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Characterizing Strong Absorbers
An N (HI) measurement is more or less precise, depending on the optical depth in the center of the H I Lyα transition. The Lyα curve of growth, which relates the absorption profile equivalent width, W , to the HI column density, has three different regimes (Fig-ure 1.6). For weak absorptions due to optically thin gas, the equivalent width increases linearly with the HI column density. As the gas transitions to optically thick, N (HI) and the Doppler parameter, b, quickly become degenerate. Lyα absorptions are already partially saturated starting at N (HI) = 1013 cm−2. In the flat, saturated regime, a wide range of column densities are possible for a given equivalent width. At high column den-sities, N (HI) > 1019 cm−2, damping wings appear and contribute substantially to the equivalent width. The curve of growth once again has a unique solution, independent of the Doppler parameter.
To measure N (HI) for an absorption system, the first step is to fit a continuum to the quasar spectrum. A precise redshift for the system can be determined by fitting low-ionization metal transitions associated with strong absorbers, if they are detected. Assuming that the low ions are kinematically associated with the neutral gas, they can be required to have the same redshift and tied Doppler parameters.
Then, fitting a Voigt profile centered on the system redshift to the HI absorption will give the column density, since the damping wings constrain the HI absorption profile for strong absorption systems. Any higher-order Lyman series absorptions available in the spectrum can help to further refine the fit. The continuum may also need to be readjusted to improve the Voigt profile fit.
The continuum placement is often uncertain in the Lyα forest, particularly near strong absorbers, and is usually the dominant source of error in an N (HI) measurement. Nonetheless, DLA column densities can be measured very reliably by iterating between Voigt profile and continuum adjustments, since the damped wings are a strong con-straint. Figure 1.7 shows an example of the Voigt profile fit to a log N (HI)= 20 90 ± 0 10 DLA.
Neutral Hydrogen Mass Density
The various absorption systems (in order of decreasing importance), DLAs, sub-DLAs, LLS, and Lyα forest absorptions, contribute to the total mass density of neutral hydro-gen, Ωg, which can be evaluated over a column density range Nmin to Nmax:
Neutral hydrogen in Lyα forest absorptions is negligible, because the gas in these systems is highly ionized. As N (HI) is difficult to determine for LLS, their contribution to Ωg is also uncertain. However, it is unlikely to be significant, since large surveys reveal that DLAs contain over 80% of the neutral gas in the Universe (e.g. Noterdaeme et al. 2012b, 2009; Zafar et al. 2013a). Systems with N (HI) ∼ 1021 cm−2 contribute the most to ΩDLAg, and ∼10% of ΩDLAg comes from gas in the highest column density absorption systems with N(HI) ≥ 0 5 × 1022 cm−2 (Noterdaeme et al. 2012b, 2009). The gas is fully neutral for DLA column densities, and thanks to the damped wings N (HI) is easy to measure from the absorption profile.
Since DLAs probe the most significant concentrations of neutral gas, these absorbers can be used to trace Ωg as a function of redshift. The mass density of neutral gas in DLAs, ΩDLAg, decreases from z = 3 5 to z ≃ 2 (Figure 1.8; Noterdaeme et al. 2012b, 2009; Prochaska et al. 2005; Prochaska & Wolfe 2009), as could be expected if star formation draws on the gas reservoir. At all epochs, ΩDLAg is significantly less than the amount of baryons in stars at z = 0, Ω⋆ = (2 5 ± 1 3) × 10−3 (Cole et al. 2001). This indicates that DLAs represent a transition phase between the ionized gas in the IGM and the cold neutral gas in the ISM.
P´eroux et al. (2003) advocated for including sub-DLAs, since their impact on Ωg in-creases above z > 3. Prochaska et al. (2005) and Guimar˜aes et al. (2009), who include both DLAs and sub-DLAs in their analysis, observe a decrease in Ωg beyond z = 3 5. Indeed, some authors argue that Ωg does not evolve significantly over 0 1 < z < 5 when the contribution from sub-DLAs is included (P´eroux et al. 2005; Zafar et al. 2013a). The decrease from z = 3 5 to z ≃ 2 is difficult to refute, but large error bars on ΩDLAg measurements at low-redshift provide leeway for interpretation.
