# Evolution of galaxy dynamics as a function of their environment throughout the last 10 Gyr with MUSE-VLT

Wilfried Mercier

► To cite this version:

Wilfried Mercier. Evolution of galaxy dynamics as a function of their environment throughout the last 10 Gyr with MUSE-VLT. Physics [physics]. Université Toulouse 3 Paul Sabatier (UT3 Paul Sabatier), 2022. English. NNT: . tel-04079515

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Université
de Toulouse

THÈSE

En vue de l'obtention du

DOCTORAT DE L'UNIVERSITÉ DE TOULOUSE

Délivré par : l'Université Toulouse 3 Paul Sabatier (UT3 Paul Sabatier)

Présentée et soutenue le 30/11/2022 par :

Wilfried MERCIER

Évolution de la dynamique des galaxies en fonction de leur environnement
au cours des dix derniers milliards d'années avec MUSE-VLT

JURY

SOUCAIL GENEVIÈVE

FÖRSTER-SCHREIBER NATASCHA

PUECH MATHIEU

KRAJNOVIĆ DAVOR

SWINBANK MARK

JABLONKA PASCALE

CONTINI THIERRY

EPINAT BENOIT

Astronome

Scientifique senior

Astronome

Scientifique senior

Professeur

Professeur

Directeur de recherche CNRS

Astronome adjoint

Présidente

Rapporteur

Rapporteur

Examinateur

Examinateur

Examinateur

Directeur de Thèse

Co-directeur de Thèse

École doctorale et spécialité :

SDU2E : Astrophysique, Sciences de l'Espace, Planétologie

Unité de Recherche :

Institut de Recherche en Astrophysique et Planétologie (UMR 5277)

Directeur(s) de Thèse :

Contin Thierry et Epinat Benoit

Rapporteurs :

Förster-Schreiber Natascha et Puech Mathieu
<figure><img src="image_3.png" /></figure>
A mon grand-père
A qui cette Thèse est dédiée.
<figure><img src="image_4.png" /></figure>
Remerciements

Effectuer une thèse est un processus étrange dont rares sont ceux, à ma connaissance, qui en sont sortis intacts. Pour ma part, j'ai la chance de pouvoir dire que mon expérience a été incroyable. Les raisons sont certainement multiples mais certaines, évidentes, méritent d'être citées. Tout d'abord, il me semble clair, avec le recul, qu'on ne peut pas complètement réussir sa thèse sans l'aide d'un encadrement de grande qualité. Sur ce point, le mien a été irréprochable, à la fois dans les interactions professionnelles et personnelles, et je tiens à remercier encore une fois chaleureusement mes encadrants, Thierry et Benoît, pour ces quatre années passées avec eux. Un grand merci de m'avoir donné l'opportunité de travailler, d'apprendre et de mieux comprendre ce domaine si complexe qu'est l'astrophysique des galaxies, et en particulier leur dynamique à partir de données IFU que j'affectionne tout particulièrement. Merci également de m'avoir permis de développer ma recherche dans ce domaine et de m'avoir insufflé une rigueur et une certaine forme d'esprit critique vis-à-vis de son propre travail et de celui des autres; peut-être plus utile maintenant que jamais dans les temps qui courent. Un énorme merci également pour les opportunités inestimables de voyages et de rencontres qui m'ont été offertes lors de conférences, d'écoles ou d'autres évènements. Ma thèse a débuté sur le sommet de Paranal, peut-être ce soir-là où le vent s'était levé ; souvenirs oniriques de travailler, marcher, se baigner au milieu du désert chilien, observer un ciel nocturne étranger, voir pour la première fois les nuages de Magellan, d'un côté les montagnes, de l'autre l'océan. De même, avoir la possibilité de venir jusqu'à Hawaii, de travailler au CFHT, marcher sur des coulées de lave, se baigner en plein milieu du mois de Janvier, ou encore grimper au sommet du Mauna Kea; tout cela est inestimable. Encore une fois, merci infiniment !

Plus généralement, je tiens à remercier toutes les personnes avec qui j'ai pu échanger ou collaborer aux cours de ces dernières années, que ce soit à l'IRAP ou ailleurs. Plus spécifiquement, je souhaite remercier le consortium MUSE et ses membres pour m'avoir donné la chance de faire parti de cette superbe aventure et de m'avoir permis de rencontrer nombres de personnes incroyables qui, je suis sûr, se reconnaîtront en lisant ces lignes. Un remerciement particulier à Valentina avec qui nous avons collaboré depuis le tout début de mon stage sur MAGIC et avec qui cela a toujours été un plaisir de discuter. Au-delà du cadre de la recherche, je veut aussi remercier chaleureusement l'association "Les étoiles brillent pour tous", l'équipe en charge du module doctoral et en particulier mes acolytes, Léo et Merwan, pour ces supers moments passés ensemble. Merci également à mes deux ex-stagiaires, Hugo et Maxime, qui ont fourni tous les deux un travail remarquable, avec qui cela a toujours été un plaisir d'interagir et pour lesquels je souhaite un futur brillant.

Enfin, sur un plan plus personnel, je souhaite remercier ma famille, ainsi que ma copine sans qui tout cela n'aurait pu avoir lieu ou du moins qui se serait déroulé de manière totalement différente.
Tout d'abord, un grand merci à Lina d'avoir été et d'être restée là pendant tout ce temps, ainsi que d'avoir apporté beaucoup de joie et de bonne humeur, cela malgré la distance au départ et par la suite certains moments difficiles, incluant cet effroyable passage qu'est la rédaction du manuscrit. Un énorme merci à ma famille, en particulier mes parents et mes grands-parents qui m'ont fait confiance depuis de nombreuses années vis-à-vis de cet objectif un peu irréaliste qu'est d'obtenir une thèse en Astrophysique. Nul doute que tout cela aurait été immensément plus difficile sans leur soutien. Ainsi, au-delà d'un travail personnel évident, cette thèse est avant tout, à mon sens, un effort et une réussite collectifs. Malheureusement, tous n'auront pas été en mesure d'être là jusqu'au bout, mais je suis certain que chacun en tire néanmoins une grande fierté, peu importe où ils se trouvent. Pour conclure, un merci spécial à mon camarade, mon meilleur ami, mon "frérot" comme on dit dans la famille, et avec qui j'ai grandi, mon toutou Kirby.

Toulouse, le 09/02/2023

Wilfried Mercier
Abstract

Understanding the morphological and dynamical evolution of galaxies across cosmic time is one of
the key goals of modern extragalactic astrophysics. Our current view is that galaxies are objects
that evolve secularly and build their stellar mass through star formation which is sustained by
cold gas accretion from the cosmic web. However, this picture is not sufficient to explain entirely
their evolution. Environmental processes can also affect their morphology, kinematics, or gas
content, as well as quench star formation, and can thus be driving mechanisms to explain the
transition from high to low redshift. Thus, important recent efforts have been put into probing
the effect of the environment on galaxies. In this endeavour, 3D spectroscopy can help because it
provides spatially resolved properties across the galaxies' extent. MUSE is one of the most
powerful 3D spectrographs thanks to its large field-of-view and high sensitivity when combined
with adaptive optics.

During this Thesis, I have used data from the deep MUSE-gAlaxy Groups In Cosmos survey (MAGIC) which targets galaxy groups/clusters in the COSMOS field, as well as foreground and background field galaxies. MAGIC is ideal to probe the impact of the environment at $0.2 \le z \le 1.5$ for a large sample of galaxies with high completeness and down to low stellar masses ($M_* \approx 10^9 M_\odot$). From this survey, I modelled the morphology of about 900 galaxies by performing a bulge-disk decomposition to extract key morphological parameters (e.g. bulge-to-disk flux ratio, disk inclination, etc.) and the ionised gas kinematics from the MUSE cubes using the [O II] doublet as kinematics tracer and taking into account beam-smearing for 600 galaxies. I also integrated a mass modelling where I constrained the kinematics using prior information from the bulge-disk decomposition to recover more precise dark matter fractions.

This has allowed me to contribute to a first analysis of the Tully-Fisher relation at $z \sim 0.7$, followed by my first paper on the analysis of major scaling relations as a function of environment. From these works, I showed that galaxies are affected by their host structure at $z \sim 0.7$ in terms of morphology and star-formation rate but not in terms of their dynamics. I continued with another analysis of the impact of the environment on the galaxies' stellar angular momentum. The first results suggest that there is a visible impact of the environment on the angular momentum, mostly associated to massive galaxies found in the densest parts of the structures. Because these galaxies also host massive bulges, the current interpretation is that they have probably suffered from a depletion of angular momentum ($\sim 20\%$) by building up their bulge component while reaching the inner parts of the structures. Furthermore, I have also worked on the development of a new methodology that produces resolved stellar mass maps using pixel-per-pixel SED fitting techniques and a corresponding machine learning application that I am currently refining.

My Thesis has shown the powerful capabilities of MAGIC to probe the impact of the
environment on galaxy evolution. This effort will be pushed forward in the near future thanks to
already existing and new MUSE surveys such as the HUDF, MUSE-WIDE, MXDF, and MUSCATEL. For the latter, I will be able to produce the galaxies’ stellar mass maps and use them to get better constraints on the galaxies’ ionised gas kinematics and on their dark matter content. Furthermore, these new developments combined with my expertise in morpho-kinematics analyses will also be beneficial for future data from next-generation instruments with the JWST or ERIS-VLT and on the longer term with HARMONI and MOSAIC on the ELT.
# Résumé

Comprendre l'évolution morphologique et dynamique des galaxies au cours du temps cosmique est l'un des objectifs principaux de l'astrophysique extragalactique moderne. Notre compréhension actuelle est que les galaxies sont des objets qui évoluent séculairement et qui assemblent leur masse via la formation stellaire entretenue par l'accrétion de gaz froid de la toile cosmique. Cependant, cette image n'est pas suffisante pour expliquer entièrement leur évolution. Des processus environnementaux peuvent aussi affecter leur morphologie, cinématique et contenu en gaz, ainsi que supprimer leur formation stellaire, et donc jouer un rôle majeur pour expliquer la transition de haut à bas redshift. Ainsi, des efforts importants ont récemment été réalisés pour sonder l'effet de l'environnement sur les galaxies. Dans ce but, la spectroscopie 3D peut aider car elle procure des données spatialement résolues des propriétés physiques des galaxies. MUSE est l'un des spectrographes 3D les plus performants grâce à son grand champs de vue et sa haute sensibilité quand il est combiné avec l'optique adaptative.

Durant cette thèse, j'ai utilisé des données issues du relevé profond "MUSE gAlaxy Groups In Cosmos survey (MAGIC)" ciblant des groupes/amas de galaxies dans le champs COSMOS, ainsi que des galaxies d'avant et d'arrière plan. MAGIC est idéal pour sonder l'impact de l'environnement à $0.2 \le z \le 1.5$ pour un grand échantillon de galaxies avec une haute complétude et jusqu'à de faibles masses stellaires ($M_* \approx 10^9 M_\odot$). Parmi ces données, j'ai modélisé la morphologie d'environ 900 galaxies en réalisant une décomposition bulbe-disque afin d'extraire les paramètres principaux (ratio de flux bulbe-disque, inclinaison du disque, etc.) et la cinématique du gaz ionisé via les cubes MUSE en utilisant le doublet [O II] comme traceur cinématique et en prenant en compte l'effet du "beam smearing" pour 600 galaxies. J'ai aussi implémenté une modélisation de masse où j'ai contraint la cinématique en utilisant les informations issues de la décomposition bulbe-disque afin d'obtenir des fractions de matière noire plus précises.

Cela m'a permis de contribuer à une première analyse de la relation de Tully-Fisher à $z \sim 0.7$, suivie de mon premier papier sur l'analyse de plusieurs relations d'échelles majeures en fonction de l'environnement. A partir de ces travaux, j'ai montré que les galaxies sont affectées par leur structure à $z \sim 0.7$ au travers de leur morphologie et de leur formation stellaire mais pas de leur dynamique. J'ai poursuivi avec une autre analyse de l'impact de l'environnement sur le moment angulaire stellaire des galaxies. Les premiers résultats suggèrent qu'il y a un impact visible de l'environnement sur le moment angulaire, associé principalement aux galaxies massives localisées dans les zones les plus denses des structures. Etant donné que ces galaxies possèdent des bulbes massifs, l'interprétation actuelle est qu'elles ont probablement souffert d'une déplétion de leur moment angulaire ($\sim 20\%$) durant le processus de formation du bulbe alors qu'elles atteignaient les parties centrales des structures. Qui plus est, j'ai aussi travaillé au développement d'une nouvelle méthode pour produire des cartes de masse résolues via une technique de "SED fitting"
pixel par pixel et via une application de "machine learning" que j'affine actuellement.
Ma thèse a montré les capacités de MAGIC pour sonder l'effet de l'environnement sur l'évolution
des galaxies. Cet effort se poursuivra dans le future proche grâce à d'autre relevés MUSE
existants et à venir comme le HUDF, MUSE-WIDE, MXDF et MUSCATEL. Pour ce dernier,
j'aurai la possibilité de produire des cartes de masse résolues et de les utiliser pour mieux
contraindre la cinématique du gaz ionisé et la fraction de matière noire dans les galaxies. Ces
nouveaux développements combinés avec mon expertise dans les analyses morpho-cinématiques
seront aussi utiles pour de futures données issues d'instruments de prochaine génération avec le
JWST ou ERIS-VLT et sur le plus long terme avec HARMONI et MOSAIC sur l'ELT.
# Contents

