 6,7 and 8, respectively). stars, we use the predictions given by two different evolu- tionary synthesis models developed by BC99 and Leitherer et al. (1999, SB99 hereafter). Each of them allows to choose different star formation histories, IMFs and metallicities. From the number of Lyman photons predicted by these models, we have computed the nebular continuum contribution using the emission and recombination coeffi- cients given by Ferland (1980) for Te = 104 K. For the Balmer, Paschen, and Brackett hydrogen recombination- lines, luminosities (and the corresponding equivalent widths) have been derived assuming the relation given by Brock- lehurst (1971) and the theoretical line-ratios expected for a low density gas (ne = 102 cm−3) with Te = 104 K in Case B recombination (Osterbrock 1989). Our values of the nebular continuum luminosity are systematically a ∼ 15% larger than the ones given by the SB99 models, probably due to differences in the assumed emission co- efficients. The contribution of the most intense forbidden emission-lines ([OII]λλ3726, 3729 Å, [OIII]λλ4959, 5007 Å, [NII]λλ6548, 6583 Å, [SII]λλ6717, 6731 Å) to the bandpasses under study has been also determined assuming the mean line ratios given by Gallego et al. (1996) for the sample. Following a complementary method, Charlot & Longhetti (2001) have calculated all these line intensities using a pho- toionization code in order to establish stronger constrains on the inferred star formation rates. We have decided not to follow their approach since it would introduce more model- dependent parameters and complicate the interpretation of the results. The predictions for the young and underlying stellar populations have been combined using the ratio between the stellar mass of the young stellar population over the total stellar mass of the galaxy (i.e., the burst strength, b) as a parameter. 3.3 Recent star formation vs. old stellar population Fig. 2 depicts the relative importance of the three sources of galaxy light considered in our models: young stars formed in a recent burst, gas (continuum spectrum plus emission Figure 2. Comparison of the relative contribution of the older and younger populations and the gas to the total flux of our modelled galaxies as a function of wavelength. The four photo- metric broad bands available for the UCM sample are marked. Three cases are considered for an Sb galaxy experiencing a recent (5 Myr) instantaneous burst with solar metallicity and strengths 0.1%, 1% and 10% of the total stellar mass of the galaxy. lines) and the underlying evolved population. Each of the panels displays the contribution of these sources to the total spectral energy distribution of a typical Sb galaxy (whose colours are given in Table 3), the most frequent Hubble type in the UCM sample. This galaxy is experiencing a recent instantaneous burst with a typical age of ∼ 5Myr (cf. Paper II) and solar metallicity. Three burst strengths have been considered: 0.1%, 1% and 10% of the total stellar mass. The four photometric bands available for our sample (BrJK) are marked. This figure shows how important a recent burst of star formation can be on the luminosity of a galaxy. A moderate burst of 1% of the total mass clearly dominates the blue op- tical spectrum. At longer wavelengths, although the effect is reduced, the young stellar population accounts for ∼ 10% of the K-band luminosity. For a stronger burst (b = 10%) the recent star formation contributes with more than 80% of the B-band light, and half of the total K-band luminosity. This illustrates the need of a careful analysis of the star formation history when determining stellar masses using optical pho- tometry, and, to a lesser extent, nIR data. We will come back to this issue in Paper II. We also remark the importance of 10 P. G. Pérez-González et al. the gaseous contribution, mostly at optical wavelengths (for a more detailed discussion see Krüger et al. 1995). 