DLA, subDLA, and LLS galaxies

A Groundbased Imaging Study of Galaxies Causing DLA, subDLA, and LLS Absorption in Quasar Spectra1

Abstract

We present results from a search for galaxies that give rise to damped Lyman alpha (DLA), subDLA, and Lyman limit system (LLS) absorption at redshifts in the spectra of background quasars. The sample was formed from a larger sample of strong Mg ii absorbers ( Å) whose H i column densities were determined by measuring the Ly line in HST UV spectra. Photometric redshifts, galaxy colours, and proximity to the quasar sightline, in decreasing order of importance, were used to identify galaxies responsible for the absorption. Our sample includes 80 absorption systems for which the absorbing galaxies have been identified, of which 54 are presented here for the first time. In some cases a reasonable identification for the absorbing galaxy could not be made.

The main results of this study are: (i) the surface density of galaxies falls off exponentially with increasing impact parameter, , from the quasar sightline relative to a constant background of galaxies, with an e-folding length of kpc. Galaxies with kpc calculated at the absorption redshift are statistically consistent with being unrelated to the absorption system, and are either background or foreground galaxies. (ii) is inversely correlated with at the 3.0 level of significance. DLA galaxies are found systematically closer to the quasar sightline, by a factor of two, than are galaxies which give rise to subDLAs or LLSs. The median impact parameter is 17.4 kpc for the DLA galaxy sample, 33.3 kpc for the subDLA sample, and 36.4 kpc for the LLS sample. We also find that the decline in with can be roughly described by an exponential with an e-folding length of 12 kpc that occurs at . (iii) Absorber galaxy luminosity relative to , , is not significantly correlated with , , or . (iv) DLA, subDLA, and LLS galaxies comprise a mix of spectral types, but are inferred to be predominantly late type galaxies based on their spectral energy distributions. (v) The properties of low-redshift DLAs and subDLAs are very different in comparison to the properties of gas-rich galaxies at the present epoch. A significantly higher fraction of low-redshift absorbers have large values, and a significantly higher fraction of the large value galaxies have luminosities . The implications of these results are discussed.

keywords:
quasars: absorption lines – galaxies: ISM – galaxies: statistics
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1 Introduction

The recognition that damped Ly absorption-line systems (DLAs) seen in quasar spectra arise in neutral-gas-rich foreground galaxies (Wolfe et al. 1986) motivated new methods for high-redshift galaxy studies years ago. These high HI column density systems, with atoms cm, trace the bulk of the observed neutral gas in the Universe, and they are, therefore, powerful probes of galaxy formation and evolution back to the redshifts of the most distant quasars. Larger datasets and deeper surveys (e.g. Prochaska, Herbert-Fort, & Wolfe 2005; Rao, Turnshek, & Nestor 2006, henceforth, RTN06; Noterdaeme et al. 2009) have improved our knowledge of the neutral gas content and distribution at all observable redshifts, including the present epoch (Ryan-Weber et al. 2003; Zwaan et al. 2005). No other technique has revealed comparable reservoirs of neutral gas beyond the local Universe. See Rao (2005) and Wolfe et al. (2005) for some past reviews. Few DLAs were known at low redshift prior to the turn of the century because the Ly line falls in the UV for . Thus, in the absence of large UV spectroscopic surveys, this meant that studies of neutral gas in what corresponds to the most recent % of the age of the Universe10 were problematic. But now MgII-based UV spectroscopic surveys (with HST-FOS, HST-STIS, HST-ACS Grism, and GALEX Grism) are identifying significant numbers of low-redshift DLAs and subDLAs (Rao & Turnshek 2000; RTN06; Monier et al. 2009a; Turnshek et al. in prep). The Mg ii -based surveys for DLAs, which are designed to be unbiased (RTN2006), can be used to infer the incidence and cosmic neutral gas mass density at (e.g. RTN06). Also, while subDLA absorbers, those with atoms cm, do not contribute much to the cosmic neutral gas mass density (Péroux et al. 2005), they are often found to have higher metallicities than DLAs (Kulkarni et al. 2007 and references therein). Lyman Limit System (LLS) absorbers are simply those with atoms cm. Both subDLAs and LLSs generally exhibit Mg ii absorption, and all strong Mg ii systems, those with Å, are Lyman limit systems (e.g., Churchill et al. 2000). However, unbiased Mg ii -based surveys for subDLAs and LLS have never been implemented.

With the identification of DLAs (and subDLAs and LLSs), follow-up work involving the study of their host galaxies, environments, neutral-gas-phase metallicities, kinematics, 21 cm spin temperatures (when possible), ionization conditions, and numerical and semi-analytic modeling has kept many astronomers busy for decades.11 Despite this, a consensus on certain aspects of DLAs is still lacking. Our previous studies indicated that DLA galaxies are of mixed morphology and that the highest systems have the smallest impact parameters, but are hosted by low luminosity () galaxies (Rao et al. 2003; Turnshek et al. 2001; see also Chun et al. 2006). On the other hand, while Chen & Lanzetta (2003) and Chen, Kennicutt, & Rauch (2005) conclude that DLA galaxies span a mix of morphological types, they also propose that a large contribution from dwarf galaxies is not required to explain the properties of DLAs. In addition, Zwaan et al. (2005) suggest that the local galaxy population can completely explain the properties of known low-redshift DLA galaxies. Studies of Mg ii galaxies, of which DLAs form a subset, have also revealed a mix of morphological types (e.g. Churchill, Kacprzak, and Steidel 2005; Kacprzak et al. 2007), although most appear to be spirals and the majority exhibit minor perturbations (as seen in HST images). From stacked images of over 2800 SDSS quasar sightlines containing MgII absorption, Zibetti et al. (2007) derive an Sbc-type average colour and average luminosity for the absorbing galaxies. Images of quasar sightlines with “ultra-strong” Mg ii systems12 point to outflows from bright () starbursting galaxies as the cause of the kinematically-complex absorption (Nestor et al. 2007; 2010). A large fraction of these are known to be DLAs (RTN06). However, the ultra-strong Mg ii regime is not addressed in this paper.

Semi-analytic and numerical models, some of which are based on results from high-resolution spectroscopic data of DLA metal absorption lines, have resulted in a variety of often competing scenarios for DLAs: large rapidly rotating protogalactic disks (Prochaska & Wolfe 1997, 1998; Wolfe & Prochaska 1998), merging protogalactic clumps in a hierarchical merging scenario (Haehnelt et al. 1998), low surface brightness galaxies (Jimenez et al. 1999), dwarf galaxies (Okoshi & Nagashima 2005), compact, faint galaxies with impact parameters smaller than 5 kpc at (Nagamine et al. 2007), and the outer regions of high- Lyman break galaxies (Møller et al. 2002; Wolfe et al. 2003). Recent high-quality H i 21 cm data of local galaxies indicate that DLA gas velocity widths are more consistent with tidal gas related to galaxy interactions or superwinds rather than galaxy disks (Zwaan et al. 2008). In addition, some recent compelling cosmological simulations relevant to interpreting the nature of Mg ii -selected galaxies in general, and DLA galaxies in particular, have been presented by Kacprzak et al. (2010).

However, there is a dearth of identified DLA (and subDLA) galaxies, and this has undoubtedly motivated the various interpretive scenarios. Therefore, larger samples of neutral-gas-selected galaxies are required to investigate the possibilities, which in turn will help constrain models of galaxy evolution and better establish the galaxy population that harbors the bulk of the neutral gas in the Universe. Traditional galaxy surveys trace galaxies by virtue of their luminous emission. Beyond the local Universe far less is known about neutral-gas-selected galaxies and their relationship to luminosity-selected galaxies.

As an extension of our earlier work (Rao et al. 2003), we have undertaken a large multi-colour optical/IR imaging programme of quasar fields containing Mg ii absorbers with measured . The absorbers were selected from Table 1 of RTN06, and were required to have absorption redshifts to optimize the possibilities for detection and characterization of galaxies in these fields. Data and results from eight DLAs in six quasar fields were presented in Turnshek et al. (2001), Rao et al. (2003), and Turnshek et al. (2004). Other observations from the literature were also considered. In total, 27 DLA, 30 subDLA, and 23 LLS galaxies (i.e. 80 absorbers in total) have been identified. In this paper, we present and analyse the entire dataset. These observations are described in §2. The identification of galaxies is described in §3 through specific examples. The entire dataset can be accessed on line at http://enki.phyast.pitt.edu/Imaging.php. A summary of the data and statistical inferences are presented in §4. Conclusions and discussion are presented in §5 and 6, respectively. Among other findings this work demonstrates that the neutral hydrogen column density, , is strongly correlated with impact parameter, , in the sense that DLA galaxies are systematically closer to the quasar sightline, by a factor of two, than are galaxies which give rise to subDLAs and LLSs. We also find that the properties of low-redshift () DLAs and subDLAs are very different in comparison to the properties of H i -rich galaxies at the present epoch. A significantly higher fraction of low-redshift absorbers have large , and a significantly higher fraction of the large galaxies have luminosities .

