Ngc 5024, Ngc 5466)

Elemental Abundance Investigation of Two Candidate Extragalactic Globular Clusters (NGC 5024, NGC 5466)

by Ashley Chutter BSc, University of Victoria, 2006

A Dissertation Submitted in Partial Fulﬁllment of the Requirements for the Degree of Master of Science in the Department of Physics and Astronomy

© Ashley Chutter, 2008 University of Victoria All rights reserved. This dissertation may not be reproduced in whole or in part by photocopy or other means, without the permission of the author. ii Elemental Abundance Investigation of Two Candidate Extragalactic Globular Clusters (NGC 5024, NGC 5466)

by Ashley Chutter BSc, University of Victoria, 2006

Supervisory Committee

Dr. K. Venn, Supervisor (Department of Physics and Astronomy)

Dr. C. Pritchet, Member (Department of Physics and Astronomy)

Dr. D. VandenBerg, Member (Department of Physics and Astronomy) iii Supervisory Committee

Dr. K. Venn, Supervisor (Department of Physics and Astronomy)

Dr. C. Pritchet, Member (Department of Physics and Astronomy)

Dr. D. VandenBerg, Member (Department of Physics and Astronomy)

Abstract

High resolution spectra have been analyzed for two and three stars respectively in the candidate extragalactic globular clusters, NGC 5024 and NGC 5466, with the High- Resolution Spectrograph on the 9.2 m Hobby-Eberly Telescope. The goal of this investigation is to evaluate the proposed extragalactic origins of these two globular clusters. Evidence of a tidal tail in NGC 5466 (Belokurov et al., 2006) and the association of NGC 5024 with the Sagittarius stream (Martinez-Delgado et al., 2004) targeted the clusters as likely remnants of recent accretion events and thus potentially of extragalactic origin. Determination of their chemical abundance patterns could provide unique evidence to either support or dispute these claims. NGC 5024 has been associated with a proposed wrap in the Sagittarius stream which could be supported if the chemistry of NGC 5024 is similar to other clusters associated with the stream. NGC 5466 has the longest tidal tail known, which hints at an origin in a now dispersed dwarf spheroidal galaxy. Additional evidence for these clusters’ capture origins has been compiled by Yoon & Lee (2002), demonstrating that these two low metallicity clusters, along with five others, are aligned in a single highly inclined plane in the iv outer halo. Confirmation that these clusters are remnants of dwarf galaxies would support a Galactic history which includes recent accretion events. Such evidence may bolster the cold dark matter hierarchical clustering scenario, which postulates the presence of a significant amount of substructure in the Milky Way. Unfortunately, at the metallicity of the target clusters ([Fe/H] = -1.9), the chemical distinction between Galactic stars and known dSph stars is not significant. The low [α/Fe] of dSph stars seen at higher metallicity is not apparent at [Fe/H] = -1.9 in either Galactic or dSph stars. Aside from a few mild discrepancies, NGC 5024 and NGC 5466 appear chemically similar to the Galactic field stars and globular clusters compiled by Pritzl et al. (2005). A moderate enhancement in the [Ba/Y] ratios relative to the halo field stars is the only positively detected chemical signature that is typically observed in dSph stars. Comparisons with Galactic GCs of similar age, metallicity and horizontal branch morphology (NGC 2298, NGC 6397 and NGC 5897) reveal a few other differences, but these could be attributed to systematic effects in the different analysis techniques. Although NGC 5024 has a similar metallicity to the GC Arp 2 that was stripped from the merging Sagittarius dwarf, neither Arp 2 (Mot- tini et al., 2008) nor the clusters in this study show any particularly unusual chemical abundance patterns. Thus, no conclusive evidence in support of or in opposition to the target clusters’ proposed extragalactic origins has been discovered. v

Table of Contents

Supervisory Committee ii

Abstract iii

Table of Contents v

List of Tables viii

List of Figures xi

1 INTRODUCTION 1

2 TARGET CLUSTERS 8 2.1 NGC 5024 ...... 8 2.2 NGC 5466 ...... 9

3 OBSERVATIONS AND DATA ANALYSIS 11 3.1 Observations ...... 11 3.2 Data Retrieval ...... 12 3.3 Data Reduction ...... 12 3.4 Combining Spectra ...... 14 3.5 Sky Subtraction ...... 15 3.6 Telluric Division ...... 15 3.7 Radial Velocities ...... 16 vi 4 SPECTRAL ANALYSIS 18 4.1 Line List and Equivalent Width Measurements ...... 18

5 ATMOSPHERIC ANALYSIS 20 5.1 Model Atmospheres ...... 20 5.2 MARCS and OSMARCS models ...... 23 5.3 Photometric ...... 25 5.4 Spectroscopic ...... 27 5.5 Atmospheric Parameters ...... 28 5.6 Atmospheric Parameter Uncertainties ...... 29

6 ABUNDANCE ANALYSIS 31 6.1 Standard Stars ...... 31 6.2 Abundance Uncertainties ...... 34 6.3 Spectrum Synthesis ...... 34 6.4 Hyperﬁne Structure ...... 35 6.5 Non-LTE Considerations ...... 37

7 DISCUSSION OF RESULTS 42 7.1 Iron ...... 42 7.2 Light Elements ...... 43 7.3 Alpha Elements ...... 43 7.4 Iron-peak Elements ...... 45 7.5 Heavy Elements ...... 45 7.6 Comparison with Galactic Globular Clusters ...... 47 7.7 NGC 5024 and the Sagittarius Dwarf ...... 51 7.8 NGC 5466 and the Tidal Tails ...... 53

8 SUMMARY 55 vii 9 Figures 64

10 Plots 78

11 Tables 89 viii

List of Tables

11.1 Cluster Information ...... 90 11.2 Target Information ...... 91 11.3 Observations ...... 92 11.3 Observations ...... 93 11.4 Line Data, Wavelengths and Radial Velocities from Doppler Shift Cal- culations - Standard Stars ...... 94 11.5 Line Data, Wavelengths and Radial Velocities from Doppler Shift Cal- culations - NGC 5024 ...... 95 11.6 Line Data, Wavelengths and Radial Velocities from Doppler Shift Cal- culations - NGC 5466 ...... 96 11.7 Radial and Heliocentric Radial Velocities ...... 97 11.8 Model Atmosphere Parameters ...... 98 11.9 Elemental Abundances and Uncertainties for Standard Stars . . . . . 99 11.9 Elemental Abundances and Uncertainties for Standard Stars . . . . . 100 11.9 Elemental Abundances and Uncertainties for Standard Stars . . . . . 101 11.10Elemental Abundance Atmospheric Model Comparison for Standard Star M13 III-18 – MARCS vs. OSMARCS ...... 102 11.10Elemental Abundance Atmospheric Model Comparison for Standard Star M13 III-18 – MARCS vs. OSMARCS ...... 103 11.10Elemental Abundance Atmospheric Model Comparison for Standard Star M13 III-18 – MARCS vs. OSMARCS ...... 104 ix 11.11Elemental Abundances and Uncertainties for NGC 5024 ...... 105 11.11Elemental Abundances and Uncertainties for NGC 5024 ...... 106 11.12Elemental Abundances and Uncertainties for NGC 5466 ...... 107 11.12Elemental Abundances and Uncertainties for NGC 5466 ...... 108 11.12Elemental Abundances and Uncertainties for NGC 5466 ...... 109 11.13Adopted Solar Abundances ...... 110 11.13Adopted Solar Abundances ...... 111 11.14Sensitivity of Abundances ...... 112 11.14Sensitivity of Abundances ...... 113 11.15Atomic Data and Equivalent Widths ...... 114 11.15Atomic Data and Equivalent Widths ...... 115 11.15Atomic Data and Equivalent Widths ...... 116 11.15Atomic Data and Equivalent Widths ...... 117 11.15Atomic Data and Equivalent Widths ...... 118 11.15Atomic Data and Equivalent Widths ...... 119 11.15Atomic Data and Equivalent Widths ...... 120 11.15Atomic Data and Equivalent Widths ...... 121 11.15Atomic Data and Equivalent Widths ...... 122 11.15Atomic Data and Equivalent Widths ...... 123 11.15Atomic Data and Equivalent Widths ...... 124 11.15Atomic Data and Equivalent Widths ...... 125 11.15Atomic Data and Equivalent Widths ...... 126 11.15Atomic Data and Equivalent Widths ...... 127 11.15Atomic Data and Equivalent Widths ...... 128 11.15Atomic Data and Equivalent Widths ...... 129 11.15Atomic Data and Equivalent Widths ...... 130 11.15Atomic Data and Equivalent Widths ...... 131 x 11.15Atomic Data and Equivalent Widths ...... 132 11.15Atomic Data and Equivalent Widths ...... 133 11.15Atomic Data and Equivalent Widths ...... 134 11.15Atomic Data and Equivalent Widths ...... 135 11.15Atomic Data and Equivalent Widths ...... 136 11.15Atomic Data and Equivalent Widths ...... 137 11.15Atomic Data and Equivalent Widths ...... 138 11.15Atomic Data and Equivalent Widths ...... 139 11.15Atomic Data and Equivalent Widths ...... 140 11.15Atomic Data and Equivalent Widths ...... 141 11.15Atomic Data and Equivalent Widths ...... 142 11.15Atomic Data and Equivalent Widths ...... 143 11.15Atomic Data and Equivalent Widths ...... 144 11.15Atomic Data and Equivalent Widths ...... 145 11.16Hyperfine Splitting Corrections for M13 III-18 ...... 146 11.16Hyperfine Splitting Corrections for M13 III-18 ...... 147 11.17Mn I and Cu I Hyperfine Splitting Corrections for NGC 5024 50371 . 148 11.18Metallicities, Ages, Horizontal Branch Parameters and Galactocentric Radii of Comparison Globular Clusters ...... 149 11.19Adopted Solar Abundances of Comparison Globular Cluster Studies . 150 11.20Applied Shifts to Comparison Globular Cluster Abundances Due to Differences in Oscillator Strengths ...... 151 xi

List of Figures

9.1 SDSS stellar map of the northern sky, showing trails and streams of stars torn from disrupted Milky Way satellites...... 65 9.2 Image of NGC 5024 ...... 66 9.3 Image of NGC 5466 ...... 67 9.4 CMD of NGC 5024 ...... 68 9.5 CMD of NGC 5466 ...... 69 9.6 MOOG plots of Fe I abundance versus excitation potential, equivalent width, and wavelength respectively for M13 III-18...... 70 9.7 MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region containing the Fe I lines at 6136.99 A˚, 6137.69 A˚ and 6137.99 A˚. 71 9.8 MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding the Ca I line at 6439.07 A˚...... 72 9.9 MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region containing spectral lines of Ca I, Ti II, Fe I and Ba II. . . . 73 9.10 MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding the O I line at 6300.31 A˚...... 74 9.11 MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding the Cu I line at 5105.54 A˚...... 75 9.12 MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding the La II line at 6390.48 A˚...... 76 xii 9.13 MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding the Eu II line at 6645.06 A˚...... 77

10.1 [X/Fe] versus metallicity for the individual α elements Mg I, Ca I, Ti I, Ti II, and their mean...... 79 10.2 [X/Fe] versus metallicity for the s-process elements Y II, Ba II, La II, and the r-process element Eu II...... 80 10.3 Ratios of [Y/Eu], [Ba/Eu], [La/Eu], and [Ba/Y] versus metallicity. . . 81 10.4 [α/Fe] versus metallicity for for our targets stars’ metallicity range. . 82 10.5 [Ba/Y] versus metallicity for for our targets stars’ metallicity range. . 83 10.6 Abundance ratios as a function of increasing atomic number for our program stars...... 84 10.7 Abundance ratios as a function of increasing atomic number for NGC 5024, NGC 5466 and NGC 2298...... 85 10.8 Abundance ratios as a function of increasing atomic number for NGC 5024, NGC 5466 and NGC 6397...... 86 10.9 Abundance ratios as a function of increasing atomic number for NGC 5024, NGC 5466 and NGC 5897...... 87 10.10Abundance ratios as a function of increasing atomic number for NGC 5024 and Arp 2...... 88 xiii

Dedication: Parents, rabbits, an oak tree. Cycling, comics, cats. 120, 404, 2347. Net force, angular momentum, SLAP. Gnome, BugBuddy, crondaemon. Survival, tenacity, love. 1

Chapter 1

INTRODUCTION

Globular clusters are dense spherical groups of hundreds of thousands of very old stars. They are intrinsically bright objects that can be observed at large distances; hence, their distances and ages can be determined from stellar evolution theory (Van- denBerg, Bergbusch & Dowler, 2006). Therefore, globular clusters are excellent tracers of galactic structure. Typically representing the oldest objects within a galaxy, they also preserve the history of the formation of that structure and are thus often called galactic “fossils”. Showing no active star formation, globular clusters are de- void of gas and dust. All of the stars in a particular cluster appear to be coeval with similar chemical compositions,1 usually having formed in the same ancient burst of star formation. Assuming that the chemical abundances in the atmospheres of cluster stars are representative of the composition of the gas out of which they formed,2 globular clusters are also good tracers of chemical evolution in galaxies. The Milky Way (MW) contains over 150 known globular clusters (Bica et al., 2006). Their chemical abundances closely mimic those of the ﬁeld stars in the halo (Pritzl et al., 2005) for many elements. A thorough knowledge of the properties of the Galactic globular cluster system, including locations, ages, kinematics and

1Current exceptions include ω Centauri, NGC 2808 and M4. The details of these unique clusters is beyond the scope of this study. 2Notable exceptions include carbon and nitrogen which are not included in this study. 2 chemical abundances can thus provide valuable insight toward an understanding of the formation and evolution of our Galaxy. Investigation of the properties of the Galactic globular clusters reveals them to be a very inhomogeneous group. This has led to the belief that the entire group does not share a common origin. In 1985, Zinn observed a distinct bi-modality in the spatial distribution of metallicity of these clusters. He found that the metal-rich globular clusters ([Fe/H] > -0.8) are confined to the bulge and disc of the Galaxy, while the metal-poor ([Fe/H] < -0.8) are generally located in the Galactic halo. Zinn also forged a natural division of the halo clusters into two groups based on their horizontal branch (HB) morphologies. The observation that clusters of similar metallicity often had different HB morphologies demonstrated the necessity for a second parameter (metallicity being the first) controlling these HB morphologies of the Galactic globular clusters. Assuming age as the second parameter (plausible though not proven) led Zinn to identify the blue HB types as the “Old Halo” group and the red HB types as the “Younger Halo” group. Zinn (1993) found that these different age groups also had different spatial distributions, placing the majority of members of the “Old Halo” in the inner halo, with “Younger Halo” clusters dominating the outer halo. It is generally believed that this scheme separates the cluster populations in terms of their formation histories as well. One of the most intriguing applications of globular cluster data is in the devel- opment of a complete model of galactic formation and evolution. Early models proposed a process of monolithic, dissipative collapse (Eggen, Lynden-Bell & Sandage, 1962; hereafter ELS), while later theories included the concept of accretion of small protogalactic fragments in a hierarchical merging scenario (Searle & Zinn, 1978; hereafter SZ). The presence of two distinct GC populations, as indicated by their bimodal metallicity distribution, rules out a simple one-stage collapse scenario. Zinn proposed that at least a significant fraction of the mass of the present day halo of the Galaxy 3 has been accumulated through mergers with satellite galaxies, and the consequent accretion of their constituent stars and globular clusters. SZ were led to the same conclusion when an examination of the abundances of a sample of Galactic globular clusters revealed no correlation between metallicity and Galactocentric radius in the outer halo (as expected by a simple collapse scenario). Zinn argued that the observed trends favoured a model in which the bulge, disc and old halo clusters formed during a dissipative collapse like that described by ELS, while the younger, metal-poor halo clusters were remnants of the mergers of their progenitors with the MW. Presently available data still appears to favour a model in which the main body of the MW

(the region Rgc < 10 kpc) was formed as described by ELS (modiﬁed by Sandage in

1990), while the extremities (the region Rgc > 15 kpc) were assembled by infall and capture of smaller fragments, as envisioned by SZ (van den Bergh & Mackey, 2004). This model has been favoured in recent years because it supports and complements the leading paradigm for the formation and evolution of structure in the Universe, that of cold dark matter (Navarro, Frenk & White, 1997). Cold dark matter (CDM) predicts the presence of a large amount of substructure in the halo of the Galaxy, as would be the result of merging dwarf galaxies being torn apart by tidal interactions with the Galactic field (Bullock, Kravtsov & Weinberg, 2001). Such tidal streams would only be preserved long enough to observe them and trace their paths in a cold dark matter scenario, as warm dark matter would rapidly disperse any such tenuous stellar associations (Bullock, 2006). The CDM scenario is thus further reinforced by recent observations of such tidally disrupted dwarf galaxy remnants and streams of spatially and kinematically associated stars and clusters trailing their progenitors. Serious doubt has been cast on the premise that the dwarf galaxies we observe today as satellites of the MW are related to the galactic building blocks involved in hierarchical merging scenarios (Tolstoy, 2004). Detailed abundance determinations of the dwarf galaxies in the halo have revealed abundance trends that are strikingly 4 different from those of field stars and globular cluster stars in the MW (Shetrone, Cote & Sargent, 2001; Venn et al., 2004). For instance, dwarf spheroidal galaxies (dSphs) tend to have RGB stars with lower [α/Fe] ratios than similar metallicity halo field stars and globular clusters. Additionally, a significant overabundance in [Ba/Y] is observed in most dSph RGB stars compared to Galactic stars (Venn et al., 2004; Pritzl et al., 2005). These chemical dissimilarities led to the conclusion that the Galactic halo could not have formed primarily via the accretion of such low mass dwarf spheroidal galaxies at late epochs. However, mergers with larger, more luminous systems were not ruled out by these observations. The apparent overlap in compositions of Galactic and dSph stars at the metal-poor tail retained the possibility of mergers with such dwarfs very early on in the history of Galactic formation (Tolstoy, 2004), before the dSphs could have experienced any significant chemical enrichment (Bullock & Johnston, 2004). The corollary of this was that most of the stars in the MW formed in situ, with only the metal-poor halo stars coming from accreted satellites (Tolstoy, 2004). Subsequently, Helmi et al. (2006) found clear differences between the metal-poor tail of the dSph metallicity distribution and that of the Galactic halo, showing that the progenitors of the observed dwarf spheroidal galaxies had to be fundamentally different from the building blocks of the MW, even at the earliest epochs. Font et al. (2006)’s ΛCDM models of MW-type halos emulated the chemical abundance patterns and stellar populations seen today in the MW stellar halo and dSphs. They concluded that the differences in chemical abundance patterns observed between Galactic halo field stars and the surviving dSph satellites arise naturally from the predictions of the hierarchical structure formation in a ΛCDM universe. In their models the inner halo formed early (> 8 Gyr ago), largely from a few massive satellite mergers, whereas satellites surviving today began merging with the MW relatively recently (only a few Gyr ago). Kazantzidis et al. (2007) created ΛCDM models 5 in order to track the structural evolution of a MW-type galaxy. Using numerical simulations of consecutive massive satellite encounters with a MW-type disc galaxy, they successfully reproduced the structure observed in the MW today, including persistent, faint, arching structures. Observations by the Sloan Digital Sky Survey have revealed trails and streams of stars torn from disrupted MW satellites (see Figure 9.1), the distribution of which suggests that the Galactic halo is nearly spherical (Belokurov et al., 2006b). The paths and widths of such coherent tidal streams are sensitive to the nature and distribution of dark matter in the MW (Ibata et al., 2002). The accumulating knowledge of such streams may therefore be useful in constraining the shape of the Galactic dark halo (Murali & Dubinski, 1999), as well as ascertaining whether or not the stellar halo replicates the substructure predicted by a ΛCDM Universe, thus probing the nature of dark matter. One of the best examples of substructure in the MW is the Sagittarius dwarf remnant (Ibata, Gilmore & Irwin, 1994) with its long, arching stream of tidally stripped stars and globular clusters. Globular clusters which are associated with such merger events remain kinematically linked with their hosts. Although their progenitor galaxy will disperse rapidly due to tidal interactions with the Galactic field, the globular clusters will be preserved for much longer due to their high densities (Gnedin, 2003; Moore et al., 2006). Several globular clusters have already been associated with the Sagittarius stream. These include: M54, Ter 7 and 8 and Arp 2 (Da Costa & Armandroff, 1995), Pal 12 (Dinescu et al., 2000), Pal 2 (Majewski et al., 2004), NGC 4147 (Bellazzini et al., 2003) and Whiting 1 (Carraro et al., 2007). NGC 5024, one of the target clusters of this investigation, has also been proposed to have been tidally stripped from the Sgr dwarf during its merger with the MW (Martinez-Delgado et al., 2004). Another example of substructure in the Galactic halo is the “Monoceros Ring” (Newberg et al., 2002), which could be the tidal debris of the dispersed Canis Major 6 (CMa) dwarf galaxy (Martinez-Delgado et al., 2005).3 Some streams have been identified in the Galaxy without any apparent progenitor. Such streams could therefore represent the residuals of ancient accretion events of fully assimilated hosts, whose chemical signatures could provide important information toward a comprehension of the MW’s formation history. The latest such detection in the “Field of Streams” is that of the “Orphan Stream”, so named for its lack of obvious progenitor (Grill- mair, 2006; Belokurov et al., 2006b), although Fellhauer et al. (2007b) argue that its progenitor may be the newly discovered disrupting dwarf galaxy UMa II (Zucker et al., 2006). Additional substructure exists in the form of tidal tails associated with Galactic globular clusters (Grillmair et al., 1995); impressive examples include the tails of Pal 5 (Odenkirchen et al., 2001; Grillmair & Dionatos, 2006) and NGC 5466 (Belokurov et al., 2006; Grillmair & Johnson , 2006), one of the target clusters of this investigation. However, even as these remarkable discoveries were made, a severe dearth in the number of observed satellite galaxies compared with that predicted by CDM simulations was revealed (Klypin et al., 1999; Moore et al., 1999). CDM predicts the presence of an order of magnitude more subhalos around the MW than the currently observed dwarf satellite galaxies can account for (Kravtsov, Gnedin & Klypin, 2004), although new satellite galaxies are being found with increasing frequency, particularly via the Sloan Digital Sky Survey data (e.g. Belokurov et al. (2007)). Several means of resolving this apparent conflict have been suggested. Bullock, Kravtsov & Weinberg (2000) proposed a natural solution in which star formation in dwarf galaxies is suppressed after re-ionization. In this scenario, the satellite galaxies observed today represent those subhalos that had already accreted a significant amount of gas prior to re-ionization. Thus, a plausible theory is that the majority of the orbiting subhalos predicted by CDM may actually be dark matter clumps containing few or no

3See Conn et al. (2005), Penarrubia et al. (2005) and Penarrubia et al. (2007) for discussions on alternative formation scenarios for the Monoceros stellar ring. 7 stars. N-body simulations run by Mayer et al. (2007) showed how such dark matter dominated dwarf galaxies could have formed via a combination of tidal shocks and ram pressure due to interactions of the progenitor subhalos with a ΛCDM MW-type halo. Hence, the faintness of these subhalos may form an explanation for why they have not yet been discovered. The potential impact on the cosmological model of the Universe and the formation of galaxies therein motivates the search for undiscovered substructure and disrupted subhalos in the MW and other galaxies. The purpose of this study is to investigate two candidate extragalactic globular clusters in the halo of the MW: one with an extensive tidal tail (NGC 5466) and the other potentially associated with the lengthy Sgr stellar stream (NGC 5024). The chemical abundances of red giant stars in each target GC are analyzed in order to search for any compositional signatures of the clusters’ formation in an environment unlike the MW. 8

Chapter 2

TARGET CLUSTERS

The two clusters which are the subjects of this investigation are merger candidates due to their kinematic and spatial properties. Yoon & Lee (2002) have shown that these two low metallicity clusters, along with ﬁve others, are aligned in a single plane in the outer halo, perpendicular to the Galactic plane. The velocities of all seven of these clusters also indicate an ordered motion around the Galaxy. (Martinez-Delgado et al., 2004) suggested that NGC 5024 may be associated with the tidal stream of the Sagittarius dwarf galaxy. NGC 5466 is associated with a tidal stream extending across 45◦ of the sky (Grillmair & Johnson , 2006), providing evidence that NGC 5466 may be the tidally stripped remnant of a merging dwarf galaxy. Since NGC 5024 is suspected to be associated with the tidal debris of the Sagittarius dwarf, a direct comparison of its stars’ chemical abundance trends with those of Sgr GC stars in addition to the comparison with Galactic ﬁeld and cluster stars (appropriate for both target clusters) is an excellent way to search for extragalactic signatures.

