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On the Calibration and Use of Adaptive Optics Systems: RAVEN On the calibration and use of Adaptive Optics systems: RAVEN observations of metal-poor stars in the Galactic Bulge and the application of focal plane wavefront sensing techniques by Masen Lamb B.Sc., University of British Columbia, 2011 A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY in the Department of Physics and Astronomy c Masen Lamb, 2017 University of Victoria All rights reserved. This dissertation may not be reproduced in whole or in part, by photocopying or other means, without the permission of the author. ii On the calibration and use of Adaptive Optics systems: RAVEN observations of metal-poor stars in the Galactic Bulge and the application of focal plane wavefront sensing techniques by Masen Lamb B.Sc., University of British Columbia, 2011 Supervisory Committee Dr. Kim Venn, Co-Supervisor (Department of Physics and Astronomy) Dr. David Andersen, Co-Supervisor (Department of Physics and Astronomy) Dr. Patrick C^ot´e,Member (Department of Physics and Astronomy) Dr. Colin Bradley, Outside Member (Department of Mechanical Engineering) iii Supervisory Committee Dr. Kim Venn, Co-Supervisor (Department of Physics and Astronomy) Dr. David Andersen, Co-Supervisor (Department of Physics and Astronomy) Dr. Patrick C^ot´e,Member (Department of Physics and Astronomy) Dr. Colin Bradley, Outside Member (Department of Mechanical Engineering) ABSTRACT Adaptive optics holds a fundamental role in the era of thirty meter class telescopes; this technology has gained such import that is incorporated into all first light instru- ments of both the upcoming E-ELT and TMT telescopes. Moreover, each of these telescopes are planning to use advanced forms of adaptive optics to exploit unprece- dented scientific niches, such as Multi-Conjugate Adaptive Optics and Multi-Object Adaptive Optics. The complexity of these systems requires careful preliminary consid- erations, such as demonstration of the technology on existing telescopes and effective calibration procedures. In this thesis I address these two considerations through two different approaches. First, I demonstrate the use of the Multi-Object Adaptive Op- tics demonstrator RAVEN to gather high-resolution spectroscopy for the first time with this technology, and I identify some of the most metal-poor stars in the Galactic bulge to date. Secondly, I develop two focal plane wavefront sensing techniques to calibrate the internal aberrations of RAVEN and explore their applications to other adaptive optics systems. iv I analyze spectra of individual stars in two Globular Clusters to establish infrared techniques that can be used with the RAVEN instrument. Detailed chemical abun- dances for five stars in NGC 5466 and NGC 5024, are presented from high-resolution optical (from the Hobby-Eberley Telescope) and infrared spectra (from the SDSS- III APOGEE survey). I find [Fe/H] = -1.97 ± 0.13 dex for NGC 5466, and [Fe/H] = -2.06 ± 0.13 dex for NGC 5024, and the typical abundance pattern for globular clusters for the remaining elements, e.g. both show evidence for mixing in their light element abundance ratios (C, N), and asymptotic giant branch contributions in their heavy element abundances (Y, Ba, and Eu). These clusters were selected to examine chemical trends that may correlate them with the Sgr dwarf galaxy remnant, but at these low metallicities no obvious differences from the Galactic abundance pattern are found. Regardless, I compare my results from the optical and infrared analyses to find that oxygen and silicon abundances determined from the infrared spectral lines are in better agreement with the other α-element ratios and with smaller random errors. Using the aforementioned infrared techniques, I derive the chemical abundances for five metal-poor stars in and towards the Galactic bulge from the H-band spectroscopy taken with RAVEN at the Subaru 8.2-m telescope. Three of these stars are in the Galactic bulge and have metallicities between -2.1 < [Fe/H] < -1.5, and high [α/Fe] ∼ +0.3, typical of Galactic disc and bulge stars in this metallicity range; [Al/Fe] and [N/Fe] are also high, whereas [C/Fe] < +0.3. An examination of their orbits suggests that two of these stars may be confined to the Galactic bulge and one is a halo trespasser, though proper motion values used to calculate orbits are quite uncertain. An additional two stars in the globular cluster M22 show [Fe/H] values consistent to within 1σ , although one of these two stars has [Fe/H] = -2.01 ± 0.09, which is on the low end for this cluster. The [α/Fe] and [Ni/Fe] values differ by 2, with the most metal-poor star showing significantly higher values for these elements. M22 is known to show element abundance variations, consistent