Samples of low-redshift DLAs are difficult to obtain, because Lyα is in the UV for z < 1 65 and requires space-based observations. Rao et al. (2006) greatly improved the statistics by detecting 41 DLAs in the range 0 11 < z < 1 65 with a Hubble Space Telescope (HST ) survey that targeted quasar lines-of-sight known to have strong Mg II absorptions (see also Turnshek et al. 2014). Whether the values for ΩDLAg are biased by the Mg II selection or a statistical fluke has been discussed. Resolving these ques-tions of selection bias would require a large blind survey for DLAs at z ∼ 1, which is observationally expensive.
Metallicity
The chemical enrichment of an absorber can be measured from metals associated with the absorption system. The abundance of a species, X, is typically calculated relative to solar values:
[X/H] ≡ log N(X) − log N(X) (1.5) where log(N (X)/N (H))⊙ is the solar abundance and N (H) = N (H I)+N (H II). Working with predominantly neutral absorption systems simplifies the analysis, since the contri-bution from ionized hydrogen, HII, is negligible and N (H) = N (H I). The N (HI) is di-rectly measured from fitting the damped absorption profile, as described above. Column densities for metal absorption lines are determined by fitting the available unsaturated transitions for a species.
Low ionization transitions, including OI, SiII, CII, AlII, FeII, and MgII, are usually read-ily apparent for strong absorption systems, as are several higher ionization transitions, like AlIII, SiIV, and CIV. Typically several transitions for the same species are red-shifted to the visual portion of the spectrum, for example SiII λλλ1304, 1526, 1808 or FeII λλλλλλ1608, 2344, 2374, 2382, 2586, 2600. Working with metal absorptions red-ward of the quasar Lyα emission peak is preferable, so as to avoid blends with HI in the Lyα forest. Since the multiple transitions have different oscillator strengths, it is possible to obtain a good measure of the ion column density. Even if some of the transitions are saturated, optically thin absorptions can often be detected. For the column density to be meaningful, it must be measured from metal absorption lines that are not saturated. High signal-to-noise (S/N) and/or high resolution spectra are particularly valuable for detecting weaker absorptions.
The best metallicity indicator is OI, because it is tightly related to HI. They have similar ionization energies, 13.618 eV for OI compared to 13.598 eV for HI, and consequently can exchange electrons during collisions (Stancil et al. 1999; Watson 1978). Due to this charge transfer, OI ionization is coupled to that of HI. However, OI λ1302 is almost always saturated for strong absorption systems, and lower wavelength transitions are typically blended with the Lyα forest.
After OI, favored species are those that are not strongly depleted onto dust grains. For Fe, Cr, and other refractory elements that are easily incorporated into dust, the gas-phase abundances do not reflect the total abundances (Jenkins 2009). If detected and free of blends, Zn and S are robust metallicity indicators as they are nearly undepleted. Conveniently, the ZnII λλ2026, 2062 absorption lines are often unsaturated and located redward of the Lyα forest. The ratio of depleted to undepleted elements provides a measure of the dust content of quasar absorbers (e.g., Khare et al. 2012; Pettini et al. 1997).
As with DLAs, N (HI) can be accurately determined for sub-DLAs from the damped absorption profile. However, since the gas may not be predominantly neutral in sub-DLAs, ionization effects could bias metallicity measurements toward higher values (e.g. Milutinovic et al. 2010). Metals with ionization potentials greater than 13.59 eV, such as FeII (ionization potential of 16.18 eV), may be associated with the ionized gas, rather than the neutral component. The observed FeII to HI ratio would thus be overestimated. Ionization corrections constrained from grids of photoionization models evaluated in CLOUDY (Ferland et al. 2013) are typically within errors on the metallicity, ∼0 15 dex (Dessauges-Zavadsky et al. 2003; Meiring et al. 2008, 2007). P´eroux et al. (2007) used photoionization models to compute the ionization states for their sub-DLA sample and determined that the cosmological mass density from metals in sub-DLAs at z ∼ 2 5 is ΩZ, sub-DLAs = 1 41 × 10−6. At this redshift, sub-DLAs account for at most 6% of the total metal mass density, ΩZ = 2 47 × 10−5.