2.1 NGC 5024

NGC 5024 is a metal-poor ([Fe/H] = -1.99; Harris, 1996), moderately compact globular cluster in Coma Berenices, belonging to the outer halo of our galaxy. See Figure 9.2 for an image of this cluster from the Palomar Sky Survey. It was discovered by Jo- hann Elert Bode in 1775. Within uncertainties, it is identical in age to M92 (Heasley 9 & Christian, 1991). In fact, it has been found that all metal-poor globular clusters are essentially coeval (e.g. Heasley & Christian, 1991; Salaris & Weiss, 2002). NGC 5024 has a visible magnitude of 7.61 and a distance of about 17.8 kpc from the sun or 18.3 kpc from the Galactic Center. There is little or no foreground reddening (Harris, 1996) due to its high Galactic latitude. The cluster’s horizontal branch is almost exclusively restricted to the blue side of the instability strip and yet the first (BV) photometric study revealed it to be rich in variable stars (Cuffey, 1965). A dynamical association of NGC 5024 with the Sgr stream was proposed by Martinez-Delgado et al. (2004). They observed two possible main sequence turn-off features in a CMD of a section of the Sgr stream and suggested two possible causes. Martinez-Delgado et al. (2004) proposed that this second turn-off was either a signature of the tidal debris tail of a nearby globular cluster (e.g. NGC 5024), or was related to an additional wrap of the Sgr stream; a more diffuse, lower surface brightness, trailing arm. Based on proximity to this second stream, Martinez-Delgado et al. identified NGC 5024 as a candidate for a past constituent of the Sgr dwarf galaxy. The proper motion of NGC 5024 supports this idea, being consistent with a dynamical association with Sgr. Thus, location and kinematics indicate that NGC 5024 is associated with the Sgr dwarf remnant, and thus likely of extragalactic origin. Our investigation of the chemistry of this cluster will provide additional evidence towards a solution. If the association of NGC 5024 with this additional arm of the Sgr stream is confirmed by its chemistry, this will also substantiate the proposed orbit of Sgr.

2.2 NGC 5466

NGC 5466 is an old, metal-poor ([Fe/H] = -2.22; Harris, 1996), sparse, dim globular cluster that lies in the constellation Bootes. See Figure 9.3 for an image of this cluster from the Palomar Sky Survey. It was discovered by William Herschel on May 17, 1784. NGC 5466 has a visible magnitude of 9.04 and a distance of about 10 15.9 kpc from the sun or 16.2 kpc from the Galactic Center. Because the cluster resides at high Galactic latitude, reddening appears to be negligible (Harris, 1996). It has a blue horizontal branch and a large, centrally concentrated distribution of blue stragglers. Evidence for the tidal perturbation of this cluster was provided by Odenkirchen & Grebel (2004), who proposed that the Galactic tidal field would drag stars away from the cluster, resulting in mass loss. They also remarked on the similarity between NGC 5466 and the sparse and disrupting Galactic globular cluster Pal 5, which they had recently shown to have long tails of tidal debris (Odenkirchen et al., 2001). Tidal tails of various extents around NGC 5466 have been claimed by different groups (Belokurov et al., 2006; Grillmair & Johnson , 2006). Belokurov et al. observed tails of the GC stretching about 2◦ in either direction, while Grillmair and Johnson reported evidence for much larger tails extending 45◦ across the sky, of a width similar to the tidal tails of Pal 5. With no known progenitor and such substantial tidal tails, NGC 5466 may be the remnant core of an accreted dwarf galaxy. The tidal tails are not associated with the Sgr dwarf debris stream, which is much broader (Grillmair & Johnson , 2006). Grillmair and Johnson also derived an orbital path for the cluster, based on proper motion measurements of Brosche et al. (1991), which was consistent with the path traced by the tidal tails. Numerical simulations conducted by Fellhauer et al. (2007) confirmed these findings, affirming NGC 5466 as the globular cluster with the current record for longest tidal tails in the MW. Fellhauer et al. also agreed that NGC 5466 is losing mass due to tidal interaction with the MW potential, although quite slowly, and will likely survive a further Hubble time, gradually wrapping extensive but tenuous tidal tails around the whole Galaxy. This makes NGC 5466 a prime target for studies of tidal disruption and substructure in a CDM paradigm, potentially contributing significant constraints on the shape of the Galactic potential. 11

Chapter 3

OBSERVATIONS AND DATA ANALYSIS

3.1 Observations

High resolution spectra have ben obtained of two and three stars respectively in the two candidate extragalactic globular clusters, NGC 5024 and NGC 5466, with the High-Resolution Spectrograph (HRS) on the 9.2m Hobby-Eberly Telescope (HET). See Figures 9.2 and 9.3 for images and Figures 9.4 and 9.5 for colour-magnitude diagrams of the globular clusters NGC 5024 and NGC 5466, with the target stars labelled. Target stars were chosen from V and I photometry and sample a color range across the red giant branch. The target stars are faint (V ∼ 14.5 mag), and thus observations were taken for about 3 hours for each star in order to obtain adequate signal to noise ratios (See Table 2.). In addition, two standard stars were selected for observation in order to compare the abundance results obtained using our telescope and techniques with those already published using data gathered with a diﬀerent telescope. We obtained high resolution spectra of two such stars, one from each of NGC 5272 (M3) and NGC 6205 (M13), with HRS on HET. These stars (M3 C41303 2217 and M13 III-18) have previously been subject to a detailed spectroscopic analysis by Cohen & Melendez (2005, 12 hereafter CM05), using high resolution spectra obtained with HIRES at the Keck Observatory. Our observations are in the visual wavelength band, covering a range of 4090 – 7890A˚, while CM05 covered a similar wavelength range from 4650 – 7800A˚. The spectral resolution of our observations was about 30,000 while the CM05 con- ﬁguration had a corresponding spectral resolution of 34,000. Their spectra for these stars thus had signal to noise ratios slightly higher than our spectra. At 5865A˚, CM05 indicated signal to noise ratios of > 100 for both M3 and M13, whereas our spectra have signal to noise ratios of ∼ 45 for M3 and ∼ 70 for M13 at that wavelength.

3.2 Data Retrieval

HET provides access to data for each observing program through an ftp account. Our data are available at ftp://[email protected]. A program specific login (N0330) and password (hoknup5) are required. After successful login, all of the data pertaining to the specific program is displayed in chronological order, in the form of zipped fits files. Each file can be simply extracted and downloaded to an appropriately titled folder. In addition, all calibration files are provided and can be accessed by moving to a higher level directory, and selecting the folder corresponding to the year of the observation. By consulting the HET Night Report Reader at http: //het.as.utexas.edu/cgi-bin/ra/reader.cgi, one can confirm the exact date that the data was taken and the names of the necessary calibration files. Each calibration file can then be extracted and downloaded into the corresponding folder for processing. The necessary calibration files include biases, flats, Thorium-Argon (ThAr) lamps, and exposures of rapidly rotating (essentially featureless) hot stars which can be used as aperture references and telluric line divisors.

3.3 Data Reduction

Once all of the necessary data files were downloaded into folders corresponding to each night of observation, the process of data reduction using IRAF V2.14 began. 13 First, the task hsplit.cl was used to separate each of the files into its constituent header [0], red [1], and blue [2] extensions, while preserving the header information in each of the image files. The following reduction steps were applied to both the red and blue image frames unless otherwise stated. Correction for the overscan region, including trimming the image to remove this region, was performed using the task ccdproc. In this process, the bias level of the overscan strip region was calculated for each image individually and this was subtracted from the trimmed image frames. The preserved header information provided the task with each image’s individual overscan and trim regions. Average bias frames were created for red frames only using the task imcombine by adopting a median combining algorithm while the frame’s readnoise and gain were taken from its header information. This average bias was then subtracted from all red frames using the task imarith. Bias frames were not subtracted from blue frames since the blue HRS CCD is very clean (as indicated by HET online data reduction tips for the High Resolution Spectrograph (HRS): http://het.as.utexas.edu/ HET/hetweb/ProgramStatus/ProgramStatus.html), and bias subtraction can actually add noise if an unclean bias is used. Besides, the bias level was already accounted for during overscan subtraction. After this, each red frame was examined individually for bad pixels using a ds9 display window, and a text file was created defining the bad columns of data. This bad pixel file was fed into the task ccdproc which corrected the specified pixels. The blue frames, as previously mentioned, are very clean, and displayed no significant bad columns. Next, average flatfields were created with the task imcombine using a median combining algorithm, cosmic ray rejection, and mode scaling. In order to normalize the flatfields, an aperture reference file is required. Thus, the spectrum of a telluric standard star was extracted using the task apall and its aperture trace was used as the aperture reference file when running the task apflatten. The ThAr lamp frames were 14 then divided by this normalized flatfield using the task imarith, although this step was not necessary for the ThAr frames to be used as wavelength calibrators. Before the science frames could be divided by the normalized flatfield, the contribution from scattered light was subtracted using the task apscatter, again using the telluric standard star as the aperture trace. The spectra of both the science and arc frames were then extracted using the task apall, again referencing the telluric standard star’s aperture trace. Once the ThAr spectra were extracted, the task ecidentify was used to: interactively locate and identify lines based on comparison with a ThAr spectral atlas, determine the dispersion relation of the spectra, and calculate a wavelength solution. The science frames were assigned a reference ThAr spectrum with the task refspectra, and the dispersion coordinate system was set with the task dispcor, yielding wavelength- calibrated science spectra. The spectra were then normalized interactively using the task continuum, typically using a 6th order Legendre function with 1.4-sigma upper clipping and 4-sigma lower clipping. This resulted in normalized spectra with continuum values of ∼ 1.00.

3.4 Combining Spectra

The task scombine was used firstly to add spectra to improve signal to noise ratios and secondly to attach multiple apertures into one continuous spectrum, as described below. First, multiple spectra obtained of the same star, on the same night, in the same wavelength region, were added together using aperture grouping and the following procedure. The un-normalized spectra were divided by the normalized spectra to yield pure continuum spectra. The un-normalized spectra were summed, as were the continuum spectra using scombine, apertures grouping. This procedure resulted in the adoption of the header information of the first image as the header information 15 for the final, combined image. This information affects the calculation of heliocentric radial velocities. Second, the individual apertures of each summed, normalized spectrum were joined into one spectrum. This was achieved using scombine and images grouping. Then, each combined un-normalized spectrum was divided by the appropriate combined continuum spectrum, resulting in a combined, normalized spectrum. This procedure minimizes the noise in the regions where the apertures overlap, and maintains a 1.00 continuum value in the final spectrum.

3.5 Sky Subtraction

The HET online reduction tips indicate that it is possible to get away without doing sky subtraction at all. Our instrument has a sky fiber; however, sky fiber spectra were not requested in Phase I of the proposal for observations at the HET. Since the target stars of this program are all sufficiently bright (V < 15.0), the continuum sky contribution will be insignificant in comparison with that of the star. Additionally, this study almost exclusively uses spectral lines with wavelengths & 4800 A˚; hence, the sky contribution should not be significant in this regime. Thus, sky subtraction has not been performed.

3.6 Telluric Division

The extracted spectra from the standard stars, which are good telluric divisors (hot, rapidly rotating, essentially featureless), were used to remove telluric atmospheric absorption lines from the science spectra. Since telluric lines only appear in the red wavelength region of our data, only the red spectra were corrected. The process described for combining spectra was again used during the telluric correction process in order to prevent noise propagation. The extracted standard star spectra were normalized using continuum and an approximately 6th order Legendre ﬁt with 1.4- sigma upper clipping and 4-sigma lower clipping. The un-normalized spectra were then divided by the normalized spectra, yielding the continuum spectra. Both the 16 continuum spectra, and the un-normalized standard star spectra were then combined into one image each, using the images combining option of the scombine task. Then, the combined standard star spectra were divided by the combined continuum spectra in order to produce combined, single image, normalized standard telluric star spectra. The similarly reduced science spectra were then divided by these standard star spectra in order to remove the contribution of telluric lines. The end result was combined, normalized science spectra, cleaned of telluric lines.

3.7 Radial Velocities

In order to determine the radial velocities of the stars, several spectral lines with known rest wavelengths were identified in the spectra. Hα (6562.81 A˚) and Hβ (4861.33 A˚) were easily located due to the substantial broadening of these lines, and were helpful in preliminary estimations of the Doppler shift. However, these lines were not used in the final radial velocity calculations, since their breadth resulted in a comparatively large uncertainty in the locations of the central wavelengths. The observed wavelengths were the central wavelength of the best-fit Gaussian. The difference between the known and observed wavelengths of these lines was applied as a

Doppler shift in order to calculate the corresponding radial velocities via vr = c∆λ/λ (see Tables 11.4, 11.5 and 11.6). Averages of the values found for each line were taken and the resultant radial velocities were assigned to each stellar spectrum. Using the task dopcor, each spectrum was shifted by its radial velocity so that all spectral lines appeared at the expected rest wavelengths. Using sky lines (Hanuschik, 2003), the alignment of each spectrum was checked. Any observed offsets from expected sky line wavelengths were, for our purposes, negligibly small (∼ 1 km s−1) at less than a 1 pixel measurement error, and so the spectra were not further corrected. Once all spectra were aligned in this way, spectra of the same star taken on different nights were combined following the procedure as described above. 17 Heliocentric radial velocities were determined using the task rvcorrect and the necessary header information, which included the date, universal time, right ascension and declination of each observation, along with the observed radial velocity (see Table 11.7). The uncertainty in our measured wavelengths, corresponding to a 1 pixel measurement error, is 0.034 A˚ for all spectra, except that of NGC 5024 22254 for which it is 0.036 A˚. The uncertainty in the radial velocity calculated for each spectral line depends upon its wavelength (∼ ±2.0 km s−1 at 5000 A˚, ∼ ±1.7 km s−1 at 6000 A˚, and ∼ ±1.4 km s−1 at 7000 A˚). Thus, the average of the calculated uncertainties for the lines used in determining the radial velocities was found, resulting in a radial velocity error of ±1.7 km s−1 for all our HET spectra, except that of NGC 5024 22254 for which it was ±1.8 km s−1. We used the stellar heliocentric radial velocities to confirm cluster membership of our program stars by comparing with velocity estimates in the literature. Our heliocentric radial velocities for the standard stars are in excellent agreement with the values found by CM05. It is interesting to note that, although the radial velocities of all the stars in NGC 5466 agree extremely well with the values from the Harris online catalogue (Harris, 1996), both stars in NGC 5024 show a significant offset of ∼ 20 km s−1. However, these two stars’ radial velocities are very similar, indicating that they are associated with one another. 18

Chapter 4

SPECTRAL ANALYSIS

4.1 Line List and Equivalent Width Measurements

A list of spectral absorption line data was made including wavelengths λ (A˚), excitation potentials χ (eV), oscillator strengths log gf, and measured equivalent widths

Wλ (mA˚). Starting from a list of spectral lines from Shetrone et al. (2003), the data was checked with that available at the NIST online database (Ralchenko et al., 2008) and any discrepancies were investigated. Any clearly identifiable unblended lines which appeared in our spectra and in the NIST database were added to the linelist. The linelist from CM05 was also examined for any additional relevant lines. The online KURUCZ database (Kurucz & Bell, 1995) was consulted occasionally for atomic data not compiled in NIST. In the case of differences between atomic data from these publications and databases, the most recent source was used. However, since our results are intended for comparison with previously published data, a recent update to the oscillator strengths of Ba II (Curry, 2004) was not incorporated into our linelist, since this atomic data resulted in significant increases to the Barium abundances (∼ 0.50 dex), which would have biased our results. See Table 11.15 for a complete list of spectral lines, atomic data, and references. Once the atomic data was thoroughly checked, as many lines as possible were identified in the spectra and the equivalent widths were measured using the splot 19 task in the IRAF echelle package. A Gaussian fit was used to approximate the shape of each line, but the result given by an integrated measurement of the line width was favoured. This fitting takes the Lorentzian broadening wing component of strong spectral lines into account, being particularly relevant in the case of saturated and damped spectral lines. When a line was blended or asymmetrical, the Gaussian fit was favoured. For unsaturated lines these two methods of measuring equivalent widths returned very similar results. Every attempt was made to maintain a consistent linelist throughout our analysis. Unfortunately, several different lines from the master linelist had to be omitted from each specific star’s linelist due to interference by sky emission lines or poor signal to noise. A measured equivalent width of < 5 mA˚ was considered a non-detection, and therefore not included. CM05 used a slightly different linelist, although they covered the same wavelength range and the same elements were represented. Additional sources added some extra spectral lines to our list, while some lines which were detected in their spectra were not apparent in ours, likely due to their slightly better resolution and higher signal to noise ratios. There were occasional differences in atomic data between the two line lists, due to more recent updates being included in our compilation. Unlike our approach of measuring the equivalent width of each individual spectral line by hand, Cohen and Melendez employed a FORTRAN code, EWDET, developed for their project to search for absorption features and measure equivalent widths auto- matically. Nevertheless, in the analysis of our standard stars, we measured equivalent widths similar to those reported by Cohen and Melendez for spectral lines present in both lists. We were also able to reproduce similar abundance results using our model atmospheres and methods when adopting their linelist and atomic data along with a small compensation for the difference in adopted solar abundances. See § 6.1 for a more detailed discussion of our standard star abundance comparison with CM05. 20

Chapter 5

ATMOSPHERIC ANALYSIS

In order to determine elemental abundances from our spectra, we must ﬁrst construct an atmospheric model of the star, which describes the behaviour of the state variables, temperature T, and gas pressure Pg and/or density ρ as a function of the optical depth τ. Such a model will represent the atmosphere of the star via an eﬀective temperature

Teff , surface gravity log¸g,metallicity [Fe/H], and microturbulence ξ. If the model atmosphere thus generated adequately reflects the actual thermodynamic conditions of the stellar atmosphere, the atmospheric chemical composition can be determined by either the measurement of the spectral line equivalent widths or the appropriate fitting of the spectral line profiles and matching of the synthetic with the observed spectrum.

5.1 Model Atmospheres

The determination of stellar abundances through high resolution spectral analysis relies on the solution of the equation of radiative transfer, which provides the variation of the radiative energy ﬂow throughout an absorbing and emitting gaseous medium:

dIν(s) = jν(s)ds − kν(s)ρIν(s)ds, 21 where Iν is the specific intensity, jν and kν are the monochromatic emissivity and absorptivity coefficients and s measures the geometrical path length. We must also determine the emission and absorption coefficients jν and kν (sometimes referred to as the opacity) which are directly proportional to the transition probabilities and number of atoms or ions in a given quantum state or energy level. Atomic and ionic populations depend upon the elemental abundance as well as the degree of excitation and ionization. These latter quantities are calculated via the solution of the statistical equilibrium equations based on the specific temperature, gas density and composition and the appropriate atomic constants. Several simplifying assumptions are made in the classical approach to atmospheric modeling. The first of these is that of local thermodynamic equilibrium (LTE). Conceptually, LTE means that the gas particles in the atmosphere are confined to an area of constant local temperature, although the photons, having a greater mean free path, may be able to escape. The distribution function for the material particles (but not necessarily the photons) is therefore defined as in thermodynamic equilibrium by the local values of the state variables via the Maxwell distribution:

n(v) m 3/2 2 dv = 4πv2 exp−(1/2)mv /kT dv, N LT E 2πkT where N is the total number of particles with mass m per cm3. All atomic and molecular level populations are thus given by Saha-Boltzmann statistics as deﬁned by the local temperature. The Boltzmann excitation distribution describes the relative population densities of atomic levels s and t of ionization stage r:

nr,s gr,s − = exp (χr,s − χr,t)/kT , nr,t LT E gr,t

where g and χ represent the respective statistical weights and excitation energies of the levels. The Saha ionization distribution gives the population ratio between the 22 ground levels of successive ionization stages:

3/2 nr+1,1 1 2gr+1,1 2πmekT − = 2 exp χr/kT , nr,1 LT E Ne gr,1 h

where Ne is the electron density, me the electron mass, χr the ionization energy of stage r. The combination of these two distributions gives the LTE population ratio between a particular level i and the ion state c to which it ionizes, i.e. the Saha- Boltmann distribution:

n 1 2g 2πm kT 3/2 c c e −χci/kT = 2 exp . ni LT E Ne gi h

Another fundamental assumption in classical atmospheric modelling is that the thick- ness of the atmosphere is small compared to the radius of the star. We can therefore treat the local geometry like that of a plane-parallel slab. Additionally, it is assumed that the atmosphere is spherically symmetric, of homogeneous composition, and static (time-independent). Also, given that the mass of the atmosphere is small compared with the total stellar mass, it is consistent with the plane-parallel atmosphere to assume that the surface gravity (¸g= GM/R2) is constant. Conservation of luminosity (no sources or sinks of energy) then dictates that the eﬀective temperature

2 1/4 (Teff = (L/4πσR ) ) must be constant as well. An equation of state which relates the state variables (ρ,Pg and T) must also be assumed. The ideal gas law generally holds in stellar atmospheres and is commonly expressed in several diﬀerent forms:

nmoleRT ρkT ρRT Pg = = NgkT = = . V µmH µ

The electron pressure and gas pressure are simply related by:

Nnuclei + Ne Pe = Pg . Ne 23 The requirement that the atmosphere be in hydrostatic equilibrium can then be expressed as: dP (r) GM(r)ρ = − = −¸gρ. dr r2

Combined with the deﬁnition of the optical depth:

dτν = −kνρdr, the ﬁnal model atmosphere can be produced, through successive and concurrent in- tegration and iteration of the stellar structure equations (via a computer program), using the T(τ) relationship to set the surface boundary conditions. The model atmosphere is then typically output in the form of values for T, Pg,Ne,Pe, ρ and kν over the entire range of optical depth τ.