with a multipopulation scenario though our results cannot discriminate this clearly given our abundance uncertainties. This is the first science demonstration of multi-object adaptive optics with high-resolution infrared spectroscopy, and we also discuss the feasibility of this technique for use in the upcoming era of 30-m class telescope facilities. Lastly, I develop two focal plane wavefront sensing techniques to calibrate the non- common path aberrations (NCPA) in adaptive optics systems. I first demonstrate these techniques in a detailed simulation of the future TMT instrument NFIRAOS. v I then validate these techniques on an experimental bench subject to NFIRAOS- like wavefront errors. The two techniques are subsequently used to identify and correct the NCPA on both RAVEN and the NFIRAOS test-bench knowns as HeNOS. The application of these techniques is also explored on the VLT/SPHERE system to identify what is known as the `Low Wind Effect’ (LWE). I first quantify the LWE in simulation and then validate the technique on an experimental bench. I then estimate the LWE from on-sky data taken with the VLT/SPHERE adaptive optics system. Lastly, I apply my focal plane wavefront sensing techniques to estimate residual mirror co-phasing errors seen on Keck with the NIRC2 adaptive optics system data. I first demonstrate the ability of my techniques to quantify these errors in a simulation of Keck/NIRC2 data. I then apply their capabilities to estimate the mirror co-phasing errors of Keck with on-sky data. vi Contents Supervisory Committee ii Abstract iii Table of Contents vi List of Tables xi List of Figures xiii Acknowledgements xxx Dedication xxxi 1 Introduction 1 1.1 NIR data-analysis techniques: robustness and scientific applications . 1 1.2 Using RAVEN to search for Metal-Poor stars in the Galactic Centre . 3 1.3 Sensing and correcting internal aberrations in AO systems . 4 1.4 Summary . 7 2 Chemical abundances in the globular clusters NGC 5024 and NGC 5466 from optical and infrared spectroscopy 9 2.1 Introduction . 9 2.2 Observations and Data Reduction . 11 2.2.1 Observing Program . 11 2.3 Equivalent Width Analysis of Optical Spectra . 14 2.3.1 ∆EW ............................... 16 2.3.2 EW comparison with standard stars . 17 2.4 Model Atmosphere and Abundance Analysis of Optical Data . 17 2.4.1 Photometric Stellar parameters . 17 vii 2.4.2 Spectroscopic stellar parameters . 19 2.4.3 Stellar parameter uncertainties . 19 2.4.4 Comparison of stellar parameters and iron with the standard stars . 22 2.5 Abundance Analysis of Infrared Data . 22 2.6 Abundance Results . 24 2.6.1 Abundance errors . 24 2.6.2 Standard star comparison . 26 2.6.3 NGC 5024/5466 stars . 27 2.7 Discussion . 41 2.7.1 Infrared Abundance Comparison with Optical and Literature Abundances . 41 2.7.2 r and s-process contributions . 43 2.7.3 Evidence for Mixing . 43 2.7.4 NGC 5024/5466 origins . 45 2.8 Summary and Conclusions . 46 3 Using the multi-object adaptive optics demonstrator RAVEN to observe metal-poor stars in and towards the Galactic Centre 48 3.1 Introduction . 48 3.2 Observations and data reduction . 51 3.2.1 RAVEN technical details . 51 3.2.2 Performance and science observations . 53 3.2.3 Target selection . 54 3.2.4 Observing strategies with MOAO . 57 3.2.5 Data reduction . 61 3.3 Model atmospheres analysis . 62 3.3.1 Stellar parameters . 62 3.3.2 Stellar parameter uncertainties . 64 3.4 Abundance analysis . 64 3.4.1 Standard star comparison . 68 3.4.2 Abundance uncertainties . 69 3.5 Abundance results . 70 3.5.1 Iron . 72 3.5.2 Carbon and nitrogen . 72 viii 3.5.3 α-elements . 73 3.5.4 Other elements . 78 3.6 Stellar orbits . 80 3.6.1 Distances . 81 3.6.2 Proper Motions and Stellar Kinematics . 81 3.6.3 Orbits . 84 3.6.4 Comparison of the two methods . 85 3.7 Discussion . 85 3.7.1 M22 . 85 3.7.2 The Bulge Candidates . 88 3.8 Summary and Conclusions . 90 4 NCPA calibration methods: validation and application to RAVEN 92 4.1 Characterization of NFIRAOS-like NCPA in simulation . 92 4.1.1 Introduction . 92 4.1.2 Estimation methods . 93 4.1.3 Zernike Modes vs Disk Harmonics . 98 4.1.4 NFIRAOS example . 99 4.1.5 Simulated NFIRAOS NCPA discussion . 105 4.2 Characterization of NFIRAOS-like NCPA on an experimental bench . 106 4.2.1 Introduction . 106 4.2.2 Methods and observations . 107 4.2.3 Method evaluation . 111 4.2.4 Phase screen estimation and correction results . 117 4.2.5 Experimental NFIRAOS NCPA discussion . 120 4.3 Characterizing the NCPA on two AO systems: RAVEN and HeNOS . 125 4.3.1 RAVEN NCPA correction . 126 4.3.2 HeNOS NCPA characterization . 126 4.3.3 Discussion . 129 4.4 Summary and Conclusions . 129 5 Applications of Phase Diversity and Focal Plane Sharpening to VLT and Keck 131 5.1 Introduction .
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