All magnitudes reported in this paper are in the AB system, and all distance related quantities are calculated using the “737” cosmology with () = (0.7,0.3,0.7).

2 Observations

The imaging data were obtained between December 1998 and June 2005 through community-access time at national facilities as well as through Ohio State University’s share of time at the MDM Observatory. The various telescopes and detectors that were employed, as well as the varying observing conditions that prevailed over the better part of a decade of observations, resulted in an unavoidably inhomogeneous dataset. Nevertheless, since most of the data are well calibrated and reach fainter magnitudes than large groundbased surveys such as the Sloan Digital Sky Survey, this observing programme has yielded the most useful and comprehensive set of images of DLA, subDLA, and LLS absorption-line-producing galaxies that has thus far been obtained.

The optical images were obtained at Kitt Peak National Observatory in Arizona. The telescopes and corresponding detectors used were 1) the KPNO 2.1 m with the T2KA or T2KB CCDs covering a 10.4′  10.4′ field-of-view at a scale of 0.305/pixel, 2) the MDM Observatory 2.4 m Hiltner with the 1024 1024 Templeton CCD covering a 4.72′  4.72′ field-of-view at 0.275 /pixel, and 3) the 3.5 m WIYN with the Tip-Tilt Module (WTTM) covering a 3.84′  4.69′ field-of-view at 0.1125/pixel. The near-infrared images were obtained on Mauna Kea, Hawaii, with the NASA IRTF 3.0 m telescope using NSFCAM which has a 76.8 76.8 field-of-view at 0.30 /pixel. The detector was the 256256 InSb array. A few images were obtained with the SpeX infrared slit-viewer/guider covering a 60 60 field-of-view at 0.12 /pixel with the Raytheon 512 512 InSb array. The optical images taken with the KPNO 2.1 m or WIYN telescopes were obtained using the Johnson-Cousins or KPNO SLOAN filters, and those observed at MDM were observed with the MDM Gunn-Thuan filters. Henceforth, we ignore the differences between the SDSS and Gunn-Thuan filter sets since the transformation between them is small. Near-infrared images were taken using the standard Mauna Kea Observatory filter set.

Optical data were taken in groups of 3 or 4 offset exposures ranging from 900 to 1800 seconds per exposure, and standard data reduction procedures were followed. The infrared observations were carried out using a series of either 30 or 60 dithered short exposures ranging from 2 to 20 seconds per exposures. The individual exposure times were chosen to prevent the quasar point spread function from saturating. Flat fielding was done using sky frames constructed from the dithered object frames. Landolt standards were used to calibrate the Johnson-Cousins observations (Landolt 1992). Photometric calibration of fields that overlapped with SDSS images was performed by comparing our instrumental magnitudes with the SDSS DR4 photometry of point sources. The photometric zeropoint solution with corresponding errors for each frame were determined by a least squares fit to the SDSS magnitudes and our instrumental magnitudes. Generally, 10 or more isolated, unsaturated stars that were common to our images and the SDSS fields were used in the calibration. UKIRT faint photometric standards (Hawarden et al. 2001) were used to calibrate the near-infrared observations.

Table 1 lists the fields for which we obtained imaging data. The first six columns give details about the absorption-line system from RTN06. Column 1 gives the quasar name, column 2, the quasar magnitude, column 3, the quasar emission redshift, column 4 gives the redshift of the Mg ii absorption-line system, column 5 the rest equivalent width of the stronger member (2796) of the Mg ii doublet, and column 6 gives the H i column density as measured from the HST UV spectrum. Column 7 lists the optical and infrared filters through which images of each quasar field were obtained. Here we summarize a few salient features of the dataset.

Quasar Mag.13 MgII MgII (Å) (cm) Filters
0021+0043 17.7 1.245 0.5203 0.5330.036 JHK
0.9420 1.7770.035
0041266 17.8 3.053 0.8626 0.670.06 18.00 R
0058+019 17.2 1.959 0.6127 1.6660.00314 UIK
01070019 18.3 0.738 0.5260 0.7840.080 JHK
01160043 18.7 1.282 0.9127 1.3790.096 JHK
0117+213 16.1 1.491 0.5764 0.910.04 UBRIJHK
01230058 18.6 1.551 0.8686 0.7570.098 18.62 JHK
01380005 18.7 1.340 0.7821 1.2080.096 JHK
01390023 19.0 1.384 0.6828 1.2430.102 JHK
0141+339 17.6 1.450 0.4709 0.780.07 g’r’i’JK
0152+0023 17.7 0.589 0.4818 1.3400.057 H
0153+0009 17.8 0.837 0.7714 2.9600.051 JHK
0253+0107 18.8 1.035 0.6317 2.5710.166 g’r’i’JHK
0254334 16.0 1.849 0.2125 2.23 BRIJK
0256+0110 18.8 1.349 0.7254 3.1040.115 g’HK
0420014 17.0 0.915 0.6331 0.750.0215 BRIJHK
0454+039 16.5 1.343 0.8596 1.450.01 JHK
0710+119 16.6 0.768 0.4629 0.620.06 18.30 g’r’
0735+178 14.9 0.4240 1.320.03 19.00 UBRIJHK
0843+136 17.8 1.877 0.6064 0.9380.03516 u’g’r’i’JHK
09530038 18.4 1.383 0.6381 1.6680.080 urJHK
0957+003 17.6 0.907 0.6720 1.9360.11817 UBRIJHK
10090026 17.4 1.244 0.8426 0.7130.038 JHK
0.8866 1.9000.039
1009+0036 19.0 1.699 0.9714 1.0930.111 JHK
1019+309 17.5 1.319 0.3461 0.700.05 K
10280100 18.2 1.531 0.6322 1.5790.087 JHK
0.7087 1.2100.066
10470047 18.4 0.740 0.5727 1.0630.117 JHK
1048+0032 18.6 1.649 0.7203 1.8780.063 u’g’r’i’JHK
1107+0048 17.5 1.392 0.7404 2.9520.025 ugriJHK
1109+0051 18.7 0.957 0.4181 1.3610.105 g’r’i’JHK
0.5520 1.4170.085
1209+107 17.8 2.193 0.3930 1.000.07 u’g’r’i’JHK
0.6295 2.6190.08318
1225+0035 18.9 1.226 0.7730 1.7440.138 JHK
1226+105 18.5 2.305 0.9376 1.6460.11019 UBRJHK
13230021 18.2 1.390 0.7160 2.2290.071 ugriJHK
13420035 18.2 0.787 0.5380 2.2560.068 ugriJHK
13450023 17.6 1.095 0.6057 1.1770.049 u’g’r’i’JHK
1354+258 18.0 2.006 0.8585 1.1760.07620 BRIJK
0.8856 0.4890.06921
14190036 18.3 0.969 0.6238 0.5970.069 HK
0.8206 1.1450.057
1426+0051 18.8 1.333 0.7352 0.8570.080 u’g’r’i’JHK
0.8424 2.6180.125
14310050 18.1 1.190 0.6085 1.8860.076 ugriJHK
0.6868 0.6130.066
14360051 18.5 1.275 0.7377 1.1420.084 u’g’r’i’JHK
0.9281 1.1740.065 18.82
1437+624 19.0 1.090 0.8723 0.710.09 18.00 K
15210009 19.0 1.318 0.9590 1.8480.096 u’r’g’i’J
1525+0026 17.0 0.801 0.5674 1.8520.035 BRIJHK
1622+239 17.5 0.927 0.6561 1.4710.05022 K
0.8913 1.6220.04223
Table 1: The Imaging Sample
Quasar Mag.24 MgII MgII (Å) (cm) Filters
1704+608 15.3 0.371 0.2220 0.5620.01325 IJK
1714+5757 18.6 1.252 0.7481 1.0990.084 ugriJHK
1715+5747 18.3 0.697 0.5579 1.0010.067 u’g’r’i’JHK
1716+5654 19.0 0.937 0.5301 1.8220.130 ugri’JH
1722+5442 18.8 1.215 0.6338 1.5350.098 u’g’r’i’
1727+5302 18.3 1.444 0.9448 2.8320.070 u’g’r’i’JHK
1.0312 0.9220.057
1729+5758 17.5 1.342 0.5541 1.8360.046 u’g’r’i’JHK
1733+5533 18.0 1.072 0.9981 2.1730.069 u’g’r’i’HK
1857+566 17.3 1.578 0.7151 0.65 UBRIJHK
2149+212 19.0 1.538 0.9114 0.72 UBRIJK
1.0023 2.46
2212299 17.4 2.706 0.6329 1.150.0226 BRJK
2223052 18.4 1.404 0.8472 0.5860.01227 BI
2328+0022 17.9 1.308 0.6519 1.8960.077 g’r’i’JHK
2334+0052 18.2 1.040 0.4713 1.2260.107 g’r’i’JHK
23530028 17.9 0.765 0.6044 1.6010.082 JHK
Table 1: Continued

We were able to obtain a complete optical and infrared (UBRIJHK or ugriJHK) dataset for 18 of the 60 fields. The largest number of fields, 53, were observed in K, while the fewest, 26, were observed in U (or u). Figure 1 gives the distribution of 3 surface brightness limits reached in each filter. The infrared data show the least spread since almost all were obtained with the IRTF NSFCAM, with the exception of two observations with the (low-sensitivity) IRTF SpeX guide camera.