3.4 Dust attenuation Instead of correcting our observational data for internal ex- tinction, we decided to implement the reddening correction in our models when predicting the optical-nIR colours and EW (Hα). In order to do so we have applied two alterna- tive recipes, the one given by Charlot & Fall (2000, CF00 hereafter), and the one presented by Calzetti et al. (2000, CALZ00 from now on). These recipes cope with three dis- tinct problems: (1) the extinction law, i.e., the wavelength dependence of the attenuation; (2) the differences between the attenuation of the gas and the stellar emission; and (3) the translation of these recipes into observables such as the colour excess calculated with the Balmer decrement. In the case of the CF00 recipe we used the attenuation curve parametrized by CALZ00 instead of that given by these authors. Although both attenuation curves are able to reproduce the observational properties of starburst galaxies in the UV-optical range, the one used in CF00 leads to unrealistically low optical-to-nIR colour excesses. In Fig. 3 we show the attenuation curves of CALZ00 (solid line), CF00 (dashed-line), and the Galactic extinction curve (Cardelli et al. 1989) for total-to-selective extinction ratios (RV ) of 3.1 (dotted-line) and 5.0 (dash-dotted). This figure shows the attenuation law given by CF00 for burst ages younger than 107 years, i.e., with power-law index n = −0.7. We have not considered the effect of the finite lifetimes of the birth clouds (explained in CF00) since the bursts in the UCM galaxies are rather young (cf. Paper II). CF00 ’s law is ‘too grey’ at wavelengths longer than the r-band. Therefore, we used the CALZ00 attenuation curve also for the CF00 extinction recipe. This means that both recipes only differ in how they relate the colour excess to the extinction of the ionized gas, and this to the attenuation of the stellar continuum. Each one of these issues are explained below. The CF00 recipe states that the stars in the burst are embedded in a gaseous cloud with two layers, an internal HII region and a more external HI envelope. This is immersed in the galaxy inter-stellar medium. Given this scenario, CF00 introduce a formulation for the attenuation of the different components. Following their notation, the attenuation of the ionized-gas emission can be written as (1− f)× τBC + τISM, where τBC is the attenuation in the birth cloud associated with the burst (τBC = τHI + τHII), τISM is the attenuation due to the ISM, and f is the fraction of the attenuation in the birth cloud due to the HII region (i.e. f = τHII/τBC). Therefore, since the attenuation of the ionized-gas emis- sion is known from the Hα/Hβ Balmer decrements given by Gallego et al. (1996) we can estimate the burst (τBC + τISM) and underlying stellar populations attenuations (τISM) for a given f and τV,ISM. This method also deals with the extinc- tion of the emission-line flux. We have assumed f = 0.1 and τV,ISM = 0.5, following CF00. In the cases where the calcu- lated τBC is incompatible with the measured E(B − V )gas, the former was set to zero. The extinction recipe given in CALZ00 is empirical. It is based on the comparison of fluxes in the UV and optical ranges for nearby starburst galaxies. It considers that the stellar continuum flux is affected by an effective extinction characterized by E(B − V )continuum, which directly relates to the measurable gas attenuation E(B − V )gas via: E(B − V )continuum = 0.44 · E(B − V )gas (5) The recipe also includes the average attenuation law given in Fig. 3. 3.5 Fitting procedure In our analysis several ‘parameters’ must be selected a pri- ori. These are: – The evolutionary synthesis model: BC99 or SB99. – The star-forming mode of the youngest stellar popula- tion: instantaneous or continuous star formation rate. These modes will be referred to as INST and CONS. – The IMF: Salpeter (1955), Scalo (1986), or Miller & Scalo (1979). In all cases, we use Mlow = 0.1M⊙ and Mup = 100M⊙ for the lower and upper mass limits of the IMF. – The extinction recipe: CF00 or CALZ00. Once these have been fixed, the method leaves 3 free parameters describing the newly-formed stars: (1) the age (from 0.89 to 100 Myr); (2) metallicity of the burst (1/5 Z⊙, 2/5 Z⊙, Z⊙, 2.5 Z⊙, 5 Z⊙), and (3) the burst strength (from 0.01% to 100%). The best-fitting model for each galaxy in the sample was derived using the method described in Gil de Paz & Madore (2002). Briefly, this procedure reproduces the Gaus- sian probability distributions