5.2 MARCS and OSMARCS models

In this investigation, we generated two versions of the atmospheric models initially developed by Gustafsson et al. (1975) and subsequently updated by Plez et al. (1992), Edvardsson et al. (1993), and Asplund et al. (1997). The original MARCS and the updated OSMARCS models both make the assumption of local thermodynamic equilibrium (LTE). Additionally, Gustafsson et al. (1975) made the common basic assumptions of plane-parallel stratiﬁcation of the atmosphere in homogeneous sta- tionary layers and hydrostatic equilibrium. The orginal hydrostatic, plane-parallel MARCS models represented line-blanketing via opacity distribution functions, and accounted for the eﬀects of convection following standard mixing length theory (Henyey et al., 1965). Line blanketing is opacity due to absorption of atomic spectral lines. The interpretation of molecular line opac- ities has since evolved, prompting the accumulation of unprecedented vaults of line

absorption data (e.g. VALD: http://ams.astro.univie.ac.at/˜vald/) for 24 application in model atmosphere calculations. Convection, an energy transport mech-

4 anism which is important in cooler atmospheres (Teff < 10 K), is indirectly observable as atmospheric velocity fields and is incorporated via the microturbulence parameter. The microturbulent velocity parameter was originally included in the models as a means of accounting for the empirically observed (but not theoretically understood) non-thermal contribution to the Doppler broadening velocity. Varia- tions in line absorption coefficients can be taken into account by setting the amount of microturbulence to match the computed line profiles with the observed. Given the effective temperature, surface gravity and metallicity of the appropriate atmosphere, the MARCS program will generate a table that represents the physical characteristics of the specified atmosphere. The columns of data represent runs of optical depth, temperature, gas pressure (logarithmic), electron pressure (logarithmic), mean molecular weight and opacity. The update by Plez et al. (1992) included a grid of spherically symmetric models for giant stars. The most recent grid of models is described in Gustafsson et al. (2008), which assume the stratification of the atmospheric layers to be spherically symmetric, supplementing with plane-parallel geometry at the highest surface gravities. This is reasonable since, at the highest surface gravities, the structures of the plane-parallel and spherical models are essentially identical (Lester & Neilson, 2008), but this is not the case at low surface gravities. Thus, due to the low gravities of the target stars in this study, the spherically symmetric OSMARCS models were preferred for the analysis. Three modifications to the code are necessary in order to generate models with spherical rather than plane-parallel geometry. The radiative transfer equation is complicated by spherical geometry since the the angle between a ray of light and the radial direction varies with depth. This results in the addition of an extra term to the transfer equation. The pressure and temperature structures are also affected by the change from plane-parallel to spherical geometry. Spherical models are generally 25 cooler in the upper layers of the atmosphere than their plane-parallel counterparts, becoming progressively cooler with increasing height but hotter in the deepest atmospheric layers. In order to generate OSMARCS models, the code based on the 2005 online grid combined with an extension for cooler stars with low log¸gand metallicity (Plez 2006, private communication) was used. Atmospheric models were thus generated with parameters iteratively constrained to well within the uncertainties of the parameters in every case. The plane-parallel MARCS models were generated for the purpose of a comparative analysis, thus enabling an easier interpretation of the results from the perspective of studies which have used the more standard MARCS models. Using the standard star M13 III-18 as an example, the abundances resulting from the analyses using MARCS and OSMARCS models were compared. As can be seen in Table 11.10, the small differences between derived abundances are less than the standard deviation for every species.

5.3 Photometric

Estimates of the eﬀective temperatures and surface gravities of the stars were determined using their (V-I), (V-K) and (J-K) colour indices (see Table 11.2). The color versus Teff scale of Alonso et al. (1999) which applies to metal-poor giants and is based on the InfraRed Flux Method (Blackwell et al., 1990) was adopted. Each temperature found from one photometric colour was similar to the others, diﬀering from the mean by at most 40 K. The (V-K) index was particularly useful, generally yielding the temperature value with the smallest deviation from the mean (Black- well & Lynas-Gray, 1998). The value of Teff was calculated from the average of the

Tvi,Tvk, and Tjk for our target stars, whereas only Tvk was used for the standard stars. J,H,K colours were obtained from the 2MASS online point source catalogue accessed via the IPAC IRSA web interface (http://irsa.ipac.caltech.edu/). 26 We acquired the necessary B,V,R,I photometry for our clusters from Dr. P. Stetson (2008, private communication) from which we created (V vs. V-I) colour magnitude diagrams for NGC 5024 and NGC 5466 (see Figures 9.4 & 9.5), with superimposed isochrones generated from the Victoria-Regina models of VandenBerg, Bergbusch & Dowler (2006, see also VandenBerg et al., 2000). In order to create the isochrones, we adopted the best available parameters for metallicity ([Fe/H] = -2.01) and α abundance ([α/Fe]= +0.3), based on the results obtained in this study (see Tables 11.11 and 11.12). The reddening of each cluster was found from the horizontal shift necessary to align the isochrones with the cluster data, using E(V-I) = 1.25E(B-V) (Bessell & Brett, 1988). The visual distance modulus of each cluster was determined from the vertical shift in V necessary to align the isochrones with the cluster data. The resultant values agreed with the values given in Harris’ online catalogue (Harris, 1996). After correcting the visual distance modulus for interstellar absorption, we calculated the distances to the clusters, which were also consistent with Harris. For

0.2((m−M)0+5) this calculation we used d = 10 pc where (m − M)0 = (m − M)v − A(V ) with A(V ) = A/1.015 and A = 3.315 ∗ E(B − V ) (Schlegel et al. (1998), Table 6). These isochrones indicate that NGC 5024 and NGC 5466 are old globular clusters, with ages of ∼ 14 Gyr. Note that this method did not include diﬀusion processes, which would have resulted in lower ages (by about 10% – 12%; VandenBerg et al., 2002). The target stars’ locations have been indicated on these CMDs (see Figures 9.4 and 9.5). The appropriate value of log¸gis constrained entirely by the true distance modulus of the cluster along with the bolometric correction. Alonso et al. (1999) provided a bolometric correction calibration which we adopted and applied in our calculation of the surface gravity. Fundamental considerations give rise to the following equation 27 for the surface gravity of a star:

¸g∗ M∗ Teff∗ log = log + 4 log + 0.4(Mbol∗ − Mbol ), ¸g M Teff

1 M = M + BC, where M = m + 5 log π + 5, and π[00] = . bol V V V d[pc]

Since the parallax of the star comes into this calculation via its distance, this technique is sometimes called the method of trigonometric parallax or simply, the trigonometric method. Since the turnoﬀ mass is a very slow function of age, a mass of 0.80 M was adopted for each of the target stars. The reddening and visual distance modulus values were taken from the Harris online catalogue (see Table 11.1). CM05 also gathered cluster data from Harris (1996), assumed a mass of 0.8 M , and cited the same sources for colour data in their preliminary photometric analysis of stars in

M3 and M13. The resultant preliminary values for Teff and log¸gwere employed as a starting point for the more rigorous method of atmospheric modelling using spectrum synthesis techniques.

5.4 Spectroscopic

The next step was the spectroscopic refinement of the atmospheric parameters (effective temperature Teff , surface gravity log¸g,microturbulence ξ, and metallicity [Fe/H]) for each star. To perform the analysis the current version (2002) of the LTE line analysis and spectral synthesis software package MOOG (Sneden, 1973) was used. The list of elemental absorption line data (λ (A˚), χ (eV), log gf, Wλ (mA˚)) was input into MOOG using the ABFIND driver along with a series of MARCS and OSMARCS model atmospheres. Any lines producing extremely deviant abundances were examined for potential sources of contamination (e.g. blends or sky line inter- 28 ference). Several blended or misidentified lines were corrected in this way. Effective temperature was verified by ensuring that the Fe I abundance was independent of excitation potential. Surface gravity was approximated by forcing Fe I lines and Fe II lines to produce the same Fe abundance. In this approach the ionization equilibrium between Fe I and Fe II was assumed, which may not be entirely accurate given non- LTE considerations (see § 6.5). Microturbulence was identified by making sure the Fe I abundance was independent of the equivalent width of the spectral lines. See Figure 9.6 for plots of these established trends as obtained for M13 III-18, using the model atmosphere parameters as indicated in Table 11.8. Once the correct parameters were determined and the appropriate model atmosphere was input along with the line list, MOOG calculated and output the corresponding elemental abundances and associated errors (see Tables 11.9 – 11.13). Cohen and Melendez used the same approach, employing the MOOG spectral synthesis program, along with the same constraints for determining the atmospheric model parameters. However, CM05 used Kurucz (Kurucz, 1993) models whereas we

favoured spherical OSMARCS models. CM05 additionally adopted the Teff value as derived from the photometric (trigonometric) method, rather than the spectroscopic technique. Fortunately, for these stars, the two diﬀerent approaches produced essentially the same value for the eﬀective temperatures.

5.5 Atmospheric Parameters

The parameters obtained via photometric analysis (Teff and log¸g)should ideally be similar to those obtained via the more rigorous spectroscopic investigation. This agreement is reached to within reasonable precision for the standard stars. The MARCS model parameters are highly consistent with the KURUCZ model parameters obtained by Cohen & Melendez (2005), albeit very slightly cooler and more metal-poor. Both spectroscopic investigations led to moderately higher Teff values 29 (by ∼ 100 K) than the photometric results, while the surface gravities were almost exactly the same. It was somewhat surprising, therefore, to discover significant differences between both the temperatures and surface gravities of the target stars as determined by these two methods. The spectroscopically determined MARCS models have Teff values that are consistent with the photometric values, but the MARCS log¸gvalues are all about 0.60 dex lower than the photometric surface gravities. The OSMARCS models have systematically higher temperatures than the MARCS models (by ∼ 150 K), but essentially identical surface gravities. The source of this discrepancy is a matter of some interest. It is possible that the photometry we have obtained for the target stars is inaccurate. A change in V of -0.10 mag would compensate for the discrepancy between the derived temperatures. However, this change would be accompanied by an increase in log¸g. The increase is small at only +0.03 dex, but certainly in the opposite sense of the necessary correction. Since an increase in temperature will thus be accompanied by an increase in surface gravity, it appears that there must be another source for the observed disparity between our photometric and spectroscopic model parameters. One possibility is the presence of non-LTE overionization. Significant non-LTE effects have been reported for Fe I lines, particularly at low [Fe/H] (see § 6.5). The main effect responsible for the departure of Fe I lines from LTE conditions is overionization by excess ultraviolet radiation. Thus, the classical assumption of ionization equilibrium is likely not satisfied, and consequently, surface gravities derived by the standard LTE analysis of Fe I lines may incur significant errors.

5.6 Atmospheric Parameter Uncertainties

The total error in atmospheric parameters is determined by an analysis of the results output by various model atmospheres using the M13 standard star spectral line list. Beginning with the best fit OSMARCS model, small variations were applied to the 30 effective temperature, surface gravity, microturbulence and metallicity independently in order to determine the change which caused a 1 σ deviation in Fe I abundance. A change in effective temperature of approximately +100 K resulted in an output iron abundance equal to the initial abundance plus its standard deviation. The application of a 0.25 dex increase in surface gravity resulted in output abundances for neutral and singly ionized iron whose values differed by the standard deviation in neutral iron abundance. Increasing the microturbulent velocity value by 0.20 km s−1 decreased the neutral iron abundance by a value equal to its standard deviation. The adopted error in [Fe/H] abundance is 0.20 dex, which is comparable to the average standard deviation in iron abundance (Fe I and Fe II standard deviations added in quadrature). These values represent the uncertainties in the atmospheric parameters as determined for the standard star in M13, and are considered to be generally representative of the expected atmospheric parameter uncertainties associated with each of the target stars. 31

Chapter 6

ABUNDANCE ANALYSIS

Before deriving conclusions from our output chemical abundances, consistency checks must be performed, and the possible effects of a few additional phenomena must be considered. The abundances found for the standard stars by Cohen & Melendez (2005, hereafter CM05) using HIRES on Keck are compared with the results of this study which used HRS on HET, and the uncertainties associated with the derived abundances are discussed. The details of the applied spectrum synthesis techniques, hyperfine structure corrections and non-LTE effects are described.

6.1 Standard Stars

Using spectra obtained with the high resolution spectrograph on HET, we derived atmospheric model parameters (see Table 11.8) and elemental abundances (see Table 11.9) for the standard stars that are highly consistent with those obtained by CM05 using spectra obtained with the high resolution spectrograph on Keck. A thorough investigation was performed into potential abundance variations due to differences between the spectral lines and atomic data adopted by CM05 and this study. Using the appropriate OSMARCS model atmospheres and our measured equivalent widths, abundances corresponding to our linelist and atomic data, our atomic data with the CM05 linelist, and both the linelist and atomic data from 32 CM05 were derived and compared.1 The linelist and atomic data from CM05 led to slightly lower temperatures, gravities and metallicities relative to the atmospheric parameters derived using our linelist and atomic data, which led to small variations in the abundances. However, no significant abundance deviations due to our somewhat different linelist or updated choices of atomic data were apparent. Switching between our sets of equivalent width measurements, which we previously noted to be very similar, revealed no significant effects upon either the model atmospheres or the derived abundances. The published abundance ratios of CM05 (altered slightly to account for differences in our adopted solar abundances, see Table 11.13) were then compared with those of this investigation (see Table 11.9). As expected from the differences in adopted linelists and atomic data, CM05 reported slightly lower metallicities for both standard stars. The next obvious deviation occurred for [O I] in the M13 star. Only one line (6300.31 A˚) was identified by CM05 in this case, whereas both forbidden lines were detected in this study, and the derived abundance was confirmed via spectrum synthesis. Both studies adopted the same atomic data for [O I], and arrived at very similar abundances for the M3 star where both lines were observed in both investigations. Thus, this discrepancy does not affect our confidence in the result here or those obtained for our target stars. Additionally, our Mg I abundances appear depleted compared to the CM05 val-

1The only significantly disparate elemental abundance was that of Barium. The source of the difference in abundance was the recently updated oscillator strengths for the Ba II spectral lines (Curry, 2004) that we had been using. CM05 used older values for the oscillator strengths (Miles & Wiese, 1969), as will have any authors of publications prior to 2004. The updated log gf values resulted in a significant increase in Barium abundance (∼ 0.5 dex) compared with the results obtained with the older oscillator strength values. Thus, we have reverted to the older oscillator strength values for Barium as used in Shetrone et al. (2003) and Cohen & Melendez (2005) in order to preserve a direct comparison between our results and those of previous analyses. Care should be taken in future analyses of this nature to avoid directly comparing abundances for Barium derived using these two very different sets of atomic data. While Barium yielded the most extreme case of discrepant abundances due to different sources of atomic data, this potential source of error should not be overlooked in comparisons of other species. It is important to maintain, as much as is possible, consistent sets of atomic data between studies when such abundance comparisons are of pivotal importance to the investigation at hand. 33 ues. This is due to the inclusion of three additional magnesium lines (at 4571.09 A˚, 5172.68 A˚ and 5183.60 A˚) not used by CM05. The third member of the triplet at 5167.32 A˚ was not included because it was too strongly blended with the Fe I line at 5167.48 A˚ to accurately disentangle and measure its equivalent width. Each of the included Mg I lines are subject to significant non-LTE effects (see § 6.5). The application of the necessary non-LTE corrections would bring our derived abundances into agreement with those of CM05. The neutral iron peak elements (Fe, Ti, V, Mn, Co, Ni, Cu) are all visibly enhanced (∼ 0.10 dex) relative to CM05 abundances. This is due to the higher effective temperatures (∼ +100 K) adopted for our model atmospheres. An offset from the CM05 value for [Ba II/Fe] of 0.16 dex is apparent for the standard star in M3. We and CM05 use the same three lines and atomic data for this species, with similar measured equivalent widths. Rather, this difference appears to originate from the substantial variation (0.20 km s−1) between our adopted microturbulent velocity values as applied in our model atmospheres. As indicated in Table 11.14, an increase in microturbulence of this magnitude will result in a decrease in Ba II abundance of the same amount. Thus, since CM05 applied a microturbulence value 0.20 km s−1 more than ours, we should expect their resultant abundance ratio to be about 0.20 dex less than ours, as is observed. The origin of this disparity in microturbulent velocities is uncertain and unexpected, since both studies applied the same constraint in the determination of the microturbulence (namely, that Fe I abundance be independent of line strength), and used similarly large samples of lines. No other significant (> 0.10 dex) divergences between our abundances and those reported by CM05 are observed and so, all such apparent deviations being accounted for, we conclude that the agreement between our results is very good. Additionally the O and Na anticorrelations identified by Kraft et al. (1992) in M13 and M3 are reproduced. That is, the M13 giant is observed to be O poor and 34 Na strong, while the M3 giant is O rich and Na weak. The consistency of these standard abundances confirms the accuracy of our derived chemical compositions as well as the validity of our methods as described in this paper. In addition, our instrumental setup with HRS on HET has been verified to produce well-calibrated spectra, consistent with acceptable standards.

6.2 Abundance Uncertainties

The sensitivities of the abundances to small variations in atmospheric parameters are indicated in Table 11.14. The small variations selected for each parameter are chosen based on the uncertainty determined for each model atmosphere parameter. Explicitly, the applied shifts are +100 K in eﬀective temperature, +0.25 dex in surface gravity, +0.20 km s−1 in microturbulence, and +0.20 dex in iron abundance. The sensitivities listed were determined using the data for the standard star in M13, and are a reasonable indication of the abundance sensitivities of the other target stars.

6.3 Spectrum Synthesis

Spectrum synthesis was used to investigate certain important elements with only a few weak lines (O, Cu, La and Eu). This technique can also be used to estimate upper limits for elemental abundances when lines are too small (i.e. < 5 mA˚ in this study) to accurately measure the equivalent widths. This approach was attempted for the estimation of aluminum abundances. Unfortunately, the presence of sky lines and a large amount of noise in the region (6696 – 6699 A˚) rendered even an upper limit virtually meaningless for this element. Al was only detected in the star in M13 for which the signal to noise was highest and the spectral region was cleanest. Synthetic spectra were created and displayed with the SYNTH driver in MOOG for the wavelength region in question. A detailed linelist including all available relevant lines in the region was compiled using a combination of the NIST and KURUCZ databases. The observed spectrum was plotted over the synthetic and displayed for 35 comparison. The Gaussian broadening term was determined from the resolution of our instrument (R ∼ 30,000) and the wavelength of the line by ∆λ = λ/R. The only remaining free parameter was then the rotational broadening term vsini which was determined by ﬁtting several clear, fairly strong lines of various species. For each star vsini was between 0 and 6 km s−1. Then, the abundance was varied until the most accurate match was obtained between the synthetic spectrum and the observed. Any discrepancies between the abundances determined from equivalent width measurements and those found from spectrum synthesis were investigated and resolved such that, in the end, none of the diﬀerences were larger than the total error (see Table 11.14) on the abundance.

6.4 Hyperﬁne Structure

The spin angular momentum of the nucleus in atoms and ions couples with the total angular momentum of the electron cloud causing hyperfine splitting of the atomic energy levels. The effect is usually negligible, with the component separations well below the equivalent width. Isotopes with an odd number of protons and/or neutrons will have an unbalanced nuclear spin and therefore experience noticeable hyperfine interactions between the nucleus and electrons. These interactions split the lines into multiple components with typical separations of 1 – 10 mA˚. This effect is relevant to stellar abundance determinations in that the hyperfine splitting (HFS) desaturates strong absorption lines, yielding overestimated equivalent width measurements. This, in turn, will lead to overestimated abundances for strong lines (with large equivalent widths) if the hyperfine splitting is ignored. Since the effect increases with line strength, it becomes necessary to account for hyperfine structure in strong lines in order to accurately measure the elemental abundance, although the effect is generally unimportant in weak, unsaturated lines. Hyperfine interactions split the absorption lines of several odd-Z elements (e.g. 36 Sc, V, Mn, Co, Cu) as well as three even-Z elements (Ba, La and Eu) that are significant to this study. For the abundance analysis HFS corrections were considered for significant hyperfine transitions of these elements. We adopt the HFS data from Prochaska et al. (2000) for Sc, V, Mn, Co, Cu and Ba, while data for La and Eu came from Lawler, Bonvallet & Sneden (2001) and Lawler et al. (2001), respectively. In order to employ this HFS data, we implemented the BLENDS driver of the MOOG spectral synthesis package, which matched the observed equivalent width of each line with that calculated from a synthesis of the blended hyperfine lines. Each hyperfine output abundance was then compared with the abundance determined neglecting the presence of hyperfine splitting. For differences amounting to less than the standard deviation of the abundance of the element in question, no corrections were applied. We used our standard star M13 III-18 as a means of tracking down potentially significant hyperfine structure corrections. Since M13 III-18 has the highest signal-to- noise, it also has the strongest lines and will therefore have the largest HFS corrections of all our program stars. Thus, the data in Table 11.16 represents an upper limit to the HFS corrections for our target stars. These corrections, considering only the lines with HFS structure, resulted in small abundance shifts for the elements in question (-0.03 for Sc II, -0.07 for V I, -0.22 for Mn I, -0.03 for Co I, -0.22 for Cu I, -0.05 for Ba II, -0.01 for La II, and -0.06 for Eu II). All of these corrections are insignificant (i.e. less than the standard deviation of the elemental abundance) except in the case of Mn I and Cu I. These abundance shifts have not been applied to the results in Table 11.9. Although Cohen & Melendez (2005) did comment on the presence of hyperfine structure splitting for Sc II, V I, Mn I, Co I, Cu I and Ba II they did not provide the results of their calculations. Thus, our HFS results cannot be compared directly with those of Cohen and Melendez, and are provided for information only. The hyperfine Mn I and Cu I lines were then put through an additional run with the BLENDS driver in MOOG, this time using the equivalent width data and 37 model atmosphere of one of our target stars, NGC 5024 50371. NGC 5024 50371 has a representative signal-to-noise ratio for our target stars, and will thus have characteristic line strengths and HFS corrections. The atmospheric model for this star is also very similar to the model atmospheres of the other target stars. Hence, the HFS corrections as calculated for NGC 5024 50371 (Table 11.17) could be applied with confidence to each of our target stars. The resultant hyperfine abundance corrections amounted to -0.14 for Mn I and only -0.3 for Cu I. These small shifts are provided for information only, and have not been directly applied to the results.