Since the K-band data are the most extensive as well as uniform, we illustrate a few properties of the dataset using the K-band data sample. Figure 2 is a plot of the K-band galaxy luminosity limit (in terms of , where for , Cirasuolo et al. 2006) as a function of redshift. Here, the limiting K-band surface brightness was used to estimate the luminosity of a fiducial 10 kpc-sized galaxy that can be detected at the redshift of the absorber. K-corrections appropriate for an Sb type galaxy have been applied to all datapoints.

The distribution of seeing values for our data, expressed in terms of the FWHM of a point source, is shown in Figure 3. The seeing is a particularly important parameter for this study because the quasar point spread function (PSF) limits our ability to study the smallest impact parameters. For ground-based imaging, techniques such as adaptive optics (AO) achieve seeing values down to a few tenths of an arcsecond. However, the presence of a bright (12 to 15 magnitude), nearby (within 30″), point source is generally required for implementing AO techniques. Since the (faint) quasar is the brightest object in the majority of our fields, we could not take advantage of AO. From Figure 3 it can be seen that the optical dataset has seeing values generally 1″, while for the infrared data, seeing values 1″ were often achieved. We were able to probe smaller impact parameters than the seeing radius for images where the quasar PSF could be subtracted. However, this was not possible for all fields, because suitable PSF stars were not always available within the image, and we did not observe PSF stars separately. In Figure 4 we plot minimum detection impact parameter histograms for the K-band images in arcsec as well as in kpc at the redshift of the absorbers. The minimum detection impact parameter for fields where the quasar PSF could not be subtracted is conservatively taken to be the radius at which the PSF blended with the background. This estimate depends on the brightness of the quasar as well as on the seeing. For PSF-subtracted fields, the minimum detection impact parameter is measured as the radius of the mask that was applied to the subtraction residuals. The average minimum impact parameters for all fields is kpc. The average minimum impact parameter for PSF-subtracted fields is kpc, and for non-PSF subtracted fields, it is kpc. We note here that whether the quasar PSF was, or was not, subtracted in our ground-based data has not influenced the identification of absorber galaxies (§3 and §4). For our -band sample, we find that the distribution of impact parameters of absorber galaxies identified in our PSF-subtracted fields and non-PSF-subtracted fields are similar, with Kolmogorov-Smirnov (KS) test probability .

Figure 1: Distribution of 3 surface brightness limits reached in the final reduced images for each of the seven filters.
Figure 2: K-band luminosity of a fiducial 10-kpc sized galaxy that would be detectable at the redshift of the absorber as a function of redshift for our dataset. The luminosity is expressed in terms of and is estimated from the 3 limiting surface brightness achieved for each field. K-corrections appropriate for an Sb type galaxy have been applied.
Figure 3: Distribution of seeing values obtained for observations in each filter. FWHM of point sources in the final reduced images are reported.
Figure 4: Distribution of minimum impact parameters from the quasar sightline for detection of galaxies in arcsec (left) and in kpc (right) at the redshift of the absorber. Fields for which the quasar PSF was subtracted are represented by the grey histogram. Not all fields had point sources (other than the quasar) that could be used to model the PSF, therefore, the quasar PSF was not subtracted in these fields. The minimum impact parameter for galaxy detection is, therefore, generally larger. This sample is represented by the unshaded histogram.

The identification of galaxies causing absorption in quasar spectra is, undoubtedly, best achieved from space. Not being able to probe to within 5 or 10 kpc of the quasar sightline is the most severe limitation of a groundbased imaging programme. Low luminosity dwarf galaxies directly along the quasar sightline will most likely be missed, resulting in an incorrect identification of the absorbing galaxy. Below, we attempt to quantify the possible number of missed galaxies in our sample due to this bias.

3 Identification of Absorbing Galaxy Candidates

The detection and photometry of sources were carried out using the automated software SExtractor (Bertin & Arnouts 1996). The SExtractor input parameter that defines the detection threshold for source identification was set to 1 above the sky background, and the minimum detection area was set to 5 adjoining pixels. “Adjoining” as implemented in SExtractor refers to any pixels touching at corners or sides. A source is considered to be a confident detection if it was detected at the or higher level through more than one filter. Its position was determined using the image with the best seeing.

Figure 1 shows that most of the -band data (38 fields) reach surface brightnesses between 21.5 and 22.5 magnitudes per square arcsec at the 3 level. Figure 5 gives the redshift distribution of the 38 absorbers in these fields, 24 of which have redshifts . This is a small enough redshift interval that we use a single value for the angular diameter distance to estimate the surface density of galaxies. We then use this sample to estimate: (1) the background (and foreground) number density of galaxies, (2) the excess around the quasar line of sight that can be attributed to the presence of an absorbing galaxy or galaxies associated with it, and (3) the number of absorbing galaxies that might have been missed due to the glare of the quasar PSF. Figure 6 shows the number of galaxies per square kpc as a function of impact parameter from the quasar calculated in annuli of width 10 kpc. The red line is the best-fit exponential profile to the data with an e-folding length of 46.1 kpc. The horizontal asymptote, which occurs at kpc, is shown by the blue dotted line. It represents the background plus foreground galaxy number density. Galaxies beyond kpc can be considered background or foreground galaxies that are not associated with the absorption systems. Moreover, assuming that the distribution can be extrapolated to impact parameter gives an estimate of the number of galaxies unaccounted for due to the presence of the quasar PSF and the inability to subtract it perfectly. This suggests that the expected number density at kpc is galaxies per square kpc per quasar field, and that galaxy candidates per field might have been missed. Or, on average, one in every 14 fields may have a galaxy at kpc that is not identify in our groundbased imaging survey. This amounts to approximately four among the 55 identified candidate galaxies in our survey (§4).

Figure 5: Redshift distribution of absorbers in quasar fields with -band surface brightness limits between 21.5 and 22.5 magnitudes per square arcsec.
Figure 6: The number density of galaxies as a function of impact parameter from the quasar, calculated in annuli of width 10 kpc. Only -band images with surface brightness limits between and magnitudes per square arcsec for absorbers between redshifts 0.5 and 0.8, where most of the absorption systems lie, were used. The red line is an exponential fit to the data points with an e-folding length of 46.1 kpc. The blue dotted line shows the background plus foreground galaxy number density of kpc. The discrepant point at an impact parameter of 125 kpc notwithstanding, galaxies beyond 100 kpc can, statistically, be considered background or foreground galaxies that are not associated with the absorption system.

Based on the above analysis, only objects within an impact parameter kpc from the quasar at the absorber redshift (or lowest absorber redshift in the case of multiple absorbers per quasar sightline) are catalogued for each field, since galaxies farther away can statistically be considered background or foreground galaxies.

The absorbing galaxy has not been confirmed spectroscopically for any of the fields presented here. A spectroscopic redshift that matches the absorption redshift would, of course, lead to a more confident identification of the absorbing galaxy (or a parcel of gas associated with it). In the absence of spectroscopic data, we assign a galaxy as a “candidate absorber” with varying levels of confidence based on several criteria. The highest level of confidence is achieved when a galaxy’s photometric redshift matches that of the Mg ii  absorption-line system within the uncertainties. Photometric redshifts were determined for galaxies that were detected in four or more filters.28 If more than one galaxy in the field was determined to have a photometric redshift that matched the absorption redshift, then the one closest to the quasar sightline was selected as the candidate absorber. Next, if photometric redshifts could not be determined (e.g., if a galaxy is detected in fewer than four filters), then we judged whether or not the galaxy’s colours were consistent with it being at the absorption redshift. This was done by comparing our measured galaxy colours with the colours derived from the redshifted ’hyperz’ galaxy templates of Hewett et al. (2006), after converting our AB magnitudes to Vega magnitudes. Lastly, if no colour information was available, or if a galaxy’s colours were inconclusive, then the “proximity criterion” was used, whereby the galaxy closest to the quasar sightline was selected as the candidate absorber. For sightlines with two absorbers, assignment of the absorbing galaxies was often ambiguous. Depending on the specifics of the field, we were sometimes unable to assign a galaxy to the absorber. In addition, some fields were observed under non-photometric conditions, while for others no calibration information was available. Although photometry could not be carried out for the objects in these fields, impact parameter information could nevertheless be extracted. The proximity criterion was employed in these cases as well. These galaxies are not part of the statistical sample analyzed here since no luminosity information exists for them.

