Multicolor Photometry of the Galaxies in Abell 1775: Substructures, Luminosity Functions, and Star-Formation Properties
An optical photometric observation in 15 bands was carried out for nearby galaxy cluster Abell 1775 by the Beijing-Arizona-Taiwan-Connecticut (BATC) multi-color system. Over 5000 sources’ spectral energy distributions (SEDs) were obtained. Since this cluster has also been observed by the Sloan Digital Sky Survey (SDSS), the BATC SEDs were combined with the SDSS five-band photometric data. Using the combined SEDs, 146 faint galaxies were selected as new member galaxies by the photometric redshift technique. Based on the positions, redshifts and 20-band SEDs of member galaxies, dynamical substructures and luminosity functions (LFs) of A1775 were investigated. The previous reported bimodal structure of A1775 has been confirmed: a poor subcluster with lower redshift, A1775A, is located southeast to the main concentration A1775B. After taking into account the new supplemented member galaxies, a new subcluster A1775C was found along the aligned direction of A1775A and A1775B. The different LF faint ends of the two subclusters indicate that A1775B is a more dynamically evolved system, while A1775A is still dynamically young. By the STARLIGHT spectral synthesis code, the star- formation histories of the member galaxies were studied. The dependence of the mean stellar ages upon the Hubble type was confirmed, and the environmental effect on star-formation activities for galaxies in A1775B has been explored.
Li Zhang et al.Multicolor Photometry of the Galaxies in A 1775: Substructures, Luminosity Functions, and Star Formation Properties \Received\Accepted
galaxies: clusters: individual (Abell 1775) — galaxies: distances and redshifts — galaxies: kinematics and dynamics — galaxies: luminosity function — stars: formation
More and more galaxy clusters have been revealed to have substructures by both the X-ray and optical surveys (Forman & Jones 1982; Beers et al. 1991; Burns et al. 1994). Numerical simulation of the evolution of galaxy clusters shows that at least of apparently relaxed clusters contain significant substructures (Salvador-Solé et al. 1993). The dynamics of these “lumpy” clusters thus provide a means for exploring cluster evolution, which may shed light on the theories of large-scale structure formation. For example, the hierarchical scenario of structure formation believes that massive clusters form through episodic merging of subunits, such as galaxy groups and poor clusters, and through the continuous accretion of field galaxies along the filaments (Zeldovich et al. 1982; West et al. 1995; Kauffmann et al. 1999; Colberg et al. 2000). Galaxy clusters also provide homogeneous samples of essentially coeval galaxies in a high-density environment, which enable studies of the evolution of stellar populations (Blakeslee et al. 2003; Poggianti et al. 2008).
Abell 1775 (A1775; z=0.0717) is a richness 2 cluster of RS-type “binary” (Abell 1958; Struble & Rood 1982; 1999). It has been observed in optical, radio, and X-ray bands, showing a complicated picture of the dynamics, substructure, and intergalactic medium. Its optical observation shows that there are two giant elliptical galaxies at the center of A1775 (Chincarini et al. 1971; Jenner 1974). These two galaxies are considered to be a signature of merger events with two less massive systems of galaxies. This inference is supported by Oegerle, Hill, and Fitchett (1995, hereafter OHF) who presented the velocity distribution of member galaxies in A1775. Although the number of member galaxies in OHF is merely 51, their result clearly indicates the presence of two subclusters along the line of sight. Though no diffuse radio halo has been detected for this cluster, two radio sources are found to be associated with the two dominant galaxies, respectively. The south-east one, B1339+266B, is a head-tail radio source, which exhibits a very narrow tail extended northeast in the radio map (Giacintucci et al. 2007). In general, the clusters containing narrow-angle tailed radio galaxies are also believed to be dynamically complex systems undergoing merger events (Bliton et al. 1998). The double peaks in the X-ray brightness map of A1775 also show evidence for the cluster’s multiple nature (OHF; McMillan et al. 1989). The main intensive X-ray peak is near the core emission of the tailed radio source, which corresponds to the main concentration of A1775, and a small clump of galaxies is also found around the other X-ray peak. These intriguing observational features tell us that this cluster is not a simple relaxed structure, but is still forming at the present epoch.
This paper presents our new optical photometry for A1775 with the Beijing-Arizona-Taiwan-Connecticut (hereafter BATC) multicolor system. The BATC multicolor photometry can provide the information about the spectral energy distributions (SEDs) for all of the objects within a field of centered on A1775. Accurate spectroscopic and photometric data of A1775 have also been distributed by the Sloan Digital Sky Survey (SDSS). For achieving a more accurate estimate of photometric redshifts for detected galaxies, the SDSS photometric data in five bands (Fukugita et al. 1996) are combined with our BATC SEDs in fifteen bands. The availability of abundant data facilitates the selection of faint member galaxies and enables us to better understand the dynamical substructures, luminosity functions, and the star-formation properties of the galaxy cluster A1775.
In section 2, the BATC multicolor photometry and data reduction are presented, as well as a method for combining the SDSS SEDs with the BATC SEDs. In section 3, using the galaxies with secure spectroscopic redshifts in the field of view, the reliability of the SED combination and the photometric redshift estimate is verified by a comparison between the photometric redshift () and the spectroscopic redshift (). Further selection for faint member galaxies based on their combined SEDs is also given in this section. In section 4, the dynamics, spatial distribution, localized velocity structure, luminosity function, and the star-formation histories of the galaxies in A1775 are discussed. Finally, a summary is made in section 5. Throughout this paper the CDM cosmology model is adopted with kmsMpc, , and .