6.5 Non-LTE Considerations

Despite an ongoing controversy regarding the effects of departures from local thermodynamic equilibrium (LTE) on stellar abundance determinations, the classical LTE approach is still widely used and remains essentially unchanged. Such non local thermodynamic equilibrium (non-LTE) effects have been shown through detailed investigations to lead to substantial variations in derived abundances and stellar parameters. The most significant impact on the stellar parameters has been observed in the derived surface gravities. The classical approach of forcing ionization equilibrium (spectroscopic gravity) leads to lower gravities than those derived from stellar colours and parallaxes (photometric/trigonometric gravity). This trend suggests that the assumption of LTE ionization equilibrium between Fe I and Fe II may not be valid and that iron may be overionized in stellar atmospheres. Where overionization is prominent, the observable effects tend to increase towards

higher Teff or lower log¸g(due to lower density) and [Fe/H] since weaker metal absorption in the ultraviolet yields more available ionizing flux (Asplund, 2005). Thevenin & Idiart (1999) explored the problem of Fe overionization in the atmospheres of metal-poor stars, concluding that the Fe I lines formed far from the conditions of LTE. They found that efficient photo-ionization in excess of LTE predictions occurs 38 in these stars, leading to an underpopulation of all neutral levels, weakened neutral lines, and an underestimate of abundances derived from the neutral state. However, as the dominant ionization state of iron in metal-poor stars, Fe II measurements are less sensitive to non-LTE conditions or model atmosphere inaccuracies. Thus, according to Kraft & Ivans (2003), where metal-poor red giants are concerned, [Fe/H] would be more reliably derived from LTE analysis of the Fe II spectrum. Our standard stars, which are of intermediate metallicity, do not show any signature of overionization. By adopting the photometric surface gravity, CM05 found that the assumption of ionization equilibrium between Fe I and Fe II held for each of the M3 and M13 standard stars, although they detected a slightly more significant difference in [Ti/Fe] as deduced from the neutral and ionized species (∼ 0.10 dex). The average difference between [Fe/H] as inferred from Fe I and Fe II lines for the RGB stars was only 0.02 dex. CM05 concluded that the observed dispersions in ion-

ization equilibrium could easily be accounted for by their uncertainty in Teff (±50 K) and thus did not apply any non-LTE corrections to these stars’ abundances. Except for a small change in temperature, we find the same atmospheric parameters for the standard stars using both photometric and spectroscopic techniques. The surface gravity yields similar [Fe/H] as inferred from Fe I and Fe II lines. However, every one of our metal-poor target stars shows the effects of non-LTE overionization. Overionization leads to a depleted Fe I abundance, which then re- quires a decreased surface gravity in order to force agreement between Fe abundances from Fe I and Fe II lines. This is clearly shown in Table 11.8 by the significant discrepancies (∼ 0.6 dex) between the photometric and spectroscopic surface gravities derived for these stars. Thus, although we and CM05 managed to avoid applying non-LTE corrections to any of the abundances for the stars in M3 and M13, it is clear that we must consider the application of non-LTE corrections to our elemental abundances in the temperature and metallicity regime of our target stars. 39 Our results therefore support the conclusion made in 1999 by Allende-Prieto et al. that departures from LTE result in deviations between spectroscopic and photometric gravities when using classical model atmospheres. For metal-poor stars, Allende Pri- eto et al. (1999) suggested a +0.3 dex non-LTE abundance correction for Fe I, which would then imply an adjustment of +0.9 dex to the spectroscopic log¸g.Additionally, not accounting for non-LTE effects on Fe I lines would result in an overestimate of

Teff , amounting to ∼ 60 – 170 K for the Sun, with even greater errors expected at lower log¸gand [Fe/H] (Asplund, 2005). These proposed corrections are similar to the offsets found between the photometric and spectroscopic atmospheric parameters in this study. Unfortunately, none of the stars in their sample had surface gravities as low as this program’s stars. The situation is still not clear, particularly for stars at low gravities and metallicities, and no consensus has yet been reached regarding the magnitude of appropriate non-LTE overionization corrections. If absolute abundances were important to this study, non-LTE effects would certainly have to be accounted for in this analysis. However, this study is only concerned with relative abundances. Thus, the following non-LTE corrections are included for interest and discussion, but have not been accounted for in the final abundances. Unfortunately, beyond magnesium, no detailed investigations into the appropriate non-LTE corrections for heavier elements could be found. It seems that, especially for stars like those considered in this study, the necessary work has not been undertaken, perhaps due to the increasingly complicated nature of the matter for elements of higher atomic number. In any case, as the primary goal here is the comparison of abundance results with those of similar classical analyses, any such non-LTE effects are not of much importance. The forbidden [O I] lines at 6300 A˚ and 6363 A˚ represent the best O abundance indicator in metal-poor stars, as these lines are not particularly sensitive to either atmospheric model parameters or non-LTE effects (Asplund, 2005). Unlike the high 40 excitation potential O I triplet at 777 nm, these lines can be perfectly described within LTE. Therefore, only the [O I] lines are used in this study, in order to completely avoid the possibility of non-LTE corrections. CM05 also used only these two [O I] lines in their abundance determinations of the two standard stars. Non-LTE corrections are unavoidable in the case of Na I. This element is one of the most studied and debated elements in terms of its non-LTE behaviour. Gratton et al. (1999) found positive non-LTE abundance corrections for red giant stars; however, Asplund (2005) asserted that these results were contrary to other studies. The non-LTE behaviour of this element is highly dependent on the precise atmospheric parameters (Teff , log¸gand [Fe/H]) (Mashonkina et al., 2000). The detailed study undertaken by Takeda et al. (2003) provides non-LTE abundance corrections for all of the sodium lines used in this study, over a broad range of atmospheric parameters, including those of this program’s stars. For example, the standard star in M13 can be represented very accurately by one of the parameter sets with Teff = 4500 K and log¸g= 1.00. Even ξ, [Fe/H], and [Na/Fe] are well matched so as to extract the correction corresponding to the equivalent width and derived abundance of each line. For M13 III-18, these non-LTE abundance corrections are: large and negative for the lines at 5682.63 A˚ (-0.15 dex) and 5688.21 A˚ (-0.20 dex), small and positive for the doublet lines at 5889.95 A˚ and 5895.92 A˚ (+0.02 dex each), and small and negative for the lines at 6154.23 A˚ (-0.025 dex) and 6160.75 A˚ (-0.03 dex). The application of these abundance corrections to each of the sodium lines would reduce the scatter, bringing each derived abundance closer to the mean. These non-LTE considerations additionally serve to resolve the apparent discrepancies between our Na I abundance and that of CM05. CM05 used the four lines which yield higher abundances under the assumption of LTE, omitting the doublet lines at 589 nm, which are underabundant in LTE. Thus, for M13 III-18, the addition of these latter two lines to the linelist depleted the derived abundance for sodium as compared with the abundances reported 41 in CM05. For the target stars, only these doublet lines were detected. According to Takeda et al. (2003), in the regime of atmospheric parameters for these stars, the non-LTE corrections for these lines would be about -0.10 dex. Each of the six Mg I lines used in this analysis are subject to non-LTE effects. Three of these lines (4702.99 A˚, 5528.40 A˚ and 5711.09 A˚) appear in the CM05 analysis of our standard stars, while the other three lines (4571.09 A˚, 5172.68 A˚ and 5183.60 A˚) do not. According to Gratton et al. (1999), all of the corresponding non-LTE corrections will be positive (∼ 0.10 dex) in our temperature, gravity and metallicity regime and would therefore increase our derived abundances. The detailed analysis of Shimanskaya et al. (2000) demonstrated that, for giants like the ones in this study (with low temperatures, surface gravities and metallicities), the non-LTE corrections for the lines used by CM05 are all negative (up to -0.20 dex), whereas the corrections for the additional three lines included in this analysis are all positive (. 0.15 dex each). Hence, the application of these non-LTE corrections would increase our values of [Mg/Fe], compensating for the apparent discrepancy between abundances. These corrections would also significantly reduce the scatter in our Mg I abundances, as each proposed shift occurs in the appropriate direction so as to bring the abundance derived from each line closer to the mean. 42

Chapter 7

DISCUSSION OF RESULTS

The abundance ratios of the target stars are compared with those of Galactic halo ﬁeld stars, globular clusters, and dSph stars from Venn et al. (2004) and Pritzl et al. (2005) (See Figures 10.1 – 10.3). The [X/Fe] ratios for each element are also compared with those of similar Galactic globular clusters (NGC 2298, NGC 6397, NGC 5897). Additionally, the chemistry of NGC 5024 is compared with that of a similar metallicity GC, Arp 2 (Mottini et al., 2008), which is a member of the Sgr stream. Based on the chemistries of the target stars, the implications on the purported extragalactic origins and associations of NGC 5024 and NGC 5466 are evaluated.

7.1 Iron

The iron abundances determined for the metal-poor globular clusters in this investigation are [Fe/H] = -1.90 ± 0.161 for NGC 5024 and [Fe/H] = -1.88 ± 0.161 for NGC 5466. These metallicities are somewhat higher than the previously estimated values of -2.04 (Zinn, 1985) for NGC 5024 and -2.22 (Zinn, 1985) for NGC 5466. The uncertainty associated with the iron abundance of 0.16 dex was used to set the metallicity range for comparison GCs and dSphs (see Figures 10.4 and 10.5).

1Total error derived from the sensitivity of iron abundance to 1 σ variations in atmospheric parameters, added in quadrature (see Table 11.14). 43

7.2 Light Elements

In terms of light element abundances (e.g. O, Na, Mg and Al), the target RGB stars all show relatively enhanced O and Mg, while Na is depleted. This is contrary to the anomalous signature (O and Mg depleted, while Na and Al are enhanced)1 often seen in metal-poor globular cluster giants (e.g. M13 III-18, one of the standard stars included in this study). Instead, these correlations match the normal trends of halo field giants (Kraft et al., 1997), which reflect the abundance yields of type II supernovae (SNe II). However, with such small number statistics, this result can not be considered representative of all of the stars in the target clusters. The spread in Na abundance that has come to be expected among globular cluster giants is apparent in both the NGC 5024 and NGC 5466 stars, being most significant in the latter (0.32 dex). Substantial star-to-star variations are also seen in the O abundances of the target stars (∼ 0.30 dex).

7.3 Alpha Elements

The creation of α (even-Z) elements (e.g. O, Mg, Si, Ca, Ti) via the fusion of Helium nuclei (α particles) occurs predominantly in SNe II, at the end of the relatively short

lives of massive stars (M > 8 Modot). The α abundance thus restricts the number of SN II explosions that can have polluted the gas from which the star formed. The results of some studies have indicated that these α elements are not all products of a single nuclear reaction chain that occurs in the same astrophysical environment. Abundance enhancements in Mg and Ti relative to Ca and Si have been observed in both the Galactic bulge (McWilliam & Rich, 1994) and disk (Edvardsson et al., 1993), suggesting that these elements are not created equally in all types of supernovae (e.g. some Ti may be produced in SN Ia). However, in the Galactic halo, the α elements

1These abundance patterns may represent either: evidence of internal nucleosynthesis and mixing in individual stars (“deep mixing” scenario), or a characteristic of chemical inhomogeneities in the material out of which the stars were formed (“primordial” scenario) 44 all have approximately the same average abundance ratio, the full range being well represented by +0.37 ± 0.08 (McWilliam, 1997). Thus, for the purposes of this study, these elements should follow the same behaviour, and are grouped together. For this investigation (and the majority of those to which we are comparing our results) the α element abundance is taken to be the average of Mg, Ca, and Ti abundances, these being the most reliable of the group. NGC 5024 and NGC 5466 reproduce a dSph α element abundance signature noted by Venn et al. (2004) for the most metal-poor dSph stars ([Fe/H] ≤ -1.8). That is, the individual α element ratios show [Ti/Fe] ≤ [Ca/Fe] ≤ [Mg/Fe]. DSph stars tend to have lower [α/Fe] ratios than Galactic field stars of similar metallicity. This is often interpreted as a product of a low SN II rate (relative to SN I) in dSphs, since only SNe II contribute to the production of the α elements, whereas iron is produced in both SNe II and SNe Ia events (preferentially in SNe Ia). Other possibilities are that dwarf galaxies have slow star formation rates (McWilliam, 1997), or that they rarely form very massive stars. It is theoretically plausible that such small galaxies are unlikely to form very massive molecular clouds and subsequently high mass stars. According to Woosley & Weaver (1995), the α element yields increase with increasing SN II progenitor mass, such that explosions of stars at the low mass end of the SN II range (8 – 12 M ) are consistent with the low (∼ solar) [α/Fe] ratios often seen in dSphs. A relative depletion in α elements is not prominent in the target stars of this study (see Figure 10.1). The suspiciously high Ti II abundances in NGC 5024 are probably an artifact of non-LTE overionization of the neutral state. The absence of this typically obvious indication of dSph membership would generally cast doubt upon the extragalactic origin of a globular cluster. However, at the metallicity of our cluster stars, the distinction between the dSph and Galactic stars is not significant. It is not until [Fe/H] > -1.9 that the dwarf spheroidal stars show a pronounced break 45 from Galactic field and GC stars and begin to have lower [α/Fe] ratios. The situation is emphasized in Figure 10.4, in which the Galactic field stars, GCs, and dSphs in the metallicity range of our target stars display essentially indistinguishable alpha abundances.

7.4 Iron-peak Elements

The Fe-peak elements (e.g. V, Cr, Mn, Co, Ni, Cu, Zn) are the highly stable end products of the nucleosynthetic sequence by nuclear fusion, being produced in the shockwaves of explosive type I supernovae. They provide the nucleic sites that capture neutrons to produce heavy elements. In general, dSph stars appear to have the same iron peak element abundance patterns as stars in the Galactic halo. One possible exception exists in Zn, which has an uncertain nucleosynthetic origin (possibly SNe Ia, SNe II and/or AGB stars), and thus may behave diﬀerently in dSphs. Shetrone et al. (2003) found that their sample of dSph stars had Zn abundances that were systematically a few dex lower than those of Galactic halo and globular cluster stars. The [Zn/Fe] ratios of NGC 5024 and NGC 5466 are very similar to the mean of their dSph sample at about -0.25 dex and quite unlike the mean of the Galactic halo stars at about solar.

7.5 Heavy Elements

Heavy elements (Z > 30) are synthesized by successive neutron captures onto iron peak nuclei, followed by β decays (electron emission). They are a mix of r and s- process elements, i.e. elements which are produced by rapid and slow neutron capture respectively. Rapid neutron capture occurs on a time scale that is short compared to β decay, whereas slow neutron capture takes long enough that β decay occurs between successive captures. Rapid capture is generally thought to take place in environments where the neutron flux is very high, like SNe II explosions. However, the slow capture (s-process) tends to take place in more quiescent circumstances, 46 such as low mass (1 – 3 M ) Asymptotic Giant Branch (AGB) stars. Eu is a nearly pure r-process element, produced almost exclusively in SNe II, whereas Y, Ba, La and Nd are predominantly created by the s-process. The relative abundances of these elements can thus tell us about the environment in which the enrichment occurred. The ratios of [Y/Fe], [Ba/Fe], [La/Fe] and [Eu/Fe] of Galactic field stars, GCs, dSph stars, and our target stars are shown in Figure 10.2. The abundance ratios of the neutron capture elements provide a form of quan- tification of the relative significance of the different enrichment processes in the star formation history of a galaxy (or globular cluster). That Eu is relatively underabundant in our target stars suggests that the r-process contribution is small. However, this could also simply be an indication of the uncertainty inherent to the determination of the Eu abundance from a single spectral line. Dwarf spheroidal galaxies appear to evolve from a state of r-process domination to that of s-process domination with increasing stellar metallicity (e.g. see the evolution of [Ba/Eu] and [La/Eu] for dSphs in Figure 10.3). Thus the oldest stars must produce heavy elements via the r-process, which makes sense since the evolution of AGB stars takes at least 1 Gyr before they can begin to contribute to the interstellar medium. Many metal-poor dSph stars therefore have low [Y/Eu] ratios. This tendency does not appear in our target stars. Due to the low Eu abundances found for NGC 5024 and NGC 5466, the s-process to r-process ratios are all high relative to the Galactic field. Y samples the first s-process peak, which may have a different source than the heavier s-process elements like Ba and La which belong to the second peak. Therefore, the ratio of [Ba/Y] is indicative of any such variation in s-process peak contributions. The slower chemical evolution in dSph means that s-process enrichment from metal- poor AGB stars becomes important. Because these stars have lower yields of light s-process elements like Y (Travaglio et al., 2004), this results in low [Y/Fe] and high [Ba/Y] ratios in dSphs as compared with Galactic field stars. Unlike the dSph sig- 47 nature of α depletion, this trend should be detectable in our target stars, being most evident around metallicities of [Fe/H] ∼ -2.0, if they originated in dSphs. As shown in Figures 10.2 and 10.3, our stars do lie at lower [Y/Fe] and higher [Ba/Y] values than the Galactic field stars. This result in shown for our target stars’ metallicity range in Figure 10.5. The [Ba/Y] offset is most significant for the stars in NGC 5024, the cluster which is proposed to have been accreted by the MW via tidal stripping from the Sagittarius dwarf spheroidal galaxy.

7.6 Comparison with Galactic Globular Clusters

The selection of comparison Galactic globular clusters was based on metallicity, age, and HB morphology. Salaris & Weiss (2002) presented homogeneous age determinations for a large sample of Galactic globular clusters, including NGC 5466. This source was used as a primary reference for isolating suitable Galactic globular clusters (from the sample in Pritzl et al., 2005) for comparison with the target stars. The ages of each of the comparison clusters and NGC 5466 were taken from Salaris & Weiss (2002) while the age of NGC 5024 (which was not included in that study) was determined from its age relative to NGC 5466 as given in De Angeli et al. (2005). Metallicities and ages based on the Zinn and West (1984) scale were compiled, along with the horizontal branch ratios (Lee, 1990), horizontal branch types (Dickens, 1972) and galactocentric radii as catalogued by Harris (1996) in Table 11.18. The horizontal branch ratio is defined as HBR = (B − R)/(B + V + R), where B denotes the number of horizontal branch stars blueward of the RR Lyrae region, V the number of stars in the RR Lyrae region, and R the number of stars redward of the RR Lyrae region. GCs with HBR > 0.9 are almost entirely blue (i.e. nearly all stars exist blueward of the RR Lyrae region). The morphological type of the horizontal branch (hbt) is represented by an integer between 1 and 7, where 1 denotes a cluster with a completely blue HB and 7 denotes a completely red HB. 48 Before directly comparing our results with the chemical abundances obtained in the various studies of the selected Galactic globular clusters (NGC 2298, NGC 6397 & NGC 5897), the data had to be scaled to compensate for differences in adopted solar abundances and atomic data. Small shifts were applied as necessary based on the different sets of solar abundance data used in each study (see Table 11.19). Addi- tionally, abundance corrections due to the variations in adopted oscillator strengths were calculated for each common spectral line observed in each star. The corrections for each specific chemical abundance were then averaged and applied as appropriate to the comparison cluster data (see Table 11.20). After the abundances of the comparison globular clusters were altered in this way, a valid comparison was performed on a consistent scale. Plots were created to illustrate the abundance comparisons with each cluster (see Figures 10.7 – 10.9). NGC 2298: McWilliam, Geisler & Rich (1992, hereafter McW92) obtained detailed chemical abundances from spectra of three red giant stars in NGC 2298 collected with the CTIO echelle spectrograph. Their instrumental setup had a resolution of R ∼ 17,000 and produced spectra with signal to noise ratios of about 100 pixel−1, with useful spectral coverage from 6160 to 7600 A˚. Following standard practice, McW92 derived effective temperatures using published (V-K) colours from Frogel et al. (1983) and calculated initial surface gravities assuming stellar masses of

0.8 M . They used MOOG (Sneden, 1973) spectrum synthesis program and stan-

dard techniques for constraining the parameters (Teff , log¸g, ξ, [Fe/H]) of their chosen atmospheric models (Bell et al., 1976). McW92 adopted solar abundances from An- ders & Grevesse (1989) except for Fe for which they used 7.52. An examination of the abundance trends plotted in Figure 10.7 shows that the abundances derived for NGC 5024 and NGC 5466 in this study are generally similar to those derived by McW92 for NGC 2298. Discrepancies include enhanced Mg, Sc, Ti II, Co, and Y in NGC 2298 compared with this study’s target clusters. 49 NGC 6397: Norris & Da Costa (1995, hereafter Nor95) obtained detailed chemical abundances from spectra of two red giant stars in NGC 6397 collected with UCLES on the Anglo-Australian telescope. Their instrumental setup had a resolution of R ∼ 38,000, with useful spectral coverage from 5050 to 7300 A˚. Following standard practice, Nor95 derived effective temperatures using published (V-K) colours from Frogel et al. (1983) and calculated initial surface gravities assuming stellar masses of 0.8 M . They used spectrum synthesis and standard techniques for constraining the parameters (Teff , log¸g, ξ, [Fe/H]) of their chosen atmospheric models (Bell et al., 1976). Nor95 claim to have adopted the solar abundances of Anders & Grevesse (1989) but the values listed in the paper are actually slightly different, typically ∼ 0.4 dex lower. An examination of the abundance trends plotted in Figure 10.8 shows that the abundances derived for NGC 5024 and NGC 5466 in this study are generally similar to those derived by Nor95 for NGC 6397. Relative to this study’s results, the abundances of Sc and Eu are a bit high, while Ba and La are on the low end. Castilho et al. (2000, hereafter Cas00) obtained detailed chemical abundances from spectra of five giants in NGC 6397 collected with CASPEC at ESO. Their instrumental setup had a resolution of R ∼ 25,000, and produced spectra with signal to noise ratios around 125 pixel−1 with useful spectral coverage from 5000 to 7500 A˚. Following standard practice, Cas00 derived effective temperatures using published (V- K) colours from Frogel et al. (1983) and calculated initial surface gravities assuming stellar masses of 0.8 M . They used spectrum synthesis and standard techniques for constraining the parameters (Teff , log¸g, ξ, [Fe/H]) of their chosen atmospheric models (Gustafsson et al., 1975). In this short paper, Cas00 did not provide the adopted solar abundances. But, the authors used Grevesse & Sauval (1998) in another paper published a few months later (Castilho et al., 2000b), and so we have based the applied shifts for solar abundance variations on this source. An examination of 50 the abundance trends plotted in Figure 10.8 shows that the abundances derived for NGC 5024 and NGC 5466 in this study are somewhat different from those derived by Cas00 for NGC 6397. Discrepancies include enhanced Na, Si, Ti (neutral and ionized) and Y, while Ca and Ba appear depleted relative to the target cluster abundances from this study. NGC 5897 Gratton (1987, hereafter Gra87) obtained detailed chemical abundances from spectra of two RGB stars in NGC 5897 collected with CASPEC at ESO. Their instrumental setup had a resolution of R ∼ 15,000, and produced spectra with signal to noise ratios around 50 pixel−1 with useful spectral coverage from 5450 to