We assign a “CL” value, or confidence level, for each galaxy identification. Galaxies which have been confidently identified through photometric redshifts that match the absorption redshift are labeled as having CL = 1. Identifications which were made based on colours that were consistent with a galaxy being at the absorption redshift, the proximity criterion, or photometric-redshift matches that were only marginally consistent with the absorption redshift are assigned confidence level CL = 2 or 3, with 2 being the more confident identification. No galaxy identification was possible for a few fields. For example, this may happen if an absorber redshift does not match the photometric redshift of any of the galaxies in a given field, or when galaxy colours are ambiguous or are consistent with a large redshift range. These fields are not assigned a CL value.

3.1 Examples

We now illustrate our process of absorbing galaxy identification with a few representative examples that include most of the issues we faced while assigning galaxies to absorption systems. The images and photometry for all objects in our sample are available on line at http://enki.phyast.pitt.edu/Imaging.php. We also provide results from photometric redshift and stellar population synthesis template fits, details of which are explained in the Appendix. Readers who are not interested in the details of galaxy selection can skip to §4.

Here we provide our reduced images, photometry tables, and photometric redshift fits and derived stellar population synthesis parameters for four fields. Sources detected within 100 kpc of the quasar sightline at the absorption redshift (or smallest absorption redshift for multiple absorbers along the same sightline) are numbered in order of increasing impact parameter from the quasar, and ellipses are drawn around sources in each image only to guide the eye. Photometry tables give positions relative to the quasar, AB magnitudes, and the detection significance, “DS”, which is defined as the number of standard deviations the source is detected above the background. , where is the net source counts, is the counts per pixel that correspond to a source detected at 1 above the background, and is the number of pixels within the detection isophote. A source is considered to be a detection if and . Tables describing photometric redshift fits give details of the stellar population templates that best fit the photometry. The information provided includes object number as marked on the images and its projected distance from the quasar in arcsec and kpc assuming that the galaxy is at the absorption redshift, age of the stellar population, star formation rate e-folding time, , extinction, , metal mass fraction, (), and the photometric redshift and error.

Example 1: the 0153+0009 field

This is an example of our highest level of confidence for absorbing galaxy identification, where the photometric redshift of the galaxy with the smallest impact parameter to the quasar matches the redshift of the absorption-line system.

The sightline towards the quasar 0153+0009 (SDSS J015318.19+000911.3) contains a subDLA system at with a column density of (RTN06). We obtained and images of this field (see Figure 7). We have used SDSS optical photometry for this field to supplement our infrared data; together the data were used to determine its photometric redshift. Our measured photometry is given in Table 2. The quasar PSF could not be subtracted as there were no suitable PSFs stars in the field, and so the quasar has been masked out. We detect nine objects within 100 kpc of the quasar.

Figure 7: 30 30 images of the 0153+0009 field. This field has a subDLA system at = 0.7714. As discussed in the text (§3.1.1), we identify Object 1 as the absorbing galaxy. The images shown above correspond to 222 222 kpc at the absorber redshift. The quasar has been masked in all the frames, and its position is marked by a “+”. The quasar PSF could not be subtracted, as there were no suitable PSF stars in the field. North is up and east is to the left. Photometry for all labeled objects is given in Table 2. Ellipses are drawn only to guide the eye. Objects that are unmarked have impact parameters greater than 100 kpc, and are not considered to be candidate absorbers.

Object 1 is at = 4.9, which is equivalent to 36.6 kpc at the absorber redshift. SDSS photometry for Object 1 was obtained from S. Zibetti (private communication) since it is not in the “photoObj” catalogue made available in the SDSS database. S. Zibetti ran his PSF subtraction software on the SDSS image (Zibetti et al. 2007), and provided us with the photometry of Object 1 in all five SDSS bands (Table 3). A photometric redshift of = 0.7450.040 is derived for Object 1 by supplementing these magnitudes with our infrared data (see Table 4). The stellar population template fit is shown in Figure 8. This is consistent with the absorption redshift to within the errors, and therefore, Object 1 is considered to be the absorbing galaxy.

The = 1.38 colour of Object 2 is not consistent with it being at the absorption redshift. Object 3 is included in the photometry table because it looks real by eye. However, based on its detection significance, DS, we do not consider it to be a confident detection. No redshift information could be extracted from the IR data on Objects 4, 5, and 8; they are not detected in the SDSS images.

Object 6 is identified as a star in the SDSS database, however, it is extended in our images. Objects 7 and 9 have , and respectively, according to the SDSS database29. The best-fit stellar population synthesis model to our IR photometry and SDSS optical photometry for Objects 6, 7, and 9 are shown in Figure 8, and the stellar population fit parameters are given in Table 4.

Figure 8: The curves are the best-fit stellar population synthesis models to the photometry for Objects 1, 6, 7, and 9 in the 0153+0009 field. The SDSS data are shown as open circles and our infrared photometric data, from Table 2, are shown as solid circles. See Table 4 for model details. As discussed in the text (§3.1.1), we identify Object 1 as the absorbing galaxy.

In summary, due to its matching photometric redshift as well as proximity, Object 1 is selected as the absorbing galaxy with CL = 1. The photometric redshift derived for Object 6 is consistent with the absorption redshift, making it likely that Objects 1 and 6 are members of the same galaxy cluster or group.

Object 30 31 32 DS 33 DS 34 DS 35
QSO 0.0 0.0 0.0 17.18 0.003 31.9 (188) 17.58 0.01 16.8 (120) 17.45 0.004 20.5 (138)
1 4.7 1.4 4.9 21.43 0.07 2.9 (41) 21.39 0.10 2.7 (22) 21.01 0.07 3.0 (35)
2 +2.5 +4.7 5.3 21.88 0.09 2.3 (34) 21.82 0.13 1.9 (21) 20.50 0.05 2.7 (63)
3 6.2 +3.4 7.1 23.22 0.22 1.7 (8)
4 +3.6 6.5 7.4 22.10 0.08 2.9 (22) 21.55 0.11 2.6 (20) 21.19 0.07 3.5 (26)
5 1.7 +7.7 7.9 23.09 0.16 2.0 (13) 22.95 0.21 2.0 (9)
6 0.4 +10.8 10.8 21.90 0.08 3.0 (26) 22.00 0.12 2.9 (12) 21.58 0.08 3.3 (19)
7 +10.8 +2.6 11.1 22.20 0.09 2.9 (20) 22.54 0.16 2.6 (8) 21.85 0.10 2.6 (19)
8 8.1 +7.6 11.1 23.12 0.20 2.2 (7)
9 7.3 +10.0 12.4 22.09 0.09 2.6 (25) 23.10 0.21 2.1 (6) 22.23 0.13 2.2 (16)
Table 2: 0153+0009: Infrared Photometry
Object 1
22.200.50
24.300.38
23.180.24
22.240.18
21.180.50
Table 3: 0153+0009: Supplemental Photometry36
Galaxy Stellar Population Synthesis Model Parameters
# 37 Age
kpc Gyr Gyr
1 4.9 36.6 12.0 5.00 1.00 0.0040 0.7450.040
6 10.8 80.1 5.00 12.0 0.30 0.0004 0.7450.113
7 11.1 82.1 3.00 3.00 0.00 0.0040 0.3440.294
9 12.4 92.2 1.00 0.10 0.00 0.0080 0.2440.157
Table 4: 0153+0009: Photometric Redshift Fits38

Example 2: the 0735+178 field

This is an example of a field where the three objects with the smallest impact parameters are ruled out as absorbing galaxy candidates. The fourth closest object is the best candidate for the absorbing galaxy.

The sightline towards the quasar 0735+178 contains a LLS at = 0.4240 with a column density (RTN06). This is an interesting system because it has relatively strong Fe II and Mg I absorption (see RTN06). These systems generally tend to have higher H i column densities (, RTN06), and therefore the identification of the galaxy causing this unusual absorption-line pattern might be illuminating. A complete optical and infrared set of images is available for this field. The images are shown in Figures 9 and 10. PSF subtractions were carried out on the optical data and no objects were detected within the subtracted region. The quasar PSF could not be subtracted on the infrared images as there were no suitable PSF stars in the field. Photometric measurements for the eight objects detected in this field are given in Tables 5 and 6.