<table><tr><td>Remerciements</td><td>i</td></tr><tr><td>Abstract</td><td>iii</td></tr><tr><td>Résumé</td><td>v</td></tr><tr><td>List of Figures</td><td>6</td></tr><tr><td>List of Tables</td><td>7</td></tr><tr><td>List of Codes</td><td>9</td></tr><tr><td>Notations and mathematical symbols</td><td>11</td></tr><tr><td>List of spectroscopic features</td><td>13</td></tr><tr><td>Foreword</td><td>15</td></tr><tr><td>Introduction en français</td><td>19</td></tr><tr><td>1 Introduction</td><td>23</td></tr><tr><td>1.1 Useful concepts of modern cosmology</td><td>23</td></tr><tr><td>1.1.1 The FLRW metric</td><td>24</td></tr><tr><td>1.1.2 The expansion of the Universe</td><td>25</td></tr><tr><td>1.1.3 Notion of redshift</td><td>26</td></tr><tr><td>1.1.4 Impact on astrophysical quantities</td><td>27</td></tr><tr><td>1.2 A concise history of our understanding of galaxies</td><td>29</td></tr><tr><td>1.2.1 The dawn of extragalactic astronomy</td><td>29</td></tr><tr><td>1.2.2 A quick march towards our current view of galaxies</td><td>30</td></tr><tr><td>1.2.3 Last steps towards modern extragalactic astrophysics</td><td>33</td></tr><tr><td>1.3 Galaxy evolution across cosmic time</td><td>35</td></tr><tr><td>1.3.1 Properties of local galaxies</td><td>35</td></tr><tr><td>1.3.2 Galaxies in the distant Universe</td><td>38</td></tr><tr><td>1.3.3 Impact of galaxies's environment</td><td>40</td></tr><tr><td>1.4 The Dark Matter enigma</td><td>43</td></tr><tr><td>1.4.1 Dark Matter or modified gravity?</td><td>44</td></tr></table>
<table>
  <tbody>
    <tr>
      <td>1.4.2</td>
      <td>Current questions regarding Dark Matter</td>
      <td>45</td>
    </tr>
    <tr>
      <td><b>2</b></td>
      <td><b>Spectroscopy in extragalactic astronomy</b></td>
      <td><b>47</b></td>
    </tr>
    <tr>
      <td>2.1</td>
      <td>Principles of spectroscopy</td>
      <td>48</td>
    </tr>
    <tr>
      <td>2.2</td>
      <td>The rise of Integral Field Spectroscopy</td>
      <td>49</td>
    </tr>
    <tr>
      <td>2.2.1</td>
      <td>Pioneering concepts: TIGER, OASIS, and SAURON</td>
      <td>49</td>
    </tr>
    <tr>
      <td>2.2.2</td>
      <td>First-generation instruments</td>
      <td>52</td>
    </tr>
    <tr>
      <td>2.2.3</td>
      <td>The MUSE revolution</td>
      <td>53</td>
    </tr>
    <tr>
      <td>2.2.4</td>
      <td>Miscellaneous current and next-generation instruments</td>
      <td>58</td>
    </tr>
    <tr>
      <td><b>3</b></td>
      <td><b>The MAGIC survey</b></td>
      <td><b>61</b></td>
    </tr>
    <tr>
      <td>3.1</td>
      <td>Survey design and observing strategy</td>
      <td>61</td>
    </tr>
    <tr>
      <td>3.2</td>
      <td>MUSE data and main survey properties</td>
      <td>64</td>
    </tr>
    <tr>
      <td>3.2.1</td>
      <td>MUSE data for the MAGIC sample</td>
      <td>64</td>
    </tr>
    <tr>
      <td>3.2.2</td>
      <td>Redshift determination</td>
      <td>65</td>
    </tr>
    <tr>
      <td>3.2.3</td>
      <td>Survey completeness</td>
      <td>68</td>
    </tr>
    <tr>
      <td>3.2.4</td>
      <td>PSF and LSF measurements</td>
      <td>69</td>
    </tr>
    <tr>
      <td>3.2.4.1</td>
      <td>LSF variation with wavelength</td>
      <td>71</td>
    </tr>
    <tr>
      <td>3.2.4.2</td>
      <td>PSF modelling</td>
      <td>71</td>
    </tr>
    <tr>
      <td>3.2.5</td>
      <td>Derivation of galaxies' physical parameters</td>
      <td>73</td>
    </tr>
    <tr>
      <td>3.2.5.1</td>
      <td>Early derivations with FAST</td>
      <td>73</td>
    </tr>
    <tr>
      <td>3.2.5.2</td>
      <td>Star formation rates from the [OII] doublet</td>
      <td>73</td>
    </tr>
    <tr>
      <td>3.2.5.3</td>
      <td>New derivation with CIGALE</td>
      <td>75</td>
    </tr>
    <tr>
      <td>3.2.5.4</td>
      <td>Comparison of physical parameters between the different modellings</td>
      <td>78</td>
    </tr>
    <tr>
      <td>3.3</td>
      <td>Structure identification and density estimation</td>
      <td>83</td>
    </tr>
    <tr>
      <td>3.3.1</td>
      <td>Structure identification with a FoF algorithm</td>
      <td>83</td>
    </tr>
    <tr>
      <td>3.3.2</td>
      <td>Local and global density estimators</td>
      <td>84</td>
    </tr>
    <tr>
      <td><b>4</b></td>
      <td><b>Morphological modelling</b></td>
      <td><b>87</b></td>
    </tr>
    <tr>
      <td>4.1</td>
      <td>Morphology of disk galaxies</td>
      <td>88</td>
    </tr>
    <tr>
      <td>4.1.1</td>
      <td>Sérsic model</td>
      <td>88</td>
    </tr>
    <tr>
      <td>4.1.2</td>
      <td>Sky projection: the curse of astrophysicists</td>
      <td>89</td>
    </tr>
    <tr>
      <td>4.1.2.1</td>
      <td>Projection for a razor-thin disk</td>
      <td>91</td>
    </tr>
    <tr>
      <td>4.1.2.2</td>
      <td>Projection of thick disks: the case of the double exponential disk</td>
      <td>92</td>
    </tr>
    <tr>
      <td>4.1.2.3</td>
      <td>From single to double exponential disk</td>
      <td>95</td>
    </tr>
    <tr>
      <td>4.2</td>
      <td>Impact of bulges</td>
      <td>97</td>
    </tr>
    <tr>
      <td>4.3</td>
      <td>Multi-component decomposition</td>
      <td>99</td>
    </tr>
    <tr>
      <td>4.3.1</td>
      <td>Bulge-disk decomposition</td>
      <td>99</td>
    </tr>
    <tr>
      <td>4.3.2</td>
      <td>Global effective radius</td>
      <td>101</td>
    </tr>
    <tr>
      <td>4.4</td>
      <td>Morphological modelling of galaxies in the MAGIC sample</td>
      <td>102</td>
    </tr>
    <tr>
      <td>4.4.1</td>
      <td>Modelling with GALFIT</td>
      <td>102</td>
    </tr>
    <tr>
      <td>4.4.2</td>
      <td>Automatic modelling for a large number of galaxies</td>
      <td>105</td>
    </tr>
  </tbody>
</table>
5 Dynamical modelling 109

5.1 Kinematics of a test particle 110

5.1.1 Kinematics in cylindrical coordinates 110

5.2 Mass modelling 111

5.2.1 Mass modelling for a kinematics tracer in a plane 112

5.2.2 Asymmetric drift correction 112

5.2.2.1 Asymmetric drift correction for thick disks 113

5.2.3 Circular velocity for a spherical distribution of mass 114

5.2.4 Examples of mass models 114

5.2.4.1 Hernquist bulge 115

5.2.4.2 Freeman's disk 115

5.2.4.3 Double exponential disk 116

5.2.4.4 NFW dark matter profile 118

5.2.4.5 Of the choice of DM profiles for dynamical models of intermediate redshift galaxies 118

5.3 Ionised gas kinematics with IFU data 122

5.3.1 Extraction of kinematics maps 122

5.3.1.1 Sub-cube extraction 122

5.3.1.2 Emission line fitting 123

5.3.1.3 Maps cleaning 124

5.3.2 Theory behind the kinematics modelling 125

5.3.2.1 Line-of-sight velocity 125

5.3.2.2 Instrumental impact on the velocity field 126

5.3.2.3 Instrumental impact on the velocity dispersion map 128

5.3.2.4 Brief comments on modelling the kinematics 129

5.3.3 Gas kinematics and dynamical modelling of the MAGIC sample 131

5.3.3.1 Contribution to MOCKING 131

5.3.3.2 Kinematics maps extraction 132

5.3.3.3 Dynamical modelling 133

6 Scaling relations in the MAGIC survey 137

7 Angular momentum in the MAGIC survey 173

8 Detailed study of dark matter 199

8.1 Resolved maps from multi-band HST photometry 200

8.1.1 Fundamental principles of SED fitting 206

8.1.1.1 Multi-band photometric observations 206

8.1.1.2 Key concepts: IMF, SSPs, SFH, and dust attenuation 208

8.1.1.3 Fitting galaxies' SEDs with LEPHARE and CIGALE 210

8.1.2 Application to resolved SED fitting 211

8.1.2.1 Pre-processing steps 211

8.1.2.2 Handling flux uncertainties 212

8.1.2.3 Pixel-per-pixel SED fitting with LEPHARE and CIGALE 214

8.1.3 A python library to easily produce resolved maps from pixel-per-pixel SED fitting 216
<table><tbody><tr><td>8.1.4</td><td>A quick look at the impact of resolved maps on morphological and kinematics models</td><td>221</td></tr><tr><td>8.2</td><td>Machine learning application with Self Organising Maps</td><td>224</td></tr><tr><td>8.2.1</td><td>A general overview of Self Organising Maps</td><td>224</td></tr><tr><td>8.2.1.1</td><td>Key concepts for the SOM</td><td>225</td></tr><tr><td>8.2.1.2</td><td>Learning phase</td><td>228</td></tr><tr><td>8.2.2</td><td>Using the SOM for predictions</td><td>229</td></tr><tr><td>8.2.3</td><td>Optimisation of the SOM</td><td>229</td></tr><tr><td>8.2.4</td><td>The need for a fast implementation</td><td>230</td></tr><tr><td>8.2.5</td><td>Current implementation of the SOM</td><td>231</td></tr><tr><td>8.2.6</td><td>First results and perspectives</td><td>232</td></tr><tr><td colspan="2">Concluding remarks and perspectives</td><td>237</td></tr><tr><td colspan="2">Conclusions et perspectives</td><td>241</td></tr><tr><td colspan="2">Observatories, instruments, and surveys</td><td>263</td></tr><tr><td colspan="2">Glossary</td><td>271</td></tr><tr><td colspan="2">Publication list</td><td>1</td></tr><tr><td colspan="2">Appendix A Major MUSE surveys</td><td>5</td></tr><tr><td>A.1</td><td>Main GTO MUSE surveys</td><td>5</td></tr><tr><td>A.2</td><td>Main non-GTO MUSE surveys</td><td>6</td></tr><tr><td colspan="2">Appendix B MAGIC field-of-views</td><td>9</td></tr><tr><td colspan="2">Appendix C Jeans' equations</td><td>25</td></tr><tr><td>C.1</td><td>From Boltzmann's to Jeans' equations</td><td>25</td></tr><tr><td>C.2</td><td>Jeans' equations in Cartesian coordinates</td><td>26</td></tr><tr><td>C.3</td><td>Jeans' equations in cylindrical coordinates</td><td>27</td></tr><tr><td>C.4</td><td>Isothermal sheet thickness profile</td><td>28</td></tr><tr><td colspan="2">Appendix D Impact of convolution on the variance</td><td>29</td></tr></tbody></table>
List of Figures