One caveat for DLA metallicity measurements is that they are integrated over the entire absorption line profile. The metallicity cannot be calculated for individual components, since the HI is saturated. Fitting the DLA Lyα line gives only the total N (HI). Metal-licity differences between components are therefore inaccessible, but it is still possible to compare the amount of depletion in each subsystem (Figure 1.10). In addition to depletion, nucleosynthesis can also affect metallicity measurements. An element may be prevalent or sparse depending on the dominant nucleosynthesis processes in the re-gion where it was produced. Obtaining metallicities for as many species as possible and considering their relative depletion (Figure 1.11) helps to identify trends in the gas composition.
Mean Metallicity
The mean metallicity is defined as Z = log(ΩZ ΩHI)) − log(ΩZ ΩHI))⊙. It depends on the comoving densities of metals, ΩZ, and neutral hydrogen, ΩHI. Although ΩZ cannot be measured directly, the mean metallicity for a redshift bin with i DLAs in a complete survey is calculated by summing over their metallicities and column densities (Lanzetta et al. 1995):
Up to z ∼ 5, The mean metallicity for DLAs decreases with increasing redshift: Z = (−0 22 ± 0 03)z − (0 65 ± 0 09) (Figure 1.12; Rafelski et al. 2012). Rafelski et al. (2014) observed that at z > 4 7 the mean metallicity drops significantly below the extrapolated linear fit. Although the mean metallicity evolves linearly with redshift, it is nonlinear in time. When viewed as a function of time, the most rapid change in metal abundances is at high redshift (see Figure 1.12, top axis).
Samples have targeted DLAs at both the metal-strong (Herbert-Fort et al. 2006; Kaplan et al. 2010) and metal-poor (Cooke et al. 2011; Dutta et al. 2014) ends of the abundance range. Kaplan et al. (2010) measure a median abundance of [M/H] ≈ −0 67 for metal-strong DLAs at z ≈ 2, which is 0.6 dex higher than a control sample of randomly selected DLAs. No DLAs with super-solar metallicities have been observed. The least enriched systems have [Fe/H] < −2, with some abundances as low as [Fe/H] ≃ −3 (Cooke et al. 2011; Dutta et al. 2014). The C/O ratio for these systems is nearly super-solar and follows a trend observed for halo stars in the Milky Way (Figure 1.13).
The Velocity-Metallicity Correlation
Ledoux et al. (2006) identified a correlation between the metallicity and the velocity width measured across 5% − 95% of the line optical depth, as per Prochaska & Wolfe (1997a), in a sample of 70 strong absorbers with N (HI) & 1020 cm−2 and redshifts 1 7 < zabs < 4 3 observed at high resolution with VLT/UVES. The velocity width is a proxy for the dark matter halo mass. The velocity-metallicity correlation (Figure 1.14) is likely the result of an underlying mass-metallicity relation for the DLA galaxies, which could imply that high metallicity systems are associated with more massive (and potentially brighter) galaxies. Møller et al. (2013) expanded the redshift range to 0 11 ≤ z ≤ 5 06 with additional DLAs from literature to investigate tentative evidence in Ledoux et al. (2006) that the mass-metallicity relation evolves with redshift. They find that the correlation zero-point remains constant at high redshift during the early phases of galaxy growth, relation with a slope of 1.12 is drawn as a red line. Upper Right: Residuals after subtracting the fit with no redshift evolution. Lower Right: Improved residual after subtracting the fit that includes redshift evolution. (Figure from Møller et al. (2013).) but increases sharply with decreasing redshift below z = 2 6 ± 0 2. DLA galaxies at low redshift are more metal-rich than those of equal mass at high redshift. Combining the velocity-metallicity and redshift-metallicity correlations, Neeleman et al. (2013) proposed a fundamental plane of DLA properties that relates their metallicity, redshift, and mass. The plane equation, which is based on data for 100 DLAs observed with Keck/HIRES, reduces the scatter around both correlations and suggests a mass-metallicity relationship with a zero-point that evolves from z = 2 − 5, in contrast to the Møller et al. (2013) results. Christensen et al. (2014) extended the mass-metallicity analysis to 12 confirmed DLA galaxies at 0 1 < z < 3 2 for which it was possible to derive stellar masses from spectral energy distribution fits to multi-band photometry. They inferred metallicity gradients and provide a formalism for calculating the stellar mass (M∗DLA) of the galaxy when the DLA metallicity and DLA galaxy impact parameter are known. Through these relations, the nature of DLA galaxies is becoming more clear.