Figure 9: 44 44 PSF-subtracted images of the 0735+178 field. This field has a LLS at = 0.4240. As discussed in the text (§3.1.2), we identify Object 4 as the absorbing galaxy. The images shown above correspond to 245 245 kpc at the absorber redshift. The central pixels of the quasar PSF subtraction residuals have been masked, and the position of its center is marked by a “+”. A nearby star, 10.9 east of the quasar, was also subtracted. All stars in the field are indicated by an “S”. North is up and east is to the left.
Figure 10: Same as Figure 9, but for and . The quasar is marked by the letter “Q”. The quasar PSF could not be subtracted as there were no suitable PSF stars in the field. As discussed in the text (§3.1.2), we identify Object 4 as the absorbing galaxy.

Objects 1, 2, and 5 are in the SDSS database as having , , and respectively. Stickel et al. (1993) obtained a spectrum of Object 1, and determined it to be at redshift = 0.645. It is therefore ruled out as the absorber candidate. The best-fit stellar population synthesis models to our photometry for Objects 2, 4, and 8 are shown in Figure 11, and the best-fit template parameters are listed in Table 7. We derive a photometric redshift for Object 2, which is inconsistent with that listed in the SDSS database. The addition of infrared photometric measurements provides stronger constraints on the fit, making our redshift determination more reliable than that reported in the SDSS database. Object 3 is only detected in the infrared, and its = 0.29 and = 0.81 colours are not consistent with it being at the absorption redshift. We note that Object 3 has 7.6, which makes it an “extremely red object” (ERO). Object 4 is classified as a star in the SDSS database, however, it is extended on our images. The photometric redshift that we derive for Object 4 is consistent with the absorption redshift, and it is identified as the candidate absorber in this field. A stellar population synthesis model could not be fit to the photometry of Object 5 probably because of its low surface brightness and low detection significance in all our images. Its photometry is therefore highly uncertain.

In summary, Object 4 is selected as the absorbing galaxy in this field since its photometric redshift, , matches the absorption redshift, and the galaxies with smaller impact parameters are ruled out as candidate absorbers. This identification is assigned CL = 1.

Figure 11: The curves are the best-fit stellar population synthesis models to our photometry (solid circles) for the objects in the 0735+178 field. See Table 7 for the model parameters. As discussed in the text (§3.1.2), we identify Object 4 as the absorbing galaxy.
Object 39 40 41 DS 42 DS 43 DS 44 DS 45
QSO +0.0 0.0 0.0 15.71 0.001 74.8 (2007) 15.50 0.001 138.8 (2187) 15.90 0.001 225.1 (1231) 15.20 0.001 37.7 (4057)
1 5.2 +5.1 7.3 23.04 0.06 2.6 (67) 23.80 0.07 2.8 (51) 23.89 0.06 2.6 (67) 19.81 0.01 3.5 (633)
2 +7.7 3.2 8.4 23.21 0.07 2.3 (66) 24.46 0.09 2.8 (28) 24.06 0.07 2.3 (66) 21.62 0.03 3.3 (125)
3 +0.1 9.0 9.0
4 1.4 +12.6 12.7 24.17 0.08 2.9 (36) 21.47 0.03 3.4 (140)
5 +10.8 10.1 14.8 23.57 0.08 2.5 (43) 23.16 0.05 3.0 (86) 24.41 0.08 2.5 (43) 22.93 0.07 2.4 (52)
6 +15.6 +0.2 15.6 25.33 0.18 2.1 (10) 24.88 0.11 4.5 (12) 26.17 0.18 2.1 (10)
7 +16.4 1.5 16.4 25.14 0.17 2.1 (12) 25.99 0.17 2.1 (12)
8 1.0 +17.3 17.3 24.73 0.15 3.4 (11) 23.72 0.06 2.4 (66) 25.58 0.15 3.4 (11) 24.39 0.14 2.3 (14)
Table 5: 0735+178: Optical Photometry
Object 46 47 48 DS 49 DS 50 DS 51
QSO +0.0 0.0 0.0 14.04 0.13 116.3 (578) 13.58 0.16 116.3 (433) 13.35 0.13 142.8 (535)
1 5.2 +5.1 7.3 19.40 0.13 4.3 (114) 18.99 0.16 4.1 (83) 18.66 0.13 5.6 (102)
2 +7.7 3.2 8.4 20.15 0.14 3.6 (67) 19.64 0.17 3.7 (51) 19.24 0.13 6.4 (53)
3 +0.1 9.0 9.0 21.31 0.15 3.3 (25) 21.02 0.19 2.6 (20) 20.21 0.14 4.9 (28)
4 1.4 +12.6 12.7 20.77 0.14 3.4 (40) 20.27 0.17 3.4 (31) 19.98 0.14 4.3 (40)
5 +10.8 10.1 14.8 21.88 0.18 2.1 (24) 22.17 0.21 2.5 (9)
6 +15.6 +0.2 15.6
7 +16.4 1.5 16.4
8 1.0 +17.3 17.3
Table 6: 0735+178: Infrared Photometry
Galaxy Stellar Population Synthesis Model Parameters
# 52 Age
kpc Gyr Gyr
2 8.4 46.5 15.0 3.00 0.10 0.0500 0.8780.038
4 12.7 70.5 0.50 0.10 0.30 0.0500 0.4230.179
8 17.3 96.5 0.10 0.10 0.00 0.0001 0.9590.644
Table 7: 0735+178: Photometric Redshift Fits53

Example 3: the 1109+0051 field

This field is not as straightforward as the previous ones. The sightline towards the quasar 1109+0051 (SDSS J110936.35+005111.3) contains two subDLA systems, one at = 0.4181 with a column density of and the other at = 0.5520 with a column density of (RTN06). Images of this field were obtained in g’, r’, J, H, and K, from which six objects are detected (Figures 12 and 13). The quasar PSF subtraction revealed no object within the subtracted region. The optical and infrared photometry are given in Tables 8 and 9, respectively.

Object 1 has an impact parameter , which at the two absorber redshifts corresponds to 7 kpc and 8 kpc, respectively. It is detected in the , and -bands. Since it overlaps with the quasar PSF, its photometry is uncertain. We consider it to qualify as a candidate absorber due to its proximity to the sightline. The best-fit stellar population synthesis models to our photometry for Objects 2, 3, 4, and 5 are shown in Figure 14, and the model parameters are tabulated in Table 10. The best-fit stellar population synthesis model to the photometry of Object 2 is only marginally consistent with (within of) the lower absorption redshift system, = 0.4181. The photometry of Object 3 results in a photometric redshift of , which is consistent with the absorption system at = 0.5520. However, as can be seen from Table 10, the photometric redshift we derive for Object 4, while inconsistent with the SDSS-derived photometric redshift of , is consistent with both absorption redshifts. In addition, the redshift derived for Object 5 is consistent with the absorption system at = 0.4181 (but inconsistent with the SDSS redshift of ). Therefore, Objects 1, 3, 4, and 5 are all potential absorber candidates for the absorption systems in this field, while Object 2 is marginally consistent at the lower redshift. Given this ambiguity, we use the proximity criterion as the deciding factor, and select Object 1 as the = 0.4181 candidate and Object 3 as the = 0.5520 candidate, both with confidence level CL = 2.

Figure 12: 36 36 PSF-subtracted and images of the 1109+0051 field. This field has two subDLA systems, one at = 0.4180 and the other at = 0.5520. As discussed in the text (§3.1.3), we identify Object 1 as the absorbing galaxy at and Object 3 as the absorbing galaxy at = 0.5520. The images shown above correspond to 199 199 kpc and 231 231 kpc at the two redshifts, respectively. The frames are smoothed to bring out LSB features. The PSF residuals have been masked. The quasar position is marked by a ”+”. North is up and east is to the left.
Figure 13: Same as Figure 12, but for J, H, and K. There is evidence for Object 1 in the frame, however, it does not meet the “5 contiguous pixels above 1” detection criterion. As discussed in the text (§3.1.3), we identify Object 1 as the absorbing galaxy at and Object 3 as the absorbing galaxy at = 0.5520.
Figure 14: The curves are the best-fit stellar population synthesis models to our photometry (solid circles) for objects in the 1109+0051 field. The best-fit parameters are listed in Table 10. As discussed in the text (§3.1.3), we identify Object 3 as the absorbing galaxy at = 0.5520.
Object 54 55 56 DS 57 DS 58
QSO 0.0 0.0 0.0 18.45 0.03 29.5 (422) 18.45 0.05 9.1 (263)
1 0.6 1.1 1.3 23.79 0.33 2.6 (26)
2 3.4 7.4 8.1 24.58 0.64 2.6 (12) 22.79 0.42 2.7 (14)
3 +8.4 5.4 10.0 24.29 0.56 2.6 (16) 23.54 0.67 2.3 (8)
4 +4.6 9.9 10.9 23.15 0.24 3.8 (34) 22.05 0.27 3.8 (20)
5 +13.4 0.7 13.4 21.44 0.07 4.8 (142) 20.52 0.10 3.0 (111)
6 11.7 10.6 15.8 22.85 0.42 2.2 (16)
Table 8: 1109+0051: Optical Photometry
Object 59 60 61 DS 62 DS 63 DS 64
QSO 0.0 0.0 0.0 18.06 0.01 12.8 (151) 18.41 0.01 9.1 (113) 18.03 0.01 10.8 (119)
1 0.6 1.1 1.3 22.24 0.13 2.6 (16) 22.36 0.17 2.1 (13)
2 3.4 7.4 0. 8.1 21.07 0.07 2.6 (47) 21.10 0.08 2.5 (34) 20.18 0.05 3.2 (55)
3 +8.4 5.4 10.0 23.98 0.29 1.7 (5) 22.63 0.19 2.1 (10) 22.88 0.23 2.4 (6)
4 +4.6 9.9 10.9 22.67 0.16 2.0 (14) 22.86 0.21 2.5 (6)
5 +13.4 0.7 13.4 20.35 0.04 3.5 (67) 20.24 0.05 3.2 (59) 20.17 0.05 3.3 (55)
6 11.7 10.6 15.8
Table 9: 1109+0051: Infrared Photometry
Galaxy Stellar Population Synthesis Model Parameters
# 65 Age
kpc Gyr Gyr
2 8.1 44.7 0.50 0.10 0.50 0.0500 0.2660.109
3 10.0 55.4 0.10 12.0 0.20 0.0500 0.6450.157
4 10.9 60.4 1.00 1.00 0.00 0.0001 0.4330.222
5 13.4 73.9 1.00 12.0 0.10 0.0080 0.3880.050
Table 10: 1109+0051: Photometric Redshift Fits66