6400 A˚. Gra87 adopted appropriate atmospheric parameters (Teff and log¸g)from Frogel et al. (1983). They performed classical line analysis and comparison with synthetic spectra, adopting model atmospheres derived by interpolation from Bell et al. (1976). Unfortunately, the adopted solar abundances are not listed, so the data is assumed to be similar to Anders & Grevesse (1989) and this source is used for the calculation of the applicable abundance shifts. Some significant abundance shifts were applied to the results from this old study due to some dramatic changes in oscillator strengths since that time. An examination of the abundance trends plotted in Figure 10.9 shows a large spread in the abundances derived by Gra87 for two stars in NGC 5897. The abundances of Cu and Ba are dramatically depleted in the NGC 5897 stars compared with those of NGC 5024 and NGC 5466, but this difference came directly from the substantial shift applied due to updated oscillator strength values for this species. These factors result in a low level of confidence in the validity of a direct comparison with the results of this study. Summarily, the target clusters of this study seem generally well matched in composition by similar Galactic globular clusters. The abundances of these comparison Galactic GCs are as much as twenty years out of date; any detected variations may be due to differences in data quality, model atmospheres and analysis techniques. 51

7.7 NGC 5024 and the Sagittarius Dwarf

An investigation of the chemical abundances of NGC 5024 based on the plots in Chapter 10 is not immediately convincing one way or the other. While the stars we have studied in NGC 5024 do reveal a mildly enhanced [Ba/Y] ratio relative to the Galactic field stars as is characteristic of dSph stars, the expected relative depletion in α elements is not seen. It should instructive to compare our derived chemical abundances with those obtained in other studies of globular cluster stars directly associated with the proposed parent galaxy of NGC 5024, the Sagittarius dwarf. A recent study (Sbordone et al., 2007) investigated the chemical composition of the Sgr dwarf and the associated GC Terzan 7. The distinctly exotic chemical composition uncovered for Sgr giants was mirrored in both Ter 7 and Pal 12. Compared to the stars in the main body of Sgr, stars in Ter 7 have lower temperatures, gravities and metallicities. Da Costa & Armandroff (1995) found that three other clusters associated with Sgr (Ter 8, Arp 2, M54) are much more metal-poor than the mean of the field stars in the dwarf itself. Chou et al. (2007) claimed that this depleted metallicity should be expected, based on their detection of a metallicity gradient in the Sgr stream. The exotic chemical signature detected in Sgr stars may therefore be diluted in the more remote stripped stars. Therefore, the extension of this composition to the low metallicity regime ([Fe/H] = -1.9) of this study’s target stars can not be guaranteed. The stars in the main body of Sgr that Sbordone et al. (2007) examined have a mean metallicity of [Fe/H] = -0.36, which is significantly more metal-rich than NGC 5024. The mean metallicity of Ter 7 is slightly lower at [Fe/H] = -0.59 (Taut- vaisiene et al., 2004; Sbordone et al., 2007). The metallicities of the other globular clusters associated with Sgr are: [Fe/H] = -2.34 ± 0.08 for Ter 8 (Mottini et al., 2008), [Fe/H] = -1.83 ± 0.08 for Arp 2 (Mottini et al., 2008), [Fe/H] = -1.55 ± 0.20 for M54 52 (Brown et al., 1999), [Fe/H] ∼ -1.30 for Pal 2 (Harris et al., 1997), [Fe/H] ∼ -0.90 for Pal 12 (Zinn, 1985; Brown, Wallerstein & Zucker, 1997; Da Costa & Armandroff, 1995; Cohen, 2004), [Fe/H] ∼ -0.65 for Whiting 1 (Carraro et al., 2007) and [Fe/H] ∼ - 1.83 for NGC 4147 (Zinn, 1985; Suntzeff, Kraft & Kinman, 1988). Since there are no published chemical abundances for NGC 4147, the GC associated with Sgr with the closest metallicity to NGC 5024 ([Fe/H] = -1.90 ± 0.16, this study) suitable for comparison is Arp 2. The elemental abundances found by Mottini et al. (2008) for red giant stars in Arp 2 were hence compared with the chemical abundances found in this study for red giant stars in NGC 5024 (See Figure 10.10). Mottini et al. (hereafter Mot08) obtained detailed chemical abundances from high-resolution spectra of two and three red giant stars in Arp 2 and Ter 8 respectively, collected with the MIKE spectrograph at Las Campanas Observatory. Their instrumental setup had a resolution of 40,000 and produced spectra with signal to noise ratios around 50 pixel−1 at 6000 A˚. They used a linelist with a wavelength range from 4200 to 7300 A˚, atomic data from Vienna Atomic Line Database (VALD), and the splot IRAF task to measure equivalent widths. Mot08 adopted the same methods that were used in this study to determine model atmosphere parameters, but chose KURUCZ models. The atmosphere parameters found by Mot08 for the Arp 2 stars are very similar to those determined for the target stars in NGC 5024; the only significant difference is a somewhat lower temperature regime (∼ 350 K cooler) for the Arp 2 stars. A different set of solar abundance data was selected for their analysis (Lodders, 2003); hence, we applied shifts to their published abundance ratios to compensate (see Table 11.19). A few shifts were also applied to their abundances based on differences in adopted oscillator strengths (see Table 11.20). This enabled a direct comparison of composition on the same scale. Figure 10.10 clearly shows the remarkable agreement between the abundance ratios of the RGB stars in NGC 5024 and those in Arp 2, one of the Sgr dSph’s tidally stripped globular clusters. 53

7.8 NGC 5466 and the Tidal Tails

The extensive tidal tails stretching to either side of NGC 5466 have identified it as a possible remnant of an accretion event. The absence of a known progenitor of NGC 5466 prevents us from performing a compositional comparison like the one carried out for NGC 5024. Previously, the only available chemical abundances for this cluster were from an anomalous Cepheid (McCarthy & Nemec, 1997). The variability of the star prohib- ited confidence in the abundance ratios as representative of the cluster as a whole. Very recently, another group elected to investigate the detailed chemical abundance patterns of RGB stars in this cluster. Ivans & Kraft (2007) have presented preliminary chemical compositions of five red giant stars in NGC 5466. These preliminary trends include a spread in [Na/Fe] of 0.3 dex, with a mean of -0.3, and a mild under- abundance of [Ni/Fe] of -0.15 dex. Our respective [Ni/Fe] ratios are highly consistent. We find a very similar spread in the [Na/Fe] ratios of the three red giants in this cluster although our mean value is significantly higher at +0.04. According to Takeda et al. (2003), the Na abundances derived from the strong Na I doublet at 589 nm require a non-LTE correction of about -0.35 dex. This would bring our mean [Na/Fe] into agreement with that of Ivans and Kraft. However, we know neither which Na I lines Ivans and Kraft have used nor whether they have applied non-LTE corrections. Regardless, the mean abundances are essentially meaningless due to the small number statistics involved; it is the range in [Na/Fe] that is interesting as it may be an indicator of AGB self-pollution and/or deep mixing (Fenner et al., 2004). Our metallicity is in good agreement with Ivans and Kraft who adopt [Fe/H] = -1.90 while the mean value for our stars is -1.88. Additional confirmation of this metallicity comes from the recent photometric investigation of Arellano Ferro et al. (2008), who report [Fe/H] = -1.91 ± 0.19 for NGC 5466. 54 In the attempt to discern whether this cluster’s chemical composition indicates that it is the remnant of a now dispersed extragalactic dSph, this study has at best found inconclusive evidence. In general, the abundance ratios of NGC 5466 seem fairly well matched with the Galactic field stars and globular clusters. The most significant variation occurs for [Y/Fe], which shows a depletion relative to the Galactic field. This one piece of evidence is not sufficient justification to confirm that this globular cluster had an accretion origin. Nevertheless, the orbital properties of this cluster, combined with its possession of lengthy tidal tails, are convincing indicators of its ongoing disruption. NGC 5466 may simply be an ordinary Galactic globular cluster whose orbital path takes it through the Galactic plane which exerts a tidal shock (Gnedin & Ostriker, 1997; Gnedin, Lee & Ostriker, 1999). The tidal interaction between cluster stars and the Galactic plane can create tails of stars, stripped from the cluster halo, extending up to several degrees of arc preceding and following the cluster along its orbital path. Thus, the observation of tidal tails associated with NGC 5466 may be merely a signature of such an interaction. 55

Chapter 8

SUMMARY

We have used high resolution spectral analysis techniques to obtain the chemical abundances of two globular clusters (NGC 5024, NGC 5466) with proposed extragalactic origins. We have scrutinized these abundance results in the attempt to discern any elucidating compositional signatures. One noteworthy compositional dis- covery in support of the merger scenario is the overabundance of [Ba/Y] of both clusters compared with the Galactic field stars. This corresponds with the finding of Venn et al. (2004) that [Ba/Y] is notably higher in dwarf spheroidal stars than in Galactic field stars. Other than this offset, the abundance trends of these two clusters are indistinguishable from those of Galactic field and GC stars. NGC 5466 is associated with the longest tidal tail on record, and has therefore been suspected of being the remnant core of a now dispersed dwarf spheroidal galaxy. But, from the perspective of its chemical abundance trends, the origin of NGC 5466 remains uncertain. A direct comparison between the chemical abundance ratios of NGC 5024 and a globular cluster of similar metallicity, Arp 2, associated with its proposed progenitor, the Sgr dSph, revealed similar compositions. However, also being similar in chemistry to other GCs and field stars at this metallicity, we have not reached a conclusion regarding the origin of NGC 5024. 56

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Chapter 9

Figures 65

Figure 9.1: SDSS stellar map of the northern sky, showing trails and streams of stars torn from disrupted Milky Way satellites. The morphology, particularly the bifurcation, of the Sagittarius stream provides evidence for a spherical Galactic dark halo. The color corresponds to distance, with red being the most distant and blue being the closest. Insets show new dwarf companions discovered by the SDSS. The locations of NGC 5024 and NGC 5466 are labelled. (Belokurov et al., 2006b) 66

Figure 9.2: Image of NGC 5024 obtained from the Aladin Java Applet of the SIMBAD astronomical database URL: http://simbad.harvard.edu/Simbad. The loaded SIMBAD image is POSSII.F.DSS2.576, from the second Palomar Observatory Sky Survey, with an optical red ﬁlter. The stars labelled 22254 and 50371 are sources #81 and #1014, respectively, from the 2MASS survey consisting of 1093 sources in this frame. 67

Figure 9.3: Image of NGC 5466 obtained from the Aladin Java Applet of the SIMBAD astronomical database URL: http://simbad.harvard.edu/Simbad. The loaded SIMBAD image is POSSII.F.DSS2.446, from the second Palomar Observatory Sky Survey, with an optical red ﬁlter. The stars labelled 1344, 9951 and 10186 are sources #77, #84 and #258 , respectively, in the 2MASS survey plane consisting of 1093 sources in this frame. 68

CMD of NGC5024

14 12Gyr 14Gyr 50371 22254 16Gyr

0 0.5 1 1.5 (V-I)

Figure 9.4: This CMD of NGC 5024 was created using P. Stetson’s V-I photometry (private communication, 2008) with superimposed isochrones generated from VandenBerg’s models (VandenBerg, Bergbusch & Dowler, 2006), having adopted the best available parameters for metallicity [Fe/H] = -2.01 and [α/Fe] = +0.3. The reddening E(B-V) = 0.02 was found from the horizontal shift E(V-I) = 0.025 necessary to align the isochrones with the cluster data, using E(V-I) = 1.25E(B-V) (Bessell & Brett, 1988), and is in agreement with the value given in Harris’ online catalogue (Harris, 1996). The visual distance modulus (m-M)v = 16.3 was determined from the vertical shift in V necessary in order to properly align the isochrones with the cluster data and agrees with the value given in Harris’ online catalogue. After correcting this visual distance modulus for interstellar absorption, we calculated the distance to the cluster to be 17.6 kpc, which is also consistent with Harris. These isochrones indicate that NGC 5024 is a very old globular cluster, with an age of ∼ 14 Gyr. 69

CMD of NGC5466

14 12Gyr 14Gyr 10186 1344 16Gyr 9951

0 0.5 1 1.5 (V-I)

Figure 9.5: This CMD of NGC 5466 was created using P. Stetson’s V-I photometry (private communication, 2008) with superimposed isochrones generated from VandenBerg’s models (VandenBerg, Bergbusch & Dowler, 2006), having adopted the best available parameters for metallicity [Fe/H] = -2.01 and [α/Fe] = +0.3. The reddening E(B-V) = 0.00 was found from the horizontal shift E(V-I) = 0.00 necessary to align the isochrones with the cluster data, using E(V-I) = 1.25E(B-V) (Bessell & Brett, 1988), and is in agreement with the value given in Harris’ online catalogue (Harris, 1996). The visual distance modulus (m-M)v = 16.0 was determined from the vertical shift in V necessary in order to properly align the isochrones with the cluster data and agrees with the value given in Harris’ online catalogue. After correcting this visual distance modulus for interstellar absorption, we calculated the distance to the cluster to be 15.8 kpc, which is also consistent with Harris. These isochrones indicate that NGC 5466 is a very old globular cluster, with an age of ∼ 14 Gyr. 70

Figure 9.6: MOOG plots of Fe I abundance versus excitation potential, equivalent width, and wavelength respectively for M13 III-18. 71

Figure 9.7: MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region containing Fe I lines at 6136.99 A˚, 6137.69 A˚ and 6137.99 A˚. These strong lines were a few of those used in order to constrain the rotational broadening of the star. The abundance of the element derived from spectrum synthesis for each line was forced to agree with the abundance found from its equivalent width. In this case, the abundance of each line from its equivalent width was 6.06, 6.19, and 6.13 respectively, each being matched well by the synthetic spectrum. The necessary rotational broadening was found to be vsini = 2.50 km/s. 72

Figure 9.8: MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding Ca I line at 6439.07 A˚. This strong line was one of several used in order to constrain the rotational broadening of the star. The abundance of the element derived from spectrum synthesis was forced to agree with the abundance found from its equivalent width. In this case, the abundance of Ca I was 5.12, and the necessary rotational broadening was found to be vsini = 2.50 km/s. 73

Figure 9.9: MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region containing spectral lines of Ca I, Ti II, Fe I and Ba II. This plot demonstrates how well the observed spectrum is matched by the synthetic spectrum using the rotational broadening of vsini = 2.50 km/s. The Ba II abundance for the line shown here matches the value derived from the equivalent width. 74

Figure 9.10: MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding O I line at 6300.31 A˚. This weak line was one of several that was examined with spectrum synthesis techniques in order to cross-check the abundance determined from the equivalent width. In this case, the abundance of O I from the equivalent width was 7.45, and spectrum synthesis conﬁrmed this abundance. The rotational broadening determined previously (vsini = 2.50 km/s) was adopted for all syntheses performed for this star. 75

Figure 9.11: MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding Cu I line at 5105.54 A˚. This weak line was one of several that was examined with spectrum synthesis techniques in order to cross-check the abundance determined from the equivalent width. In this case, the abundance of Cu I from the equivalent width was 2.34, and spectrum synthesis conﬁrmed this abundance. The rotational broadening determined previously (vsini = 2.50 km/s) was adopted for all syntheses performed for this star. 76

Figure 9.12: MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding La II line at 6390.48 A˚. This weak line was one of several that was examined with spectrum synthesis techniques in order to cross-check the abundance determined from the equivalent width. In this case, the abundance of La II from the equivalent width was 0.04, and spectrum synthesis conﬁrmed this abundance. The rotational broadening determined previously (vsini = 2.50 km/s) was adopted for all syntheses performed for this star. 77

Figure 9.13: MOOG plot of synthetic spectra overlaid upon spectrum of M13 III-18 in region surrounding Eu II line at 6645.06 A˚. This weak line was one of several that was examined with spectrum synthesis techniques in order to cross-check the abundance determined from the equivalent width. In this case, the abundance of Eu II from the equivalent width was -0.36, and spectrum synthesis conﬁrmed this abundance. The rotational broadening determined previously (vsini = 2.50 km/s) was adopted for all syntheses performed for this star. 78

Chapter 10

Plots 79

0.5

-0.5

0.5

-0.5

0.5

-0.5

0.5

-0.5

0.5

-0.5 -4 -3 -2 -1 0 [Fe/H]

Figure 10.1: [X/Fe] versus metallicity for the individual α elements Mg I, Ca I, Ti I, Ti II, and their mean where [α/Fe] = [(Mg I+CaI+0.5(Ti I+Ti II))/3Fe]. Small filled circles represent galactic field stars (Venn et al., 2004), large open circles: globular clusters (Pritzl et al., 2005), and open squares: dwarf spheroidal galaxies (Venn et al., 2004). Globular cluster points are averages of the best available member data, whereas dwarf galaxy stars are each represented by an individual point. Blue filled hexagons signify data for our standard star in M13, green filled pentagons: our standard star in M3, red filled squares: our target stars in NGC 5024 and yellow filled triangles: our target stars in NGC 5466. 80

0.5

-0.5

-1 1

0.5

-0.5

-1

0.5

-0.5

0.5

-0.5

-4 -3 -2 -1 0 [Fe/H]

Figure 10.2: [X/Fe] versus metallicity for s-process elements Y II, Ba II, La II, and r-process element Eu II. Same symbols as in Figure 10.1. 81

0.5 0 -0.5 -1 -1.5 1 0.5 0 -0.5 -1

1 0.5 0 -0.5 -1 1.5 1 0.5 0 -0.5

-4 -3 -2 -1 0 [Fe/H]

Figure 10.3: Ratios of [Y/Eu], [Ba/Eu], [La/Eu], and [Ba/Y] versus metallicity. Same symbols as in Figure 10.1. 82

0.6

0.5

0.4

0.3

0.2

0.1

-0.1

-0.2 -2 -1.9 -1.8 [Fe/H]

Figure 10.4: [α/Fe] versus metallicity for our targets stars’ metallicity range where [α/Fe] = [(Mg I+CaI+0.5(Ti I+Ti II))/3Fe]. Small filled circles represent galactic field stars (Venn et al., 2004) and open squares: dwarf spheroidal galaxies (Venn et al., 2004). Globular clusters (Pritzl et al., 2005) are indicated by filled cyan circles. Globular cluster points are averages of the best available member data, whereas dwarf galaxy stars are each represented by an individual point. From left to right (i.e. lowest to highest metallicity) the globular clusters are: NGC 6397, NGC 2298, M55, NGC 7492, NGC 5897 and NGC 6541, and the dSphs are: Umi177, Scl400, Car10, SexS35/SexS56, Umi0, HIP343 and Scl 479. Red filled squares represent our target stars in NGC 5024 and yellow filled triangles: our target stars in NGC 5466. Stars from the Sgr dSph associated GC Arp2 (Mottini et al., 2008) are labelled with magenta circles. 83

0.8

0.6

0.4

0.2

-0.2

-2 -1.9 -1.8 [Fe/H]

Figure 10.5: [Ba/Fe] versus metallicity for our targets stars’ metallicity range. Small filled circles represent galactic field stars (Venn et al., 2004) and open squares: dwarf spheroidal galaxies (Venn et al., 2004). Globular clusters (Pritzl et al., 2005) are indicated by filled cyan circles. Globular cluster points are averages of the best available member data, whereas dwarf galaxy stars are each represented by an individual point. From left to right (i.e. lowest to highest metallicity) the globular clusters are: NGC 6397, NGC 2298, M55 and NGC 7492 and the dSphs are: Umi177, Scl400, Car10, SexS35/SexS56, Umi0, HIP343 and Scl 479. Red filled squares represent our target stars in NGC 5024 and yellow filled triangles: our target stars in NGC 5466. Stars from the Sgr dSph associated GC Arp2 (Mottini et al., 2008) are labelled by magenta circles. 84

0.5

-0.5

M13 M3 NGC5024 -1 NGC5466

O Na Mg Al Si K Ca Sc Ti V Cr Mn Co Ni Cu Zn Y Ba La Nd Eu

Figure 10.6: Abundance ratios as a function of increasing atomic number. Same symbols as in Figure 6. 85

0.5

-0.5

NGC5024 NGC5466 NGC2298

-1 Mg Si Ca Sc TiI TiII V Cr Co Ni Y Ba La Eu

Figure 10.7: Abundance ratios as a function of increasing atomic number. In this plot we compare the abundance pattern in NGC 5024 and NGC 5466 with that of NGC 2298, a similar age and metallicity Galactic globular cluster. NGC 2298 data is from McWilliam, Geisler & Rich (1992) who assign no error bar to any abundance derived from a single spectral line. It is apparent that the abundances of stars in NGC 5024 and NGC 5466 show some deviations from those in NGC 2298, suggesting that the stars formed from gas of different chemical composition. The host clusters may thus have different star formation and chemical enrichment histories and may have formed in different environments. 86

0.5

-0.5

NGC5024 NGC5466 NGC6397

-1 O Na Mg Si Ca Sc Ti TiII V Cr Ni Y Ba La Nd Eu

Figure 10.8: Abundance ratios as a function of increasing atomic number. In this plot we compare the abundance pattern in NGC 5024 and NGC 5466 with that of NGC 6397, a similar age and metallicity Galactic globular cluster. NGC 6397 data is from Norris & Da Costa (1995) (filled triangles) and Castilho et al. (2000) (hollow triangles). Error bars for Norris & Da Costa data represent only the scatter and do not include any systematic error. Castilho et al. provide no information regarding the uncertainties on their abundances. It is apparent that the abundances of stars in NGC 5024 and NGC 5466 show some deviations from those in NGC 6397, suggesting that the stars formed from gas of different chemical composition. The host clusters may thus have different star formation and chemical enrichment histories and may have formed in different environments. 87

0.5

-0.5

NGC5024

-1 NGC5466 NGC5897

Na Mg Si Ca TiI V Cr Ni Cu Ba

Figure 10.9: Abundance ratios as a function of increasing atomic number. In this plot we compare the abundance pattern in NGC 5024 and NGC 5466 with that of NGC 5897, a similar age and metallicity Galactic globular cluster. NGC 5897 data is from Gratton (1987). No associated errors on the abundances are provided. The data point for [Cu/Fe] for NGC 5897 is below the visible area of the plot at -1.62, significantly deviant from the values of NGC 5024 and NGC 5466. The [Ba/Fe] value for NGC 5897 is also substantially deficient compared with the target cluster values. It is apparent that the abundances of stars in NGC 5024 and NGC 5466 show some deviations from those in NGC 5897, suggesting that the stars formed from gas of different chemical composition. The host clusters may thus have different star formation and chemical enrichment histories and may have formed in different environments. 88

0.5

-0.5

NGC5024 -1 Arp 2

O Mg Si Ca Ti TiII Cr Mn Co Ni Cu Y Ba La Nd Eu

Figure 10.10: Abundance ratios as a function of increasing atomic number. In this plot we compare the abundance pattern in NGC 5024 with that of Arp 2, a similar metallicity globular cluster associated with its supposed parent dwarf spheroidal galaxy Sgr. Arp 2 data is from Mottini et al. (2008) who assign no error bar to any abundances derived from a single spectral line. It is apparent that NGC 5024 abundances show a very similar pattern to that of Arp 2, providing signiﬁcant evidence in favour of this proposed association. 89