associated with the observa- tional errors in B − r, r − J , J − K, and 2.5 · log[EW (Hα)] using Monte Carlo simulations with a total of 1000 test ‘par- ticles’. Comparing these particles with our models for the range of parameters given above, we obtain a total of 1000 solutions. The comparison was carried out using a model grid containing ∼ 2·104 points in the BC99 case and ∼ 2·105 for the SB99 models. Both a reduced χ2 and a Maximum Likelihood estimator were used to measure the goodness of the fit. We included 2–3 colour terms and an EW (Hα) term. The observational uncertainties were taken into account. We used the following formulae: L(t, b, Z) = ( 3−4 ∏ n=1 1√ 2π∆Cn exp ( − (cn − Cn)2 2∆Cn 2 ) )1/N (6) χ2 = 1 N 3−4 ∑ n=1 (cn − Cn)2 ∆C2 n (7) where Cn and cn are, respectively, the observed and mod- elled data values (colours and 2.5 · log EW (Hα)), ∆Cn are their corresponding errors and N is the number of terms in the sum or the product. N = 3 (N = 4) when we used two (three) colours plus EW (Hα). The distributions in the space of solutions were studied using Principal Component Analysis. This fitting procedure gives the best-fitting set of model parameters, the corre- sponding uncertainty intervals, and the possible degenera- cies between these parameters within the uncertainty inter- vals. See Gil de Paz & Madore (2002) for details. Stellar populations in local star-forming galaxies.I.–Data and modelling procedure. 11 Figure 3. Wavelength dependence of 4 extinction laws: Calzetti et al. (2000); Charlot & Fall (2000, bursts ages younger than 107 years have been assumed) and Cardelli et al. (1989) for R=3.1 and R=5.0. The effective wavelengths of the bands considered in this work are shown. 4 DISCUSSION 4.1 Goodness of the fit Somewhat surprisingly, we did not find significant differ- ences in the results obtained with the χ2 and the Maximum Likelihood estimators. Therefore, all the following discussion (and the results for the fitted parameters given in Paper II) will refer to the modelling performed with the χ2 minimiza- tion. Out of the 163 UCM galaxies (excluding AGNs) with more than two observed broad-bands, a total of 9 galax- ies present χ2 values greater than 4.0 in all possible models considered. This χ2 value corresponds to average differences between the observed and modelled colours of ∼ 0.3 mag (∼ 30% in flux) for typical uncertainties of 0.15 mag in the colours and considering the EW term as negligible. Two of these galaxies (UCM2304+1621 and UCM2351+2321) present best-fittings which perfectly match the B, J and K luminosities, but fail to reproduce the r-band magni- tudes by 0.3–0.5 mag, indicating that there may be a prob- lem with their r-band data. Three of the remaining objects with high χ2 values are face-on spirals with resolved struc- ture (UCM1304+2818, UCM2249+2149 and 2302+2053E), and another one (UCM2255+1654) is an edge-on galaxy. All of them exhibit strong dust lanes, most visible in the B band, that may indicate a complex extinction be- haviour (see discussion below). The remaining three galaxies (UCM1647+2727, UCM1657+2901 and UCM2316+2028) are compact objects that seem to have a burst affecting the whole galaxy (revealed by our Hα images, Pérez-González et al. 2002c). The minimum number of rejected fits1 (19 galaxies) is achieved for SB99 models with an instantaneous burst, Salpeter IMF and CALZ00 extinction. Using the same pa- rameters, 20 rejected fits were found for BC99 models. In other model/parameter combinations, the number of re- jected fits increases. For example, 26 fits are rejected with SB99, instantaneous burst, Salpeter IMF and the CF00 recipe. Up to 74 are rejected for continuous SFR models. All the objects without valid fits will not be used in the following discussion. We have kept the two galaxies with suspect r-band photometry. Fig. 4 shows the comparison of χ2 values for several pairs of input models. Information on the Hα/Hβ emission- line ratios is also shown since extinction turns out to be a crucial parameter in the goodness of the model fits. The shaded area corresponds the zone of poor fits. In the top- left diagram, BC99 and SB99 models with the same of the 1 Fits are rejected if χ2 > 4 12 P. G. Pérez-González et