<table><tbody><tr><td>1.1</td><td>Examples of Hubble's galaxy types</td><td>31</td></tr><tr><td>1.2</td><td>Colour bimodality in the local Universe</td><td>36</td></tr><tr><td>2.1</td><td>Original design of the TIGER Integral Field Spectrograph</td><td>50</td></tr><tr><td>2.2</td><td>Examples of early velocity fields from TIGER, OASIS, and SAURON</td><td>51</td></tr><tr><td>2.3</td><td>Illustration of the field splitting and image slicing for MUSE</td><td>54</td></tr><tr><td>2.4</td><td>Illustration of a raw and processed MUSE observation</td><td>55</td></tr><tr><td>2.5</td><td>Redshift interval for the main spectral features detected with MUSE</td><td>56</td></tr><tr><td>3.1</td><td>Example of a MUSE observation in MAGIC</td><td>62</td></tr><tr><td>3.2</td><td>Examples of MUSE spectra</td><td>66</td></tr><tr><td>3.3</td><td>Redshift distribution of the MAGIC survey</td><td>67</td></tr><tr><td>3.4</td><td>Completeness of the MAGIC survey</td><td>69</td></tr><tr><td>3.5</td><td>Illustration of the fitting procedure for the MUSE PSF</td><td>70</td></tr><tr><td>3.6</td><td>Comparison between the different SFR estimates from CIGALE</td><td>76</td></tr><tr><td>3.7</td><td>Main Sequence and physical parameters for galaxies in MAGIC</td><td>79</td></tr><tr><td>3.8</td><td>Comparison between the stellar mass from CIGALE and that from FAST</td><td>80</td></tr><tr><td>3.9</td><td>Comparison of the MS relations built with different stellar masses and SFRs</td><td>81</td></tr><tr><td>4.1</td><td>Example of an azimuthally averaged surface brightness profile</td><td>88</td></tr><tr><td>4.2</td><td>Geometry for the sky projection of a disk</td><td>90</td></tr><tr><td>4.3</td><td>Projection of a double exponential disk</td><td>93</td></tr><tr><td>4.4</td><td>Impact of thickness on central surface brightness</td><td>95</td></tr><tr><td>4.5</td><td>Impact of a single Sérsic fit to a galaxy with a non-negligible bulge contribution</td><td>98</td></tr><tr><td>4.6</td><td>Flux distribution and B/T as a function of radius</td><td>100</td></tr><tr><td>4.7</td><td>Example of current summary file for GALFIT</td><td>105</td></tr><tr><td>5.1</td><td>Examples of various mass models</td><td>116</td></tr><tr><td>5.2</td><td>Impact of the DM choice on dynamical models</td><td>121</td></tr><tr><td>5.3</td><td>Illustration of the kinematics maps extraction with CAMEL</td><td>123</td></tr><tr><td>5.4</td><td>Illustration of the cleaning process for the kinematics maps</td><td>124</td></tr><tr><td>5.5</td><td>Illustration of the instrumental impact on the kinematics maps</td><td>127</td></tr><tr><td>8.1</td><td>First batch of HST images for the test sample used for resolved SED fitting</td><td>204</td></tr><tr><td>8.2</td><td>Second batch of HST images for the test sample for resolved SED fitting</td><td>205</td></tr></tbody></table>
<table><tr><td>8.3</td><td>HST filters' throughput used for the resolved SED modelling</td><td>206</td></tr><tr><td>8.4</td><td>Illustration of the impact of redshift and filters on a galaxy's SED</td><td>207</td></tr><tr><td>8.5</td><td>Examples of resolved stellar maps from LEPHARE and CIGALE</td><td>215</td></tr><tr><td>8.6</td><td>GALFIT fit for galaxy ID1 using a stellar mass map versus the F160W map.</td><td>221</td></tr><tr><td>8.7</td><td>MOCKING fit for galaxy ID1 using a stellar mass map versus the F160W map.</td><td>223</td></tr><tr><td>8.8</td><td>Illustration of the learning phase for SOMs</td><td>227</td></tr><tr><td>8.9</td><td>Example of a resolved stellar mass map using the SOM</td><td>233</td></tr><tr><td>8.10</td><td>Performance of the SOM with noisy data</td><td>234</td></tr><tr><td>B.1</td><td>MUSE observation for COSMOS group 23</td><td>10</td></tr><tr><td>B.2</td><td>MUSE observation for COSMOS group 26</td><td>11</td></tr><tr><td>B.3</td><td>MUSE observation for COSMOS group 28</td><td>12</td></tr><tr><td>B.4</td><td>MUSE observation for COSMOS group 30</td><td>13</td></tr><tr><td>B.5</td><td>MUSE observation for COSMOS group 32</td><td>14</td></tr><tr><td>B.6</td><td>MUSE observation for COSMOS group 34</td><td>15</td></tr><tr><td>B.7</td><td>MUSE observation for COSMOS group 35</td><td>16</td></tr><tr><td>B.8</td><td>MUSE observation for COSMOS group 51</td><td>17</td></tr><tr><td>B.9</td><td>MUSE observation for COSMOS group 61</td><td>18</td></tr><tr><td>B.10</td><td>MUSE observation for COSMOS group 79</td><td>19</td></tr><tr><td>B.11</td><td>MUSE observation for COSMOS group 84</td><td>20</td></tr><tr><td>B.12</td><td>MUSE observation for COSMOS group 87</td><td>21</td></tr><tr><td>B.13</td><td>MUSE observation for COSMOS group 114</td><td>22</td></tr><tr><td>B.14</td><td>MUSE observation for COSMOS group 172</td><td>23</td></tr></table>
# List of Tables

3.1 Summary of the main characteristics of each MUSE field from Epinat et al. (in prep.). 63

3.2 Models and grid of parameters for the SED modelling with CIGALE of galaxies in MAGIC. 77

8.1 Main characteristics of the test sample used for resolved SED fitting. 202

8.2 Zero point and PSF FWHM values for the HST bands. 212
List of Codes

<table><tr><td>4.1</td><td>Example of GALFIT FEEDME file.</td><td>104</td></tr><tr><td>4.2</td><td>Example of GALFIT CONSTRAINTS file.</td><td>104</td></tr><tr><td>4.3</td><td>GALFIT python wrapper code example.</td><td>107</td></tr><tr><td>5.1</td><td>Example of a CAMEL configuration file for galaxy 114_CGR79.</td><td>132</td></tr><tr><td>5.2</td><td>Example of a MOCKING configuration file for galaxy 114_CGR79.</td><td>135</td></tr><tr><td>8.1</td><td>First part of the example of a python script to perform SED fitting.</td><td>218</td></tr><tr><td>8.2</td><td>Second part of the example of a python script to perform SED fitting that is specific to LEPHARE.</td><td>219</td></tr><tr><td>8.3</td><td>Third part of the example of a python script to perform SED fitting that is specific to CIGALE.</td><td>220</td></tr></table>
Notations and mathematical symbols

Notation/Symbol Description

$\vec{\nabla}, \vec{\nabla}_{\vec{v}}$ Gradient with respect to spatial and velocity coordinates, respectively. The latter is used chiefly in Appendix C to compute Jeans' equations.

$f(\vec{x}, \vec{v}, t)$ Distribution function in phase space used to derive Jeans' equations.

$\overline{\sigma^2}$ Stress tensor appearing in Jeans' equations. Its diagonal terms correspond to the velocity dispersion squared along the three directions.

$\langle \vec{x} \rangle$ Average of vector $\vec{x}$ in velocity space given a distribution function $f$.

$\gamma, \Gamma$ Lower incomplete and complete gamma functions.

$R_{eff}$ Effective or half-light/half-mass radius, that is which encloses half of the total light/mass of the galaxy.

$R_d, R_{22}$ Disk scale length and radius of maximum rotation for a Freeman's disk. They are connected to the disk effective radius through the following relations: $R_d = R_{eff,d}/b_1$ and $R_{22} = 2.2R_d$ with $b_1 \approx 1.6783$.

$\rho, \rho_M$ 3D light and mass distribution, respectively.

$\Sigma, \Sigma_M$ Intrinsic surface brightness and mass surface density, respectively. This is the surface brightness of a galaxy seen face-on.

$\Sigma_{obs}$ Observed surface brightness. This is the surface brightness of a galaxy when projected on the sky.

$h(\vec{r})$ Thickness profile for thick disks. For a razor-thin disk $h(\vec{r}) = \delta(z)$.

$q, q_0$ Observed and intrinsic axis ratios. The former is the combination of both the intrinsic axis ratio and the projection effects of the galaxy on the plane of the sky.
<table><thead><tr><th>Notation/Symbol</th><th>Description</th></tr></thead><tbody><tr><td><i>i</i>, <i>i</i><sub>0</sub></td><td>Observed inclination derived from the observed axis ratio and intrinsic inclination. For a razor-thin disk <i>q</i> = cos <i>i</i> and <i>i</i> = <i>i</i><sub>0</sub>. An inclination of 0° (90°) corresponds to a face-on (edge-on) galaxy. For other geometries, the observed axis ratio must be corrected beforehand to compute the intrinsic inclination.</td></tr><tr><td><i>F</i>(<i>R</i>),<br><i>M</i>(<i>R</i>)</td><td>Flux and mass integrated in an aperture of radius <i>R</i>, respectively. The integration can be carried out from observations in a circular or elliptical aperture on the plane of the sky or from models in a sphere of radius <i>R</i>.</td></tr><tr><td><i>F</i><sub>λ</sub>, <i>F</i><sub>ν</sub></td><td>Flux density in units of wavelength or frequency.</td></tr><tr><td><i>D</i><sub>A</sub>, <i>D</i><sub>L</sub></td><td>Angular diameter and luminosity distances.</td></tr><tr><td><i>z</i>, <i>z</i><sub>c</sub>, <i>z</i><sub>sys</sub></td><td>Total, cosmological, and systemic redshift. The latter is associated to the bulk velocity of the galaxy along the line-of-sight when modelling their kinematics.</td></tr><tr><td>Φ</td><td>Gravitational potential.</td></tr><tr><td><i>V</i><sub>R</sub>, <i>V</i><sub>z</sub>, <i>V</i><sub>θ</sub>, <i>V</i><sub>c</sub></td><td>Radial, vertical, rotation and circular velocities, respectively. The circular velocity does not take into account the effect of asymmetric drift correction.</td></tr><tr><td><i>V</i><sub>ac</sub></td><td>Asymmetric drift correction that lowers the observed rotation velocity due to non streaming motions.</td></tr><tr><td><i>V</i><sub>θ,corr</sub></td><td>Asymmetric drift corrected rotation velocity.</td></tr><tr><td>σ<sub>V</sub>, σ<sub>R</sub></td><td>Velocity dispersion along the line-of-sight and along the radial direction, respectively.</td></tr><tr><td><i>V</i><sub>b</sub></td><td>Rotation velocity generated by a bulge mass distribution.</td></tr><tr><td><i>V</i><sub>RT</sub>, <i>V</i><sub>d</sub>, <i>V</i><sub>DE</sub></td><td>Rotation velocities generated by disk distributions. The first corresponds to a razor-thin disk, the second to a double exponential disk approximation, and the last to a double exponential disk corrected in the inner parts.</td></tr><tr><td><i>V</i><sub>h</sub></td><td>Rotation velocity generated by a DM halo.</td></tr><tr><td><i>f</i><sub>DM</sub></td><td>Fraction of DM with respect to the total mass of the galaxy.</td></tr></tbody></table>
List of spectroscopic features

[NII] Nitrogen two, two forbidden emission lines at 6548 Å and 6583 Å close to Hα. 51, 122

[OIII] Oxygen three, a group of forbidden emission lines whose brightest line is observed at 5007 Å produced by the transition of an electron in a doubly ionised oxygen atom. 51, 57, 60, 65, 71, 72, 122

[OII] Oxygen two, a bright doublet of emission lines observed at 3726 Å and 3729 Å produced by the transition of an electron in a singly ionised oxygen atom. 57, 60, 64, 65, 67–69, 71–74, 77, 78, 80, 82, 83, 87, 122, 124, 131–133, 137, 138, 201

[SII] Sulphur two, two forbidden emission lines at 6716 Å and 6731 Å redward of Hα. 122

Balmer break A sudden drop in flux shortward of 3646 Å due to completely ionised electrons from the second energy level of the hydrogen atom by photons with higher energy. 57, 65

[CIII] Carbon three, two UV semi-forbidden lines at 1907 Å and 1909 Å. 57

CaII H Second calcium-II doublet line, also known as Fraunhofer H line, a rest-frame violet absorption line at 3968 Å first observed by Joseph von Fraunhofer in the spectrum of the Sun. 57, 65

CaII K First calcium-II doublet line, also known as Fraunhofer K line, a rest-frame violet absorption line at 3933 Å first observed by Joseph von Fraunhofer in the spectrum of the Sun. 57, 65

D4000 The flux or flux density ratio between a red-wise and a blue-wise narrow band around a rest-frame wavelength of 4000 Å. 65

G-band A broad absorption line at 4301 Å caused by CH molecules and less significantly by iron. 57, 65

Hα H-alpha, a rest-frame red emission/absorption line of the Balmer series at 6562 Å due to the transition of an electron in an hydrogen atom from its third energy level to its second's. Its brightness, rest-frame wavelength, and relation to star forming regions make it an ideal tracer of star formation in galaxies. 33, 37, 44, 54, 57, 60, 65, 68, 73, 74, 122
Hβ H-beta, a rest-frame blue-green emission/absorption line of the Balmer series at 4861 Å due to the transition of an electron in an hydrogen atom from its fourth energy level to its second's. 51, 60, 65, 122

Hδ H-delta, a rest-frame violet emission/absorption line of the Balmer series at 4101 Å due to the transition of an electron in an hydrogen atom from its sixth energy level to its second's. 122

Hγ H-gamma, a rest-frame blue emission/absorption line of the Balmer series at 4341 Å due to the transition of an electron in an hydrogen atom from its fifth energy level to its second's. 122

Lyα Lyman alpha, a rest-frame ultraviolet emission line at 1215 Å due to the transition of an electron in an hydrogen atom from its second energy level to the ground level, discovered by Theodore Lyman, and observed in high redshift galaxies. 5, 6, 33, 57, 58, 64, 67–69

Lyman break A sudden drop in flux shortward of 911 Å due to higher energy photons being completely absorbed by neutral gas. 57, 65

MgII Magnesium two, a NUV resonant doublet at 2796 Å and 2803 Å. 6, 7, 57
# Foreword

This work is dedicated to the study of the morphological and dynamical evolution of galaxies across cosmic time with the help of the Multi-Unit Spectroscopic Explorer (MUSE). During these three years, my main focus has been to study the impact of the environment on the physical, morphological, and dynamical properties of galaxies in the MUSE-gAlaxy Groups In Cosmos (MAGIC) sample at intermediate redshift ($0.2 \le z \le 1.5$). MAGIC is a deep survey specifically designed to efficiently probe the impact of the environment on the dynamics of galaxies. Using this data combined with HST images, I have contributed to four papers, two of which have been published (Abril-Melgarejo et al. 2021; Mercier et al. 2022) and two are almost complete (analysis of the angular momentum discussed in Chapter 7 and the MAGIC survey paper in Chapter 3). These papers have allowed us to put the strongest constraints up to date on the impact of the environment at intermediate redshift on major scaling relations. In turn, these results provide insights into the interplay of the morphology and the dynamics of galaxies with their host environment.

Originally, the plan was to perform a first self-consistent analysis of the impact of the environment on the dynamics of galaxies in the MAGIC survey and then to apply the same method to the MUSE Cosmic Assembly survey Targeting Extragalactic Legacy fields (MUSCATEL) survey. However, due to social strikes across Chile and an unexpected pandemics across the globe, VLT operations had to shut down which has produced delays in the acquisition of MUSCATEL. Hence, the plan shifted towards a different trajectory. The new idea was to focus my efforts on MAGIC for the time being by improving our current methodology (i.e. implementing mass models, see Chapter 5) so that it would be ready when MUSECATEL would become available. These new developments shall be even more important for the next generation of integral field spectrographs that will provide spatially resolved kinematics observations with unprecedented resolution and sensitivity at high redshift.