Chapter 11

Tables 90 V E(B-V) v (kpc) (m-M) sun )R 1 0.30.24.10.3 7.7 10.4 17.8 14.48 15.12 5.78 15.9 6.19 16.31 7.61 16.00 0.02 9.04 0.01 0.02 0.00 − ± ± ± ± (km s r Table 11.1. Cluster Information Cluster ID R.A. DEC [Fe/H] V Note. — Harris (1996) NGC 6205 (M13)NGC 5272 16:41:41.44 (M3)NGC +36:27:36.9 5024 (M53) 13:42:11.23NGC 5466 -1.54 +28:22:31.6 13:12:55.3 -245.6 -1.57 +18:10:09 -147.6 -1.99 14:05:27.3 -79.1 +28:32:04 -2.22 107.7 a

91 ddmmsss ± Table 11.2. Target Information 2217 13:41:30.30 +28:22:17.0 ... 14.10 13.75 13.10 ... 11.698 11.118 10.969 13413024+2822163 50371 1322254 13 17.36 1310186 12 +18 47.93 14 46.6 149951 05 +18 44.55 06 16.428 32.21344 +28 14 15.611 31 05 16.513 13.6 41.10 14.560 14 15.919 05 +28 20.73 29 13.802 48.3 14.872 +28 29 13.405 14.196 ... 42.0 12.574 13.721 11.973 ... 12.932 11.878 12.367 ...... 12.230 14.626 13131736+1814463 ... 13124794+1806320 14.979 ...... 14.666 13.504 ... 12.712 13.876 ... 12.137 13.092 13.508 12.107 12.551 12.725 14054453+2831135 12.422 12.153 12.056 14054108+2829482 14052071+2829419 III-18 16:41:24.66 +36:25:45.1 ... 13.97 12.77 ...... 10.601 9.928 9.830 16412464+3625449 C41303 Target ID R.A. DEC U B V R I J H K 2MASS designation 2MASS naming convention: 2MASSJhhmmssss a Note. — Target stars U, B, V, R, I colours from Peter Stetson (private communication), J, H, K colours from 2MASS online point source M3 NGC 5024 NGC 5466 NGC 5466 NGC 5466 NGC 5024 M13 catalogue 92 ˚ A 7000 ˚ A 6250 ˚ A 5500 ˚ A 4750 a ˚ A Table 11.3. Observations (s) 5936 15 1500.015 1500.0 09:01:04.2015 16:41:45.66 72000 09:26:51.9815 +36:24:12.2 16:41:46.31 1500.015 09:01:04.20 +36:25:00.3 1500.0 06:08:05.10 16:41:45.66 11115 13:41:56.23 +36:24:12.2 141000 06:33:54.41 11110 +28:19:13.7 06:08:05.10 13:41:56.76 1693.510 20 ... 13:41:56.23 +28:20:01.1 1693.5 10:54:20.4210 30 54 +28:19:13.7 13:13:43.43 81288 11:23:21.3909 54 50 +18:11:41.6 13:13:42.33 1400.0 5009 ... 10:54:20.42 45 +18:12:26.0 10 1300.0 07:09:11.79 13:13:43.4309 73 12 70 13:13:04.92 +18:11:41.6 ... 07:36:03.99 75 73 +18:04:47.0 30 60 13:13:03.99 20 ... +18:04:43.1 16 25 60 57 120 ... 18 40 65 30 57 33 35 115 35 ... 35 55 25 ... 55 50 35 ...... 40 60 ... 40 75 30 ...... 75 ...... 25 40 45 45 03 03 03 03 03 03 03 03 03 05 05 05 2008 2007 2005 2008 b b b 22172217 2008 2217 2008 b 5037150371 2007 50371 2007 2225422254 2005 22254 2005 III-18III-18III-18 2008 2008 C41303 C41303 C41303 Target ID Date EXP UT R.A. DEC Signal to Noise M13 M13 M13 M3 M3 M3 NGC 5024 NGC 5024 NGC 5024 NGC 5024 NGC 5024 NGC 5024 93 ˚ A 7000 ˚ A 2x2. Data for 6250 ˚ A GC0 5500 IS0 ˚ A 0sky 4750 2as a ˚ A 316g5936 central 30k Table 11.3 (cont’d) (s) 5936 01 1800.001 1500.0 04:39:20.2001 14:06:03.08 79200 05:18:56.9906 +28:29:10.7 14:06:03.15 1700.006 04:39:20.20 +28:29:18.2 1650.0 06:23:29.63 14:06:03.0806 82 14:05:54.80 +28:29:10.7 80400 06:52:31.7917 67 +28:28:20.0 14:05:55.06 1800.021 06:23:29.63 ... +28:28:31.6 20 1800.0 03:38:35.61 14:05:54.8024 48 17 14:05:35.50 +28:28:20.0 1380.0 11:59:43.0624 48 +28:28:03.1 14:05:34.08 45 1620.0 05:11:26.79 3524 ... +28:27:37.4 10 14:05:40.06 39 158400 05:39:48.02 70 +28:27:34.3 15 05:11:26.79 14:05:40.64 28 60 55 14:05:40.06 +28:27:37.2 24 20 45 52 +28:27:34.3 13 25 49 45 75 14 32 ... 50 40 13 28 32 12 80 28 24 50 35 20 36 25 24 32 50 60 30 28 33 18 65 23 22 75 07 07 07 06 06 06 07 12 06 06 06 2006 2005 2006 b b b 1018610186 2006 10186 2006 99519951 2005 9951 2005 13441344 2005 1344 2005 1344 2006 1344 2006 22254 was reduced by collaborator Konstantin Fedotov, whose methods did not preserve the indicated header Target ID Date EXP UT R.A. DEC Signal to Noise Combined spectra http://het.as.utexas.edu/HET/hetweb/ProgramStatus/ProgramStatus.html a b Note. — All exposures were taken with the same setup: HRS NGC 5466 NGC 5466 NGC 5466 NGC 5466 NGC 5466 NGC 5466 NGC 5466 NGC 5466 NGC 5466 NGC 5466 NGC 5466 NGC 5024 information in theprovided. ﬁnal spectra. The individual collected spectra were not accessible; only the ﬁnal combined spectra were 94

Table 11.4. Line Data, Wavelengths and Radial Velocities from Doppler Shift Calculations - Standard Stars

Ion LAB RMT M13 III-18 M3 C41303 2217 a b λ No λ Vr λ Vr (A˚)(A˚) (km s−1)(A˚) (km s−1)

Mg I 5172.68 2 5168.35 -251.38 5170.03 -153.69 Mg I 5183.60 2 5179.27 -250.84 5180.95 -153.61 Na I 5889.95 1 5885.02 -251.11 5886.95 -152.88 Na I 5895.92 1 5891.00 -250.55 5892.92 -152.65 Fe I 6137.69 207 6132.53 -252.41 6134.55 -153.67 Ba II 6141.71 2 6136.57 -251.22 6138.59 -152.55 Fe I 6230.73 207 6225.52 -250.66 6227.54 -153.40 Ca I 6439.07 18 6433.70 -250.19 6435.78 -153.28 Ca I 6493.78 18 6488.30 -253.16 6490.45 -153.84 Ba II 6496.90 2 6491.47 -250.64 6493.58 -153.21

aRalchenko et al. (2008) bMoore (1945) 95

Table 11.5. Line Data, Wavelengths and Radial Velocities from Doppler Shift Calculations - NGC 5024

Ion LAB RMT NGC 5024 50371 NGC 5024 22254 a b λ No λ Vr λ Vr (A˚)(A˚) (km s−1)(A˚) (km s−1)

Mg I 5172.68 2 5171.47 -70.19 5171.98 -40.60 Mg I 5183.60 2 5182.38 -70.61 5182.90 -40.51 Na I 5889.95 1 5888.54 -71.82 5889.16 -40.23 Na I 5895.92 1 5894.52 -71.23 5895.12 -40.71 Fe I 6137.69 207 6136.21 -72.34 6136.83 -42.03 Ba II 6141.71 2 6140.24 -72.00 6140.86 -41.52 Fe I 6230.73 207 6229.23 -72.03 6229.89 -40.44 Ca I 6439.07 18 6437.53 -71.75 6438.20 -40.53 Ca I 6493.78 18 6492.23 -71.61 6492.90 -40.65 Ba II 6496.90 2 6495.34 -71.94 6496.02 -40.63

aRalchenko et al. (2008) bMoore (1945) 96 ) 1 − 24) r V 06 ) (km s λ ˚ A 5174.925185.84 129.91 5892.49 129.40 5898.47 129.37 6140.32 129.75 6144.37 128.55 6233.42 129.93 6441.85 129.52 6496.59 129.52 6499.70 129.82 129.29 )( 1 − 21) 1344 (2006 ) r V 12 ) (km s λ ˚ A 5174.125185.06 83.52 5891.58 84.50 5897.56 83.02 6139.40 83.24 6143.44 83.58 6232.47 84.50 6440.86 83.78 6495.60 83.40 6498.71 84.08 83.67 )( 1 − 17) 1344 (2005 r V 07 ) (km s λ ˚ A 5174.925185.86 129.66 5892.49 130.80 5898.48 129.37 6140.36 130.26 6144.37 130.50 6233.42 129.78 6441.85 129.71 6496.59 129.52 6499.72 129.82 130.31 )( 1 − r V Calculations - NGC 5466 ) (km s λ ˚ A 5174.875185.81 126.76 5892.43 127.90 5898.41 126.32 6140.30 126.49 6144.31 127.57 6233.36 127.00 6441.80 126.63 6496.53 127.19 6499.65 127.04 126.98 )( 1 − r V ) (km s λ Table 11.6. Line Data, Wavelengths and Radial Velocities from Doppler Shift ˚ A 5174.945185.85 130.82 5892.50 129.98 5898.48 129.88 6140.36 130.05 6144.39 130.31 6233.44 130.76 6441.87 130.67 6496.61 130.45 6499.73 130.28 130.77 a )( ˚ A λ ( Ralchenko et al. (2008) a Ion LAB 10186 9951 1344 (2005 Mg IMg 5172.68 INa 5183.60 INa I 5889.95 Fe I 5895.92 Ba II 6137.69 Fe 6141.71 ICa I 6230.73 Ca I 6439.07 Ba II 6493.78 6496.90 97

Table 11.7. Radial and Heliocentric Radial Velocities

a b c d ID Vr Vrhelio Vrhelio Vrhelio (km s−1) (km s−1) (km s−1) (km s−1)

M13 III-18 (2008 03 05) -251.22 -236.48 -234.9 -245.6 ±0.3 M3 C41303 2217 (2008 03 05) -153.28 -145.88 -144.5 -147.6 ±0.2 NGC 5024 50371 (2007 03 10) -71.55 -61.94 ... -79.1 ±4.1 NGC 5024 22254 (2005 05 09) -40.78 -57.82 ... -79.1 ±4.1 NGC 5466 10186 (2006 07 01) 130.40 107.45 ... 107.7 ±0.3 NGC 5466 9951 (2005 06 06) 126.99 107.24 ... 107.7 ±0.3 NGC 5466 1344 (2005 07 17) 129.97 106.99 ... 107.7 ±0.3 NGC 5466 1344 (2005 12 21) 83.65 106.69 ... 107.7 ±0.3 NGC 5466 1344 (2006 06 24) 129.51 107.05 ... 107.7 ±0.3

aThese radial velocities are straight averages of all the radial velocities found from the spectral lines as listed in the previous table. bThe heliocentric radial velocities are determined from the radial velocities using rvcorrect and the necessary header information (UT,RA,DEC,Vr) cCohen & Melendez (2005) dAccepted values for host clusters from Harris online catalogue (Harris, 1996)

Note. — The stars in NGC 5024 both have signiﬁcantly diﬀerent radial velocities from those published in the Harris online catalogue, and yet the velocities are similar to one another. 98 a 0.20) ± [Fe/H] ( a rather than ) 1 vk − T = ξ eff T 0.25 km s ± ( a log¸g 0.50 dex) ± ( a eff ...... 100 K) 45004525 1.0046104575 1.1047004700 0.65 1.654650 0.75 0.60 1.40 0.60 -1.35 0.65 1.72 1.45 -1.30 1.52 1.55 -1.82 1.47 -1.97 -1.95 -1.81 -1.88 ± [Fe/H] T )( 1 − ξ MARCS OSMARCS log¸g eff Table 11.8. Model Atmosphere Parameters 4400 0.954350 1.004450 1.65 1.104436 1.65 1.204500 -1.36 1.40 0.654450 -1.43 1.60 0.754500 -1.30 1.82 0.604525 -1.37 1.55 0.704500 -1.80 1.91 0.65 -2.00 1.74 -2.00 1.55 -1.85 -1.90 ) (K) (km s

M log¸g T 3 as is the case for the target stars. / Photometric Spectroscopic ) eff ...... T vj 4347 1.16 4255 0.96 T b c + vk T 2217 2217 b c 5037122254 449010186 4526 1.10 9951 4539 1.25 1344 4542 1.28 4485 1.42 1.26 + vi ID (K) (0.8 T III-18 III-18 C41303 C41303 = ( This work. Photometric parameters for standard stars are determined from (V-K) colours, that is, The representative 1 sigma error (measurement performed on M13) for our OSMARCS model parameters. Cohen & Melendez (2005) - Kurucz models a b c Note. — The spherical OSMARCS models systematically indicate higher temperatures and microturbulent velocities than eff M13 M3 M3 NGC 5024 NGC 5024 NGC 5466 NGC 5466 NGC 5466 M13 T the plane-parallel MARCS models for NGC 5024 and NGC 5466 stars. 99 (N) N a √ / σ ...... 0.52 0.050.41 (2) 0.110.24 (3) 0.050.13 (9) 0.20 0.05 (15) 0.19 0.05 (7) 0.05 (25) -1.37-1.34 0.05 (126) 0.05 (14) -0.23 0.09 (3) 2217 c41303 (N) [X/Fe] [X/Fe] σ This work CM05 ...... 6.22 0.106.22 (135)7.90 0.09 -1.30 (12)4.65 0.03 (2) -1.30 6.33 0.12 (4) 0.54 0.15 (6)6.52 -0.22 4.46 0.10 0.05 (9)5.22 0.15 (2)1.91 0.13 0.31 (19)3.90 0.68 0.06 (8) 0.21 0.12 (26) 0.16 0.30 (N) Ab N a √ / σ ...... 0.520.30 0.060.84 (4) 0.140.40 (3) 0.10 (1) 0.050.15 (8) 0.26 0.05 (13) 0.18 0.05 (7) 0.05 (22) -1.43-1.46 0.05 (123) -0.16 0.05 (13) 0.10 (1) III-18 M3 M13 (N) [X/Fe] [X/Fe] σ Table 11.9. Elemental Abundances and Uncertainties for Standard Stars This work CM05 Ion Ab Fe IIO 6.17 I 0.06 (12) 7.44Mg I -1.35 0.01 6.34 (2) 0.13 (5) 0.13 0.16 Fe I 6.17 0.08 (133) -1.35 Na I 5.27Al I 0.12 (6)Si I 5.91K I 0.45 6.47 0.05 (2)Ca I 4.32 0.05Sc (9) 5.12 II 0.89 0.07Ti (2) 1.94 I 0.13 (17) 0.31 0.07 3.80 (8) 0.59 0.16 0.09 (29) 0.24 0.25 100 (N) N a √ / σ ...... 0.04 0.06 (9) 0.12 0.05 (3) -0.18 0.06 (8) -0.27-0.11 0.14 (4) -0.14 0.03 (3) -0.56 0.05 (15) -0.10 0.21 (2) -0.12 0.05 (2) 0.10 (4) 2217 c41303 (N) [X/Fe] [X/Fe] σ This work CM05 3.872.53 0.12 (9) 0.104.36 (14) 0.27 4.31 0.07 -0.17 (9)3.91 0.06 (2) 0.02 3.60 0.09 (5) -0.03 4.87 0.09 (3) -0.18 0.132.43 (19) -0.02 3.20 0.10 -0.06 (1)0.73 0.10 (1) -0.48 1.15 0.09 (7) -0.10 0.13 (3) -0.18 0.28 (N) Ab N a √ / σ Table 11.9 (cont’d) ...... 0.02 0.05 (7) 0.32 0.05 (3) -0.11 0.05 (8) -0.25-0.02 0.08 (4) -0.07 0.06 (4) -0.61 0.05 (18) -0.05 0.13 (2) -0.23 0.05 (2) 0.06 (5) III-18 M3 M13 (N) [X/Fe] [X/Fe] σ This work CM05 Ion Ab V I 2.64 0.07 (13)Mn I -0.01 3.89 0.10 (6) -0.15 Ti II 3.87Cr I 0.14 (9)Cr II 4.31 0.32 4.22 0.05 (8)Co 0.05 I (3)Ni 0.02 I 3.59 -0.07 Cu I 0.07 4.88 (3)Zn I 2.34 0.10 (21)Y 0.02 II 0.01 3.17 (3) 0.00 Ba II 0.03 0.75 (2) -0.52 1.18 0.08 (7) -0.08 0.08 (3) -0.11 0.36 101 (N) ] where N a √ / σ F e/H [ − ) for the species σ 0.280.50 0.060.20 (5) 0.10 (1) 0.13 (43) -0.01 0.15 (2) odot ) 2217 X of Mg I, Ca I, Ti I and ( σ 10 is c41303 log α 0, on the standard scale where − . ) X ( (N) [X/Fe] [X/Fe] ) + 12 σ 10 This work CM05 H log /N A = N

( 0.48 0.10 (5)5.15 0.33 0.28 (61) 0.20 -0.06 0.07 (3)-0.27 0.11 0.10 (1) 0.51 ) 10 log (N) Ab X/F e ( N a ) = 10 √ X / ( log σ Table 11.9 (cont’d) 10 − ) log . The entries for Fe I and Fe II in the [X/Fe] column represent 0.100.31 0.090.57 (3) 0.060.17 (7) 0.10 (1) 0.16 (38) odot X/F e ) = ) ( X III-18 M3 ( 10 F e . For this they adopted a minimum value of 0.05 dex when unrealistically ( σ Ab log 10 M13 log ] = − were calculated (e.g.. Fe I with its very large value of N) and assigned a value of 0.10 ) N (N) [X/Fe] [X/Fe] X/F e F e rather than √ σ ( / This work CM05 σ N 10 √ / log σ 5.10 0.25 (61) 0.20 ) = 12. [ ] = H ( Cohen & Melendez (2005), using models from Kurucz (1993). Note that Cohen & Melendez (2005) 10 a Note. — In this table we record the mean abundances and standard deviations ( Ion Ab La IINd II 0.04Eu 0.41 II 0.05 (3)α -0.36 0.05 (6) 0.10 0.19 (1) 0.31 0.47 F e/H observed in M3log and M13. published small values of dex for any specieswhen with only only one one line detectedmodiﬁed is line slightly detected. from (e.g.. The their abundance Eu(See published results II). Table values given 14). We to here adopt compensate for the for Cohen same updates & practice to Melendez in the (2005) the solar have chemical situation been composition [Fe I/H] and [Feresults II/H], come which from have OSMARCS been model equalized atmospheres under (see the Table 8). assumption of Error ionization in equilibrium. Our [ Ti II added in quadrature. 102 0.01 0.01 0.00 0.03 0.02 0.01 -0.01 -0.01 -0.06 -0.01 -0.01 -0.03 (N) [X/Fe] [X/Fe] σ 6.16 0.096.16 (133)7.36 0.07 -1.36 (12)5.25 0.11 (2) -1.36 6.34 0.16 (6)5.91 0.06 0.15 (5)6.45 0.44 0.07 (2)4.31 0.17 0.06 (9)5.14 0.90 0.05 (2)1.90 0.13 0.30 (17)3.81 0.59 0.07 (8) 0.19 3.87 0.10 (29) 0.21 0.15 (9) 0.27 0.33 III-18 – MARCS vs. OSMARCS (N) [X/Fe] Ab σ OSMARCS MARCS ∆ Star M13 Ion Ab Fe I 6.17 0.09 (133) -1.35 Al ISi I 5.91 6.47 0.05 (2)Ca I 0.05Sc (9) 5.12 II 0.89 1.94 0.13 (17) 0.31 Ti II 0.07 (8) 0.16 3.87 0.24 0.14 (9) 0.32 Fe IIO 6.17 INa 0.06 I (12) 7.43Mg 5.27 I -1.35 0.11 6.34 (2) 0.12 (6) 0.13 (5) 0.12 K I 0.45 0.16 4.32 0.07Ti (2) I 3.80 0.59 0.09 (29) 0.25 Table 11.10. Elemental Abundance Atmospheric Model Comparison for Standard 103 0.01 0.02 0.00 0.00 0.03 0.06 -0.01 -0.04 -0.03 -0.02 -0.05 -0.06 (N) [X/Fe] [X/Fe] σ 2.62 0.084.31 (13)4.23 0.05 -0.02 (8)3.88 0.05 (3) 0.03 3.54 0.11 (6) -0.05 4.87 0.07 (3) -0.15 0.112.30 (21) -0.02 3.19 0.03 (3) 0.00 0.72 0.02 (2) -0.55 1.12 0.08 (7) -0.05 0.06 (3) -0.13 0.34 0.31 0.06 (5) 0.25 -0.03 0.09 (3) 0.13 Table 11.10 (cont’d) (N) [X/Fe] Ab σ OSMARCS MARCS ∆ Ion Ab V I 2.64 0.07 (13) -0.01 Cr ICr II 4.31Mn I 4.22 0.05 (8)Co I 3.89 0.05 (3)Ni I 0.10 0.02 3.59 (6) -0.07 Cu I 0.07 4.88 (3) -0.15 Zn I 2.34 0.10 (21)Y 0.02 II 0.01 3.17 (3) 0.00 Ba II 0.03 0.75 (2)La -0.52 1.18 II 0.08 (7)Nd -0.08 0.08 0.04 II (3) 0.41 -0.11 0.05 (3) 0.36 0.05 (5) 0.19 0.31 104 0.02 -0.06 (N) [X/Fe] [X/Fe] σ 5.11 0.27 (61) 0.22 -0.43 0.10 (1) 0.41 Table 11.10 (cont’d) (N) [X/Fe] Ab σ OSMARCS MARCS ∆ 5.10 0.25 (61) 0.20 Note. — Model parameters as indicated in Table 10.8. Ion Ab Eu IIα -0.36 0.10 (1) 0.47 105