2 Observations and Data Reduction
2.1 Multicolor Photometry by the BATC System
Observations of A1775 were carried out by the BATC multi-color system with the 60/90 cm f/3 Schmidt telescope at the Xinglong station, National Astronomical Observatories of China (NAOC). Before 2006 October, an old Ford CCD camera with a format of 20482048 was used. The field of view was , with a scale of pixel. For pursuing a better spatial resolution and a higher sensitivity in the blue bands, a new E2V 40964096 thinned CCD camera was equipped. The new CCD has a high quantum efficiency of 92.2% at 4000Å and the field of view has been extended to with a spatial scale of pixel. The pixel sizes for the old and new CCDs are 15 and 12, respectively, corresponding to a pixel size ratio of 5:4. 15 intermediate-band filters covering the wavelength range from 3000 to 10000Å are contained in the BATC filter system. These filters were especially designed to avoid bright night sky emission lines (Fan et al. 1996). The transmission curves of the BATC filters can be found in Figure 1 of Yuan Zhou, and Jiang (2003).
From 1996 to 2006, we accumulated 37 hr in only 12 bands, from d to p, with the old CCD camera. In recent two years the exposures in the a, b, c filters were completed with the new CCD camera. The observational statistics is given in Table 1. The total exposure time reaches more than 48 hr. With an automatic data-processing software, PIPELINE I (Fan et al. 1996), the standard procedures of bias subtraction, flat-fielding correction, and position calibration were carried out. The technique of integral pixel shifting was used in the image combination, during which the cosmic rays and bad pixels were removed by comparing multiple images.
For detecting and measuring the flux of sources within a given aperture in the combined BATC images, a photometry package, PIPELINE II, developed on the basis of DAOPHOT kernel (Stetson 1987; Zhou et al. 2003) was used. An object was considered to be detected if its signal-to-noise ratio was larger than 3.5 threshold in the i, j, and k bands. Considering that the pixel size ratio between the old and new CCDs is 5:4, a radius of 4 pixels for the images in 12 bands (from d to p), and a radius of 5 pixels for the images in the other three bands (from a to c) were adopted as the photometric apertures, respectively. A flux calibration in the h band was performed using the Oke-Gunn primary flux standard stars HD 19445, HD 84937, BD+26 2606, and BD+17 4708 (Oke & Gunn 1983). To achieve the relative SEDs of sources detected by the BATC system, Zhou et al. (1999) developed a method of model calibration on the basis of the stellar SED library. No calibration images of the standard stars are needed during the flux calibration. Using this model calibration method, as a result, the SEDs of more than 5000 sources have been obtained for further analysis.
For assessing the measurement errors at specified magnitudes, sources are separated into different bins of magnitudes with an interval of 0.5 mag, and it is found that magnitude error in each filter is larger at fainter depths. A typical error is less than 0.02 mag for those stars brighter than 16.5 mag, and about 0.05 mag for stars with V mag.
2.2 Combining the SDSS and BATC SEDs
Apart from the BATC photometric data, the SDSS photometric data were also used in our analysis. For explicitly distinguishing the SDSS filter names from those of the BATC, the SDSS filters and magnitudes are referred to as , , , , and in this paper, which correspond to central wavelengths of 3560, 4680, 6180, 7500 and 8870Å. From all of the SDSS-detected sources in our field of view, the extended sources (galaxies) were extracted according to their morphology classification given in the SDSS photometric catalog, and were then cross-identified with objects detected in the BATC observations. A searching circle with a radius of centered at the SDSS galaxies was adopted. By balancing the position offsets and SED features of the counterparts, the identification is rather unambiguous. Finally, 2248 galaxies with mag detected by both surveys were achieved.
Our previous studies show that the higher resolution of SED can improve the accuracy of the photometric redshift estimate (Yuan et al. 2003; Yang et al. 2004). For the SDSS photometric data of galaxies, following the aperture correction method described in Yuan, Zhou, and Jiang (2003), the SDSS colors of galaxies were derived by the same aperture of BATC, that is an aperture of radius . For a given galaxy detected by the SDSS imaging observation, the profile of its surface brightness was quantified by various models. The total magnitude estimated within 8 for deVaucouleurs profile or 4 for exponential profile is termed the model magnitude, where is the effective radius and its value can be found in the SDSS photometric catalog. An aperture correction was applied to the SDSS model magnitudes () by
where is the profile function of the surface intensity (e.g. the exponential or deVaucouleurs model). The corresponding parameters that quantify the preferred brightness profile for each galaxy can be found in the SDSS photometric archive. The typical values of estimated by equation (1) is 0.0624.
For galaxies detected in both surveys, there might be an systematic offset between the two photometric systems, which is called the zero point. It can be determined by contrasting the BATC SEDs with the aperture-corrected SDSS SEDs. The zero point is simply calculated by averaging the magnitude differences at 6166Å and 7480Å, the effective wavelengths of the and filters. Interpolation was performed during calculating the BATC magnitudes at 6166 and 7480Å. This algorithm of zero point is slight different from that in Liu et al. (2011). Figure 1 presents the zero-point distribution of 2248 galaxies with mag detected by both surveys. It can be seen that the SED zero-points are concentrated at -0.2 mag. The zero points for different galaxies are slightly different, since the deviation of the surface brightness profile from the preferential model is different from source to source.
As a result, the combined SEDs of 2248 galaxies bright than mag in the band were obtained, which include the flux-calibrated BATC SEDs in 15 filter bands and the aperture corrected SDSS SEDs in 5 filter bands. In the following analysis, we will focus on 881 galaxies brighter than mag in the band in the A1775 field.
3 Selection of Faint Cluster Galaxies
3.1 Accuracy of Photometric Redshift
Among the galaxies detected by both photometric surveys, 190 galaxies have been spectroscopically observed by the SDSS. This spectroscopic sample provides us with an opportunity to test the reliability of . For nearby galaxies, the most obvious and useful spectral feature in redshift determination is the 4000Å Balmer break, which ought to be better reflected by the combined 20-band SEDs. Especially when a galaxy has a large photometric uncertainty in one filter of BATC, the magnitude in the nearby SDSS band can be a good compensation, and vice-versa. Thus, the combined photometric data of galaxies are used to get .