In this manuscript, I provide a summary of all the work that I have carried out over the last three years, either alone or with the help of Master students whose internship I supervised (see Chapter 8). I start the discussion with an introduction that is split in two different chapters. In Chapter 1, I give a general overview of the current field of extragalactic astronomy. Because I feel that one cannot completely grasp the modern questions that are tackled by current research without keeping in mind the historical development of the field and of its ideas, I give, after a brief discussion about cosmology, a quick historical overview of the development of extragalactic astrophysics from its very beginning up to this day. In Chapter 2, I rather focus on the instrumental side by discussing the development of integral field spectroscopy. In particular, I discuss in details the main instrument that I have been using, MUSE, and also a few other similar instruments currently operational or that shall become so in the near- or mid-term future.
Because this work has relied so far entirely on MAGIC, I give a thorough description of the survey design and of the characteristics of the data. In Chapter 3, I provide the key characteristics of the survey (redshift determination, completeness, Point Spread Function, Line Spread Function, structure identification, etc.) and I give a first quick discussion of the physical properties of the sample of galaxies at $z < 1.5$. Then, I switch to more theoretical aspects in Chapters 4 and 5 where I present the methodology used to model the morphology and the kinematics of intermediate redshift galaxies in MAGIC. For the morphological modelling, I focus on the bulge-disk decomposition used in the analysis of the scaling relations (see Chapter 6) and of the angular momentum (see Chapter 7) where I emphasise the importance of such a decomposition for galaxies with massive bulges. I also present a python code that I developed at the beginning of my Thesis to automatise the morphological modelling performed with GALFIT. For the kinematics part, I discuss the theory behind the mass models that I incorporated and used for the first time in the kinematics fitting tool MOCKING. I also discuss how I fitted the galaxies' resolved kinematics starting from the MUSE cubes and how I took instrumental effects such as beam smearing into account to recover the galaxies' intrinsic rotation and velocity dispersion. As mentioned previously, Chapters 6 and 7 present the two main analyses that I have carried out during this Thesis. The first chapter includes my published analysis of three scaling relations (Main Sequence relation, size-mass relation, and Tully Fisher relation) as a function of environment in the MAGIC survey and the second chapter includes a still ongoing but nearly finished analysis of the angular momentum in MAGIC using a novel approach that combines our best-fit kinematics models from Mercier et al. (2022) with high-resolution HST images to get the most accurate angular momentum estimate for a large sample with our current dataset. In the last chapter of this Thesis (see Chapter 8) I present ongoing developments regarding the production of spatially resolved maps of physical parameters (e.g. stellar mass or star formation rate - SFR) using pixel-per-pixel spectral energy distribution fitting (see Sect. 8.1) and using machine learning techniques (see Sect. 8.2). In both cases, I discuss the maturity of the method at the moment, the difficulty we have encountered and the solutions that we have proposed, and I show a few examples of current results before mentioning future applications. Finally, I finish this manuscript by mentioning the perspectives of this work in the near-future with plans for further analyses in MAGIC and MUSECATEL, as well as further improvements of our method in preparation for next-generation integral field spectrographs installed on the future Extremely Large Telescopes such as HARMONI or MOSAIC.

In parallel to the work described in this Thesis, I have also contributed throughout the last three years to a few additional analyses as co-author (see the list of publications for a short description of my contribution). First, I have contributed at the beginning of this Thesis mainly on the sample selection and on the galaxies' morphology in the first analysis of the Tully-Fisher relation in MAGIC (Abril-Melgarejo et al. 2021). My second important contribution, still in MAGIC, is concerning the survey paper (Epinat et al., in prep.). This includes mainly the MUSE point spread function modelling and characterisation as a function of the observed wavelength and all the work related to the modelling and the morphology and kinematics of the [O II] emitters in the sample (bulge-disk decomposition, [O II] fluxes measurements, kinematics mass modelling, [O II] star formation rates, etc.). I have also contributed to other analyses that use MUSE data apart from MAGIC that are related to my field of expertise. Among these, I can cite my short contributions to the analyses of the ionised gas angular momentum in the HUBBLE Ultra Deep Field in Bouché et al. (2021) and of the impact of gas flows on the mass-metallicity and the SFR-mass-metallicity relations (Langan et al., in prep.), and my more significant contributions to
the measurements of spectroscopic redshifts for a large sample of galaxies in a survey covering massive lensing clusters (Richard et al. 2021) and to the morphological modelling of the nine $z \sim 1$ star-forming galaxies in the MUSE Extreme Deep Field for which we constrained the shape of their dark matter profile (Bouché et al. 2022).
# Introduction (foreword in French)

Ce travail est dédié à l'étude de l'évolution morphologique et dynamique des galaxies au cours du temps cosmique avec l'aide de l'instrument « Multi-Unit Spectroscopic Explorer » (MUSE). Durant ces trois années, mon attention s'est portée sur l'étude de l'impact de l'environnement sur les propriétés physiques, morphologiques et dynamiques des galaxies dans le relevé « MUSE-gAlaxy Groups In Cosmos » (MAGIC) à redshift intermédiaire ($0.2 \le z \le 1.5$). MAGIC est un relevé profond conçu spécifiquement pour sonder efficacement l'impact de l'environnement sur la dynamique des galaxies. A l'aide de ces données combinées avec des images HST, j'ai contribué à quatre articles, dont deux ont été publiés (Abril-Melgarejo et al. 2021; Mercier et al. 2022) et deux sont quasiment terminés (analyse du moment angulaire discutée au Chapitre 7 et description du relevé MAGIC au Chapitre 3). Ces articles nous ont permis de poser les plus fortes contraintes à ce jour sur l'impact de l'environnement à redshift intermédiaire sur plusieurs relations d'échelles majeures des galaxies. En conséquence, ces résultats nous renseignent sur les interactions entre la morphologie et la dynamique des galaxies avec leur environnement.

Le plan initial était d'effectuer une première analyse auto-cohérente de l'impact de l'environnement sur la dynamique des galaxies dans le relevé MAGIC, puis d'appliquer la même méthode pour le nouveau relevé « MUSE Cosmic Assembly survey Targeting Extragalactic Legacy fields » (MUSCATEL). Cependant, suite à des manifestations au Chili et à l'arrivée inattendue d'une pandémie mondiale, les opérations du VLT ont dû être arrêtées ce qui a produit des délais dans l'acquisition de MUSCATEL. De fait, le plan s'est orienté vers un objectif différent. La nouvelle idée était de concentrer mes efforts sur MAGIC en améliorant notre méthodologie (c'est-à-dire d'implémenter des modèles de masse, voir Chapitre 5) de telle sorte que cela serait prêt quand les données MUSCATEL deviendraient disponibles. Ces nouveaux développements seront d'autant plus importants pour la prochaine génération de spectrographes à intégrale de champs qui fourniront des observations cinématiques spatialement résolues avec une résolution et une sensibilité à haut redshift inégalées.

Dans ce manuscrit, je résume le travail que j'ai effectué au cours des ces trois dernières années, soit seul, soit avec l'aide d'étudiants en Master donc j'ai supervisé les stages (voir Chapitre 8). Je commence par une introduction séparée en deux chapitres différents. Dans le Chapitre 1, je donne une vue d'ensemble du champs de recherche actuel qu'est l'astronomie extragalactique. Parce que je considère qu'on ne peut pas complètement appréhender les questions modernes qui sont étudiées par la recherche actuelle sans avoir en tête les développements historiques de la discipline et de ses idées, je fourni, après une brève introduction à la cosmologie, un résumé rapide du développement de l'astrophysique extragalactique depuis son commencement jusqu'à aujourd'hui. Dans le Chapitre 2, je me concentre plutôt sur le côté instrumental en discutant le développement de la spectroscopie à intégrale de champs. En particulier, je discute en détails l'instrument principal
que j'ai utilisé, MUSE, ainsi que quelques autres instruments actuellement opérationnels ou qui le
seront à court ou moyen terme. Parce que ce travail n'aurait pas pu avoir lieu sans MAGIC, je
fourni une description détaillée du relevé. Dans le Chapitre 3, je donne les caractéristiques
principales du relevé (détermination des redshifts, complétude, fonction d'étalement du point -
PSF, fonction d'étalement de la raie, identification des structures, etc.) et je fourni une discussion
rapide des propriétés physiques de l'échantillon de galaxies à z < 1.5. Ensuite, je me concentre sur
des aspects plus théoriques dans les Chapitres 4 et 5 où je présente la méthodologie utilisée pour
modéliser la morphologie et la cinématique des galaxies à redshift intermédiaire dans MAGIC.
Pour la modélisation morphologique, je me concentre sur la décomposition bulbe-disque utilisée
dans l'analyse des relations d'échelles (voir Chapitre 6) et du moment angulaire (voir Chapitre 7)
où je mets en avant l'importance d'une telle décomposition pour des galaxies avec des bulbes
massifs. Je présente aussi un code python que j'ai développé au tout début de ma Thèse et qui
automatise la modélisation morphologique faite avec GALFIT. Concernant la partie cinématique,
je discute la théorie derrière les modèles de masse que j'ai incorporés et utilisés pour la première
fois dans le code d'ajustement cinématique MOCKING. Je discute aussi comment j'ai ajusté la
cinématique résolue des galaxies à partir des cubes de données MUSE et comment j'ai pris en
compte les effets instrumentaux comme le « beam-smearing » pour obtenir la rotation et la
dispersion de vitesse intrinsèques des galaxies. Comme mentionné précédemment, les Chapitres 6
et 7 présentent les deux analyses principales que j'ai effectué durant cette Thèse. Le premier des
deux chapitres inclut mon analyse publiée de trois relations d'échelles (séquence principale,
relation masse-taille et relation de Tully-Fisher) en fonction de l'environnement dans le relevé
MAGIC, et le second inclut une analyse quasiment terminée du moment angulaire dans MAGIC
en utilisant une approche novatrice qui combine nos modèles cinématiques issus de Mercier et al.
(2022) avec les images à haute resolution HST pour obtenir l'estimation la plus précise du
moment angulaire pour un grand échantillon de galaxies. Dans le dernier chapitre de cette Thèse
(voir Chapitre 8), je présente des développements en cours concernant la construction de cartes de
paramètres physiques (ex : masse stellaire, ou taux de formation stellaire - SFR) spatialement
résolue à l'aide d'une technique d'ajustement de distribution d'énergie spectrale pixel par pixel
(voir Sect. 8.1) et d'une application d'apprentissage machine (voir Sect. 8.2). Dans les deux cas, je
discute de la maturité des méthodes dans leurs états actuels, des difficultés rencontrées et des
solutions qui ont été proposées. Je montre aussi quelques exemples de résultats avant de
mentionner les applications futures. Finalement, je termine ce manuscrit en discutant les
perspectives de ce travail dans le futur proche avec mes plans pour de nouvelles analyses avec
MAGIC et MUSCATEL, ainsi que de futures améliorations de notre méthode en préparation de
la prochaine génération de spectrographes à intégral de champs qui seront installés sur les
télescopes extrêmement grands tel que HARMONI ou MOSAIC.

En parallèle du travail décrit dans cette Thèse, j'ai aussi contribué au cours de ces trois dernières
années à plusieurs analyses supplémentaires en tant que co-auteur (voir la liste de publications
pour une courte description de ma contribution). En premier lieu, j'ai contribué au tout début de
cette Thèse à la sélection de l'échantillon ainsi qu'à la caractérisation de la morphologie des
galaxies lors de la première analyse de la relation de Tully-Fisher dans MAGIC (Abril-Melgarejo
et al. 2021). Ma seconde contribution importante, toujours en rapport avec MAGIC, concerne le
papier décrivant le relevé (Epinat et al., in prep.). Cela inclut principalement la modélisation et la
caractérisation de la PSF de MUSE en fonction de la longueur d'onde observée, ainsi que tout ce
qui touche à la modélisation morphologique et cinématique des émetteurs [OII] dans l'échantillon
(décomposition bulbe-disque, mesure des flux [OII], modélisation de masse, taux de formation
stellaire [O II], etc.). J'ai aussi contribué à d'autres analyses qui utilisent des données MUSE au-delà de MAGIC et qui sont en rapport avec mon domaine d'expertise. Parmi celles-ci, je peux citer d'abord mes contributions mineures aux analyses du moment angulaire du gaz ionisé dans le « HUBBLE Ultra Deep Field » de Bouché et al. (2021) et de l'impact de l'accrétion et de l'éjection de gaz dans les galaxies sur les relations de masse-métallicité et de SFR-masse-métallicité (Langan et al., in prep.). Ensuite, je peux mentionner mes contributions plus importantes sur la mesure des redshifts spectroscopiques pour un grand échantillon de galaxies dans un relevé ciblant des amas de galaxies avec de forts effets de lentille gravitationnelle (Richard et al. 2021) et sur la modélisation morphologique de neufs galaxies à formation d'étoiles à $z \sim 1$ dans le relevé « MUSE Extreme Deep Field » pour lesquelles nous avons pu contraindre les profils de halo de matière noire (Bouché et al. 2022).
# Chapter 1

## A quick introduction to galaxy morpho-dynamical evolution

Extragalactic astrophysics is a complex field of research with many specialities. This Thesis is mainly concerned with the dynamical evolution of galaxies across cosmic time but, to understand it plainly, one must relate it to the evolution of other key aspects related to galaxies such as their morphology or physical properties. Besides, our understanding of galaxy evolution has tremendously changed throughout the last century and it is therefore enlightening to remind ourselves where this field of research stood one hundred years ago and to compare it where it is now. Hence, in this Chapter, I provide an overview of our current understanding of galaxy evolution.