Table 11.11. Elemental Abundances and Uncertainties for NGC 5024

50371 22254 Mean ∆ Ion Ab σ (N) [X/Fe] Ab σ (N) [X/Fe] [X/Fe] dex

Fe I 5.70 0.10 (96) -1.82 5.55 0.12 (95) -1.97 -1.90 0.15 Fe II 5.70 0.08 (8) -1.82 5.55 0.11 (8) -1.97 -1.90 0.15 O I 7.49 0.05 (2) 0.65 7.00 0.02 (2) 0.31 0.48 0.34 Na I 4.27 0.09 (2) -0.08 4.21 0.04 (2) 0.01 -0.04 0.09 Mg I 6.03 0.06 (6) 0.32 5.96 0.16 (5) 0.40 0.36 0.08 Si I 5.97 0.10 (3) 0.28 5.96 0.05 (5) 0.42 0.35 0.14 K I 3.97 0.09 (2) 0.71 4.19 0.11 (2) 1.08 0.90 0.37 Ca I 4.76 0.18 (17) 0.27 4.62 0.10 (13) 0.28 0.28 0.01 Sc II 1.33 0.09 (7) 0.10 1.20 0.10 (7) 0.12 0.11 0.02 Ti I 3.24 0.10 (18) 0.16 3.03 0.10 (18) 0.10 0.13 0.06 Ti II 3.46 0.10 (7) 0.38 3.27 0.09 (9) 0.34 0.36 0.04 V I 1.95 0.12 (8) -0.23 1.88 0.09 (2) -0.15 -0.19 0.08 Cr I 3.56 0.05 (8) -0.26 3.49 0.14 (8) -0.18 -0.22 0.08 Cr II 3.52 0.12 (2) -0.30 3.52 0.10 (1) -0.15 -0.23 0.15 Mn I 3.22 0.05 (3) -0.35 3.02 0.06 (2) -0.40 -0.45 0.09 Co I 3.00 0.10 (1) -0.10 2.93 0.10 (1) -0.02 -0.06 0.08 Ni I 4.39 0.11 (12) -0.04 4.19 0.13 (12) -0.07 -0.06 0.03 Cu I 1.56 0.05 (2) -0.83 1.40 0.07 (2) -0.84 -0.84 0.01 Zn I 2.54 0.11 (2) -0.24 2.48 0.06 (2) -0.15 -0.20 0.09 Y II -0.01 0.14 (6) -0.40 -0.02 0.06 (7) -0.26 -0.33 0.14 106

Table 11.11 (cont’d)

50371 22254 Mean ∆ Ion Ab σ (N) [X/Fe] Ab σ (N) [X/Fe] [X/Fe] dex

Ba II 0.55 0.03 (2) 0.20 0.56 0.03 (2) 0.36 0.28 0.16 La II -0.50 0.10 (1) 0.19 -0.57 0.10 (1) 0.27 0.23 0.08 Nd II -0.57 0.06 (6) -0.20 -0.64 0.04 (4) -0.12 -0.16 0.08 Eu II -1.00 0.10 (1) 0.30 -1.14 0.10 (1) 0.31 0.31 0.01 α 4.71 0.24 (48) 0.29 4.58 0.23 (45) 0.30 0.29 0.01 107 0.350.04 0.26 0.25 0.32 0.40 0.08 0.64 0.23 0.25 0.10 0.08 0.110.18 0.04 0.05 -1.88-1.88 0.14 0.14 -0.12 0.05 -0.12 0.16 (N) [X/Fe] [X/Fe] dex σ 5.64 0.105.64 (89)7.17 0.05 -1.88 (7)4.28 0.08 (2) -1.88 5.90 0.06 (2) 0.39 5.89 0.14 (6) -0.01 3.89 0.07 (4) 0.25 4.71 0.12 (2) 0.26 0.151.07 (17) 0.69 3.14 0.10 (8) 0.28 0.123.21 (18) -0.10 1.91 0.14 (6) 0.12 0.09 (3) 0.19 -0.21 (N) [X/Fe] Ab σ 5.71 0.135.71 (100)7.05 -1.81 0.09 (9)4.58 0.03 (2)6.01 -1.81 0.05 (2)6.19 0.20 0.09 (6)3.91 0.22 0.07 (3)4.78 0.29 0.10 (1)1.08 0.13 0.49 (16)3.17 0.64 0.13 (9) 0.28 3.24 0.12 (16)2.08 -0.16 0.12 (8) 0.08 0.08 (6) 0.15 -0.11 (N) [X/Fe] Ab 10186 9951 1344 Mean ∆ σ Table 11.12. Elemental Abundances and Uncertainties for NGC 5466 Ion Ab Fe I 5.57 0.11 (100) -1.95 Fe IIO 5.57 INa I 0.08 (8) 7.17Mg 4.12 I 0.04Si -1.95 5.79 (2) I 0.04 (2)K I 0.16 6.02 (6) 0.46 Ca -0.10 I 3.72 0.10Sc (1) 0.21 4.56 II 0.02Ti (2) 0.99 I 0.11 (17) 0.46 Ti II 0.11 3.07 (8) 0.59 V 0.20 3.15 I 0.12 (19) -0.11 0.12 2.00 (7) 0.12 0.09 (7) 0.20 -0.05 108 0.10 0.01 0.11 0.04 -0.16-0.18 0.11 -0.19 0.07 -0.27 0.08 -0.12 0.04 -0.78 0.07 -0.25 0.04 -0.52 0.10 -0.10 0.15 0.25 -0.28 0.11 (N) [X/Fe] [X/Fe] dex σ ...... 3.673.55 0.07 (8)3.27 0.08 (2) -0.09 2.75 0.11 (4) -0.21 4.25 0.10 (1) -0.24 0.151.57 (13) -0.29 0.04 -0.10 (2) -0.76 0.18 0.05 (3) -0.11 -0.19 0.07 (5)-0.65 -0.52 -0.69 0.00 (2)-1.29 0.04 (5) 0.10 0.10 (1) -0.26 0.07 (N) [X/Fe] Ab σ Table 11.12 (cont’d) ...... 3.643.63 0.09 (9)3.42 0.09 (2) -0.19 2.83 0.10 (4) -0.20 4.25 0.10 (1) -0.16 0.14 (14) -0.28 2.49 -0.17 0.10 (1)0.14 -0.30 0.08 (2) -0.20 -0.20 0.09 (5)-0.59 -0.60 -0.70 0.01 (2)-1.15 0.05 (3) 0.09 0.10 (1) -0.34 0.14 (N) [X/Fe] Ab 10186 9951 1344 Mean ∆ σ Ion Ab Nd II -0.73 0.04 (3) -0.23 Cr IIMn I 3.56Co I 3.26 0.00 (2)Ni I 0.14 2.73 (4)Cu -0.13 I 4.18 0.10Zn (1) -0.18 I 1.46 0.15Y (14) II -0.24 2.45 0.10Ba (1) -0.10 II -0.19 0.10La (1) II -0.80 0.25 0.06 (4) -0.71 -0.20 0.22 (2)Eu -0.45 II 0.10 (1) -1.32 0.03 0.11 0.10 (1) 0.11 Cr I 3.49 0.10 (8) -0.20 109 0.22 0.04 (N) [X/Fe] [X/Fe] dex σ 4.60 0.26 (47) 0.23 (N) [X/Fe] Ab σ Table 11.12 (cont’d) 4.67 0.23 (46) 0.23 (N) [X/Fe] Ab 10186 9951 1344 Mean ∆ σ 4.49 0.26 (49) 0.19 Note. — Unfortunately, the interference of sky emission lines with the Cu lines in 9951 and the Ion Ab α Zn line in 1344synthesis prevent was a considered reasonable in measurement these of cases, the but equivalent the widths deformation of of these the lines. lines Spectrum was too great. 110

Table 11.13. Adopted Solar Abundances

Element This worka CM05b ∆

O 8.66 8.85 -0.19 Na 6.17 6.33 -0.16 Mg 7.53 7.54 -0.01 Al 6.37 6.47 -0.10 Si 7.51 7.55 -0.04 K 5.08 ...... Ca 6.31 6.36 -0.05 Sc 3.05 3.10 -0.05 Ti 4.90 4.99 -0.09 V 4.00 4.00 0.00 Cr 5.64 5.67 -0.03 Mn 5.39 5.39 0.00 Fe 7.45 7.45 0.00 Co 4.92 4.92 0.00 Ni 6.23 6.25 -0.02 Cu 4.21 4.21 0.00 Zn 4.60 4.60 0.00 Y 2.21 2.24 -0.03 Ba 2.17 2.13 0.04 Zr 2.59 2.60 -0.01 La 1.13 1.14 -0.01 111

Table 11.13 (cont’d)

Element This worka CM05b ∆

Nd 1.45 1.45 0.00 Eu 0.52 0.51 0.01 Dy 1.14 1.10 0.04

aAsplund, Grevesse & Sauval (2005) bPrimarily Anders & Grevesse (1989) 112

Table 11.14. Sensitivity of Abundances

∆(Teff ) ∆(log¸g) ∆(ξ) ∆([Fe/H]) Total Error Ion +100 K +0.25 dex +0.20 km/s +0.20 dex

Fe I 0.12 0.01 -0.11 0.00 0.16 Fe II -0.06 0.11 -0.07 0.07 0.16 O I -0.01 0.10 0.00 0.09 0.13 Na I 0.12 -0.05 -0.04 0.02 0.14 Mg I 0.10 -0.04 -0.07 0.01 0.13 Al I 0.07 -0.01 -0.03 -0.02 0.08 Si I 0.01 0.03 -0.02 0.02 0.04 K I 0.16 0.03 -0.15 -0.03 0.22 Ca I 0.12 0.00 -0.10 -0.02 0.16 Sc II -0.01 0.10 -0.06 0.06 0.13 Ti I 0.20 0.02 -0.10 -0.02 0.23 Ti II -0.01 0.10 -0.11 0.06 0.16 V I 0.20 0.02 -0.03 -0.02 0.20 Cr I 0.19 0.01 -0.17 -0.02 0.26 Cr II -0.06 0.08 -0.05 0.04 0.12 Mn I 0.13 0.00 -0.08 -0.02 0.15 Co I 0.12 0.03 0.01 0.02 0.13 Ni I 0.10 0.03 -0.09 0.01 0.14 Cu I 0.12 0.03 -0.05 0.00 0.13 Zn I -0.04 0.05 -0.09 0.03 0.11 113

Table 11.14 (cont’d)

∆(Teff ) ∆(log¸g) ∆(ξ) ∆([Fe/H]) Total Error Ion +100 K +0.25 dex +0.20 km/s +0.20 dex

Y II 0.00 0.09 -0.10 0.05 0.14 Ba II 0.03 0.09 -0.20 0.08 0.24 La II 0.03 0.04 -0.05 0.07 0.10 Nd II 0.02 0.10 -0.05 0.06 0.13 Eu II -0.01 0.11 -0.03 0.07 0.13