Example 4: the 1715+5747 field

This is a case where no galaxy is identified as the absorber. The sightline towards the quasar 1715+5747 (SDSS J171539.86+574722.2) contains a subDLA system at = 0.5579 with a column density of (RTN06). A complete optical and infrared dataset was obtained for this field. Figures 15 and 16 show that only three objects are detected within 100 kpc of the quasar at . PSF subtractions were carried out on the optical images and no objects were detected within the subtracted region. The quasar PSF could not be subtracted on the infrared images as there were no suitable PSF stars in the field. Object 1 is located 3.5 from the quasar sightline which corresponds to 22.3 kpc at the absorption redshift. Objects 2 and 3 have and , respectively, according to the SDSS database.

Figure 15: 30 30 PSF subtracted images of the field 1715+5747. This field has a subDLA system at = 0.5579. None of the three objects in this field is a galaxy at the absorption redshift, and so the absorber galaxy in this field remains unidentified (§3.1.4). The image shown above corresponds to 220 220 kpc at the absorber redshift. The quasar PSF subtraction residuals have been masked, and the position of the quasar is marked by a “+”. The track northeast of Object 3 is a cosmic ray as are the two sources south and southwest of Object 1 in the -band image. North is up and east is to the left.
Figure 16: 30 30 images of the field 1715+5747. This field has a subDLA system at = 0.5579. None of the three objects in this field is a galaxy at the absorption redshift, and so the absorber galaxy in this field remains unidentified (§3.1.4). The images shown above correspond to 220 220 kpc at the absorber redshift. The quasar is marked by the letter “Q”. The quasar PSF could not be subtracted as there were no suitable PSF stars in the field. North is up and east is to the left.

The best-fit stellar population synthesis model to our photometry for Objects 1, 2, and 3 are shown in Figure 17, and the model parameters are listed in Table 13. The photometric redshift we derive for Object 1 does not match the absorption redshift. While the SDSS photometric redshift for Object 2 is consistent with the redshift of the absorption system and our optical photometric measurements agree well with those measured by the SDSS, the addition of our IR data results in a very different photometric redshift for Object 2. Again, as was the case for Object 2 in the 0735+178 field, the addition of IR data was crucial for the determination of the galaxy’s redshift. With regards to Object 3, we derive a photometric redshift that is consistent with the one obtained by the SDSS.

Figure 17: The curves are the best-fit stellar population synthesis models to our photometry (solid circles) for Objects in the 1715+5747 field. The best-fit model parameters are listed in Table 13. None of the three galaxies is at the absorption redshift (§3.1.4)

Thus, none of the objects detected in this field have photometric redshifts consistent with the absorption redshift. Based on their proximity to the quasar sightline, one might expect either Object 1 or 2 to be the absorbing galaxy. However, until spectroscopic data or better photometry are available that might prove our results to be incorrect, we consider our data on this field to be inconclusive, i.e., we do not have an absorbing galaxy identification. It may be one of the cases where the absorbing galaxy is (5.2 kpc) from the quasar sightline, or at a larger impact parameter and fainter than the brightness limit of our K-band data, = 0.09.

Object 67 68 69 DS 70 DS 71 DS 72 DS 73
QSO 0.0 0.0 0.0 19.69 0.15 21.9 (496) 18.21 0.04 40.5 (758) 18.44 0.04 18.4 (770) 18.55 0.05 20.5 (424)
1 1.4 3.2 3.5 24.87 0.41 2.1 (34) 24.76 0.53 2.0 (21) 21.56 0.08 3.5 (160)
2 4.3 +0.9 4.4 23.99 0.27 2.7 (78) 22.07 0.07 4.1 (224) 21.07 0.05 4.4 (282) 20.74 0.06 5.0 (230)
3 +3.2 +11.1 11.5 22.46 0.19 3.3 (266) 20.49 0.05 8.4 (456) 19.51 0.04 8.4 (630) 19.20 0.05 8.8 (539)
Table 11: 1715+5747: Optical Photometry
Object 74 75 76 DS 77 DS 78 DS 79
QSO 0.0 0.0 0.0 18.07 0.01 11.8 (82) 17.82 0.01 12.2 (103) 17.28 0.01 16.0 (139)
1 1.4 3.2 3.5 20.54 0.08 2.8 (35) 20.21 0.06 3.4 (41) 19.82 0.04 3.2 (68)
2 4.3 +0.9 4.4 20.13 0.06 3.2 (46) 19.69 0.04 3.7 (61) 19.48 0.03 4.0 (74)
3 +3.2 +11.1 11.5 18.57 0.03 3.5 (174) 18.17 0.02 4.6 (196) 17.92 0.01 5.0 (249)
Table 12: 1715+5747: Infrared Photometry
Galaxy Stellar Population Synthesis Model Parameters
# 80 Age
kpc Gyr Gyr
1 3.5 22.3 1.00 0.10 0.50 0.0001 0.8900.066
2 4.4 28.6 0.50 0.10 0.20 0.0500 0.2870.044
3 11.5 74.4 0.50 0.10 0.20 0.0500 0.3410.107
Table 13: 1715+5747: Photometric Redshift Fits81

4 Galaxy Properties

4.1 Earlier work

Absorber galaxies that had been previously identified are presented in Table 14. The first results from our DLA imaging programme that were presented in Turnshek et al. (2001) and Rao et al. (2003) are included in this table. Additionally, our current sample (Table 1) has five fields that were studied by other investigators, however, our new images did not alter the earlier conclusions. These five are also included in Table 14 with previous studies referenced.

Mg ii absorbers from RTN06 are tabulated in the first section of Table 14, and those not in RTN06 are included in the second section of the table. Column 1 is the quasar designation, column 2 gives the quasar emission redshift, columns 3 and 4, the Mg ii  absorption redshift and rest equivalent width, and column 5, the H i column density of the absorber. Column 6 gives the impact parameter of the identified galaxy in kpc, and columns 7 and 8 give the galaxy’s AB magnitude and absolute luminosity with respect to (see §4.2). The relevant filter is noted in parentheses. The reference for the galaxy’s parameters is given in column 9 and the method by which it was identified is given in column 10. “Specz” indicates that a spectroscopic redshift was used to identify the galaxy, “Photoz” indicates that the galaxy’s photometric redshift matched the absorption redshift, and “Prox” indicates that the closest galaxy to the quasar sightline was chosen as the absorbing galaxy. Column 11 indicates the confidence level, CL, assigned to the identification (see §3). “Photoz” and “Prox” identifications are assigned CL = 1 and CL = 2, respectively. Specz is assigned CL = 1, except for the galaxy in the 1622+239 field. Steidel et al. (1997) obtained a spectroscopic redshift that matches for the galaxy at kpc in this field, but commented that a galaxy this faint and this far away could not be the DLA absorber. More recently, Kacprzak et al. (2007) have identified this galaxy as the absorber in their work, and we have adopted this new interpretation as well. However, we have assigned this galaxy an identification confidence level of CL = 2, because we feel that we cannot be as confident about the validity of this identification as we are about the rest of the spectroscopically-identified galaxy candidates (also see §6).