I start with a short theoretical section concerning the cosmological context in extragalactic astrophysics. In particular, Sect. 1.1 allows me to write down the important cosmological concepts that are linked to observational extragalactic astrophysics (e.g. redshift, fluxes, distance measurements, etc.) and that are used throughout this Thesis. In Sect. 1.2, I proceed with a relatively condensed summary of the historical developments that led to our modern view of galaxies. In Sect. 1.3, I describe our current understanding of galaxy properties and their evolution across cosmic time, separating those found in the local Universe in Sect. 1.3.1 from high-redshift galaxies in Sect. 1.3.2, and from the impact of their host environment in Sect. 1.3.3. Finally, I conclude this chapter by quickly mentioning in Sect. 1.4 the current evidence and questions regarding the presence of Dark Matter (DM) in galaxies and galaxy clusters.

### 1.1 Useful concepts of modern cosmology

Galaxies are objects embedded in a Universe evolving with cosmic time. In order to study the evolution of their intrinsic properties such as their shape, mass, size, stellar populations, amount of cold gas, etc., we need to take into account the impact of our Universe's cosmology on these properties. The goal of this Thesis is to study the dynamical evolution of galaxies and not to use them as tracers of our cosmological model. Therefore, I will not give a detailed account of the underlying principles and derivations of the current cosmological model. Instead, I will focus on how the current Λ Cold Dark Matter (ΛCDM) cosmological model impacts measurements of key
physical quantities useful for my analysis (e.g. distance, size, luminosity, etc.).

### 1.1.1 The FLRW metric

Modern cosmology is built on the foundations of General Relativity (GR) even though a similar solution, though not behaving precisely in the same way, could also be derived in the framework of classical mechanics. In order to understand how the Universe evolves and how it affects galaxies' properties, one needs to find an expression of curvature of space-time encapsulated in its metric. In GR the metric is described as a second-rank tensor $g_{\mu\nu}$ which can be thought of as a matrix with two dimensions. Because the framework of GR is in four-space (time plus spatial three-space) the metric has 16 components that reduces to ten because it is symmetric ($\forall \mu, \nu, g_{\mu\nu} = g_{\nu\mu}$). A common way to write it is through the line element $ds$ that describes an infinitesimal displacement along all directions (including time): $ds^2 = g_{\mu\nu}dx^\mu dx^\nu$, where I have used Einstein's summation convention where an implicit sum is to be understood when the same symbol appears as a subscript and superscript in a product. For instance, in 3D Euclidian geometry, the metric writes $ds^2 = dx^2 + dy^2 + dz^2$ whereas on a two-sphere it rather writes $ds^2 = R^2d\theta^2 + R^2\sin^2\theta d\phi^2$ where $R$ is the radius of curvature of the sphere and $(\theta, \phi)$ are the usual spherical coordinates. The two key hypotheses at the basis of our modern $\Lambda$CDM cosmological model are the homogeneity and isotropy of the Universe which are summarised in the cosmological principle that states that we are not located at any special location in our Universe. A typical evidence supporting such hypotheses at least to first order is the large homogeneity of the Cosmic Microwave Background (CMB). If we further assume that there exists a set of fundamental observers whose motion makes them always see the Universe as isotropic and that are equipped with clocks measuring the same proper time called cosmic time, then the metric in a curved, homogeneous, isotropic, and expanding Universe becomes the Friedmann-Lemaître-Robertson-Walker metric (FLRW) that writes (e.g. Longair 2008)

$$ds^2 = dt^2 - \frac{a^2(t)}{c^2} \left[ dr^2 + R_c^2(t_0) \sin^2\left(\frac{r}{R_c(t_0)}\right) (d\theta^2 + \sin^2\theta d\phi^2) \right] \\ = dt^2 - \frac{a^2(t)}{c^2} \left[ \frac{dr_1^2}{1 - \kappa r_1^2} + r_1^2 (d\theta^2 + \sin^2 d\phi^2) \right], \qquad (1.1)$$

where $c$ is the speed of light, $t$ is the aforementioned cosmic time, $R_c(t_0)$ is the curvature of space-time at present time $t_0$, $r$ is the comoving distance along the line-of-sight (LOS), that is the distance from us not taking into account the expansion of the Universe, $a(t)dr$ is the infinitesimal element of proper distance (also called physical distance) along the LOS at time $t$ (i.e. taking into account the expansion of the Universe), and $a(t)r_1d\theta$ and $a(t)r_1\sin\theta d\phi$ are the elements of proper distance at time $t$ along the two perpendicular directions with respect to the LOS. The second expression is a bit more common than the first one and is obtained by defining a new proper length $r_1 = R_c(t_0)\sin(r/R_c(t_0))$ and the Gaussian curvature of space-time $\kappa = 1/R_c^2(t_0)$. In both expressions $a(t)$ is a unitless scale factor that encompasses the expansion of the Universe, that is it tells us how to convert a comoving distance into a physical one and vice versa. A common convention is to set $a(t_0) = 1$, that is the scale factor of the Universe is unity at present time. As an indication, I note that in Eq. 1.1 $r$ and $r_1$ have units of distances but there exists another convention for which the transformation $|\kappa|r_1^2 \rightarrow r_1^2$ is applied to Eq. 1.1 so that $a(t)$ becomes
$R(t) = a(t)R_c(t_0)$ and $\kappa$ becomes $k \in \{-1, 0, 1\}$. When $k = -1, 0$, and $1$ the geometry is said to be hyperbolic, flat, and spherical, respectively.

1.1.2 The expansion of the Universe

Equation 1.1 provides us with the geometry of space-time but it does not tell us anything about how the structure of the Universe evolves with time. To know how fast the Universe expands or contracts we need to derive the expression for the scale factor $a(t)$. This is only possible using the 16 Einstein's equations that write

$$R_{\mu\nu} - \frac{1}{2}g_{\mu\nu}R + \Lambda g_{\mu\nu} = -\frac{8\pi G}{c^2}T_{\mu\nu}, \qquad (1.2)$$

where $R_{\mu\nu}$, $g_{\mu\nu}$, and $T_{\mu\nu}$ are second-rank tensors, with $R_{\mu\nu}$ the Ricci tensor, $g_{\mu\nu}$ the metric, and $T_{\mu\nu}$ the stress-energy tensor. In Eq. 1.2, $R$ is the Ricci scalar that can be derived from the Ricci tensor and the metric, $c$ is the speed of light, and $G$ is the gravitational constant. In what follows I do not provide further details about GR and the derivation of Einstein's equations because it is beyond the scope of this Thesis. More information can be found in any textbook on GR and/or cosmology. Nevertheless, I can add the few following information: (i) the Ricci tensor $R_{\mu\nu}$ is connected to the metric and so to the curvature of space-time and (ii) the stress-energy tensor $T_{\mu\nu}$ describes the density, flux, pressure, and stress of a given fluid and acts as the source of gravity in Einstein's equations. Using the FLRW metric and assuming a perfect fluid whose stress-energy tensor writes $T^{\mu\nu} = (\rho + P/c^2)u^\mu u^\nu + Pg^{\mu\nu}$, with $\rho$ its total mass density (including radiation), $P$ its pressure and $u$ the four-velocity vector, Einstein's equations reduce to the two following Friedmann-Lemaître equations (Friedmann 1922, 1924; Lemaître 1927):

$$\frac{\ddot{a}}{a} = -\frac{4\pi G}{3} \left( \rho + \frac{3P}{c^2} \right) + \frac{\Lambda}{3} \qquad (1.3)$$

$$H^2 + \frac{kc^2}{a^2} = \frac{8\pi G\rho}{3} + \frac{\Lambda}{3}, \qquad (1.4)$$

where $H(t) = \dot{a}(t)/a(t)$ is called the Hubble constant and $\Lambda$ is the cosmological constant from which the $\Lambda$CDM model takes its name. Without a cosmological constant, the solution with $k < 0$ corresponds to an open Universe that expands forever and that with $k > 0$ corresponds to a closed Universe that expands first and then collapses onto itself after some time. The solution with $k = 0$ is called an Einstein-de Sitter Universe and corresponds to the critical case where there is just enough matter to reduce its expansion but not enough to trigger its collapse. The corresponding critical density is given by

$$\rho_c = \frac{3H^2}{8\pi G}. \qquad (1.5)$$

Contrary to the matter and radiation contents represented by $P$ and $\rho$ that will always decelerate the expansion of the Universe, the cosmological constant can act as an acceleration term if it is positive. In particular, the first Friedmann-Lemaître equation tells us that if $\Lambda > 4\pi(\rho + 3P)$ then the Universe will be accelerated (as long as $P > -\rho/3$). Thus, since the discovery of the acceleration of the expansion of the Universe (Riess 1998; Perlmutter et al. 1999), the cosmological constant has been added into Einstein's and Friedmann-Lemaître equations to take into account the effect of dark energy.
### 1.1.3 Notion of redshift

An important notion in extragalactic astronomy is that of redshift. It corresponds to the shift of a spectrum with respect to its rest-frame wavelength position because of the motion of the galaxy and of the expansion of the Universe. Thus, in essence a galaxy's spectrum can be blue- or red-shifted, but since at large enough distances the expansion of the Universe takes over, we only refer to it as redshift. By definition, it writes

$$z = \frac{\lambda_{\text{obs}} - \lambda_{\text{em}}}{\lambda_{\text{em}}}, \qquad (1.6)$$

where $\lambda_{\text{obs}}$ is the observed wavelength and $\lambda_{\text{em}}$ the emitted one. Hence, we have the two following scaling relations:

$$\begin{aligned} \lambda_{\text{obs}} &= (1+z)\lambda_{\text{em}} \\ \nu_{\text{em}} &= (1+z)\nu_{\text{obs}}, \end{aligned} \qquad (1.7)$$

where $\nu = c/\lambda$ is the frequency. In special relativity, the redshift due to the velocity $v$ along the line of sight writes

$$\begin{aligned} 1+z &= \sqrt{\frac{1+v/c}{1-v/c}} \\ &\approx 1+\frac{v}{c}, \end{aligned} \qquad (1.8)$$

which reduces to the classical expression for low velocities with respect to the speed of light. In cosmology, its expression is different because it must take into account the expansion of the Universe encapsulated in the scale factor $a(t)$. Its expression can be easily derived from the FLRW metric considering that a packet of photons emitted at time $t_{\text{em}}$ during a time interval $\Delta t_{\text{em}}$ is received at time $t_{\text{obs}}$ during an interval $\Delta t_{\text{obs}}$. The light propagates radially towards us along a null geodesic (i.e. $ds^2 = d\theta^2 = d\phi^2 = 0$) so that we have $cdt = a(t)dr$. The front of the wave packet propagates from the space-time position ($t_{\text{em}}$, $r$) to ($t_{\text{obs}}$, 0) and the rear of the wave packet propagates from ($t_{\text{em}} + \Delta t_{\text{em}}$, $r$) to ($t_{\text{obs}} + \Delta t_{\text{obs}}$, 0). Thus, for both the front and the rear of the wave packet we can integrate $cdt/a(t)$ on one side and $dr$ on the other. Because they share the same integral along $r$, we can equate them to obtain

$$\begin{aligned} \int_{t_{\text{em}}}^{t_{\text{obs}}} dt/a(t) &= \int_{t_{\text{em}}+\Delta t_{\text{em}}}^{t_{\text{obs}}+\Delta t_{\text{obs}}} dt/a(t) \\ &\approx \int_{t_{\text{em}}}^{t_{\text{obs}}} dt/a(t) + \frac{\Delta t_{\text{obs}}}{a(t_{\text{obs}})} - \frac{\Delta t_{\text{em}}}{a(t_{\text{em}})}, \end{aligned} \qquad (1.9)$$

which is valid for small $\Delta t_{\text{obs}}$ and $\Delta t_{\text{em}}$. Thus, we get the cosmological time dilation expression

$$\frac{\Delta t_{\text{obs}}}{\Delta t_{\text{em}}} = \frac{a(t_{\text{obs}})}{a(t_{\text{em}})}. \qquad (1.10)$$
Given that by convention $a(t_{\text{obs}}) = a(t_0) = 1$, it reduces to $\Delta t_{\text{em}} = a(t_{\text{em}})\Delta t_{\text{obs}}$. If $\Delta t_{\text{obs}}$ and $\Delta t_{\text{em}}$ are understood as the period of the wave, then we have $\nu_{\text{em}} = \nu_{\text{obs}}/a(t_{\text{em}})$, which gives

$$1 + z_c = 1/a(t_{\text{em}}), \qquad (1.11)$$

where $z_c$ is the cosmological redshift of the source.

There is one last aspect that needs be discussed. Indeed, the redshift of a galaxy is not simply the result of the expansion of the Universe but can be affected by further motions. For instance, a galaxy can have its own proper motion along the LOS, it can be located in a group or in a cluster of galaxies which will have their own bulk velocity as well, or it can rotate which will change the value of the redshift depending on whether we measure it in a part of the galaxy that rotates faster or slower. Thus, we need to derive a law of composition for redshifts to combine all these effects together. To do so, let us imagine a galaxy at a cosmological redshift $z_c$ and an observer located at the same redshift. For this observer, the galaxy has a LOS velocity that produces a second redshift $z_1$, so that the light emitted by the galaxy at a wavelength $\lambda_{\text{em}}$ will appear at the wavelength $\lambda_1 = (1 + z_1)\lambda_{\text{em}}$. On the other hand, the light will appear for us as if emitted in the frame of the observer at the wavelength $\lambda_1$ and will be redshifted to the observed wavelength $\lambda_{\text{obs}} = (1 + z_c)\lambda_1 = (1 + z_c)(1 + z_1)\lambda_{\text{em}}$. If the global redshift can be split into multiple components, then we can generalise the previous result and obtain the law of composition for redshfits

$$\lambda_{\text{obs}} = \prod_i (1 + z_i) \lambda_{\text{em}}. \qquad (1.12)$$

### 1.1.4 Impact on astrophysical quantities

Now that we have quickly discussed the theory behind cosmology, we still need to derive how key physical quantities useful for this Thesis are affected by the expansion of the Universe. As already discussed in Sect. 1.1.1, we can assign a distance to an object without taking into account the expansion of the Universe: its comoving distance $r$. To transform it into a physical distance we must apply the scale factor to take into account the expansion of the Universe, $a(t)r$, and we call it its proper distance. But these two distances are not the only ones we can define. There are at least two more that can be useful in combination with other physical quantities: the angular diameter distance and the luminosity distance.