The SED fitting method “Hyperz”(Bolzonella, Miralles, & Pelló¡ä 2000) was performed for obtaining . Templates of normal galaxies are taken into account. For correcting the intrinsic extinction, the reddening law of the Milky Way (Allen 1976) was adopted, and was allowed to vary in a range from 0.0 to 0.2, with steps of 0.02. The photometric redshift of a galaxy was searched from 0.0 to 0.5, with an increment of 0.005. By comparing the observed SED with the SEDs in the template library, the best fit galaxy template was found, and its corresponding redshift was taken as the of the observed galaxy. Meanwhile, the type of the observed galaxy was also ascertained.
Figure 2 shows comparisons between and for these 190 bright galaxies. s in panel (a) were derived by 5 broad-band photometric data from SDSS, s in panel (b) were derived by the combined SDSS and BATC SEDs. The solid lines in the two panels are for and the dashed lines indicate . The error bar of , which corresponds to 68% is also given. It can be seen that the estimate is basically consistent with , and in panel (b), which was derived by combined photometric data, seems to have a smaller dispersion. Many galaxies are concentrated at . A few catastrophic outliers also appear, it is likely that these galaxies have peculiar features in internal dust extinction and metallicity evolution. The corresponding distribution of offsets for the above-two cases are given in figure 3. A gaussian curve represented by a dashed line was used to fit the distribution of . The results showed that the centroid of in panel (b) is closer to zero, and its dispersion () is 0.007, which is smaller than that in panel(a) (). This indicates that we obtained is generally credible, and for most of the galaxies, their s have been improved by combined multi-band photometric data.
3.2 Cluster Membership of Faint Galaxies
For a better understanding of the dynamical substructures in this cluster, many faint member galaxies should be taken into account, but only a limited number of bright member galaxies have been spectroscopically observed, for instance, the limiting magnitude for the SDSS spectral survey is mag, which corresponds to an absolute magnitude mag for A1775 (). To overcome this limit, the multicolor photometric data are employed to complement faint member galaxies with mag mag. After an exclusion of galaxies with secure spectroscopic redshifts, there are 657 galaxies brighter than mag left. Based on the combined SEDs of these galaxies, the photometric redshift technique is applied again with the same galaxy templates and extinction law.
Figure 4 gives the distribution of these 657 galaxies. The peak at corresponds to A1775. In order to select faint galaxies belonging to A1775, the value of the former spectroscopic galaxies was applied for selecting likely members. For spectroscopic galaxies with , the mean value and the standard deviation of the distribution are 0.073 and 0.008, respectively, which indicates a larger dispersion in the distribution with respect to the distribution. In order to decrease the contamination of foreground and background galaxies, a strict 2 clipping algorithm (Yahil & Vidal 1977) was taken as the selection criterion. Faint galaxies with have been picked out as possible member galaxies for further analysis. As a result, 146 faint member candidates of A1775 were obtained. Based on the sample of spectroscopic galaxies, the efficiency of the photometric selection technique can be estimated. It is revealed that more than 85% of the members galaxies were selected by . The fraction of field galaxy contamination due to errors in is below 3%. Table 2 presents a catalog of the SED information of these newly selected member galaxies, as well as their SDSS-given positions, values, and morphology indices T (E, S0, Sa, Sb, Sc, Sd, and Im galaxies are represented by 1 to 7, respectively).
4 Properties of the Galaxies in A1775
Within the BATC field of view, there are 224 galaxies with known spectroscopic redshifts; among them, 190 galaxies with mag mag have been spectroscopically observed by the SDSS, and the remaining 34 bright galaxies are listed in the NASA/IPAC Extragalactic Database (NED) only. Figure 5a shows the distribution of these 224 galaxies. 151 galaxies with were selected as probable member galaxies of A1775. After applying the 2 clipping algorithm (Yahil & Vidal 1977), no galaxies were excluded. Thus, it is unambiguous to regard these 151 galaxies as spectroscopically confirmed member galaxies. These member galaxies are referred to as “sample I” (see table 3). Combining with 146 faint member candidates newly selected, an enlarged sample of 297(=151+146) member galaxies is constructed to study the substructures and luminosity functions, to which we refer to as “sample II”.
4.1 The KMM Partition and Velocity Distribution
The profile of the line-of-sight velocity distribution is a useful tool for investigating the dynamics of galaxy clusters (Quintana et al. 1996; Muriel et al. 2002). The possible deviations from a Gaussian distribution of the cluster galaxies might provide important indications of substructure and ongoing merger. Figure 5b shows the corresponding velocity distribution of the galaxies in Figure 5a. The bimodal velocity distribution clearly implies that there are two subclusters in A1775. Following OHF, the low-redshift subcluster is referred to as A1775A, and the subcluster with high redshift is referred to as A1775B. The velocities of the two central giant elliptical galaxies are marked with arrows. Although the two galaxies appears to be close to each other in optical images, their radial velocities are significantly different.
To separate member galaxies of A1775A and A1775B more reliably , a prevalent partition method, KMM algorithm, was applied to the 151 member galaxies in sample I on the basis of their positional and redshift information. The KMM is a maximum-likelihood algorithm which assigns objects into groups and assesses the improvement in fitting a multi-group model over a single group model (Ashman et al. 1994; Nemec &Nemec 1993). After setting the initial parameters of each subcluster, including estimated mean values and standard deviations of the position and radial velocity, the solution of the KMM algorithm was obtained: there are 49 galaxies belonging to A1775A, and 102 galaxies belonging to A1775B. It was noticed that the two central dominant galaxies had been divided into different subclusters. The galaxy, SDSS J134149.14+2622224.5, with a radial velocity of 22704 km, is similar to the mean velocity of A1775B, and is thus assigned to A1775B. The other giant elliptical galaxy, SDSS J134150.45+262213.0, is assigned to A1775A with a membership possibility of 65.5%. Its radial velocity is 20812 km, which significantly deviates from the velocity centroid of A1775A.
