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1 Introduction

  Galaxies and clusters probe the Large Scale Structure (LSS) of the matter distribution in the Universe at various scales of mass, spatial separation, and density. The comparison of such different regimes allows to gain a significant insight into the relation among invisible and luminous matter. Galaxy groups can be regarded as systems intermediate between galaxies and galaxy clusters. They provide constraints through two different routes: as galaxy systems, through their internal properties (velocity dispersion $\sigma_{v}$, radius R, etc.); as LSS tracers, through their "external'' properties (abundance, clustering, fraction of grouped galaxies, etc.). Groups therefore yield quite useful counterchecks to models based on galaxy and cluster data.

The main target of this work is to present a large and homogeneous catalog of galaxy groups in the Southern Galactic Hemisphere, extracted from the Perseus-Pisces redshift Survey (PPS hereafter; Giovanelli & Haynes 1993; Wegner et al. 1993, and references therein). The total number of groups is $N_{\rm G} \approx 200$ (depending on the details of the identification procedure, Sect. 3). This is significantly larger than in most previous studies, where grouping procedures similar to ours were applied to galaxy data of comparable quality to (but smaller extent than) PPS. To avoid possible confusion, we note explicitly that here we deal with loose groups of galaxies. Many studies concentrated on compact groups, a rather special case of the more general loose groups considered here. The relation among compact and loose groups is discussed in Diaferio et al. (1994), Mamon (1996a), Governato et al. (1996).

Our group catalog is meant to be as homogeneous as possible to those previously published and well-studied. Unfortunately, group properties are very sensitive to the details of the identification recipe (e.g., Pisani et al. 1992). On the other hand, most of the actually available samples of loose groups were compiled following the same grouping criteria, the adaptive Friends-Of-Friends (FOF) algorithms introduced by Huchra & Geller (1982, HG82 hereafter; see also Nolthenius & White 1987, NW87 hereafter). Still, group properties are systematically influenced by the user's choice of search parameters (HG82; NW87; Moore et al. 1993; Nolthenius et al. 1994, 1997; Frederic 1995a,b; MFW93, NKP94, NKP97, F95a, F95b hereafter). This must be taken into account by a careful, self-consistent match of FOF parameters among different catalogs. Several authors (NW87; MFW93; NKP94; NKP97; F95a, b) used cosmological N-body simulations of dark matter models to calibrate the "optimal'' FOF algorithm. In the first place, this aims at obtaining the highest possible completeness and reliability of FOF groups (NW87; MFW93; F95a, b). It is worth to mention that this approach can then be reverted in order to constrain the models. Once a grouping procedure is found successful, it is applied to real and simulated data, and outputs are self-consistently compared (NW87; NKP94; NKP97).

The earliest sample of FOF groups is the HG82 catalog ($N_{\rm G}=92$)based on the NB survey of nearby bright galaxies. Geller & Huchra (1983) and Nolthenius (1993; N93 hereafter) compiled two larger catalogs ($N_{\rm G} \sim 170$) from the CfA1 survey (Huchra et al. 1983). These and similar CfA1 samples have been widely studied (Mezzetti et al. 1985; Heisler et al. 1985; Giuricin et al. 1986a,b, 1988; NW87; Pisani et al. 1992; MFW93; N93; NKP94, NKP97). Groups were then selected from deeper galaxy surveys. Maia et al. (1989; Maia & da Costa 1990) identified $N_{\rm G}=87$ groups in the SSRS1 survey (da Costa et al. 1988), while Ramella et al. (1989; RGH89 hereafter) selected $N_{\rm G} \sim 130$ systems from the CfA2 Slices (de Lapparent et al. 1986; Huchra et al. 1990, 1995). Groups in the Las Campanas Redshift Survey (Shectman et al. 1996) were considered by Tucker et al. (1993) and by Tucker (1994) in his Ph.D. Thesis. Their study is still underway (Tucker et al. 1997).

Very recently Ramella et al. (1997a; RPG97 herefter) published a larger group sample ($N_{\rm G}=406$), previously announced by Pisani et al. (1994; PGHR94), based on the whole CfA2 North survey. RPG97 also announced the compilation of a further group catalog whose details should be soon provided (Ramella et al. 1997b). It should include the SSRS2 survey (da Costa et al. 1994), which lies in the Southern Galactic Hemisphere as PPS but in a completely independent area of the sky. Loose groups in PPS ($N_{\rm G} \sim 200$)were systematically identified and analyzed in Trasarti-Battistoni (1996; TB96 hereafter) in his Ph.D. Thesis, and Trasarti-Battistoni et al. (1997; TBIB97 hereafter). Two earlier studies are due to Haynes & Giovanelli (1988) and Wegner et al. (1993). There, groups were selected from a much smaller subsample of PPS than we do here, and they were mainly considereded as useful tracers of LSS.

Up to date, the largest group catalog ($N_{\rm G} = 453$) is that of Garcia (1993). On the other hand, the parent galaxy catalog EDB (Garcia et al. 1993) is not a homogeneous redshift survey, but rather it is based on a compilation of galaxy data coming from very different sources, though a great effort toward homogeneization of galaxy data (Paturel et al. 1989a,b) was actually made. The sample depth is B=14.0, much shallower than for PPS, CfA, or SSRS. Furthermore, groups are identified by means of FOF algorithms as well as other techniques. This precludes any direct, straightforward comparison of Garcia's groups with most available group samples and numerical simulations. Similar criticisms apply to the group catalogs identified from the PGC sample (Gourgoulhon et al. 1992; Fouqué et al. 1992), and to a lesser extent to other group catalogs (Tully 1987; Giudice 1995, 1997).

The PPS sample is ideal for our purposes. It is highly homogeneous, apparent-magnitude-complete, and covers a wide solid angle. Furthermore, it is based on the same parent angular catalog CGCG (Zwicky et al. 1961-68) as the CfA survey, but is deeper than CfA1 and SSRS1, wider than the CfA2 Slices, contains more galaxies than each of such samples, and it is directly comparable to the CfA2 North and SSRS2 surveys. Groups are identified with the FOF recipe of HG82, but our search parameters match those adopted for the other group catalogs compiled from galaxy samples of the same depth as ours. Thus, our catalogs can be directly compared-with/combined-to other observational samples and/or numerical simulations of cosmological models (in particular: RGH89, RPG97, F95a, b). In fact, this approach already allowed us (TBIB97) to compare group clustering in PPS with previous analyses of CfA1, SSRS1, and CfA2 Slices (Jing & Zhang 1988; Maia et al. 1989; Ramella et al. 1990). There, we show that many previously unexplained discrepancies among such analysis are essentially due to the different FOF parameters adopted by different authors. This clearly indicates the need of a careful choice of search parameters prior to any comparison of different group samples.

The plan of the paper is the following. We describe the galaxy data in Sect. 2, and the group identification procedure in Sect. 3. The catalogs of groups and group properties are presented in Sect. 4. Section 5 is a summary. Distances are measured in $h^{-1}~{\rm Mpc}$, where the Hubble parameter is $H_0 = 100 \ h \ {\rm km\ s}^{-1}\ {\rm Mpc}^{-1}$,and absolute magnitudes are computed assuming h=1.

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