The angular diameter distance $D_A$ corresponds to the distance that must be used to derive the physical size of an object or the physical separation between two close objects at the same cosmological redshift (noted $d$) with an apparent angular size or separation $\Delta\theta$ on the plane of the sky through the Euclidian formula

$$d = D_A \Delta\theta. \qquad (1.13)$$

To derive it, one can use the FLRW metric and consider the line element along the direction $\theta$. The physical size will be given by integrating it, which gives

$$\begin{aligned} d &= a(t) R_c(t_0) \sin \left( \frac{r}{R_c(t_0)} \right) \Delta\theta \\ &= \frac{r_1}{1 + z_c} \Delta\theta, \end{aligned} \qquad (1.14)$$
where $r_1$ is defined in Eq. 1.1 and reduces to the usual Euclidian distance $r_1 \approx r$ when $r \ll R_c(t_0)$. Thus, the angular diameter distance scales with radius as

$$D_A = \frac{r_1}{1 + z_c} \qquad (1.15)$$

In cosmology the angular diameter distance increases up to a turnover point ($z \approx 1.5$ for $\Lambda$CDM) and then decreases again. Thus, for an object with a fixed physical size this means that its angular size on the plane of the sky will first decrease up to the turnover point and then will increase again. Hence, contrary to our intuition in Euclidean geometry where the further away an object is from us the smaller is its angular extent, high-redshift galaxies can appear larger than lower redshift counterparts with the same physical size.

On the other hand, the luminosity distance comes from working out the impact of cosmology on the flux that we observe. Indeed, let us consider an isotropic source with intrinsic luminosity $L = \Delta E_{em}/\Delta t_{em}$, where $\Delta E_{em}$ is the emitted energy in an interval $\Delta t_{em}$. At present time, its luminosity will be distributed over a spherical area of $4\pi a^2(t_0)r^2 = 4\pi r^2$, since $a(t_0) = 1$ by convention, so that a telescope at a comoving distance $r$ from the source and with an area $A$ will receive a fraction $A/(4\pi r^2)$ of the total emitted luminosity. At the same time, the received luminosity $L_{obs}$ is just the product of the telescope area by the observed flux, hence we have

$$\begin{aligned} L_{obs} &= F \times A \\ &= \frac{\Delta E_{obs}}{\Delta t_{obs}} \times \frac{A}{4\pi r^2}. \end{aligned} \qquad (1.16)$$

But, we know from Eq. 1.7 that the observed photons' frequency and therefore energy both scale as $\Delta E_{obs} = \Delta E_{em}/(1+z)$ and from Eqs. 1.10 and 1.11 that the observed time interval within which the photons will be received scales as $\Delta t_{obs} = (1+z)\Delta t_{em}$. Thus, we find the relation

$$F = \frac{L}{4\pi D_L^2}, \qquad (1.17)$$

where we have defined the luminosity distance as

$$D_L = r(1 + z). \qquad (1.18)$$

Furthermore, I will also use the concept of flux density in what follows. In this Thesis, I call flux density the flux per unit wavelength (noted $F_\lambda$) or per unit frequency (noted $F_\nu$). Its unit will either be in erg s$^{-1}$ Å$^{-1}$ cm$^{-2}$ for $F_\lambda$ or in erg s$^{-1}$ Hz$^{-1}$ cm$^{-2}$ for $F_\nu$. The derivation of the impact of cosmology on the observed flux density is very similar to that of the flux. The only difference is that it is divided either by a frequency or by a wavelength so that, based on Eq. 1.7, we have

$$F_{\nu,\text{obs}}(\nu_{\text{obs}}) = F_{\nu,\text{em}}(\nu_{\text{em}}/(1+z)) \times (1+z) \qquad (1.19)$$

$$F_{\lambda,\text{obs}}(\lambda_{\text{obs}}) = \frac{F_{\lambda,\text{em}}(\lambda_{\text{em}}(1+z))}{1+z} \qquad (1.20)$$

We see that in both cases we have a shift of the frequency or wavelength range as well as a scale factor that is either larger than or less than unity depending on whether we consider $F_\nu$ or $F_\lambda$.
1.2 A concise history of our understanding of galaxies

1.2.1 The dawn of extragalactic astronomy

Among the topics in Astronomy, extragalactic astrophysics is a quite recent field of research, in some way that is barely one hundred years old. A certainly important reason for such a late development in the study of galaxies is that there are actually only a handful which are visible with the naked eye on the celestial sphere. The most visible of all is our Galaxy, the Milky Way. Beside it, our closest companion, the Andromeda galaxy (M31), is supposed to be visible in the northern hemisphere and so is the Triangulum galaxy (M33). However, even though they are supposed to be very luminous, they span large areas on the sky which make them hardly visible without the aid of optical systems. Additionally, in the southern hemisphere two bright and easily visible galaxies can also be seen: the Small and the Large Magellanic Clouds. But apart from these close and bright objects, no other galaxy can be seen without the use of binoculars or refractive/reflective telescopes. However, this picture changed throughout the eighteenth and nineteenth centuries when astronomers such as Charles Messier or John Herschel started to make catalogues of such objects that were called at the time nebulae.

As the number of observed nebulae grew with time, the question of their distance to us became unavoidable. Given that precise distance measurements were lacking up to 1925, two competing ideas faced each other regarding this question. Some astronomers thought that the nebulae were objects located within our own Galaxy, whereas others rather thought that they were *Island Universes* to use the terminology devised by Immanuel Kant but inspired by the earlier works of Emanuel Swedenborg and Thomas Wright (Swedenborg 1734; Wright & Rafinesque 1837), that is external systems composed of stars similar to the Milky Way, hence extragalactic objects. Thus, it is not totally inaccurate to say that, before a first conclusive answer was brought by Edwin Hubble in 1925, the size of the Universe, or rather our comprehension of it, did not extend beyond the visible boundaries of the Milky Way. One of the reasons behind the longevity of the debate is that the class of nebulae that were observed at the time did not only incorporate objects that we would refer to nowadays as galaxies but also globular clusters and planetary nebulae that are both indeed found in the Galaxy. Besides, the debate was definitely exacerbated by the fact that, until the very end of the nineteenth century, observations of nebulae were restricted to scarce hand-drawings and a handful of not-so-conclusive spectra. In 1914 and in subsequent years, spectroscopic observations of galaxies such as M31, M81, or M33 made, among other astronomers, by Vesto Melvin Slipher showed that some of the nebulae had radial and rotation velocities much greater than those of stars in the Milky Way (e.g. Slipher 1913). Actually, the velocities were so large that it was found that these objects, if they were indeed part of the Galaxy, could not be gravitationally bound. However, this did not yet prove that they were located well beyond the confines of the Milky Way. A definite proof that at least some of these objects are indeed located far away and are therefore similar to our Galaxy in terms of size and luminosity was given by Edwin Hubble for the first time in 1925 (Hubble 1925). His evidence came from the measurements of the magnitudes and periods of oscillation of 47 variable stars in M33 and 36 in M31 that he associated with Cepheid stars. A few years before, it had been shown by Henrietta Leavitt that Cepheids have a period of oscillation that correlates with their intrinsic luminosity (Leavitt 1908; Leavitt & Pickering 1912). Hence, by measuring M33 and M31 Cepheids' period, Hubble could derive their intrinsic luminosity and compare it with their observed flux to determine their distance. Under the assumptions that there is no significant absorption in both galaxies, that the variable stars do belong to them, and that Cepheids are ubiquitous in the Universe he found a
distance of 285 kpc for both M33 and M31, much beyond the 5 kpc that were thought to be the radius of the Milky Way at the time (Shapley & Curtis 1921). Even with a more modern upper limit for the size of our Galaxy of roughly 45 kpc this would still mean that after Hubble's discovery the size of the Universe had expanded by at least a factor of nine and its volume by nearly a thousand. More details about the long march from the nebulae to the galaxy world across the eighteenth, nineteenth, and early twentieth centuries and the subsequent birth of the field of extragalactic astrophysics can be found in Gordon (1969) and Longair & Giacconi (2007).

### 1.2.2 A quick march towards our current view of galaxies

From this moment, the field of extragalactic astrophysics really began and the discoveries that followed accelerated at an impressive rate. I will come back to some specific points in later sections but I can nevertheless give a brief account of the major steps forward that led towards our current understanding of galaxy evolution. To begin with, in parallel to resolving the great debate regarding the nature and the distances of nebulae/galaxies, Hubble had also devised a visual classification (Hubble 1926) based on observations of 400 galaxies and so apparently did Knut Lundmark the same year (Lundmark 1926). Both classifications were similar in the sense that they split galaxies in three distinct groups with ramifications for each: ellipticals, spirals, and irregulars. Examples taken from Hubble (1926) for these three classes are shown in Fig. 1.1. As discussed in Hubble's footnote, the classification was adopted so as to be as descriptive as possible, that is to classify galaxies based on their observable morphological features rather than on a putative early understanding of galaxy evolution. Yet, from his own point of view and influenced by James Jeans' theory, Hubble not only saw it as a classification scheme but also as a sort of evolutionary track with objects starting as elliptical systems and evolving into spirals within which the gas was thought to collapse to form stars. This view regarding the evolution of galaxies led him to emphasise the role of nebular gas in galaxies and thus influenced him in keeping to use the term "extragalactic nebulae" whereas other astronomers such as Lundmark rather recognised the importance of stars and therefore called them instead galaxies. By the 1950s the latter term had taken over and would be solely used in following publications (Smith 2009). The details of the classification and the physical properties associated to each class of galaxies are discussed further in Sect. 1.3.1. Though simple in nature, this classification has been and is still widely used nowadays, mainly for studies at low redshift (see Sect. 1.3.2 for a discussion regarding the morphology of galaxies at high redshift), and is commonly referred to as the Hubble fork diagram<fnref n="1" />. Parallelly to the development of the Hubble diagram and of the settling of the great debate, early works by Slipher had already shown that a majority of galaxies were receding from us with large velocities (Slipher 1913, 1915). Alternatively, in 1927, George Lemaître published a paper within which he used Einstein's GR to derive the dynamics of an expanding Universe (Lemaître 1927). Using Slipher's velocity measurements and recently published Hubble's distances for the same galaxies he observed for the first time a correlation between distance and velocity (i.e. the further away a galaxy, the faster it recedes from us) that seemingly proved the expansion of the Universe. However, his work did not meet great international success given that the original paper was published in a Belgian journal and that Lemaître himself removed the part concerning

<footnote n="1">¹Updated classifications have been proposed since then, including for instance that of van den Bergh (1976) where lenticular galaxies form a sequence parallel to that of spirals, that of Kormendy & Bender (1996) where ellipticals are classified according to their isophotal shape, that of Kormendy & Bender (2012) that combines the two previous classifications, or that of Cappellari et al. (2011b) which takes into account the galaxy stellar kinematics.</footnote>
<figure><img src="image_5.png" /><figcaption>Figure 1.1: Montage illustrating various Hubble's types. Ellipticals are shown on the first line from less to more disky, spirals are shown on the second line from little to important spiral structure, an example of barred spiral galaxy is shown on the bottom left (NGC 7479), and two irregular galaxies are shown on the last line (NGC 3034 and NGC 4449). Images are taken from Hubble's original publication (Hubble 1926).</figcaption></figure>
the observed correlation between distance and velocity in the 1931 English translation (Lemaître 1931; Livio 2011). Hence, a few years later, Hubble would publish his own analysis also using Slipher's velocities and his own updated distance measurements (Hubble 1929) to re-discover the same correlation, now dubbed the Hubble-Lemaître law. The constant of proportionality on the other hand would retain the latter name and be labelled in the years to follow as the Hubble constant (noted $H_0$), that is a constant that describes the current rate of expansion of the Universe. Around the same time, studies of the spatial distribution of galaxies around the Milky Way started to be done (e.g Shapley & Ames 1926) and showed the existence of clusters of galaxies, focussing particularly on the Virgo cluster. Then, by the 1930s astronomers started to realise that absorption by material along the LOS, especially near the Galactic plane, had to be taken into account (Trumpler 1930; Joy 1939, e.g.) and in 1933 Fritz Zwicky proposed a first argument for the existence of a large missing mass in galaxy clusters (Zwicky 1933, see also Sect. 1.4.1 for a more thorough discussion).

Quickly afterwards would the second world war (WWII) begin which, as some authors have argued (e.g. Longair 2019), has certainly played a crucial role in the developments of physics and modern astrophysics. For instance, it is in the wake of WWII and at the dawn of the Space Race that the industry of space rockets that was crucial for the birth of space-based astronomy would massively develop. In a similar fashion, the large investments made on radio techniques and on the development of infrared detectors, both primarily for the sake of war and intelligence, would later greatly benefit the fields of radio and infrared astronomy, respectively. Indeed, in the 1950s, what was then thought of as “radio stars” would be found to actually be, at least for some of them, extragalactic sources (Baade & Minkowski 1954a,b). Thus, it became obvious that to study galaxies, optical observations would not suffice but that the whole spectrum would have to be taken into account. During the same decade, Gérard de Vaucouleurs would suggest for the first time the existence of super-clusters of galaxies (de Vaucouleurs 1958) and the first radio studies of neutral gas (HI) using the 21 cm line would begin, first on the Milky Way and then on nearby galaxies (e.g. Ewen & Purcell 1951; Kerr & Hindman 1953; Raimond & Volders 1957). Later on, the 1960s saw an increased interest among the astronomical community in the active nuclei of galaxies with regards to their evolution (e.g. Markarian 1963; Ambartsumian 1968). It is during this same period that the European Southern Observatory (ESO) was founded partly to compete with American observatories that were the leading astronomical facilities of the time and partly to open up the southern sky to this field of research. It would nevertheless take another decade before first light would be achieved in Chile where the observing sites had been chosen.