Figure 6 give the rest-frame velocity distribution of member galaxies in A1775A and A1775B. To characterize the kinematical properties of these two subclusters, two robust estimators, namely the biweight location () and scale (), was used, which are defined by Beers Flynn, and Gebhardt (1990). These two quantities are analogous to the mean value and standard deviation, and they are robust for a broad range of probable non-Gaussian underlying populations because of their insensitivity to outliers. For 49 galaxies in A1775A, we obtained and ; for 102 galaxies in A1775B, we got and . The velocity difference between the two subclusters is about in the rest-frame of A1775. The previous OHF’s results for A1775A are , ; for A1775B they are , . Compared with their results, the centroid velocities of the two subclusters that we obtained are basically consistent with theirs, but the intrinsic dispersion of A1775B that we gained is larger. Since the spectroscopically confirmed member galaxies that we used were twice more than that which they used, we believe our results are more reliable.
4.2 Spatial Distribution
Figure 7a shows the spatial distribution of the 151 galaxies in sample I with respect to the central position of A1775 (13h41m55.6s, +26d21m53s; J2000.0, NED-given), superposed with the contour map of the surface density which was smoothed by a Gaussian window with . Two subclusters are clearly presented: the main concentration corresponds to the high-velocity subcluster A1775B (member galaxies of it are denoted by “”), and the low-velocity subcluster A1775A (its member galaxies are denoted by “”) is located at about southeast of A1775B. Two peaks of X-ray emission detected by ROSAT are marked with “”. Two central giant elliptical galaxies taken as a galaxy pair by Chincarini et al.(1971) are marked with “”. A rich cluster with double dominant galaxies preferentially indicates an ongoing merger event in this cluster. The well-studied nearby rich cluster, Coma, is a good example (Colless & Dunn 1996).
It is interesting that a narrow-angle tail radio source is found to be exactly associated with the southeast dominant galaxy whose velocity significantly deviates from A1775A, but is assigned to A1775A (Giacintucci et al. 2007). Generally speaking, a head-tail radio galaxy is regard as being the most striking example of the interaction between the intra-cluster medium (ICM) and radio sources. According to the viewpoint of Bliton et al.(1998), those clusters containing narrow-angle tailed radio galaxies are dynamically complex systems undergoing merger events. The soft X-ray band observation of A1775 by ROSAT realed that there are two X-ray peaks. The main X-ray peak is basically associated with the center of subcluster A1775B, while the fainter X-ray peak has some offset from the galaxy density peak of A1775A and it is offset towards the gravitational potential of A1775B. This might also be a signature of subcluster interacting. It may indicate that the clump A1775A is in the process of falling into A1775B.
Figure 7b shows the spatial distribution of the galaxies in sample II, including the newly selected faint member galaxies (denoted by “”). After supplementing, 146 faint galaxies, the clump A1775A became more significant; and two new clumps were found: one is located at NW of the main concentration, namely A1775C, just along the direction aligned with A1775A and A1775B; the other, namely A1775D, is at SW of A1775B. Besides, the spatial distribution of the galaxies in the inner region of A1775B, defined by a surface density larger than 0.35 arcmin, seems to be in alignment with A1775A, A1775B, and A1775C, which may reflect some helpful clues about the dynamical evolution history of A1775. However, because no abnormities around the positions of A1775C and A1775D have been found in both the X-ray and radio bands, the presence of A1775C and A1775D can’t eliminate the projection effect and it needs to be verified by follow-up spectroscopy of faint member galaxies. In our following dynamical analysis, the algorithm will be used to check if the new discovered structures A1775C and A1775D are real galaxy clumps.
On the whole, the bimodal structure in A1775 along the NW-SE direction has been unveiled in both optical and X-ray bands. Coincidentally, the connection direction of the two subclusters (A1775A and A1775B) is just consistent with the aligned direction of the central double galaxy, which may directly give us some clues about the evolution of this cluster; the subclusters A1775A and A1775B might have been interacted, and the original dominant galaxy in A1775A seems to be “pulled out” by the gravitation of the main subcluster, A1775B. This made the velocity of the galaxy significantly deviate from the centroid velocity of A1775A, and enabled the galaxy to interact with the ICM. It thus formed a head-tail radio source.
4.3 Localized Velocity Structure
To probe the robustness of the above subcluster detections, the (Colless & Dunn 1996) was performed to quantify the localized variation in the velocity distribution for both sample I and sample II. The is sensitive to spatially compact subsystems that have either an average velocity that differs from the cluster mean, or a velocity dispersion that differs from the global one, or both. Keeping the spirit of the Dressler-Shectman test (Dressler& Shectman 1988), Colless & Dunn (1996) defined a statistic, , as follows: , where n is the size of the local group (n nearest neighbor galaxies), is the number of all member galaxies of a cluster, and is the statistic in the standard K-S test. The statistic expresses the accumulated difference between the local velocity distribution and the whole cluster velocity distribution. The probability of the substructure detection can be estimated by a large number of Monte Carlo simulations.
For sample I, the presence of two subclusters in A1775 is strongly supported. For each size of the local group, Monte Carlo simulations were performed to estimate the probability of substructures under this situation. As shown in table 4, in a wide range of local sizes, the value of is lower than 1%, which means that the probability of the substructures existence is more than 99%. Among them, the optimum neighbor size is n=9, for which all of the simulated cases are found to have values smaller than the observed case (). That is to say the probability of substructures existence in this case is nearly 100%. Figure 8a shows the local velocity deviation for galaxies in sample I with a bubble plot. The bubble size for each galaxy is proportional to , which reflects the probability of the local velocity distribution different from the whole cluster velocity distribution in this place. The larger is the bubble, the greater is the difference between the local and overall velocity distributions. A comparison with Figure 7 a shows that the bubble clustering indeed appears at the positions of clumps A1775A and A1775B, and the probability of substructure detection is nearly 100%.
