Stacked Average Far-Infrared Spectrum of Dusty Star
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UC Irvine UC Irvine Electronic Theses and Dissertations Title The Interstellar Medium of Dusty Galaxies, Photometric Redshifts with Self-Organizing Maps, and Cosmic Infrared Background Fluctuations Permalink https://escholarship.org/uc/item/1fd5k82q Author Wilson, Derek Publication Date 2021 License https://creativecommons.org/licenses/by/4.0/ 4.0 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, IRVINE The Interstellar Medium of Dusty Galaxies, Photometric Redshifts with Self-Organizing Maps, and Cosmic Infrared Background Fluctuations DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Physics by Derek Nathaniel Diaz Wilson Dissertation Committee: Professor Asantha Cooray, Chair Professor Michael Cooper Professor David Kirkby 2021 Chapter 1 © 2017 The Astrophysical Journal Chapter 2 © 2020 The Astrophysical Journal All other materials © 2021 Derek Wilson DEDICATION To my family and friends ii TABLE OF CONTENTS Page LIST OF FIGURES v LIST OF TABLES vii ACKNOWLEDGEMENTS viii CURRICULUM VITAE x ABSTRACT OF THE DISSERTATION xii Chapter 1: Stacked Average Far-infrared Spectrum of Dusty Star-forming Galaxies from the Herschel/SPIRE Fourier Transform Spectrometer 1 Introduction 1 Data 3 Stacking Analysis 8 Stacking Results 14 Low-redshift stacks 23 Intermediate-redshift stacks 24 High-redshift stacks 25 Discussion 31 The CO SLED 31 Atomic and Molecular Line Ratios 33 PDR Modeling 51 Summary 60 Chapter 2: Photometric Redshift Estimation with Galaxy Morphology using Self- Organizing Maps 62 Introduction 62 Data 65 Redshift Measurement Algorithm 70 SOMs on Galaxies 76 Probability Distributions 82 Discussion 87 Summary 92 Chapter 3: Near- and Far-IR Cross-Power Spectra in the North Ecliptic Pole region with Spitzer and Herschel 94 iii Introduction 94 Data 95 Masking Point Sources 99 Angular Power Spectra 101 Mode-Coupling Matrix 104 Beam Correction 106 Transfer Function 108 Noise Estimate 109 Error Estimation 110 Final Power Spectra 112 Summary 122 Appendix to Chapter 1 123 Bibliography 133 iv LIST OF FIGURES Page Figure 1: FTS redshift and luminosity histograms. 5 Figure 2: Stacked FTS spectra, all data 16 Figure 3: Stacked FTS spectra, 0.005 < z < 0.05 17 Figure 4: Stacked FTS spectra, 0.05 < z < 0.2 18 Figure 5: Stacked FTS spectra, 0.2 < z < 0.5 19 Figure 6: Stacked FTS spectra, 0.8 < z < 2 20 Figure 7: Stacked FTS spectra, 2 < z < 4 21 Figure 8: Stacked FTS spectra, in luminosity bins 22 Figure 9: Fitting to atomic and molecular lines, 0.005 < z < 0.05 27 Figure 10: Fitting to atomic and molecular lines, 0.05 < z < 0.2 28 Figure 11: Fitting to [C II], 0.2 < z < 0.5. 29 Figure 12: Fitting to atomic and molecular lines, z > 2 30 Figure 13: CO spectral line energy distribution 33 Figure 14: H20 spectral line energy distribution 35 Figure 15: ISM conditions via neutral carbon ratios. 36 Figure 16: Line luminosity to total luminosity ratios. 41 Figure 17: (L[C II] + L[O I]) / LIR 43 Figure 18: L[O III] / L[C II] 44 Figure 19: L[O I] / L[C II] 45 Figure 20: [N II] luminosity relative to total IR luminosity. 46 Figure 21: PDR modelling at low redshifts 55 Figure 22: PDR modelling at high redshifts 56 Figure 23: PDR modeling results compared to the literature. 57 Figure 24: Spectroscopic redshift sample for SOMs 67 Figure 25: Example self-organizing map decomposition 75 Figure 26: Photo-z predictions using SOMs 80 Figure 27: Comparison of photo-z codes 81 Figure 28: Estimated redshift probabilities 83 Figure 29: Probability Integral Transform 85 Figure 30: Quantile-Quantile plot confidence test 86 Figure 31: SOM predictions with and without R50 89 Figure 32: Comparison of simulated R50 with real R50 data 90 Figure 33: Redshift uncertainty as a function of scatter in R50 91 Figure 34: Self-calibrated mosaics for each epoch taken with IRAC at 3.6 µm 98 Figure 35: Herschel NEP maps from the Herschel Science Archive 98 Figure 36: IRAC point-spread functions 100 Figure 37: Herschel SPIRE photometer point-spread functions 100 Figure 38: Masked Spitzer skymap 101 v Figure 39: Mode-coupling matrix on a logarithmic scale 105 Figure 40: Testing the mode-coupling matrix 106 Figure 41: Beam correction for each PSF 107 Figure 42: Mosaicking transfer functions for each Spitzer image at 3.6 µm 109 Figure 43: Combining multiple power spectra 112 Figure 44: Spitzer auto- and cross-spectra 113 Figure 45: Cross-power spectra of Spitzer 3.6 µm × Herschel 250, 350, and 500 µm 114 Figure 46: Cross-power spectra of Spitzer 4.5 µm × Herschel 250, 350, and 500 µm 114 Figure 47: Uncorrected correlation coefficients for Spitzer 3.6 µm × 4.5 µm. 117 Figure 48: Uncorrected correlation coefficients for Spitzer 3.6 µm × Herschel 250, 350, and 500 µm. 118 Figure 49: Uncorrected correlation coefficients