Across the 1970s and 1980s, both observational and theoretical developments were made concerning the clustering of galaxies on very large scales, with evidence on both sides supporting that galaxy clusters assembled into a large scale structure (Zeldovich 1978; Einasto et al. 1980), nowadays referred to as the cosmic web. Furthermore, investigations of the optical properties of galaxies in rich clusters at $z \approx 0.3$ compared to those in the vicinity of the Milky Way showed that the former had bluer galaxies in their central parts (e.g. Butcher & Oemler 1978).

Subsequent photometric and spectroscopic analyses at slightly higher redshift confirmed previous observations of what would be known as the Butcher–Oemler effect (e.g. MacLaren et al. 1988; Butcher & Oemler 1984). The explanation for this effect was that either “high” redshift galaxies located in clusters had suffered from an enhancement of star-formation at $z \approx 0.3-0.4$ (MacLaren et al. 1988) or that local galaxies had seen their star formation quenched with respect to those located in the field at the same redshift (Butcher & Oemler 1984). Hence, these observations shed the first lights on the importance of the impact of the environment on the
evolution of galaxies. Perhaps even more importantly, the 1970s saw a number of kinematics
studies using neutral (HI) and ionised (Hα) gas of nearby galaxies that showed that they have flat
rotation curves up to large distances (e.g. Rogstad & Shostak 1972; Roberts & Rots 1973; Bosma
1978, 1981a,b; Rubin et al. 1978a,b, 1980), hence suggesting that there might be a DM component
in galaxies similarly to galaxy clusters. By the end of the 1970s, the Canada-France-Hawaii
Telescope (CFHT) was also inaugurated at Mauna Kea in Hawaii which allowed for observations
with very good seeing conditions. It is with the help of this telescope that the first serendipitous
detection of a gravitational arc in the Abell cluster A370 would be done (Soucail et al. 1987;
Soucail 1987). During the same period, Tully et al. (1975) discovered a correlation between galaxy
luminosity and spectral line width, a proxy for the rotation velocity, that would later be known as
the Tully-Fisher relation (TFR). A similar relation would also be found for elliptical galaxies, but
with the velocity dispersion instead of the rotation velocity, approximately at the same time
(Faber & Jackson 1976), now referred to as the Faber-Jackson relation. It is also during this
decade that another important scaling relation, the mass-metallicity relation (MZR), would be
found (e.g. Lequeux et al. 1979; Skillman et al. 1989) which further showed the importance of
feedback processes on the evolution of galaxies, as already discussed a few years back in
theoretical papers (e.g. Larson 1974; White & Rees 1978a).

During the 1990s, efforts were made into observing high-redshift galaxies to constrain their evolution. Early deep photometric and/or spectroscopic ground-based surveys (Broadhurst et al. 1988; Cowie et al. 1991, e.g.) were mostly limited to intermediate redshifts ($z \approx 0.3 - 0.4$, roughly 5 Gyr of galaxy evolution) but a leading observing method at the time was to use background quasi-stellar objects (QSOs) to observe foreground galaxies through the absorption of their neutral gas (e.g. Steidel & Hamilton 1993; Pettini et al. 1994). At the same period was launched the Hubble Space Telescope (HST), the first large space telescope with a primary mirror of 2.4 m built in collaboration between the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). Early HST observations (e.g. Dressler et al. 1994b,a; Dickinson 1995) showed that even with low integration times it was possible to get deep images unveiling a large number of galaxies. Furthermore, these initial studies highlighted that by $z \sim 1$ the galaxies in clusters could still be classified between spirals and ellipticals, as in the local Universe. However, they also noted that there was a significant fraction of irregular and seemingly interacting galaxies. In parallel, using the ultraviolet (UV) filters aboard the HST, Giavalisco et al. (1995) managed to observe a Lyα-emitting galaxy at $z = 3.4$, proving that it was possible to resolve high-redshift galaxies with HST. The complex picture regarding the high-redshift Universe that emerged from the aforementioned early analyses incited the telescope's committee to perform a deep observation of a single field devoid of any already detected bright objects or low-redshift galaxy clusters for ten consecutive days (Williams et al. 1996). This field that would profoundly affect extragalactic astrophysics is most famously known as the Hubble Deep Field (HDF).

1.2.3 Last steps towards modern extragalactic astrophysics

Following the release of the HDF and subsequent observations such as the Hubble Ultra Deep Field (HUDF), further major breakthroughs in our understanding of galaxy evolution were made. As for the previous section, I cannot cite them all but I can give a flavour of what we have learned since the early 2000s. To begin with, by mid-2000s multi-wavelength photometric and spectroscopic observations combined with various Star Formation Rate (SFR) estimates and Spectral Energy Distribution (SED) models suggested that there is a tight correlation between
stellar mass and SFR (e.g. Noeske et al. 2007; Elbaz et al. 2007; Daddi et al. 2007). This relation
is now referred to as the star-forming Main Sequence (MS) and, as discussed in more details in
Sect. 1.3, it is still extensively studied in the literature (e.g. Whitaker et al. 2014; Boogaard et al.
2018; Mercier et al. 2022). To explain these new scaling relations and older ones such as the MZR
that hold at both low and high redshift, the “bathtub model” (Bouché et al. 2010; Lilly et al.
2013) was developed in which stellar mass growth and star formation are induced by a continuous
accretion of gas and regulated by feedback processes at the same time. Variations of this model
exist between authors concerning the importance of different feedback processes and how to
implement the effect of the environment but it has nevertheless shown how simple regulation
mechanisms can produce such scaling relations. The early 2000s also saw an increased interest in
supermassive black-holes as a possible early feedback process for high-redshift galaxies (e.g. Silk &
Rees 1998; Di Matteo et al. 2005) and to explain the observed black hole mass-velocity dispersion
relation (e.g. Ferrarese & Merritt 2000; Tremaine et al. 2002). Roughly ten years after the HST
became operational two additional space-based American telescopes were launched, the first
observing in the infrared (IR) and named SPITZER and the second in the UV and named Galaxy
Evolution Explorer (GALEX). Combined with HST, these three telescopes greatly increased our
understanding of the star formation history of galaxies across cosmic time (e.g. Calzetti et al.
2007). In particular, these new data allowed to confirm early results (e.g. Lilly et al. 1996; Madau
et al. 1996) that the comoving SFR density is larger at higher redshift up to a turnover point
around $z \sim 2$ beyond which it decreases again (e.g. Hopkins 2004; Hopkins & Beacom 2006). The
advent of large ground- and space-based photometric surveys also allowed the study of the
morphological evolution of galaxies. During the 2000s it was found that galaxies’ stellar mass
correlates with their size but, according to later studies (e.g. Trujillo & Aguerri 2004; Trujillo
et al. 2006; van der Wel et al. 2014b), that the zero point of the relation strongly evolves with
redshift. Combined with statistical modellings of the projected shape of galaxies on the plane of
the sky (e.g. van der Wel et al. 2014a; Zhang et al. 2019), these observations clearly showed that
the morphology of galaxies has substantially changed with cosmic time and that high-redshift
galaxies do not settle as easily on the Hubble diagram as local galaxies do.

The twenty-first century also saw a tremendous increase in kinematics studies of galaxies across
cosmic time. Prior to this era, these were fairly limited to relatively small samples of low-redshift
galaxies almost exclusively observed with long-slit spectroscopy since 3D spectroscopy was only in
its infancy (see Sect. 2.2.1 for a discussion on the topic). Nevertheless, by the end of the 1990s
first “high” redshift kinematics observations were made (e.g. Vogt et al. 1996; Simard & Pritchet
1998) that showed that (i) rotating disks are already present at $z \sim 1$, (ii) there is a TFR at
theses redshifts similar to the local Universe, though with more scatter, and (iii) that there is a
significant (around 30%) fraction of galaxies that are kinematically disturbed (at least their gas
component). The following decades saw the development of Very Large Telescopes (VLTs) to
which were associated Multi-Object Spectrographs (MOS) and 3D spectroscopes that either
allowed to observe large sample of galaxies with multi-slit spectroscopy or smaller samples of
galaxies with spatially resolved (i.e. 2D) kinematics. The first relatively large surveys that came
out of these instruments confirmed early arguments regarding the presence of rotating and
kinematically disturbed gas disks in high-redshift galaxies (e.g. Förster Schreiber et al. 2006b,
2009a; Law et al. 2009; Contini et al. 2012; Epinat et al. 2012; Contini et al. 2016). In particular,
the presence of a large proportion of dispersion-dominated objects triggered interesting
discussions on whether the large dispersion values were intrinsic or instrumental-driven (e.g.
Shapiro et al. 2008; Puech et al. 2007, 2008a; Newman et al. 2013). These observations also led to
the discussion of whether the TFR evolved with cosmic time (e.g. Puech et al. 2008a; Vergani et al. 2012; Contini et al. 2016), but no clear trend could be found. The ubiquity of high velocity dispersions and morphologically disturbed galaxies at high redshift also raised the question of whether galaxy mergers were more common in the early Universe. Kinematics studies clearly helped in showing that the merger fraction was higher at higher redshift up to a turnover point at $z \sim 3$ (e.g. Puech et al. 2012; López-Sanjuan et al. 2013a; Ventou et al. 2017, 2019).

Our modern picture of extragalactic astrophysics and of the formation and evolution of galaxies would not have reached its current state without the quick development of cosmological and zoom-in simulations. Early simulations that integrated baryonic components were first developed during the 1990s (e.g. White & Frenk 1991; Katz et al. 1992; Kauffmann et al. 1993), though they were either limited to rather small volumes or required the use of semi-analytical models. These were much further developed across the 2000s and 2010s so that they have now become key tools to understand the evolution of galaxies. For instance, we can cite ILLUSTRIS and its follow-up project The Next Generation Illustris Simulations (ILLUSTRIS-TNG) (Vogelsberger et al. 2014; Springel et al. 2018) that are hydrodynamical simulations, MILLENIUM (Springel et al. 2005) which is the first semi-analytical simulation from the Virgo consortium that was followed by their second hydrodynamical simulation Evolution and Assembly of GaLaxies and their Environments (EAGLE) (Schaye et al. 2015; Crain et al. 2015), or the Feedback In Realistic Environments (FIRE) simulation (Hopkins et al. 2014) that has been designed to resolve the interstellar medium (ISM) and star formation. These simulations have shown or confirmed, among many other things, the importance of DM haloes for galaxies build-up, the importance of gas inflows from the cosmic web to fuel star formation on Gyr timescales, or that multiple feedback processes are required (e.g. active galactic nucleus - AGN, radiative, supernovae, etc.) to recover the observed scaling relations at both low and high redshift.

## 1.3 Galaxy evolution across cosmic time

In this section, I briefly discuss the properties of galaxies at low (Sect. 1.3.1) and high (Sect. 1.3.2) redshift. Some parts will be reminiscent of Sect. 1.2 but the objective of this section is different. In Sect. 1.2, I tried to give an historical perspective on the evolution of the field of extragalactic astrophysics and how quickly our understanding of galaxy evolution has changed in a relatively short amount of time. On the other hand, in this section I will rather give a broad depiction of our current view of galaxies and how this is linked to their evolution across cosmic time.

### 1.3.1 Properties of local galaxies

As already quickly discussed in Sect. 1.2.2, galaxies in the local Universe are usually classified, mostly for historical reasons, using an updated version of the Hubble diagram. Nevertheless, this classification scheme is far from perfect, for instance because it does not include irregular, peculiar, and dwarf galaxies, or because the classification of ellipticals is not physical but rather mostly depends on the galaxies' inclination on the plane of the sky (e.g. van den Bergh 1976). Hence, other classifications have been suggested in the meantime in terms of morphology (e.g. de Vaucouleurs 1974; van den Bergh 1976; Kormendy & Bender 1996, 2012) or kinematics (e.g. Cappellari et al. 2011a,b). Still, for simplicity only the Hubble diagram will be considered in what follows. The two main classes that populate this diagram are elliptical and spiral galaxies that are also usually called, for historical reasons as well, early-type and late-type galaxies, respectively.
As mentioned, other types of galaxies exist, though they are less common at low redshift. For instance, we can cite irregular galaxies that cannot be associated to neither elliptical nor spiral galaxies, peculiar galaxies that typically include merging galaxies or in interaction, dwarf galaxies that can resemble ellipticals, spirals, or irregulars but that are smaller, less massive and less bright, or low-surface brightness galaxies that are equivalent to the ellipticals and spirals but with an overall low surface brightness that renders their detection difficult. Even though this classification was initially built on morphological (and magnitude) criteria, there are actually key physical differences between the various classes that hint at the fact that these populations either have not followed the same evolutionary track or that they are not at the same stage of their evolution.

<figure><img src="image_6.png" /></figure>

Figure 1.2: Example of a colour-magnitude diagram adapted from Baldry et al. (2006) that shows the colour bimodality observed in the local Universe. The vertical axis shows the u-band minus r-band rest-frame galaxy colour and the horizontal axis shows the absolute magnitude in the u-band. Hence, redder galaxies are found on the top of the plot and brighter galaxies on the right. The blue sequence is visible on the lower left part of the plot around a colour of roughly 1.2 mag (hence bluer and fainter) and the red sequence on the top right part of the plot around a colour of roughly 2.5 mag (redder and brighter). Galaxies located between the two sequences are said to belong to the green valley.