Quasar Impact par. 82 Ref.83 ID
(Å) (cm) (kpc) Method CL
MgII Systems from RTN06:
0002+051 1.899 0.8514 1.09 19.08 25.9 22.90()84 0.92 1 Specz 1
0058+019 1.959 0.6127 1.66685 20.04 7.3 23.7() 0.17 2,3 Specz 1
0117+213 1.491 0.5764 0.91 19.15 7.3 86 2.54 4 Specz 1
0302223 1.409 1.0096 1.16 20.36 25.887 24.56() 0.22 5,6 Specz 1
0420014 0.915 0.6331 0.7588 18.54 14.6 89 0.34 4 Specz 1
0454+039 1.343 0.8596 1.45 20.67 5.5 24.76() 0.14 4,5 Specz 1
0738+313 0.630 0.2213 0.61 20.90 19.2 19.7() 0.10 7 Specz 1
0827+243 0.941 0.5247 2.56390 20.30 32.8 18.97() 1.20 8,9 Specz 1
0952+179 1.478 0.2377 1.08791 21.32 4.2 22.10() 0.01 8 Prox 2
1038+064 1.265 0.4416 0.66 18.30 56.0 21.26()92 0.29 10 Specz 1
1127145 1.187 0.3130 2.21 21.71 45.6 19.26() 0.59 1,8 Specz 1
1148+386 1.304 0.5533 0.48293 18 20.3 21.50()94 0.48 10 Specz 1
1209+107 2.193 0.3930 1.00 19.46 34.9 22.22() 0.14 5 Specz 1
1229021 1.038 0.7571 0.38495 18.36 10.5 25.66() 0.02 5,11 Prox 2
1241+176 1.282 0.5505 0.57096 18.90 21.4 21.96()97 0.31 10 Specz 1
1317+277 1.014 0.6601 0.34 18.57 103.2 21.91()98 0.61 10 Specz 1
1622+239 0.927 0.6561 1.47199 20.36 99.6 22.67() 0.05 10,12100 Specz 2
0.8913 1.622101 19.23 21.4 21.43() 0.65 12 Specz 1
1623+269 2.521 0.8881 1.214102 18.66 48.2 24.20()103 0.21 10 Specz 1
1629+120 1.792 0.5313 1.666104 20.70 17.1 19.55() 1.04 8 Photoz 1
2128123 0.501 0.4297 0.41 19.18 48.8 20.98()105 0.35 10 Specz 1
Others:
0051+0041 1.189 0.7397 2.4 20.4 24.1 22.45() 0.41 13 Specz 1
0151+045 0.404 0.1602 1.55 19.84 17.7 19.31() 0.14 14 Specz 1
0235+164 0.940 0.5243 2.42 21.70 13.1 20.2() 0.72 3 Specz 1
0439433 0.593 0.1009 1.62 19.85 7.6 17.2() 0.98 3 Specz 1
0809+483 0.871 0.4369 2.00 20.80 8.4 19.9() 0.59 3 Specz 1
11221649 2.400 0.6850 1.83 20.45 25.2 22.4() 0.35 3,15 Photoz 1
1137+3907 1.027 0.7195 3.0 21.1 10.8 19.8() 0.16 13 Specz 1
1229021 1.038 0.3950 2.22 20.75 7.5 22.31() 0.08 5 Prox 2
Table 14: Absorbing Galaxy Identifications (Previously known)

4.2 Current work

Table LABEL:IDsummary provides details on DLA candidate galaxies in the 55 quasar fields that appear here for the first time. The first five columns are as described above for Table 14. We note here that column density values less than cm were obtained by fitting Voigt profiles with the same Doppler broadening parameter as the stronger subDLA and DLA lines (Rao & Turnshek 2000; RTN06). The column densities should therefore be considered approximate, but less than cm. Nevertheless, these are legitimate Mg ii  absorption systems for which absorbing galaxies have been identified. Column 6 gives the object in each field that was identified as the absorbing galaxy candidate. As indicated in §3, the numbering is in order of increasing distance from the quasar sightline. Columns 7 and 8 are the galaxy’s impact parameter in arcsec and kpc, respectively, and column 9 gives the galaxy’s photometric redshift and associated error, which were determined if the field was observed through four or more filters.

Columns 10 and 11 give the galaxy’s AB magnitude and absolute luminosity with respect to . -band AB magnitudes and luminosities are provided unless the object was not observed (or detected) in , in which case the non- filter is noted. Our magnitude errors are typically 10 to 20%. See, for example, the photometry tables of individual fields in §3.

Quasar Obj. Impact parameter 106 ID
(Å) (cm) # () (kpc) Method CL
0021+0043 1.245 0.5203 0.533 19.54 1 10.8 67.3 0.549 0.070 19.25 0.73 Photoz 1
0.9420 1.777 19.38 2 10.8 85.2 20.11 1.26 Colour 2
0041266 3.053 0.8626 0.67 18.00 1 11.6 89.2 107 Prox 3
01070019 0.738 0.5260 0.784 18.48 1 2.6 16.3 0.564 0.157 20.11 0.31 Photoz 1
01160043 1.282 0.9127 1.379 19.95 1 8.1 63.4 0.717 0.248 20.71 0.66 Photoz 1
01230058 1.551 0.8686 0.757 18.62 1 1.3 10.0 21.1: 0.41 Prox 3
01380005 1.340 0.7821 1.208 19.81 2 6.5 48.4 22.34 0.11 Prox 3
01390023 1.384 0.6828 1.243 20.60 2 5.7 40.3 0.661 0.075 21.60 0.14 Photoz 1
0141+339 1.450 0.4709 0.78 18.88 1 5.3 31.3 20.79 0.14 Prox 3
0152+0023 0.589 0.4818 1.340 19.78 2 5.3 31.7 0.518 0.110 21.45() 0.10 Photoz 1
0153+0009 0.837 0.7714 2.960 19.70 1 4.9 36.3 0.745 0.040 21.01 0.33 Photoz 1
0253+0107 1.035 0.6317 2.571 20.78 1 1.2 8.2 0.632108 21.5: 0.14 Photoz 2
0254334 1.849 0.2125 2.23 19.41 1 5.5 19.0 0.0300.220 22.86 0.005 Photoz 2
0256+0110 1.349 0.7254 3.104 20.70 1 2.4 17.4 0.8150.080 19.55 1.17 Photoz 2
0710+119 0.768 0.4629 0.62 18.30
0735+178 0.424 0.4240 1.32 19.00 4 12.7 70.7 0.423 0.179 19.98 0.22 Photoz 1
0843+136 1.877 0.6064 0.938109 19.56 8 10.1 68.0 0.443 0.281 22.46 0.05 Photoz 2
09530038 1.383 0.6381 1.668 19.90 1 11.9 81.8 0.644 0.150 19.78 0.71 Photoz 1
0957+003 0.907 0.6720 1.936110 19.59
1009+0036 1.699 0.9714 1.093 20.00 1 2.5 19.9 111 Prox 3
10090026 1.244 0.8426 0.713 20.20 2 5.2 39.7 21.68 0.23 Prox 3
0.8866 1.900 19.48
1019+309 1.319 0.3461 0.70 18.18 3 9.2 45.1 0.244 0.167 21.81 0.03 Photoz 2
10280100 1.531 0.6322 1.579 19.95
0.7087 1.210 20.04
10470047 0.740 0.5727 1.063 19.36 1 4.7 30.7 21.10 0.17 Prox 2
1048+0032 1.649 0.7203 1.878 18.78 3 7.4 53.5 0.947 0.300 20.54 0.46 Photoz 1
1107+0048 1.392 0.7404 2.952 21.00 2 7.9 57.7 23.83(r) 0.17 Colour 3
1109+0051 0.957 0.4181 1.361 19.08 1 1.3 7.2 22.24() 0.05 Prox 2
0.5520 1.417 19.60 3 10.0 64.2 0.645 0.157 22.88 0.03 Photoz 2
1209+107 2.193 0.6295 2.619112 20.30 1 1.7 11.6 0.644 0.100 19.89 0.55 Photoz 1
1225+0035 1.226 0.7730 1.744 21.38 1 8.2 60.8 113 Prox 2
1226+105 2.305 0.9376 1.646114 19.41 1 4.6 36.2 0.9470.060 20.44 0.77 Photoz 1
13230021 1.390 0.7160 2.229 20.54 1 1.4 10.1 21.90() 0.97 Prox 2
13420035 0.787 0.5380 2.256 19.78
13450023 1.095 0.6057 1.177 18.85 2 7.6 51.0 0.628 0.040 22.24 0.06 Photoz 1
1354+258 2.006 0.8585 1.176115 18.57 2 4.0 30.7 23.78() 0.48 Prox 3
0.8856 0.489116 18.76 3 12.2 94.6 23.68() 0.49 Prox 3
14190036 0.969 0.6238 0.597 19.04 3 9.6 65.3 0.499 0.177117 22.89() 0.17 Photoz 2
0.8206 1.145 18.78
1426+0051 1.333 0.7352 0.857 18.85 1 5.0 36.4 22.96() 0.44 Prox 2
0.8424 2.618 19.65
14310050 1.190 0.6085 1.886 19.18 1 2.6 17.5 0.737 0.224 21.2: 0.17 Photoz 2
0.6868 0.613 18.40 2 3.3 23.4 23.2() 0.28 Colour 2
14360051 1.275 0.7377 1.142 20.08
0.9281 1.174 18.82
1437+624 1.090 0.8723 0.71 18.00 2 9.5 73.3 0.694 0.190 20.70 0.60 Photoz 1
15210009 1.318 0.9590 1.848 19.40 1 8.5 67.4 23.46() 0.10 Colour 2
1525+0026 0.801 0.5674 1.852 19.78 1 4.8 31.3 19.59 0.66 Prox 3
1704+608 0.371 0.2220 0.562118 18.23 2 7.7 27.5 0.220 0.050 19.63 0.08 Photoz 1
1714+5757 1.252 0.7481 1.099 19.23 1 2.4 17.6 24.33() 0.13 Prox 3
1715+5747 0.697 0.5579 1.001 19.18
1716+5654 0.937 0.5301 1.822 19.98 1 1.1 6.9 0.5301119 23.44() 0.07 Photoz 2
1722+5442 1.215 0.6338 1.535 19.00 2 6.6 45.2 24.10() 0.09 Colour 3
1727+5302 1.444 0.9448 2.832 21.16 1 3.1 24.5 0.9448120 23.14 0.08 Photoz 2
1.0312 0.922 21.41 2 3.6 29.0 20.94 0.71 Prox 2
1729+5758 1.342 0.5541 1.836 18.60 2 5.6 36.0 0.503 0.140 20.56 0.26 Photoz 1
1733+5533 1.072 0.9981 2.173 20.70 1 8.4 67.2 24.4() 0.47 Colour 2
1857+566 1.578 0.7151 0.65 18.56
2149+212 1.538 0.9114 0.72 20.70 1 1.7 13.3 22.31() 0.31 Prox 2
1.0023 2.46 19.30 3 5.5 44.0 22.37() 0.41 Prox 3
Table 15: Absorbing Galaxy Identifications (This work)
Quasar Obj. Impact parameter 121 ID
(Å) (cm) # () (kpc) Method CL
2212299 2.706 0.6329 1.15122 19.75 1 2.3 16.0 20.90 0.25 Colour 2
2223052 1.404 0.8472 0.586123 18.48 1 6.9 52.8 24.62() 0.32 Prox 2
2328+0022 1.308 0.6519 1.896 20.32 1 1.7 11.8 0.815 0.242 22.61()124 0.33 Photoz 1
2334+0052 1.040 0.4713 1.226 20.65 1 5.5 32.5 0.4713125 20.37 0.20 Photoz 2
23530028 0.765 0.6044 1.601 21.54 1 4.9 32.9 0.844 0.300 19.27 1.01 Photoz 1