al. Figure 4. Plots of the χ2 obtained in the best-fittings comparing several a priori model inputs. Different symbols represent different Hα/Hβ line ratios (i.e., different extinctions). The top-left diagram compares the two families of stellar synthesis models (BC99 and SB99) for the same values of the other input parameters (i.e., Salpeter IMF, CF00 recipe and instantaneous SFR; see labels in the upper-left corner). Different IMFs are compared in the upper-right diagram, star formation scenarios in the bottom-left one and extinction recipes in the bottom-right plot. remaining parameters are compared. Both models provide comparable results for most galaxies. The bottom-left plot compares instantaneous and con- tinuous star-formation SB99 models. It is quite clear that better fits are obtained for most of the galaxies with short bursts. A large fraction of the continuous star-formation models are rejected by the observations. There are a hand- ful of galaxies with better constant star-formation, but in all cases almost equally good fits are obtained for the burst models. The top-right diagram shows that the quality of the fits for Miller-Scalo and Salpeter IMFs is indistinguishable. The same is true for the Scalo IMF (not shown). At this point we are not able to establish which of the tested IMFs best reproduces the observed properties of the UCM galaxies. We will return to this issue later. Finally, the two extinction recipes are compared in the lower-right panel. The CALZ00 recipe seems to yield better fits than the CF00 one for high extinction objects (group of filled stars on the right). On the other hand, for some Stellar populations in local star-forming galaxies.I.–Data and modelling procedure. 13 IMF N % Bruzual & Charlot 1999 models SALP INST 10 6 14 9 CONS 4 3 4 3 Leitherer et al. 1999 models SALP INST 54 33 30 18 SALP CONS 2 1 1 1 IMF N % SCA INST 5 3 4 3 CONS 1 1 1 1 IMF N % MSCA INST 6 4 10 6 CONS 8 5 9 6 Figure 5. Distribution of the best-fittings (those with a lowest value of χ2) for the UCM sample according to the input parameters. Continuous-line rectangles stand for CF00 extinction and dashed ones for the CALZ00 law (with sizes proportional to the total number of objects). other galaxies, specially those with low values of the Hα/Hβ ratio, CF00 works better. For some cases neither provides confident results. Fig. 5 shows the distribution of the best model fits for the UCM galaxies according to the model input parameters. The χ2 estimator for each galaxy and model has been as- sumed to be the median of all the 1000 Montecarlo particles and it has been normalized with the number of colours used in its calculation. For each galaxy, we select the model that best-fittings its observational data, i.e showing the lowest value of the χ2 estimator. A total of 87 objects are best modelled with the SB99 models rather than with the BC99 ones. This corresponds to 53% of the complete sample. On average, these galaxies present redder observed B − r colours and higher EW (Hα) values than the objects best modelled with BC99 models: (B − r)SB99 = 0.9 ± 0.3 vs. (B − r)BC99 = 0.7 ± 0.3 and EW (HαSB99) = 60± 60 Å vs. EW (HαBC99) = 110± 90 Å. Moreover, the average metallicity estimated by SB99 mod- els is lower than what BC99 predict. We will discuss these points in Paper II. We have only used SB99 models with a Salpeter IMF. If we only consider the galaxies best fitted with that IMF, the percentage of best-fittings achieved with this evolutionary code increases to 73%. Fig. 5 also shows that 82% of the UCM sample is best described by an instantaneous burst of star formation. The objects favouring a constant SFR are characterized by lower extinctions and higher equivalent widths (〈E(B − V )〉 = 0.6 mag and 〈EW (Hα)〉 = 168 Å) than those best modelled with instantaneous bursts (0.8 mag and 64 Å). Among the galaxies best modelled with the BC99 mod- els, two of the IMFs considered seem to dominate over the other one: the most common in this distribution are the Salpeter IMF (42%) and Miller-Scalo’s (42% of the total number of galaxies best fitted by BC99 models). If we also take into account the galaxies modelled with SB99 tem- plates, for 73% of the galaxies a Salpeter IMF yields