When we applied the on sample II, the probability of substructure detection was still great, with . The degree of the difference between the local and overall velocity distributions for groups of 7 nearest neighbors is shown by a bubble plot in Figure 8b. Compared with Figure 8a, the bubble sizes in A1775A and A1775B appear to be smaller, which is likely due to the photometric redshift errors of the newly selected members. The double structures detected with the spectroscopically confirmed member galaxies have been, to some extent, smoothed in the velocity domain. Besides, a bunch of bubbles is present at the position of the clump A1775C; however, no bubble clustering can be found at the A1775D position. This implies that A1775C might be a real clump, while A1775D might be an unreal substructure which is due to the projection effect.
4.4 Luminosity Functions of Subclusters
The luminosity function (LF) in a cluster is a key observational diagnostic for studying the formation and evolution of galaxies in a dense environment. Assuming that galaxy mass-to-light ratios are nearly constant for similar types of galaxies, the LF can potentially provide a direct link to the initial mass function and hence the distribution of the density perturbations that are thought to give rise to galaxies (Press & Schechter 1974). Previous studies showed that the BM type and the core or outskirts region of the cluster may all affect the galaxy LF (Biviano et al. 1995; Durret, Adami & Lobo 2002; Yang et al. 2004). The LFs of galaxy clusters have been well described by the Schechter function, which was first proposed by Schechter (1976):
where , , and are the normalization parameter, the characteristic absolute magnitude, and the slope parameter at faint tail, respectively.
Although the LF of cluster A1775 as a whole was studied by Barkhouse et al. (2007), we are the first to explore the LFs of the subclusters A1775A and A1775B separately. For the spectroscopically confirmed member galaxies in sample I, the SDSS spectroscopy is down to mag, corresponding to a limit of mag for A1775. These bright member galaxies alone are considered to be insufficient to constrain the LF shape. Fortunately, the benefit from the supplemented member galaxies selected by , is that the faint parts of the LFs can be better constrained. These galaxies are selected by a criterion of being bright than mag, which corresponds to an absolute magnitude limit of mag for A1775. It is about 2.0 mag deeper than the spectroscopic galaxy sample. To reveal the luminosity function of each subcluster, the newly-selected member galaxies were separated into two subclusters. Considering the poor precision of the estimate, we elected to perform the KMM partition algorithm on the basis of only the position information. As a result, 55 galaxies are assigned to A1775A, and 91 galaxies are assigned to A1775B. The overall rate of correct allocation is estimated to be over 94%.
Figure 9 shows the LFs for galaxies in the two subclusters, with an bin of 0.5 mag. The dashed line means SDSS spectroscopy completeness. For the poorer subcluster, A1775A (panel a), the best fit with a single Schechter function is mag, and . A flat galaxy count is extended to the faint end at mag. However, for the main concentration A1775B (panel b), the best fit of LF with Schechter function shows mag, and , which exhibits a deficit of galaxies fainter than mag. Meanwhile, there are many relatively bright galaxies between mag and mag in this subcluster. The difference of LFs between the two subclusters is rather significant, which is due to the different galaxy contents of these two regions. A1775B has a higher fraction of bright/massive galaxies, and a drop can be expected near mag. For the poor and loose subcluster A1775A, faint galaxies are predominant. The observed paucity of faint galaxies in A1775B can be partially explained by the fact that faint galaxies may have been swallowed by relatively bright galaxies. Hence the richer system A1775B might be a more dynamically evolved system and the poorer systems A1775A might evolve marginally slower.
Since BATC photometry is complete down to mag (see Table 1), all member galaxies brighter than mag corresponding to mag should have been detected by BATC. However, the cluster members we added in analyzing the LFs were selected by the clipping method and since there is a bias between and , the completeness of members galaxies in sample II down to mag may not reach 100%. Conservatively, at least 85% of the member galaxies are included in this galaxy sample and the estimated fraction of field galaxy contamination is below 3%.
The spatial variations of the LF faint end are also mentioned by other authors. The work of Yang et al. (2004) reveals that cluster A168 consists of two merging subclusters; the LF of A168S shows a decay tail, while the LF of A168N shows an increasing one. They interpreted it by the cannibalism model of Hausman & Ostriker (1978), and regarded the formation and evolution of these two subclusters might be different. The nearby cluster Coma is also a good example. Adami et al. (2007) found that there is clearly a dichotomy between the LF in the north-northeast regions and the LF in the south-southwest regions. The former has a steeply rising LF end, but the latter has a much flatter LF end. They believe that the merging of faint galaxies with brighter objects may partly paly a role in flattening the faint end slope of the LF. Moreover, by using a sample of clusters with only two substructures, Krywult (2007) investigated the LF of galaxies in each substructure. He also found a similar result with us: the end slope of the LF is lower in the dominant substructure than in the second one.
4.5 Star Formation Histories of Member Galaxies
The star formation histories (SFHs) of galaxies in a cluster may shed some light on the dynamical evolution of the cluster. Within our field of view, there are 136 member galaxies that have been spectroscopically observed by the SDSS, which facilitates us to investigate the SFHs of galaxies with different morphological types, and to explore the environmental effect on the SFHs of the member galaxies.
The spectra of these galaxies are extracted from the SDSS DR6. We take the STARLIGHT spectral synthesis code (Bruzual & Charlot 2003) which aims to decompose an observed spectrum into a series of simple stellar populations (SSPs) of various ages and metallicities. Each SSP contributes a fraction (j=1,,) to the flux at a chosen normalization wavelength (). By running STARLIGHT, astrophysically interesting output can be obtained, such as the SFHs of a galaxy, its extinction and velocity dispersion (Cid Fernandes et al. 2005). A base of SSPs were used from the evolutionary synthesis models of Bruzual & Charlot (2003), spanning 15 ages () between 1 Myr to 13 Gyr and 3 metallicities, 0.2, 1, and 2.5 . Stellar extinction was modelled with the extinction law of Cardelli, Clayton & Mathis (1989) with . Here, we mainly emphasis on the statistics of the characteristic stellar ages for all of these member galaxies. To characterize the SFH of a specific galaxy, the mean stellar age, which is defined to condense the whole age distribution of SSPs to a single number, is used (Asari et al. 2007),
where the subscript L denotes a light-weighted average.