Note. — Selected small variations in stellar parameters based on 1 σ deviation in iron abundance. Variation in [Fe/H] derived from standard deviations on Fe I and Fe II abundances added in quadrature. These sensitivities were determined based on the standard star data from M13 III- 18. Last column indicates value of all errors added in quadrature. This total error is actually an overestimate since this method treats each of the atmospheric parameters as independent quantities, but they are actually related to one another. For each species, this total error value is also comparable to but slightly larger than the standard deviation of its abundance as output by MOOG. This total error is the one used for the error bars in our plots of abundance trends (Figures 10.1 – 10.4). 114 85 105 97 88 90 80 70 75 75 114108 120105 110 ... 125 130 105 130 112 120 130 125 115105 160 ... 105 145 115 105 120 115 ) ˚ A (m λ ... 110 W 75 75 110125 100 130 110 125 105 147 110 100 125 95 160130 150 110 130 115 2217 50371 22254 10186 9951 1344 ...... 135 155 190 130 210 140 145 ... 140 167 160 175 185 135 170 150 115 160 M13 M3 NGC 5024 NGC 5466 Table 11.15. Atomic Data and Equivalent Widths (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 4872.144890.75 2.884891.49 2.87 -0.5904903.31 2.85 NIST -0.420 2.88 NIST -0.1404920.50 NIST -1.0704939.69 2.83 NIST 4966.10 0.86 0.060 3.33 -3.339 NIST NIST -0.890 NIST 4871.32 2.86 -0.410 NIST 4918.99 2.86 -0.360 NIST 4994.13 0.91 -3.079 NIST Ion Fe I 4859.74 2.88 -0.860 NIST 115 ... 125...... 117 108 90 100 110 65 68 ... 105135 115 140 ... 140 117105 120 110 120 110 125140 130 140 125 135 ) ˚ A (m λ ... 115 ... 115 ...... W 70 ... 160 140 140128 125 125 110 105 150152 125 125 138 115 2217 50371 22254 10186 9951 1344 60 140 175 135 150 150 130 100 160 195 150 ...... 50 150 198 150 155 112 176 195 163 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5150.84 0.99 -3.0605162.29 NIST 4.18 0.020 NIST 5006.125012.07 2.835079.74 0.86 -0.6285083.34 0.99 She03 -2.642 0.96 NIST -3.2205151.91 NIST -2.9585159.05 1.01 NIST 4.28 -3.3235166.28 NIST -0.8105171.60 0.00 NIST 5192.34 1.48 -4.195 3.00 NIST -1.793 NIST -0.420 CM05 Ion 116 ... 125 110 7675 80 7562 ... 90 79 72 90 68 70 ... 80 80 95 80 90 120 125 ... 112 115 114 125105 131 115 130 115 ) ˚ A (m λ ... 120 ... 70 ... 80 W 85 73 95 79 100 77 145 120 104138 95 130 130 115 120 115 2217 50371 22254 10186 9951 1344 160 125 110 150 105 135 165 145 105 120 145 ...... 170 130 165 110 140 185 170 120 162 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5194.945198.71 1.565215.19 2.22 -2.0905216.27 3.27 NIST -2.1345217.40 1.61 NIST -0.9305225.53 3.21 She03 -2.1505232.94 0.11 NIST -1.0705266.56 2.94 CM05 -4.7905302.30 3.00 NIST -0.2005307.36 3.28 NIST -0.4905324.18 1.61 NIST -0.880 3.21 NIST -2.986 NIST -0.240 NIST Ion 117 8582 8550 8760 95 5560 80 6578 55 6624 63 7873 75 ...45 ... 8558 ... 4078 ... 62 46 83 70 77 ) ˚ A (m λ ...... 65 85 W 7090 50 65 359550 23 67 83 94 40 52 67 110100 93 85 2217 50371 22254 10186 9951 1344 95 65 90 90 125 122 106 110 120 120 104 ...... 98 92 95 140 130 105 118 130 112 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5332.90 1.56 -2.940 NIST 5339.935364.86 3.275367.48 4.45 -0.6805369.96 4.42 NIST 0.2205383.37 4.37 NIST 0.3505389.48 4.31 NIST 0.3505393.17 4.42 NIST 0.5005400.50 3.24 -0.400 NIST 5410.91 4.37 NIST -0.9105415.20 4.47 NIST -0.150 4.39 NIST 0.280 NIST 0.510 NIST Ion 118 ...... 72 934520 82 ...... 19 25 26 ... 170 195 190 125110 140120 132 132 142 127 127 ) ˚ A (m λ ...... 50 25 ...... 35 W 100220 84 186 160155 132 160 125 130 2217 50371 22254 10186 9951 1344 ... 82 60 35 58 24 68 120 275 160 170 ... 55 35 60 35 75 128 290 190 175 190 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5424.07 4.32 0.520 NIST 5554.885560.21 4.555567.39 4.35 -0.440 2.61 NIST -1.190 NIST -2.810 NIST 5429.695445.04 0.965466.39 4.39 -1.8795497.52 4.37 NIST -0.0105501.46 1.01 NIST -0.6305506.78 0.96 NIST -2.8495525.55 0.99 NIST -2.960 4.23 NIST -2.797 NIST -1.330 NIST Ion 119 ...... 15...... 10 8 7590 ...57 11092 85 75 103 100 70 102 56 7730 76 4015 34 20 ... 105 117 114 ) ˚ A (m λ ... 68 ...... W 95 84 841538 65 ... 40 107 90 122138 ... 110 2217 50371 22254 10186 9951 1344 ...... 25 70 35 60 115 130 105 140 145 ... 25 45 80 30 55 127 148 108 163 120 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5624.54 3.425662.52 -0.900 4.18 NIST 5686.52 -0.570 4.55 CM05 -0.630 NIST 5569.625572.84 3.425576.09 3.40 -0.5305586.76 3.43 NIST -0.3105615.64 3.37 NIST -1.0105624.04 3.33 NIST -0.210 4.39 NIST -0.1405641.44 NIST -1.480 4.26 NIST 5679.02 -1.170 4.65 NIST -0.910 NIST Ion 120 ...... 27 ...... 47 65 68 2540 ...12 ...20 ...... 40 30 15 25 ) ˚ A (m λ ...... W 65 60 50 50 30 ... 2217 50371 22254 10186 9951 1344 25 50 38 55 78 45 60 55 70 55 105 ...... 18 55 42 60 85 45 64 65 108 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5701.55 2.565705.98 -2.2165731.76 4.61 NIST 5753.12 4.26 -0.530 4.26 NIST -1.290 NIST -0.760 NIST 5934.656027.05 3.93 4.08 -1.180 NIST -1.220 NIST 5705.47 4.30 -1.600 NIST 5762.995816.37 4.215883.81 4.55 -0.4605930.17 3.96 NIST -0.690 4.65 NIST -1.360 NIST -0.230 NIST Ion 121 ...... 20...... 30 ...... 1585 14 95 ... 30 95 98 ... 110 ... 100 40 57 53 105 105 110 ) ˚ A (m λ ...... W 5544 48 ... 2558 ... 45 110 ... 132 105 125 95 2217 50371 22254 10186 9951 1344 ... 46 50 72 50 35 48 128 100 150 100 40 60 75 62 25 55 145 155 100 158 100 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6055.99 4.73 -0.4606136.61 NIST 2.45 -1.399 NIST 6157.736165.36 4.086170.50 4.14 -1.2506173.34 4.80 NIST -1.550 2.22 NIST -0.430 NIST -2.879 NIST 6065.486082.71 2.61 2.22 -1.5306136.99 NIST -3.5726137.69 2.20 NIST 6151.62 2.59 -2.950 2.18 NIST -1.403 NIST -3.299 NIST Ion 122 ... 43... 50 ...... 120...... 120 68... 58 70 ... 6560 70 ... 75 23 75 3597 30 11060 100 88 83 108 120 116 ) ˚ A (m λ ...... 85 ...... 68 W 5385 ... 80 30 ... 9590 74 72 127 120 140 108 115 105 2217 50371 22254 10186 9951 1344 98 38 65 94 150 102 120 160 142 117 108 ...... 50 70 165 100 115 122 150 130 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6191.56 2.436213.43 -1.416 2.22 NIST -2.6506230.73 NIST 6240.65 2.56 2.22 -1.2816252.55 NIST -3.390 2.40 NIST 6265.13 -1.687 2.18 NIST -2.550 NIST 6200.31 2.616219.28 -2.4376229.23 2.20 NIST 2.85 -2.434 NIST -2.9706246.32 NIST 3.606254.26 -0.960 2.28 NIST -2.480 NIST Ion 123 ...... 45... 45 ...... 2056 2540 60 ...... 45 65 80 ...... 39 80 ... 553754 49 46 67 45 79 ) ˚ A (m λ ...... 60 ...... W 309070 ... 88 65 6450 48 88 38 72 100 90 2217 50371 22254 10186 9951 1344 ...... 25 90 88 72 85 122 108 125 58 35 95 85 90 35 125 105 100 132 125 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6270.22 2.86 -2.710 NIST 6322.69 2.59 -2.426 NIST 6355.03 2.85 -2.400 NIST 6280.626297.79 0.866311.50 2.22 -4.386 2.83 NIST -2.7406335.33 NIST -3.2206336.82 2.20 NIST 6344.15 3.69 -2.230 2.43 NIST -1.0506358.69 NIST -2.9226380.75 0.86 NIST 4.19 -4.468 NIST -1.400 NIST Ion 124 ...... 40 48 7562 ...20 6092 90 ... 65 94 25 30 105 52 50 105 95 102 103 103 98 135 128 135 ) ˚ A (m λ ...... 108 W 8535 64 ... 3945 ... 46 50 45 100 ... 115124 110 116 153 137 2217 50371 22254 10186 9951 1344 ... 30 50 75 92 136 125 106 136 145 165 30 55 70 95 98 155 135 110 145 150 175 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6392.546393.60 2.28 2.43 -4.030 NIST -1.610 NIST 6481.87 2.28 -2.984 NIST 6400.006411.65 3.606419.94 3.65 -0.5206421.35 4.73 NIST -0.8206430.84 2.28 NIST -0.2506475.63 2.18 NIST -2.027 2.56 NIST -2.0056494.98 NIST -2.9406498.94 2.40 NIST 0.96 -1.273 NIST -4.699 NIST Ion 125 ...... 20 ...... 40 ... 66 35 ... 1770 ...... 26 23 80 348555 35 102 ... 90 60 ) ˚ A (m λ ... 85 ...... 68 W 3025 30 3545 20 20 30 73 ... 103 ... 2217 50371 22254 10186 9951 1344 60 58 70 78 45 30 76 120 122 108 106 65 50 78 80 45 30 90 128 136 115 115 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6518.36 2.83 -2.7506574.23 NIST 6575.02 0.99 2.59 -5.0406592.91 NIST -2.820 2.73 NIST -1.6006609.11 NIST 6663.44 2.56 2.42 -2.692 NIST -2.478 NIST 6546.246569.21 2.76 4.73 -1.650 NIST -0.4206581.21 NIST 1.486593.87 -4.8506608.02 2.43 NIST 2.28 -2.422 NIST -4.040 NIST Ion 126 ...... 18 ... 48 57 50 6042 ... 5022 72 60 20 ... ) ˚ A (m λ ...... W 66 66 757120 60 30 75 ...... 2217 50371 22254 10186 9951 1344 ...... 42 40 50 28 35 50 75 100 105 ...... 45 30 44 25 30 50 75 115 110 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6739.526750.15 1.56 2.42 -4.9406855.18 NIST -2.6206858.15 4.56 NIST 6861.95 4.61 -0.7406945.20 2.42 CM05 -1.050 2.42 NIST -3.900 NIST -2.4827016.06 NIST 2.42 -3.200 NIST 6703.57 2.76 -3.1506806.85 NIST 2.73 -3.210 NIST 6978.856988.52 2.48 2.40 -2.501 NIST -3.660 NIST Ion 127 ...... 10 65 ... 56 ... 100 90 35 3560 ...... 8080 ... 85 85 ...... 130 130 125 ) ˚ A (m λ ...... W 3256 32 80 56 85 80 85 75 75 140 125 100 82 2217 50371 22254 10186 9951 1344 50 36 68 30 95 90 85 42 102 140 105 48 42 80 30 95 90 45 100 125 145 105 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 7022.957038.22 4.197130.92 4.22 -1.2607418.67 4.22 NIST -1.3107583.79 4.14 NIST -0.7907748.27 3.02 NIST -1.590 2.95 NIST -1.9805197.58 NIST -1.7705234.63 3.23 NIST 5264.81 3.22 -2.1005276.00 3.23 NIST -2.220 3.20 CM05 -3.190 NIST -1.940 NIST Ion Fe II 4923.93 2.89 -1.320 NIST 128 8 5 8 ... 22 20 ...... 4030 50 ...25 42 45 ... 3445 5520 34 45 40 16 46 18 ) ˚ A (m λ ...... 15 ...... W 45 ... 354550 20 35 35 15 30 14 5 2217 50371 22254 10186 9951 1344 30 55 35 25 40 48 50 38 16 40 55 6 36 60 44 30 35 52 52 18 82 100 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5425.255534.85 3.206247.56 3.25 -3.3606416.92 3.89 -2.920 NIST 6432.68 3.89 -2.520 NIST 6456.38 2.89 -2.850 NIST 6516.08 3.90 -3.740 NIST 2.89 -2.310 NIST 6363.78 -3.450 NIST 0.02 NIST 5688.21 -10.257 2.10 NIST -0.452 NIST Ion O II 6300.31Na I 0.00 5682.63 -9.776 2.10 NIST -0.706 NIST 129 ...... 30 45 40 205180 240 220 225 195 100100 120240 110 115 250 260 110 105 300 250 115 290 110 ) ˚ A (m λ ...... W 50 50 245210 225 205 140115 ... 300 100 350 275 130 320 125 2217 50371 22254 10186 9951 1344 ...... 85 275 245 150 135 390 480 150 ... 25 48 80 65 435 355 160 150 500 160 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5895.926154.23 0.00 2.10 -0.194 NIST -1.5474702.99 NIST 5172.68 4.345183.60 2.71 -0.4405528.40 2.72 NIST -0.3935711.09 4.34 NIST -0.167 4.34 NIST -0.498 NIST -1.724 NIST 5889.95 0.00 0.1086160.75 NIST 2.10 -1.246 NIST Ion Mg I 4571.09 0.00 -5.623 NIST Al I 6696.02 3.14 -1.342 NIST 130 10 8 ... 7 ...... 14...... 12 ...... 15... 20 ... 10 ...... ) ˚ A (m λ ...... 9 ... 16 8 ...... W 1030 11 10 ... 12 2217 50371 22254 10186 9951 1344 ...... 22 24 40 30 25 50 20 60 28 ... 40 20 20 45 30 22 26 22 60 24 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6698.67 3.14 -1.643 NIST 5948.54 5.08 -1.230 KUR 5665.565684.48 4.925690.43 4.95 -2.0405701.10 4.93 KUR -1.6505708.40 4.93 KUR -1.8705772.15 4.95 KUR -2.0505793.07 5.08 KUR -1.470 4.93 KUR -1.7507034.90 KUR -2.060 5.87 KUR -0.880 KUR Ion Si I 5645.61 4.93 -2.140 KUR 131 ...... 122 118 ...... 3035 3582 4830 45 10040 46 4254 88 5278 42 80 55 95 69 92 120100 ... 115 128 120 ) ˚ A (m λ ...... W 5765 37 54 40 5880 40 50 65 160130 165 135 103 95 100142 90 110 2217 50371 22254 10186 9951 1344 85 88 80 90 55 190 155 115 112 120 155 ...... 90 85 55 193 165 135 110 140 158 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5581.975588.76 2.525590.12 2.53 -0.7105601.29 2.52 NIST 0.2105857.45 2.53 -0.710 NIST 6102.72 2.93 NIST -0.6906122.22 1.88 NIST 0.2306161.30 1.89 -0.790 NIST 2.52 NIST -0.315 NIST -1.030 NIST 7698.96 0.00 -0.168 NIST Ion K I 7664.90Ca I 0.00 5261.71 0.135 2.52 NIST -0.730 NIST 132 1835 2855 ... 30 6940 45 45 60 5575 5040 62 8480 42 ...73 84 100 ... 80 105 ... 118 124 130 108 105 108 ) ˚ A (m λ ...... W 304570 ...... 62 ... 5593 55 40 100 92 ... 150 ... 130 110 108 87 2217 50371 22254 10186 9951 1344 ... 65 90 92 92 170 110 145 100 125 130 62 90 90 90 180 110 155 115 120 135 108 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6166.44 2.52 -0.900 NIST 6449.81 2.52 -0.550 NIST 6162.17 1.90 -0.089 NIST 6169.046169.56 2.526439.07 2.53 -0.540 2.53 NIST -0.2706471.66 NIST 0.4706493.78 2.53 NIST 6499.65 2.52 -0.5907148.15 2.52 NIST 0.140 2.71 -0.590 NIST NIST 0.208 KUR Ion Sc II 5031.02 1.36 -0.260 KUR 133 ... 25... 30 ...... 30 ...... 5210 6370 1063 54 7520 ... 7028 76 25 55 3030 26 38 3540 30 40 40 ) ˚ A (m λ ...... 25 ...... W 60 50 8045 70 65 35 4555 42 40 45 100 85 2217 50371 22254 10186 9951 1344 ...... 75 22 85 50 55 65 55 55 96 ... 25 98 55 68 75 65 65 70 105 100 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5239.81 1.46 -0.770 KUR 6245.64 1.51 -1.130 CM05 5318.355526.79 1.365657.90 1.77 -2.0405667.15 1.51 KUR 0.1305669.04 1.50 -0.500 KUR 5684.20 1.50 KUR -1.240 1.51 KUR -1.1206604.60 KUR -1.050 1.36 KUR 4885.08 -1.480 1.89 KUR 0.358 NIST Ion Ti I 4840.87 0.90 -0.510 NIST 134 ...... 17 9725 10592 30 104 95 ... 13 25 9544 2052 95 4050 ... 5532 53 5434 62 50 ...... 50 50 ) ˚ A (m λ ...... 54 W 30 ... 3580 20 75 60 53 65 40 110 110 118115 85 100 2217 50371 22254 10186 9951 1344 ...... 70 75 140 145 140 115 115 106 100 ...... 70 90 80 150 150 150 105 115 120 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 4913.624981.73 1.87 0.85 0.161 NIST 0.504 NIST 4997.104999.51 0.005007.21 0.83 -2.1185009.65 0.82 NIST 0.2505016.16 0.02 NIST 0.1125020.03 0.85 -2.259 NIST 5022.87 0.84 NIST -0.5745024.84 0.83 NIST -0.4155036.47 0.82 NIST -0.434 1.44 NIST -0.602 NIST 0.130 NIST Ion 135 ...... 74...... 80 ...... 70 90 73 2384 ...76 76 ... 9815 78 98 ... 31 ) ˚ A (m λ ...... W 93 75 50 36 32 31 105 95 112113 88 90 2217 50371 22254 10186 9951 1344 45 57 57 92 32 82 65 120 130 140 135 40 60 56 50 95 70 135 145 100 150 155 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5039.95 0.025071.47 -1.1305113.44 1.46 NIST 5145.47 1.44 -1.0635147.48 1.46 NIST -0.783 0.00 NIST -0.574 NIST -2.012 NIST 5866.46 1.07 -0.840 NIST 5064.66 0.05 -0.991 NIST 5173.755210.39 0.005490.15 0.05 -1.118 1.46 NIST -0.8835899.32 NIST -0.933 1.05 NIST -1.154 NIST Ion 136 ...... 28 ...... 2217 2420 23 35 ... 20 65 28 603280 65 35 85 35 ... ) ˚ A (m λ ...... 35 W 323535 30 25 30 85 80 95 80 2217 50371 22254 10186 9951 1344 ...... 50 50 85 65 50 88 60 58 90 58 54 86 85 80 68 45 70 55 105 100 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5922.116126.22 1.056258.10 1.07 -1.465 1.44 NIST -1.424 NIST -0.355 NIST 7357.74 1.44 -1.1215005.18 NIST 1.57 -2.540 NIST 6261.107209.44 1.437251.72 1.46 -0.479 1.43 NIST -0.500 NIST -0.7704911.20 NIST 2.125129.15 -0.330 1.89 NIST -1.400 NIST Ion Ti II 4805.10 2.06 -1.120 NIST 137 6 ...... 106 105 ...... 25 ... 14 ... 7880 80 7480 75 70 ... 8560 7514 ... 71 72 15 70 14 ) ˚ A (m λ 8 ...... 75 ...... W 90 75 8882 70 22 65 35 ... 10 ...... 125100 103 84 2217 50371 22254 10186 9951 1344 ... 90 95 90 78 70 78 75 30 48 115 ... 85 78 85 35 62 105 100 132 112 100 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5185.915226.56 1.895336.81 1.57 -1.3505381.02 1.58 NIST -1.2905418.75 1.57 NIST -1.700 1.58 NIST -2.0804864.73 NIST -1.9994875.49 0.02 KUR 5670.85 0.04 -0.960 1.08 NIST -0.810 NIST -0.420 NIST 5154.07 1.57 -1.920 NIST 5698.52 1.06 -0.110 NIST Ion V I 4851.48 0.00 -1.138 NIST 138 ... 8 125 ... 10 8 65 ...... 12 ...... 10...... 16 ...... ) ˚ A (m λ 8 ... 6 ...... 9 ...... W 12 12 10 ... 2217 50371 22254 10186 9951 1344 ...... 35 45 48 35 40 65 35 28 35 ...... 60 35 40 80 50 35 43 40 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5703.576081.44 1.056090.22 1.05 -0.2116119.52 1.08 NIST -0.5786199.20 1.06 NIST -0.062 0.29 NIST -0.3206243.10 NIST -1.280 0.20 NIST 6274.65 -0.9806285.15 0.27 NIST 6292.83 0.28 -1.670 0.29 NIST -1.510 NIST -1.470 NIST 6216.37 0.286251.82 -1.290 0.29 NIST -1.340 NIST Ion 139 ... 80 78 ...... 4050 5075 6018 60 8075 70 2055 90 9092 30 7535 90 98 ... 35 102 35 135 140 135 ) ˚ A (m λ ...... W 607890 65 30 55 95 80 78 30 95 28 68 ... 155 130 110 105 2217 50371 22254 10186 9951 1344 85 50 40 120 200 100 115 130 130 120 145 ... 50 40 130 220 115 122 140 145 128 160 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5296.695298.27 0.985300.75 0.98 -1.4105345.81 0.98 NIST -1.1605348.31 1.00 NIST -2.1305409.78 1.00 NIST -0.980 1.03 NIST -1.2904876.47 NIST -0.720 3.86 NIST -1.470 NIST 5247.56 0.96 -1.630 NIST 5206.04 0.94 0.019 NIST Ion Cr II 4848.24 3.86 -1.130 NIST Cr I 4652.16 1.00 -1.030 NIST 140 6 10 8 ... 76 60 ...... 18 ...... 25 302572 25 ...75 70 ...... 70 80 12 15 15 ) ˚ A (m λ ...... W 2570 20 80 ... 80 65 65 28 26 2217 50371 22254 10186 9951 1344 ...... 75 35 55 28 70 30 24 115 ...... 40 78 40 60 25 40 22 115 125 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5237.33 4.07 -1.1604783.43 NIST 4823.52 2.305407.42 2.32 0.042 2.14 0.144 NIST -1.743 NIST NIST 5530.77 1.71 -2.060 NIST 4766.42 2.92 0.100 NIST 5420.365537.74 2.14 2.19 -1.460 NIST -2.0175647.23 CM05 2.28 -1.560 NIST Ion Mn I 4754.04 2.28 -0.085 NIST Co I 5483.34 1.71 -1.490 NIST 141 ...... 30...... 30 ... 30 ... 6035 6032 3550 70 4542 30 45 ... 4025 50 ... 4035 34 ... 40 ) ˚ A (m λ ...... 70 ...... 45 ...... 42 ... W 4346 43 62 46 50 4055 30 43 2217 50371 22254 10186 9951 1344 ...... 80 85 80 80 75 70 38 85 ... 14 78 82 95 85 84 50 98 105 105 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 4904.414980.16 3.545035.37 3.61 -0.1705080.52 3.64 NIST -0.1105578.72 3.66 NIST 0.2905587.86 1.68 NIST 0.1305592.26 1.94 -2.640 NIST 5748.35 1.95 NIST -2.1405754.68 1.68 NIST -2.590 1.94 NIST -3.260 NIST -2.340 NIST 6632.43 2.28 -2.000 NIST Ion Ni I 4714.42 3.38 0.230 NIST 142 ...... 6 ...... 14 ... 35 38 50 20 ...6542 24 68 6040 75 45 68 45 65 41 ... ) ˚ A (m λ ...... 65 ... W 5515 45 28 ... 90 ... 75 6075 40 68 2217 50371 22254 10186 9951 1344 ... 92 30 20 50 50 30 95 95 115 108 98 46 38 30 65 62 36 98 122 118 108 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 6108.12 1.686176.81 -2.4406177.25 4.09 NIST 6327.60 1.83 -0.530 1.68 NIST -3.5106643.63 NIST -3.150 1.68 NIST -2.3006914.56 NIST 1.95 -2.270 NIST 6128.97 1.68 -3.320 NIST 6586.31 1.956767.77 -2.8106772.32 1.83 NIST 3.66 -2.1707122.20 NIST -0.990 3.54 NIST 0.050 NIST Ion 143 ...... 12 ...... 28 30 5020 ...... 55 30 4037 4055 4555 ... 5045 40 50 52 45 55 42 ) ˚ A (m λ ...... 55 W 5635 ... 12 28 4040 10 50 30 60 40 70 45 60 40 55 35 2217 50371 22254 10186 9951 1344 ...... 88 80 60 65 80 75 65 65 88 85 26 60 60 65 75 90 90 75 70 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 7422.28 3.64 -0.130 NIST 5700.245782.13 1.64 1.64 -2.3124810.53 KUR -1.720 4.08 KUR 4883.68 -0.1374900.12 1.08 NIST 5087.42 1.03 0.0705200.41 1.08 -0.090 KUR 0.99 KUR -0.170 KUR -0.570 KUR Ion Cu I 5105.54 1.39Zn I -1.516 4722.15 KUR Y II 4.03 4854.86 -0.338 0.99 NIST -0.380 KUR 144 ...... 85 ... 62 ... 58 ... 10 ...... 10 12 ... 1017 12 ...... 18 120132 120 122 120 116 ) ˚ A (m λ ...... 13 W 1730 24 24 70 ... 251515 20 ...... 155150 140 135 2217 50371 22254 10186 9951 1344 ... 40 45 70 15 20 40 38 105 145 155 48 50 85 22 24 62 45 44 120 175 172 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5662.93 1.946141.71 0.160 0.70 KUR -0.0775303.53 She03 6390.48 0.32 0.32 -1.3505092.79 Law01 -1.4105212.36 0.38 Law01 0.20 -0.610 Den03 -0.960 Den03 5509.90 0.99 -1.010 KUR 6496.90 0.60 -0.380 She03 Ion Ba II 5853.68 0.60 -1.010 She03 Nd II 4959.12 0.06 -0.80 Den03 La II 4333.75 0.17 -0.060 Law01 145 9 12 9 ... 16 15 14 ...18 15 18 20 ) ˚ A (m λ W 162023 14 16 20 22 12 2217 50371 22254 10186 9951 1344 55 55 60 30 55 58 62 30 M13 M3 NGC 5024 NGC 5466 Table 11.15 (cont’d) (eV) log gf REF III-18 c41303 χ ) ˚ A ( λ 5293.16 0.82 0.100 Den03 5249.58 0.975319.82 0.200 0.55 Den03 -0.140 Den03 Note. — References: NIST = Ralchenko et al. (2008), KUR = Kurucz & Bell (1995), CM05 = Cohen Ion Eu II 6645.06 1.38 0.204 KUR & Melendez (2005), She03 == Shetrone Den et Hartog al. et (2003), al. Law01 (2003) = Lawler, Bonvallet & Sneden (2001), Den03 146

Table 11.16. Hyperﬁne Splitting Corrections for M13 III-18

Ion λ Wλ Ab Ab ∆ (A˚) (mA˚) (Wλ) (HFS)

Sc II 5318.35 25 1.96 1.96 0.00 5526.79 105 1.80 1.77 -0.03 5657.90 98 1.93 1.88 -0.05 5667.15 55 1.87 1.85 -0.02 5669.04 68 1.97 1.98 0.01 5684.20 75 2.07 2.01 -0.06 6245.64 65 1.90 1.86 -0.04 6604.60 65 2.03 2.01 -0.02 V I 4851.48 78 2.65 2.45 -0.20 4864.73 85 2.62 2.46 -0.16 4875.49 100 2.78 2.48 -0.30 5670.85 35 2.59 2.56 -0.03 5703.57 60 2.72 2.73 0.01 6081.44 35 2.66 2.65 -0.01 6119.52 40 2.50 2.50 0.00 6243.10 80 2.68 2.56 -0.03 6251.82 50 2.61 2.55 -0.06 6274.65 35 2.68 2.66 -0.02 6285.15 43 2.65 2.64 -0.01 Mn I 4762.37 90 3.68 3.46 -0.22 147

Table 11.16 (cont’d)

Ion λ Wλ Ab Ab ∆ (A˚) (mA˚) (Wλ) (HFS)

4783.43 120 3.94 3.57 -0.37 5537.74 28 3.93 3.86 -0.07 Co I 5530.77 40 3.63 3.56 -0.07 5647.23 22 3.51 3.49 -0.02 6632.43 14 3.64 3.63 -0.01 Cu I 5105.54 85 2.35 2.10 -0.25 5782.13 60 2.39 2.20 -0.19 Ba II 5853.68 120 1.09 1.05 -0.04 6141.71 175 1.20 1.17 -0.03 6496.90 172 1.24 1.16 -0.08 La II 5303.53 22 0.00 -0.02 -0.02 6390.48 24 0.02 0.01 -0.01 Eu II 6645.06 30 -0.36 -0.41 -0.05

Note. — Since M13 III-18 has the highest signal to noise, it also has the strongest lines and will therefore have the largest HFS corrections of all our program stars. Thus, these represent an upper limit to the HFS corrections for our target stars. All such corrections are insigniﬁcant (i.e. less than the standard deviation of the elemental abundance) except in the case of Mn I and Cu I and a few V I lines. HFS data from Prochaska et al. (2000) for Sc II, V I, Mn I, Co I, Cu I and Ba II, Lawler, Bonvallet & Sneden (2001) for La II, and Lawler et al. (2001) for Eu II. 148

Table 11.17. Mn I and Cu I Hyperﬁne Splitting Corrections for NGC 5024 50371

Ion λ Wλ Ab Ab ∆ (A˚) (mA˚) (Wλ) (HFS)

Mn I 4754.04 70 3.19 3.04 -0.15 4783.43 80 3.28 3.10 -0.18 4823.52 80 3.19 3.11 -0.08 Cu I 5105.50 35 1.60 1.56 -0.04 5782.13 12 1.53 1.51 -0.02

Note. — NGC 5024 50371 has a representative signal to noise and line strength for our target stars, and will thus also have representative HFS corrections. The total resultant abundance shifts are -0.14 for Mn and -0.03 for Cu. HFS data from Prochaska et al. (2000) for Mn I and Cu I. 149

Table 11.18. Metallicities, Ages, Horizontal Branch Parameters and Galactocentric Radii of Comparison Globular Clusters

Cluster ID [Fe/H] Age (Gyr) HBR hbt Rgc (kpc)

NGC 5024 -2.04 12.6 0.81 2 18.3 NGC 5466 -2.22 12.5 0.58 2 17.2 NGC 2298 -1.85 12.9 0.93 1 15.7 NGC 6397 -1.94 12.5 0.98 1 6.0 NGC 5897 -1.93 12.4 0.86 2 7.7 Arp 2 -1.85 11.5 0.86 2 21.4

Note. — Data from Salaris & Weiss (2002), except for NGC 5024 which is not included in that analysis. Data for this cluster is taken from Harris (1996), except for age which comes from De Angeli et al. (2005). 150

Table 11.19. Adopted Solar Abundances of Comparison Globular Cluster Studies

Element This worka McW92b ∆ Nor95c ∆ Cas00d ∆ Mot08e ∆

O 8.66 8.93 -0.27 8.89 -0.23 8.83 -0.17 8.69 -0.03 Na 6.17 6.33 -0.16 6.29 -0.12 6.33 -0.16 6.30 -0.13 Mg 7.53 7.58 -0.05 7.54 -0.01 7.58 -0.05 7.55 -0.02 Si 7.51 7.55 -0.04 7.51 0.00 7.55 -0.04 7.54 -0.03 Ca 6.31 6.36 -0.05 6.32 -0.01 6.36 -0.05 6.34 -0.03 Sc 3.05 3.10 -0.05 3.06 -0.01 3.17 -0.12 3.07 -0.02 Ti 4.90 4.99 -0.09 4.95 -0.05 5.02 -0.12 4.92 -0.02 V 4.00 4.00 0.00 3.96 0.04 4.00 0.00 4.00 0.00 Cr 5.64 5.67 -0.03 5.63 0.01 5.67 -0.03 5.65 -0.01 Fe 7.45 7.52 -0.07 7.46 -0.01 7.50 -0.05 7.51 -0.06 Co 4.92 4.92 0.00 ...... 4.92 0.00 4.91 0.01 Ni 6.23 6.25 -0.02 6.21 0.02 6.25 -0.02 6.22 0.01 Cu 4.21 4.21 0.00 4.17 0.04 4.21 0.00 4.26 -0.05 Y 2.21 2.24 -0.03 2.20 0.01 2.24 -0.03 2.20 0.01 Ba 2.17 2.13 0.04 2.09 0.08 2.13 0.04 2.18 -0.01 La 1.13 1.22 -0.09 1.18 -0.05 1.17 -0.04 1.18 -0.05 Nd 1.45 1.50 -0.05 1.46 -0.01 1.50 -0.05 1.46 -0.01 Eu 0.52 0.51 0.01 0.47 0.05 0.51 0.01 0.52 0.00

aAsplund, Grevesse & Sauval (2005) bMcWilliam, Geisler & Rich (1992) analysis of NGC 2298 used Anders & Grevesse (1989) except for Fe (in Anders & Grevesse the value is 7.67) cNorris & Da Costa (1995) analysis of NGC 6397 claimed they used Anders & Grevesse (1989), but their values are slightly diﬀerent (generally -0.04 dex) dCastilho et al. (2000) analysis of NGC 6397 used Grevesse & Sauval (1998) eMottini et al. (2008) analysis of Arp 2 used Lodders (2003) except for Fe (in Lodders the value is 7.47) 151

Table 11.20. Applied Shifts to Comparison Globular Cluster Abundances Due to Diﬀerences in Oscillator Strengths

Ion McW92 Nor95 Cas00 Gra87 Mot08

O I ... 0.00 +0.03 ... 0.00 Na I ... -0.03 +0.03 +0.08 ... Mg I 0.00 -0.02 +0.22 +0.22 -0.11 Si I 0.00 -0.10 +0.24 +0.20 0.00 Ca I -0.15 -0.29 -0.04 +0.15 -0.03 Sc II 0.00 +0.16 ...... Ti I 0.00 +0.16 0.00 +0.12 0.00 Ti II 0.00 -0.21 0.00 ... -0.02 V I 0.00 -0.19 ... +0.18 ... Cr I 0.00 -0.08 ... -0.12 0.00 Co I 0.00 0.00 ...... 0.00 Ni I 0.00 +0.09 ... +0.18 0.00 Cu I ... 0.00 ... -1.03 0.00 Y II 0.00 0.00 0.00 ... 0.00 Ba II 0.00 -0.01 +0.10 -0.54 0.00 La II -0.11 +0.15 ...... 0.00 Nd II ... -0.16 ...... -0.06 Eu II 0.00 +0.45 ...... 0.00