the best-fittings. These results are in agreement with several studies claiming that a Salpeter slope best reproduces the distribution of stellar masses in massive star formation sce- narios (with perhaps a flattening at low masses; see, for ex- ample, Massey & Hunter 1998; Selman et al. 1999; Sakhibov & Smirnov 2000; Schaerer et al. 2000). However, it is impor- tant to emphasise that we have obtained these figures by a simple comparison of the values of the χ2 estimator. A proper discussion on the IMF in UCM galaxies must involve parameters such as the upper mass limit or the fraction of ionizing photons escaping from the birth cloud. This is far beyond the scope of the present paper. Finally, the CF00 extinction recipe best reproduces the observed colours and gas emission for 55% of the sample. We notice again that high extinctions prevail on the objects best fitted with the CALZ00 law, with 〈E(B − V )〉 = 0.9 ± 0.5 (cf. 〈E(B − V )〉 = 0.6 ± 0.4 for CF00). Figs. 6 and 7 present residual colour-colour diagrams showing the differences between fitted and measured values for several pairs of observables. Input parameters are SB99 models, instantaneous SFR, Salpeter IMF and CF00 extinc- tion recipe. Information about spectroscopic type (Fig. 6) and Hα/Hβ ratio (Fig. 7) is also shown in order to search for correlations between these quantities and the goodness of the fit. The median error for each measured colour is in- dicated by the error bars. In the case of EW (Hα) we have plotted the lines of equality for fitted and measured values. First, it is clear that the AGNs are not well-fitted (three other AGNs are outside the boundaries of these plots, to- gether with two of the galaxies mentioned at the beginning of this section). As expected, the contribution of the ac- tive nucleus cannot be reproduced by the stellar synthesis models. These AGN will be excluded from the rest of the discussion. A group of objects, mainly disk-like galaxies, exhibit a deficit of observed B-band light: their B − r and B − J colours are redder than the best-fit model predictions (e.g., objects with large ∆(B − r) values in top-left panel). Most of these objects have high Hα/Hβ ratios. In some cases Hβ was not detectable. For the galaxies with undetected Hβ, an average E(B−V ) based on the spectroscopic type was used initially, but this clearly underestimated the extinction and showed fitted colours which were much bluer than the mea- sured ones. For that reason, we decided to use instead the average of the 25% highest Hα/Hβ ratios for this spectral class. This value was the one finally assumed and the one 14 P. G. Pérez-González et al. Figure 6. Differences between fitted and measured values for optical and nIR colours, and EW (Hα). Average errors are shown in each panel. Different symbols stand for disk-like, HII-like and AGN galaxies. The data refers to instantaneous SB99 models with a Salpeter IMF and CF00 extinction. Stellar populations in local star-forming galaxies.I.–Data and modelling procedure. 15 Figure 7. Same as in Fig. 6 but the symbols represent different values of the Hα/Hβ ratio, an extinction indicator. 16 P. G. Pérez-González et al. used to generate Fig.s 6 and 7. Although this yielded better fits, it seems that we are still somewhat short of the real extinction value for some objects. At this point it is important to remind the reader that we are using EW (Hα) and Hα/Hβ values measured in the long-slit spectra, and assume that they are representative of the whole galaxy. Another group of galaxies have optical-nIR colours which are not well-fitted by the models, such as the ob- ject with positive differences in the top-right panel. A vi- sual inspection of these objects reveals that a number of them are high-inclination galaxies (ellipticity larger than 0.3), some with clear dust-lanes best observed in the B im- ages. Examples include UCM0044+2246, UCM2255+1654 and UCM2329+2427. The CF00 extinction recipe fails to model these highly-reddened galaxies (see Fig. 7), while CALZ00 provides better results. Among the 15 worst fit- ted objects of this kind, 50% have EW (Hα) lower than 30 Å and virtually all of the rest below 60 Å. The observed J − K colours for these galaxies are also redder