Apparent magnitudes are provided, unless otherwise noted. The symbol “:” indicates that the magnitude is uncertain because the galaxy overlaps with the quasar PSF.
Observations not photometric.
“BestTemplate” fit calculated by fixing the redshift of the stellar population template at the absorption redshift, to illustrate that a galaxy template consistent with the measured photometry exists.
Measurements of have been changed from RTN06 values to reflect the more recent measurements of Quider et al. (2011).
SDSS photometric redshift, -converted SDSS magnitudes are provided.
Measurements of have been changed from RTN06 values to reflect the more recent measurements of Mathes et al. (in preparation).
SDSS magnitudes provided by S. Zibetti (private communication).

Table 15: Continued

The following values were used to determine values for the galaxies listed in Tables 14 and LABEL:IDsummary in the filters indicated:

(, Dahlen et al. 2005)
(, Dahlen et al. 2005)
(, Gabasch et al. 2004)
(, Gabasch et al. 2004)
(Dahlen et al. 2005)
(, Wolf et al. 2003)
(, Ilbert et al. 2005)
(, Ilbert et al. 2005)
(, Dahlen et al. 2005)
(, Dahlen et al. 2005)
(Jones et al. 2006; assuming no evolution between and 0.5)
(Cirasuolo et al. 2006)

-corrections for galaxies whose redshifts were obtained using template fits to the photometry were determined from the template fits themselves. For the rest, an Sb-type -correction in the observed filter at the redshift of the absorber was assumed.

Columns 12 and 13 give the method by which the DLA galaxy candidate was identified, and CL, the confidence level of this identification (§3). Of the 66 absorbers in Table LABEL:IDsummary, 17 have photometric redshifts that match the absorption redshift, and are assigned CL . Thirty-seven identifications were made either with colours that were consistent with the galaxy being at the absorption redshift, the proximity criterion, or photometric-redshift matches that were only marginally consistent with the absorption redshift. These are labeled as having CL = 2 or 3, with 2 being the more confident identification. No galaxy identification was possible for 12 absorbers. Examples of some of these were given in §3.

Figure 18 shows that the CL = 1 and CL = 2 or 3 samples have very similar impact parameter and luminosity distributions. Here, we have included galaxies from Tables 14 and LABEL:IDsummary. In Figure 18, impact parameter, , is plotted versus log H i column density for the 80 galaxies that have and measurements. Galaxy luminosity is represented by the size of the symbol (see caption). We will discuss the - plane in more detail later, however, this plot clearly shows that the CL values do not cluster with either parameter, or with luminosity. In addition, Kolmogorov-Smirnov (KS) tests show that the two CL samples are drawn from the same parent population: the KS test probabilities are 0.08 for the two luminosity distributions, 0.68 for the two impact parameter distributions, and 0.94 for the two H i column density distributions. Therefore, this is evidence that we are statistically selecting similar candidate galaxies in all of these samples. Hereafter, we will no longer separate the sample by CL value, and will explore the properties of all candidate galaxies irrespective of their indentification method.

Figure 18: Impact parameter, , versus . Galaxy luminosity is represented by the size of the symbol. The smallest symbols are galaxies with , the medium-sized symbols, , and the largest symbols represent . Red crosses represent galaxies with identification confidence level CL = 1, and blue ‘+’ symbols are those that have CL = 2 or 3. The dashed line is at the DLA threshold column density of .

Our galaxy sample is essentially defined by five parameters: absorption redshift, , Mg ii 2796 rest equivalent width, , H i column density, , galaxy impact parameter, , and galaxy luminosity, which we express as a fraction of , . The three galaxy identifications from Table 15 that have measured values but no measurements are not included. The sample we analyse includes 80 absorption systems and their identified galaxies. Figure 19 shows the distributions of these properties at a glance. Open circles are systems with and solid circles are DLAs. In Table LABEL:Spearman, we provide results from the Spearman rank correlation test in order to quantify possible correlations among the various parameters126. Column 1 gives the pair of parameters between which the correlation test was performed, and column 2 is the Spearman rank coefficient, . A value of indicates no correlation, while indicate a perfect correlation and a perfect anticorrelation, respectively. Column 3 gives , the significance of the deviation of from 0. A small value of indicates significant correlation (positive ) or anticorrelation (negative ). Column 4 gives the number of standard deviations that the given correlation deviates from the null hypothesis.

Parameters
, 0.10 0.390 0.9
, 0.02 0.875 0.2
, 0.18 0.103 1.6
, 0.19 0.089 1.7
, 0.53 5.1E-7 4.7
, 0.068 1.8
, 0.09 0.419 0.8
, 0.07 0.526 0.7
, 0.002 3.0
, 0.14 0.230 1.2
Table 16: Spearman Rank Correlation Test Results
Figure 19: Absorber properties at a glance. Filled circles are DLAs and open circles are systems with . For clarity, the upper limit arrows for column density are not shown. See Tables 14 and LABEL:IDsummary for the four systems with upper limits for , but with measured values for and .

In addition, Table 17 lists KS test probabilities that two given samples are drawn from the same parent population. In the first set, , , in kpc, and are compared for three different samples of H i column density: the DLA () and subDLA () samples, and for the subDLA and Lyman limit system (LLS, ) samples. There are 27 galaxies in the DLA sample, 30 in the subDLA sample, and 23 in the LLS sample. Next, the sample is split by the median value of 127, and then by the median value of .

Parameter DLA vs. SubDLA128 SubDLA vs. LLS129
0.595 0.624
0.003 0.0003
0.089 0.828
0.976 0.087
Å vs. Å130
0.893
0.361
0.0001
0.139
kpc vs. kpc131
0.724
0.531
0.043