for Spitzer 4.5 µm × Herschel 250, 350, and 500 µm. 118 Figure 50: Corrected correlation coefficients for Spitzer 3.6 µm × 4.5 µm. 119 Figure 51: Corrected correlation coefficients for Spitzer 3.6 µm × Herschel 250, 350, and 500 µm. 120 Figure 52: Corrected correlation coefficients for Spitzer 4.5 µm × Herschel 250, 350, and 500 µm. 121 Figure 53: Stacked spectra, 0.005 < z < 0.05 with inverse variance weighting 123 vi LIST OF TABLES Page Table 1: Fluxes of observed spectral lines in each redshift bin 47 Table 2: Fluxes in luminosity bins at 0.005 < z < 0.05 48 Table 3: Fluxes in luminosity bins at 0.8 < z < 4 49 Table 4: Uncorrected line ratios for high-redshift sources 50 Table 5: Uncorrected line ratios for low-redshift sources 50 Table 6: Features used for SOM training 68 Table 7: SOM performance metrics 77 Table 8: Photo-z code performance metrics 81 Table 9: Observation IDs and Integration Times 124 Table 10: Properties of sources in the stacks 128 vii ACKNOWLEDGEMENTS I would like to express my gratitude to my advisor, Professor Asantha Cooray, for his support and guidance over the duration of my graduate studies. I would also like to express my gratitude to my fellow graduate students and post- docs in the research group for their support and friendship. Thank you to Milad Pourrahmani, Hooshang Nayyeri, Hasitha Eranda, and Kevin Andrade for the insightful conversations. In addition, I would like to thank my committee members, Professor Michael Cooper, Professor David Kirkby, and Professor David Buote (advancement committee). A significant portion of the text in this dissertation is a reprint of the material as it appears in ”Stacked Average Far-infrared Spectrum of Dusty Star-forming Galaxies from the Herschel/SPIRE Fourier Transform Spectrometer” (ApJ, 848, 30) and “Photometric Redshift Estimation with Galaxy Morphology Using Self-Organizing Maps” (ApJ, 888, 83). Some of the co-authors listed in these publications directed and supervised research which forms the basis for the following dissertation. I would like to acknowledge the Astrophysical Journal for granting permission to reproduce my previously published works in this dissertation. A thank you as well to the co-authors who contributed to my published works: Asantha Cooray, Hooshang Nayyeri, Matteo Bonato, Charles Bradford, David Clements, Gianfranco De Zotti, Tanio Di̓az-Santos, Duncan Farrah, Georgios Magdis, Michał Michałowski, Chris Pearson, Dimitra Rigopoulou, Ivan Valtchanov, Lingyu Wang, Julie Wardlow, and Boris Häußler. I would like to make a few acknowledgements regarding funding, data, and scientific instruments used over my graduate career. Support for Chapters 1 and 2 was provided in part by NSF grant AST-1313319, NASA grant NNX16AF38G, GAANN P200A150121, HST- GO-13718, HST-GO-14083, and National Science Foundation Award #1633631. Support for Chapter 3 came partially from SPHEREx, CIBER, and a UCI Irvine Department of Physics Fellowship. I would thank Rodrigo Herrera-Camus, Eckhard Sturm, Javier Gracia-Carpio, and SHINING for sharing a compilation of [C II], [O III], and [O I] line measurements as well as FIR data to which I compare my results in Chapter 1. I also wish to thank Paul Van der Werf for the very useful suggestions and recommendations regarding Chapter 1. Concerning the scientific instruments used in my work, the Herschel spacecraft was designed, built, tested, and launched under a contract to ESA managed by the viii Herschel/Planck Project team by an industrial consortium under the overall responsibility of the prime contractor Thales Alenia Space (Cannes), and including Astrium (Friedrichshafen) responsible for the payload module and for system testing at spacecraft level, Thales Alenia Space (Turin) responsible for the service module, and Astrium (Toulouse) responsible for the telescope, with in excess of a hundred subcontractors. SPIRE has been developed by a consortium of institutes led by Cardiff University (UK) and including Univ. Lethbridge (Canada); NAOC (China); CEA, LAM (France); IFSI, Univ. Padua (Italy); IAC (Spain); Stockholm Observatory (Sweden); Imperial College London, RAL, UCL- MSSL, UKATC, Univ. Sussex (UK); and Caltech, JPL, NHSC, Univ. Colorado (USA). This development has been supported by national funding agencies: CSA (Canada); NAOC (China); CEA, CNES, CNRS (France); ASI (Italy); MCINN (Spain); SNSB (Sweden); STFC, UKSA (UK); and NASA (USA). HIPE is a joint development by the Herschel Science Ground Segment Consortium, consisting of ESA, the NASA Herschel Science Center, and the HIFI, PACS and SPIRE consortia. My research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. Chapter 2 contains work based on observations taken by the CANDELS Multi-Cycle Treasury Program with the NASA/ESA HST, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555.