than the model predictions, indicating, perhaps, that the underlying old population is more dominant in them. The problem with extinction gets obviously worse as we move to shorter wavelengths. Some objects may be so ex- tincted that we may be observing just the ‘surface’ of the galaxy disks in B while we can see deeper layers in the nIR (see, for example, Corradi et al. 1996). Since we are ob- serving fewer stars in the blue bands, the measured colours would be redder than what the models predict. Moreover, significant uncertainties still remain in the extinction recipes when trying to match observations spanning a large wave- length range such as optical-nIR colours. In the diagrams involving the EW (Hα) we see that the models succeed reasonably well in fitting the observed data, although there seems to be a relatively small tendency to underestimate the observed values. Since the measured Hα EW s are based on long-slit spectroscopy, and thus domi- nated by the central values, we could be overestimating them if the star formation is significantly more concentrated than the old stars. 4.2 Solution degeneracy The technique that we have developed to derive the stellar properties of the UCM galaxies is based on the use of the observational errors and a Principal Component Analysis (PCA) study of the solutions. This procedure allows us to obtain information about the degeneracy of the results in the {t, b, Z} parameter space. In GdP00 we applied a sin- gle linkage hierarchical clustering method (Murtagh & Heck 1987) in order to study the clustering of solutions achieved in the 1000 Montecarlo particles fitted for each galaxy. That paper pointed out that the clustering pattern is dominated by the discretization in metallicity of the evolutionary syn- thesis models. Thus, little can be learnt using this clustering method before performing the PCA. Instead, in the present work we have applied the PCA to all the Montecarlo par- ticles and obtained average values and standard deviations for the entire set of solutions of each galaxy. This method shows that, on average for the complete UCM sample, 69± 2% of the scatter of the Montecarlo par- ticles is represented by the first principal component in the Figure 8. Histograms of the 3 components of the first vector of the PCA for the UCM Survey galaxies. The plot refers to SB99 models, Salpeter IMF, instantaneous burst and CALZ00 recipe. PCA. In less than 3% of the sample this fraction is less than half of the total scatter. In GdP00 the clustering char- acterization removed the scattering of the solutions due to metallicity. The effect was that the component of the PCA vector in the Z direction was null in most cases. Now the distribution of this component for the whole sample is some- what flatter, with the strongest peak at −0.5 (see Fig. 8). This figure also shows that the age and burst strength com- ponents are similar. This means that both quantities are correlated: if we increase the model age, we need to increase the burst strength in order to keep the same Hα equivalent width. Moreover, since the strongest peak in the metallic- ity direction has opposite sign to the other two, there is an age-metallicity degeneracy (anti-correlation). 5 SUMMARY In this paper, the first of a series, we have described a method to derive the properties of the star-formation and the stellar populations in star-forming galaxies using broad- band photometry and spectroscopy. We also present the available data for the UCM Survey galaxies, covering the op- tical and nIR spectral ranges. The technique is based on the assumption that our galaxies have a composite stellar pop- ulation. The evolved component resembles that of a typical quiescent spiral/lenticular galaxy, whereas the young stel- lar population component is generated with an evolutionary synthesis model. This fact means that our modelling refers to the properties of a recent star formation event which takes place in excess of what is typical in a normal spiral or lentic- ular galaxy. The model parameters considered are: (1) stellar evolutionary synthesis (the Bruzual & Charlot 1999 and Lei- therer et al. 1999 models); (2) IMFs (Salpeter 1955; Scalo 1986; Miller & Scalo 1979); (3) star formation modes (instan- taneous and constant); and (4) extinction recipes (Calzetti et al. 2000 and Charlot & Fall 2000). We have developed a statistical tool that takes into ac- count the observational uncertainties and a careful interpre- tation of the model fits. The procedure is tested with the UCM sample data, and used to study the dependence of the goodness of the model fits on several a priori input param- eters. We find that our modelling is able to reproduce the Stellar populations in local star-forming galaxies.I.