Many previous works have focused on studying the variation of SFHs with the Hubble type (Gallagher et al. 1984; Sandage 1986; Abraham et al. 1999). They suggested that the properties of the Hubble sequence in past times can be systematized by considering the time variation of the star-formation rate. In our work, the morphological types were obtained by our SED-fitting code based on the HYPERZ, and the classification indices, ranging from 1 to 7, are defined to denote E, S0, Sa, Sb, Sc, Sd, and Im galaxies, respectively. Figure 10 shows the mean stellar ages of member galaxies in A1775A (denoted by “”) and A1775B (denoted by “”) along the Hubble sequence. In general, the light-weighted mean stellar ages of early-type galaxies are found to be systematically greater than those of late-type galaxies, and they exhibit a larger dispersion. Among all of the different types of galaxies, the mean stellar age distribution of S0 galaxies is very similar to that of E galaxies. For the late-type galaxies, the more significant is the disk that the galaxy possesses, the younger is the mean stellar age that it has. It is likely that early-type galaxies burst their star-formation activity at an early epoch and deplete the gas rapidly, and no gas disk in such galaxies can be seen now. Meanwhile, late-type galaxies exhibit on average a more protracted SFH. Since the stellar mass and dynamical environment could also influence the SFHs, a certain dispersion in the distribution of the mean stellar ages is reasonable, even for those galaxies with the same Hubble type.
It is well accepted that environment plays a key role in the evolution of galaxies (Gobat et al. 2008; Braglia et al. 2009). Figure 11 shows how the galaxies’ SFHs vary with their distances to the center of each subcluster, which is defined by the peaks of X-ray surface brightness. For subcluster A1775B (panel b), the mean stellar ages of galaxies seem to decrease with the increasing cluster centric distance. A linear fit to member galaxies of A1775B gives , and the correlation coefficient is -0.34. This trend is partly due to the contribution of the morphology-density relation (Dressler 1980). The majority of early-type galaxies reside in the core region of A1775B (with a radius smaller than 1 Mpc), they have relatively high mean stellar ages, while most late-type galaxies residing in the outskirts of A1775B have lower mean stellar ages, on average. To separate between the morphology-density relation and the SF-density relation, the galaxy sample is divided into two populations, the early-type (denoted by “”) and the late-type galaxies (denoted by “”). It is noticed that the early-type galaxies present a similar trend to the age gradient shown by the solid line in Figure 11b, while the late-type galaxies seem to show an opposite trend. A physical interpretation of this phenomenon is beyond the scope of this paper. However, for galaxies in A1775A, no clear environment effect on the galaxies’SFHs is found, and a large dispersion can be seen, even for galaxies in the core region. To further investigate the environmental trend of the late-type galaxies in a cluster, more member galaxies and a sample of clusters are needed. It should be mentioned that the fraction of late-type galaxies in A1775A is about 28%, more than that in A1775B (19%), which indicates that the loose subcluster A1775A is still a dynamically young system.
This paper presents the multicolor photometry for the nearby rich cluster of galaxies A1775, using the 60/90 cm Schmidt Telescope of the NAOC. A1775 is also covered by SDSS photometry and spectroscopy. After an aperture correction of the SDSS magnitudes and a flux calibration of the BATC magnitudes, the SEDs obtained by these two photometric systems were carefully combined. For a sample of bright galaxies with known spectroscopic redshifts, by comparing their with , the reliability of the combined SEDs could be verified. For galaxies without redshift information, after applying the photometric redshift technique, 146 faint galaxies were selected as probable cluster members. By adding them to the sample of 151 spectroscopically confirmed member galaxies (sample I), we achieved an enlarged sample of 297 cluster galaxies (sample II).
Based on the positions and redshifts of member galaxies in A1775, the spatial distribution and dynamics of the cluster galaxies were investigated. Spatially, A1775 has a double structure, a subcluster with a lower redshift, A1775A, is located about SE to the main concentration A1775B. These two substructures are also detected in the X-ray brightness map. The spatial distribution of the galaxies in sample II makes the substructure A1775A more significant, and a new clump A1775C is found. The KMM partition of the galaxies in sample I shows that there are 49 and 102 spectroscopically confirmed member galaxies in A1775A and A1775B, respectively. Compared with the main concentration A1775B, A1775A appears to be a poor and loose subcluster with a smaller velocity dispersion of . Two central dominant elliptical galaxies, one of them associated with the head-tail radio source, are assigned to different subclusters. The original dominant galaxy in A1775A seems to be “pulled out” by the gravitation of the main subcluster A1775B.
With the 20-band SEDs of the member galaxies, the LF function for
each subcluster was fitted. Supplementing the faint member galaxies
makes it possible to constrain the LF shape at the faint end. The
remarkable difference in the LFs between the two subclusters indicates
that they are at different stages of dynamical evolution. A1775B is
a more dynamically evolved system, while A1775A is still dynamically
young. In fact, the spatial variations of the LF faint end have also
been noticed by other authors. This phenomena are more common
in clusters with substructures, especially with bimodal structures
(Adami et al. 2007; Yang et al. 2004; Krywult 2007). The similar
results of other people give us confidence in our result. By the
STARLIGHT spectral synthesis code, the SFHs of the member galaxies
with available SDSS spectroscopy have been studied. The variations
of the mean stellar ages with Hubble type have been verified,
in the sense that early-type galaxies are likely to have higher
mean stellar ages. The environmental effect on the mean stellar ages
of cluster galaxies is found in A1775B. The galaxies in the core
region of A1775B are likely to have longer mean stellar ages,
which means that these massive galaxies form the bulk of their
stars earlier than those in the outskirts. Such an environmental
effect is not found for galaxies in the poor subcluster A1775A.