Table of contents :
1 Introduction
1.1 A Brief Cosmic History
1.1.1 Growth of Galaxies
1.2 Absorption Systems
1.2.1 N(Hi) Frequency Distribution
1.2.2 Characterizing Strong Absorbers
1.2.2.1 Neutral Hydrogen Mass Density
1.2.2.2 Metallicity
1.3 Relating Absorption Line Systems and Galaxies
1.3.1 Mg ii Systems
1.3.2 CGM
1.3.3 DLA Systems
1.3.4 DLA Galaxies in Simulations
1.3.5 Observing DLA Galaxies
1.4 Thesis Work
2 SDSS-III Baryon Oscillation Spectroscopic Survey
2.1 Survey Goals
2.2 Telescope and Spectrograph
2.3 Data Processing and Quasar Redshift Estimation
2.4 Data Releases
2.5 Value-Added Catalogs
2.6 Quasar and Absorption System Science
2.7 Survey Results
2.8 Future Prospects
3 A glance at the host galaxy of high-redshift quasars using strong damped Lyman-alpha systems as coronagraphs
3.1 Introduction
3.1.1 Observing Quasar Host Galaxies
3.1.2 Associated DLAs
3.2 Sample Definition
3.2.1 Strong associated DLAs
3.2.2 Measuring DLA column densities and emissions
3.2.3 The Statistical Sample
3.2.4 The Emission Properties Sample
3.2.5 The Redshift Distribution
3.3 Anticipated Number of Intervening DLA Systems within 1 500 km s−1 of zQSO
3.3.1 Anticipated Number in DR9
3.3.2 The Effect of Clustering near Quasars
3.4 Characterizing the Statistical Sample
3.4.1 Scenario
3.4.2 Kinematics
3.4.3 Metals
3.4.4 Reddening
3.5 Characterizing the Narrow Lyα Emission
3.5.1 Correlation with other properties
3.5.2 Position and profile of the emission line
3.5.3 Comparison with Lyman Break Galaxies
3.5.4 Comparison with Lyman-Alpha Emitters
3.5.5 Comparison with Radio Galaxies
3.6 DLAs with partial coverage
3.7 Discussion and Conclusions
3.8 Follow-Up Projects
3.8.1 Observations with Magellan/MagE
3.8.2 Observations with VLT/X-shooter
3.8.3 Observations with HST/WFC3
4 Close Line-of-Sight Pairs
4.1 Introduction
4.2 Close Line-of-Sight Pairs in SDSS-III BOSS
4.2.1 The Transverse Correlation Function for Lyα Forest Absorptions
4.2.2 Quasar Host Galaxy Environments
4.3 VLT/X-shooter Follow-Up Observations
4.3.1 Pair SDSS J0239-0106
4.3.2 Pair SDSS J2338-0003
4.3.3 Pair SDSS J0913-0107
4.4 Preliminary Conclusions
5 A ∼6 Mpc overdensity at z ≃ 2.7 detected along a pair of quasar sight lines: filament or protocluster?
5.1 Introduction
5.2 Data
5.3 Absorption Systems
5.3.1 Background Quasar Line-of-Sight
5.3.1.1 Hi Absorption Systems
5.3.1.2 Abundances
5.3.2 Foreground Quasar Line-of-Sight
5.3.2.1 Hi Absorption Systems
5.3.2.2 Abundances
5.4 Discussion and Conclusions
6 Conclusions and Prospects 149
6.1 Conclusions
6.2 Prospects
6.2.1 Follow-Up Projects
6.2.2 Future Work