–Data and modelling procedure. 17 photometric and spectroscopic properties of almost all the star-forming galaxies of the UCM Survey. Our test on the a priori model parameter choices, based on our χ2 estimator, reveals that: • both SB99 and BC99 models provide reasonable and comparable fits. The SB99 models provide marginally bet- ter results, in particular for redder galaxies with relatively higher Hα equivalent widths. • UCM galaxies clearly show a preference for instanta- neous bursts of recent star formation rather than constant star-formation rates. • The models with a Salpeter initial mass function better reproduce the observations for nearly 75% of the sample, although a number of galaxies also present best results us- ing the other IMFs and this result must be regarded with caution. • The extinction description developed by CF00 yields satisfactory results for the majority of our sample galaxies (with a variation in the extinction law), but it fails to repro- duce the properties of high extinction objects. Among all the possible combinations of input param- eters, an important number of galaxies (one third) is best modelled with SB99 code, Salpeter IMF, instantaneous SFR and CF00 extinction recipe. In Paper II, we will use the techniques developed here to study, in detail, the properties of the UCM galaxies. ACKNOWLEDGMENTS This paper is partially based on data from CAHA, the German-Spanish Astronomical Centre, Calar Alto, oper- ated by the Max-Planck-Institute for Astronomy, Heidel- berg, jointly with the Spanish National Commission for As- tronomy. Also partially based on data obtained with the 2.3m Bok Telescope of the University of Arizona on Kitt Peak National Observatory, National Optical Astronomy Observatory, which is operated by the Association of Uni- versities for Research in Astronomy, Inc. (AURA) under co- operative agreement with the National Science Foundation. Also partially based on observations made with the Isaac Newton and Jacobus Kapteyn Telescopes, operated on the island of La Palma by the Isaac Newton Group in the Span- ish Observatorio del Roque de los Muchachos of the Instituto de Astrof́ısica de Canarias. This research has made use of the NASA/IPAC Ex- tragalactic Database (NED) and the NASA/IPAC Infrared Science Archive which are operated by the Jet Propulsion Laboratory, California Institute of Technology, under con- tract with the National Aeronautics and Space Administra- tion. 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. PGPG wishes to acknowledge the Spanish Ministry of Education and Culture for the reception of a Formación de Profesorado Universitario fellowship. AGdP acknowledges financial support from NASA through a Long Term Space Astrophysics grant to B.F. Madore. During the course of this work AAH has been supported by the National Aeronautics and Space Administration grant NAG 5-3042 through the University of Arizona and Contract 960785 through the Jet Propulsion Laboratory. AAS acknowledges generous finan- cial support from the Royal Society. We also would like to thank George and Marcia Rieke for kindly allowing us to use their near-infrared camera on the University of Arizona 2.3m Bok Telescope. We are grateful to the anonymous referee for her/his helpful comments and suggestions. The present work was supported by the Spanish Pro- grama Nacional de Astronomı́a y Astrof́ısica under grant AYA2000-1790. REFERENCES Abraham R. G., van den Bergh S., 2002, in Disks of Galax- ies: Kinematics, Dynamics and Perturbations. ASP Con- ference Proceedings, Vol. 275. Edited by E. Athanassoula. A. Bosma and R. Mujica. ISBN: 1-58381-117-6. Puebla, Mexico., eds. 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