We would like to thank the referee who gives the invaluable suggestions to improve the paper. Our research is based on data collected at National Astronomical Observatory of China, which is operated by Chinese Academy of Sciences. We are grateful to all staff members for their support during observations. The database SDSS and NED are also used in our work. We would like to thank Prof. Weihao Bian, Mr. Wei Jing at the Nanjing Normal university, Prof. Jun Ma, Jianghua Wu, and Zhenyu Wu at the National Astronomical Observatories and Prof. Kong Xu, Dr. Lin Lin at the University of Science and Technology of China for stimulating discussion and helpful suggestions. This work was supported by the National Natural Science Foundation of China (NSFC) under Nos.10778618 and 10633020, and by the National Basic Research Program of China (973 Program) under No.2007CB815403.
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|1||13 39 52.04||26 10 13.3||0.0727||a, B||77||13 42 02.46||26 20 43.3||0.0750||a, B|
|2||13 39 54.78||26 23 12.9||0.0747||a, B||78||13 42 02.84||26 21 38.3||0.0753||a, B|
|3||13 39 59.18||26 09 02.0||0.0740||a, B||79||13 42 05.03||26 36 05.6||0.0764||a, B|
|4||13 40 08.69||26 10 38.2||0.0652||a, A||80||13 42 05.13||26 34 49.3||0.0756||a, B|
|5||13 40 11.08||26 03 30.9||0.0778||a, B||81||13 42 06.02||26 20 10.3||0.0771||a, B|
|6||13 40 12.19||26 14 52.4||0.0764||a, B||82||13 42 06.69||26 16 19.3||0.0760||a, B|
|7||13 40 13.57||26 33 54.7||0.0831||c, B||83||13 42 06.83||26 22 14.3||0.0771||a, B|
|8||13 40 13.90||26 33 52.1||0.0758||a, B||84||13 42 09.78||26 33 44.8||0.0741||a, B|
|9||13 40 20.19||26 09 39.7||0.0729||a, B||85||13 42 10.56||26 09 12.6||0.0661||a, A|
|10||13 40 30.67||26 39 39.7||0.0769||a, B||86||13 42 10.86||26 20 06.4||0.0779||a, B|
|11||13 40 31.05||26 18 26.6||0.0625||c, A||87||13 42 14.45||26 13 20.0||0.0734||a, B|
|12||13 40 35.35||26 00 53.6||0.0755||a, B||88||13 42 16.88||26 33 33.4||0.0765||a, B|
|13||13 40 38.40||26 20 11.0||0.0758||a, B||89||13 42 18.28||26 19 20.3||0.0753||a, B|
|14||13 40 41.21||26 36 55.4||0.0649||a, A||90||13 42 20.84||26 11 50.5||0.0661||a, A|
|15||13 40 42.35||26 24 38.2||0.0750||a, B||91||13 42 24.62||26 28 23.5||0.0659||a, A|
|16||13 40 44.21||26 13 44.7||0.0775||a, B||92||13 42 25.61||26 12 44.8||0.0658||a, A|
|17||13 40 44.89||26 11 11.2||0.0645||a, A||93||13 42 25.62||26 26 27.3||0.0716||a, B|
|18||13 40 46.85||26 31 41.7||0.0690||a, A||94||13 42 26.23||26 32 12.6||0.0763||a, B|
|19||13 40 47.89||26 11 43.1||0.0756||c, B||95||13 42 29.82||25 58 19.6||0.0735||a, B|
|20||13 40 48.92||26 04 17.1||0.0656||b, A||96||13 42 31.87||26 29 14.0||0.0655||a, A|
|21||13 40 49.16||26 29 15.5||0.0648||a, A||97||13 42 33.38||26 37 31.8||0.0759||a, B|
|22||13 40 49.74||26 03 51.5||0.0650||d, A||98||13 42 35.66||26 15 34.0||0.0639||a, A|
|23||13 40 50.52||26 05 54.6||0.0652||a, A||99||13 42 35.87||26 23 02.1||0.0771||a, B|
|24||13 40 53.43||26 21 00.8||0.0775||a, B||100||13 42 37.12||26 34 38.3||0.0731||a, B|
|25||13 40 55.55||26 17 57.0||0.0739||a, B||101||13 42 39.43||26 25 54.1||0.0736||a, B|
|26||13 40 55.60||26 15 18.3||0.0752||a, B||102||13 42 39.87||26 09 35.7||0.0654||a, A|
|27||13 40 55.95||26 24 51.8||0.0759||a, B||103||13 42 41.39||26 14 23.3||0.0664||a, A|
|28||13 40 56.59||26 29 12.3||0.0750||a, B||104||13 42 41.46||26 28 13.3||0.0645||a, A|
|29||13 40 57.07||26 10 21.6||0.0634||a, A||105||13 42 41.99||26 14 23.2||0.0654||b, A|
|30||13 40 58.86||26 35 05.2||0.0759||a, B||106||13 42 42.02||26 17 09.7||0.0677||a, A|
|31||13 41 00.52||26 29 07.2||0.0760||b, B||107||13 42 43.22||26 12 16.0||0.0658||a, A|
|32||13 41 06.32||26 36 52.6||0.0773||a, B||108||13 42 44.86||26 10 58.1||0.0663||a, A|
|33||13 41 06.38||26 15 31.5||0.0805||a, B||109||13 42 46.36||26 17 30.9||0.0665||a, A|
|34||13 41 07.95||26 30 48.3||0.0703||a, B||110||13 42 47.07||26 18 33.6||0.0739||a, B|
|35||13 41 13.43||26 29 33.2||0.0734||a, B||111||13 42 47.17||26 21 53.9||0.0644||a, A|
|36||13 41 16.60||26 23 35.8||0.0736||a, B||112||13 42 48.34||26 45 00.1||0.0764||a, B|
|37||13 41 17.08||26 16 19.4||0.0639||a, A||113||13 42 50.81||26 16 40.5||0.0731||a, B|
|38||13 41 18.04||26 47 51.4||0.0765||a, B||114||13 42 52.17||26 12 10.7||0.0643||a, A|
|39||13 41 19.72||26 21 14.8||0.0734||a, B||115||13 42 52.86||26 35 33.3||0.0696||a, B|
|40||13 41 20.05||25 53 25.7||0.0735||a, B||116||13 42 53.79||26 08 37.8||0.0719||a, B|
|41||13 41 20.11||26 30 06.7||0.0707||a, B||117||13 42 54.30||26 13 57.1||0.0743||a, B|
|42||13 41 22.94||26 28 09.4||0.0795||a, B||118||13 42 55.45||26 16 28.0||0.0763||a, B|
|43||13 41 25.93||26 33 12.4||0.0747||a, B||119||13 42 57.45||26 25 30.1||0.0733||a, B|
|44||13 41 27.21||26 25 41.8||0.0749||a, B||120||13 42 57.86||26 02 25.0||0.0659||a, A|
|45||13 41 29.17||26 10 08.2||0.0768||a, B||121||13 42 57.99||25 56 23.2||0.0632||a, A|
|46||13 41 32.25||26 01 27.6||0.0662||a, A||122||13 42 59.01||26 15 49.3||0.0673||a, A|
|47||13 41 35.18||26 21 24.0||0.0726||a, B||123||13 43 03.34||26 45 08.5||0.0757||a, B|
|48||13 41 36.69||26 41 26.4||0.0779||a, B||124||13 43 07.49||26 03 26.9||0.0672||a, A|
|49||13 41 37.42||26 20 27.6||0.0781||a, B||125||13 43 09.64||26 10 40.6||0.0644||a, A|
|50||13 41 38.59||26 06 09.7||0.0640||a, A||126||13 43 10.24||25 56 59.1||0.0612||a, A|
|51||13 41 38.90||26 28 47.4||0.0769||a, B||127||13 43 12.10||26 02 24.5||0.0616||a, A|
|52||13 41 38.95||26 14 27.9||0.0707||a, B||128||13 43 14.77||26 00 57.4||0.0846||a, B|
|53||13 41 39.52||26 09 22.4||0.0749||a, B||129||13 43 15.32||26 39 03.9||0.0760||a, B|
|54||13 41 39.97||26 25 11.4||0.0648||a, A||130||13 43 15.55||26 09 57.8||0.0647||b, A|
|55||13 41 40.11||26 29 40.3||0.0753||a, B||131||13 43 15.84||26 09 52.8||0.0642||a, A|
|56||13 41 41.24||26 17 45.2||0.0724||a, B||132||13 43 17.21||26 30 34.8||0.0750||a, B|
|57||13 41 42.42||26 15 31.9||0.0738||a, B||133||13 43 17.28||26 19 43.2||0.0775||a, B|
|58||13 41 43.81||26 17 36.2||0.0757||b, B||134||13 43 18.32||26 14 07.1||0.0660||a, A|
|59||13 41 46.49||26 19 35.0||0.0744||a, B||135||13 43 22.85||26 26 36.9||0.0769||a, B|
|60||13 41 47.14||26 27 34.3||0.0779||a, B||136||13 43 25.33||26 13 10.6||0.0742||a, B|
|61||13 41 47.19||26 22 51.4||0.0772||a, B||137||13 43 29.13||26 29 36.7||0.0764||a, B|
|62||13 41 49.14||26 22 24.5||0.0757||f, B||138||13 43 29.44||26 09 32.8||0.0661||a, A|
|63||13 41 49.83||26 08 41.6||0.0732||a, B||139||13 43 30.99||25 55 52.9||0.0642||a, A|
|64||13 41 50.45||26 22 13.0||0.0694||a, A||140||13 43 31.08||26 42 03.1||0.0787||a, B|
|65||13 41 50.60||26 21 10.6||0.0759||a, B||141||13 43 42.26||26 15 47.1||0.0745||a, B|
|66||13 41 50.91||26 22 28.3||0.0750||e, B||142||13 43 45.77||26 20 15.8||0.0735||a, B|
|67||13 41 51.81||26 05 56.9||0.0661||a, A||143||13 43 49.09||26 09 27.0||0.0833||a, B|
|68||13 41 53.39||26 25 12.6||0.0773||a, B||144||13 44 00.22||26 44 42.8||0.0712||a, B|
|69||13 41 54.08||26 22 50.8||0.0758||a, B||145||13 44 01.90||25 56 28.3||0.0620||a, A|
|70||13 41 55.13||26 20 35.7||0.0736||a, B||146||13 44 02.81||26 09 05.7||0.0666||a, A|
|71||13 41 56.48||26 27 16.4||0.0736||a, B||147||13 44 02.86||26 06 35.8||0.0672||a, A|
|72||13 41 57.71||26 24 17.1||0.0767||a, B||148||13 44 03.33||26 18 12.8||0.0653||a, A|
|73||13 41 58.54||26 21 46.3||0.0748||a, B||149||13 44 05.41||26 20 17.7||0.0770||a, B|
|74||13 41 59.50||26 23 18.3||0.0734||a, B||150||13 44 08.67||26 20 56.1||0.0651||a, A|
|75||13 42 00.48||26 18 38.2||0.0782||a, B||151||13 44 09.92||26 48 02.9||0.0734||a, B|
|76||13 42 02.30||26 10 42.8||0.0744||a, B|