To begin with, let us consider ellipticals and spirals since they form the bulk of galaxies in the local Universe. Elliptical galaxies are characterised by a smooth surface brightness distribution that is typically described by a de Vaucouleurs profile (de Vaucouleurs 1948). These galaxies mainly contain old and metal-rich stars with little cold gas and thus little to no star-formation at all which therefore render their colour quite red compared to spiral galaxies. Their smooth surface brightness can easily be fitted with elliptical isophotes, hence their name. Even though these galaxies have a very low amount of cold gas, it was nevertheless found that they possess a significant fraction of hot gas that emits in the X-rays (e.g. Roberts et al. 1991). From a kinematics point-of-view, elliptical galaxies are found to have little but non-zero rotation (e.g. Cappellari et al. 2007; Emsellem et al. 2007) and exhibit strong correlations between (i) their stellar velocity dispersion and luminosity or stellar mass, known as the Faber-Jackson relation, and (ii) their stellar velocity dispersion and size. Both relations were found to actually be projections of a more fundamental relation dubbed the fundamental plane (Djorgovski & Davis 1987). On the other hand, spiral galaxies are thin disk-like structures with usually a small but
non-zero thickness. They tend to have more inner structure than ellipticals since they exhibit spiral arms and tend to have a bar and a bulge in their inner parts. Galaxies that have the structure of a disk but the smooth surface brightness distribution of ellipticals are called lenticular galaxies. The bulge component is a key characteristic that most spirals, though not all, have. Contrary to the disk and in particular to the spiral arms that are dominated by massive blue young stars, the bulge is made of a larger variety of stars, including old ones. Additionally, spiral galaxies have a large fraction of cold gas either under its molecular phase (H₂), mainly located in the arms and in star-forming regions, or under its atomic phase (HI) which is much more extended than the stellar disk. Combined with the prevalence of massive young stars that produce ionising photons, these facts make spiral galaxies much more star-forming than ellipticals. The kinematics of spiral galaxies is typically that of a rotating disk. Contrary to what would be expected, the rotation curves of disk galaxies are ubiquitously found to be flat at large radii, as shown by early investigations of rotation curves derived from Hα and HI observations (e.g. Rogstad & Shostak 1972; Roberts & Rots 1973; Rubin et al. 1978a; Bosma 1978, 1981a,b). As already discussed, these observations were interpreted as the fact that spiral galaxies must contain massive DM haloes that dominate the stellar and gas dynamics at large distances. One of their most important kinematics scaling relations is the TFR that was initially discovered as a correlation between the luminosity of a galaxy and its rotation velocity (either derived from the stars or the gas) at large distances (a proxy for the DM halo mass, Tully et al. 1975). Later on, it was found that this relation also holds when using stellar masses instead of luminosities. Spiral and elliptical galaxies also obey additional scaling relations (e.g. size-mass or mass-metallicity) and in particular one that is linked to their evolution: the mass-SFR relation (e.g. Noeske et al. 2007; Elbaz et al. 2007; Daddi et al. 2007). Indeed, star-forming galaxies, hence mostly spirals, tend to follow a scaling law in the stellar mass-SFR plane called the MS. Instead, ellipticals mostly populate a red sequence below this sequence. This separation in two populations in the mass-SFR diagram is also seen in colour histograms and colour-magnitude diagrams as shown in Fig. 1.2. In the local Universe, bright galaxies, hence mostly ellipticals, dominate the luminosity and mass budgets (e.g. Schechter 1976) but, in terms of numbers, most of the galaxies are actually low-mass objects. Furthermore, it was found with recent large spectroscopic surveys, in particular that of the Sloan Digital Sky Survey (SDSS), that there is a clear correlation between the galaxies' stellar mass and their gas-phase metallicity (e.g. Tremonti et al. 2004) consistent with galactic winds impacting more importantly low-mass galaxies that have shallower gravitational potentials.

Other types of galaxies also exist in the local Universe. For instance, in the mass-SFR diagram discussed above, starburst galaxies are found to lie above the MS. These galaxies usually have blue spectra that are indicative of the presence of massive hot stars and high star-formation, thought to be mainly produced by recent mergers between gas-rich progenitors. Another type of galaxies that has become more and more studied in recent years because of their dynamical properties are dwarf galaxies. Historically speaking, dwarfs were just low-luminosity, and therefore low-mass, counterparts of ellipticals, spirals, and irregulars (e.g. Baade 1944; Sandage & Binggeli 1984). However, they are interesting in various aspects. First, the fact that such low-mass objects still exist in the local Universe means that they must have had a relatively moderate mass assembly which must be taken into account when constraining the physical processes at the origin of the mass build-up of the whole galaxy population. Second, these systems do not always scale along the same scaling laws as their more massive counterparts. For instance, one of the historical reasons why dwarfs were considered as a separate class was that the more massive they become, the higher their surface brightness, which is the exact opposite
behaviour of more massive elliptical and spiral galaxies (e.g. Kormendy 1985). Lastly, dwarfs form a population of DM-dominated objects which make them perfect candidates to study the properties and the distribution of DM (e.g. Gilmore et al. 2007).

### 1.3.2 Galaxies in the distant Universe

It was found quite early that galaxies at high-redshift are different from their local counterparts in many aspects. To begin with, the Hubble classification between spirals and ellipticals becomes more difficult to use in the distant Universe. The reason is certainly a combination of the facts that (i) we are probing galaxies at an earlier phase of their evolution before they settled along the Hubble sequence and (ii) high-redshift galaxies are also smaller and fainter because of cosmology, hence sub-structures such as spiral arms are more difficult to detect for these objects. Indeed, it is now clear that galaxies have significantly evolved across cosmic time. For instance, as already discussed in Sect. 1.2.3, the morphology of galaxies has greatly changed from high to low redshift with a larger fraction of morphologically disturbed objects found at high redshift (e.g. Brinchmann et al. 1998), with disks that tend to be much thicker for high-mass galaxies, and with galaxies that have prolate rather than oblate (i.e. elongated rather than flattened along the axis of symmetry) shapes at low stellar mass (e.g. van der Wel et al. 2014a; Zhang et al. 2019). In addition, studies of the evolution of the comoving SFR density across cosmic time have shown that galaxies have experienced an increase in star formation activity up to a peak around $z \sim 2-3$ and then a reduction to the current value measured at $z=0$ (e.g. Madau & Dickinson 2014; Gruppioni et al. 2020). The question of what caused this peak or rather why the SFR density was reduced after that turnover point is still open. Given that the SFR is linked to the amount of cold gas located in galaxies but also to the efficiency to convert this gas into new stars, different mechanisms have been suggested. For instance, feedback processes (e.g. AGN, stellar winds, etc.) might have removed a fraction of the gas, thus reducing, potentially momentarily if the gas is then re-accreted, the star formation activity. Other mechanisms rather linked to the environment of galaxies have also been proposed such as ram-pressure stripping, thermal evaporation, or galaxy harassment (Gunn & Gott 1972; Cowie & Songaila 1977, see Sect. 1.3.3). Beside the evolution of their SFR, galaxies have also changed in terms of mass and size and that differently if they are star-forming or quiescent. Indeed, the stellar mass function of star-forming galaxies has mainly increased for its low-mass end whereas that of quiescent galaxies has increased across the entire mass range (e.g. Ilbert et al. 2010; Muzzin et al. 2013). These two populations are necessarily linked to each other since star-forming galaxies will populate the quiescent population once quenched. Such results are also consistent with recent studies of the evolution of the merger fraction with cosmic time using close pair counts (e.g. López-Sanjuan et al. 2013a; Tasca et al. 2014; Ventou et al. 2017) and simulations (e.g. Puech et al. 2012; Snyder et al. 2017; Ventou et al. 2019) that show that the merger fraction increases to nearly 20% (compared to a few percent at $z=0$) with redshift up to $z \approx 3$ and slowly decreases beyond. Furthermore, both populations of galaxies have also increased in size across cosmic time, with quiescent galaxies showing a steeper increase with redshift (e.g. van der Wel et al. 2014a). These two evolutions (stellar mass and size) can also be seen as the result of the fact that galaxies at high redshift follow a similar size-mass relation as those at low redshift, hence that an increase in stellar mass seems to produce an increase in size. The stellar mass evolution can also be linked to that of the SFR through the mass-SFR relation, with high-redshift star-forming galaxies also found to be located along a MS. In order for the MS to have survived across billion years timescales, it means
that the physical processes that produce it in the local Universe must have already played an
important role at earlier cosmic times. However, because star-formation was higher in the past we
see an evolution of the zero-point of the relation with redshift (e.g. Speagle et al. 2014) that holds
at low stellar masses (e.g. Whitaker et al. 2014; Boogaard et al. 2018). Linked to the size, mass,
and SFR evolutions with redshift, there is also a visible gas-phase metallicity evolution. Even
though measuring precisely the metallicity at high redshift is not simple, large samples at $z \sim 2$
have been assembled that show that galaxies in the distant Universe had a lower metallicity than
in the local Universe (e.g. Erb et al. 2006; Wuyts et al. 2014, 2016). Furthermore, high redshift
estimates of the cold gas fraction (both under atomic and molecular phase, e.g. see Tacconi et al.
2020; Walter et al. 2020) have also shown that distant galaxies were much more cold gas-rich than
at the current epoch (by a factor of roughly two in HI and five in H$_2$ between $z = 0$ and $z \approx 2$).

Galaxies have also evolved dynamically throughout cosmic time. In the local Universe, galaxy
disks that are dynamically supported by their own rotation are ubiquitous but at higher redshift
the picture becomes more complex. As discussed quickly in Sect. 1.3.1, a first striking feature of
the observed velocity fields of a non-negligible fraction of intermediate and high redshift galaxies
is their lack of rotation in their gas component (e.g. Förster Schreiber et al. 2006b, 2009a; Epinat
et al. 2009; Law et al. 2009; Contini et al. 2012; Epinat et al. 2012; Contini et al. 2016). This has
led to substantial dynamical classifications between rotationally supported, dispersion dominated,
and kinematically disturbed galaxies using the ionised gas as kinematics tracer (e.g. Flores et al.
2006; Yang et al. 2008; Epinat et al. 2009; Contini et al. 2016). The proportion of galaxies
between the three classes is roughly one third each, though the exact numbers depend on the
selection function of the survey and the criteria used for the classification. At the same time, this
also means that at $z \ge 2$ a significant fraction of galaxies are already rotationally supported disk
systems, which implies that their dynamical assembly and relaxation must have happened quickly
(at most roughly 3 Gyr at $z \ge 2$). Besides, there is no strong evidence that the TFR zero-point for
rotationally supported galaxies evolves with cosmic time. Hence, because the rotation velocity is
tightly linked to the galaxies’ gravitational potential, this shows that there must have been a
strong interplay between the distribution of DM and the baryons as the galaxies accreted cold gas.

Based on current evidence (see below) and on our understanding of galaxy formation and
evolution, we would expect high-redshift galaxies to be less massive and more gas-rich than in the
local Universe (hence the DM fraction should be either equal to or higher than that at $z = 0$), but
also not yet dynamically relaxed given that the higher gas fractions seen at high redshift should
produce larger velocity dispersion values as well. Such an effect on the dispersion has indeed been
observed (e.g. Stott et al. 2016) but it has also raised the question of whether the measured
velocity dispersions are overestimated or not, that is whether instrumental effects (beam smearing,
for more details see Sect. 5.3) whose impact is expected to be stronger at higher redshift where the
spatial resolution is lower are correctly taken into account or not (e.g. Epinat et al. 2010, 2012; Di
Teodoro & Fraternali 2015; Bouché et al. 2015). Similarly, the question of the evolution of the
DM fraction with redshift is still open. Recent observations do suggest that high-redshift galaxies
require a DM component when modelling their gas kinematics (e.g. Lang et al. 2017; Genzel et al.
2017, 2020; Tiley et al. 2019b; Bouché et al. 2022; Sharma et al. 2021; Price et al. 2021), but some
have nevertheless highlighted that they might have lower DM fractions than in the local Universe
(e.g. Lang et al. 2017; Genzel et al. 2017, 2020; Sharma et al. 2021; Price et al. 2021; Sharma et al.
2021). This observed decrease in DM fraction seems to be inversely correlated with the density of
the stellar disk and the mass of the bulge component (e.g. see Genzel et al. 2020). A few different
explanations can be given. First, some authors, such as Tiley et al. (2019b), have suggested that
the observed trend might be a spurious effect induced by the stacking technique that makes the
average rotation curve appear to fall, hence giving the impression that high-redshift galaxies are
depleted in DM with respect to their low-redshift counterparts. A second important explanation
is related to the radius where the DM fraction is estimated. Indeed, the aforementioned studies
usually use the ionised or molecular gas components to probe the kinematics but neither are
found in the outer parts of the galaxies. In practice, this means that the DM fraction is typically
estimated around the half-light radius of the stellar disk component of the galaxies. On the
contrary, the bulk of the mass of the DM halo is expected to be distributed at much larger
distances (e.g. Courteau & Dutton 2015). Furthermore, galaxies are also expected to build-up
their stellar mass with cosmic time and therefore to grow in size, meaning that the DM fraction of
high-redshift galaxies will be estimated closer to the centre (where the mass of the DM halo is
negligible) than their low-redshift counterparts. Hence, we can imagine a scenario where a galaxy
builds up its stellar mass with cosmic time while retaining the mass and shape of its DM halo. In
this scenario, the DM fraction estimated at the virial radius of the halo will be high at high
redshift since little stellar mass will have had enough time to build up. However, it will decrease
with cosmic time since only the stellar mass will increase with decreasing redshift. On the other
hand, if the DM fraction is estimated at the stellar half-light radius of the galaxy, its value will be
initially relatively low as it will be estimated close to the centre where little DM mass is found
while most of the stellar mass will be concentrated. But, as the galaxy builds up its stellar mass,
its half-light radius will increase so that the DM fraction will be evaluated further out where the
bulk of the DM mass is located, hence increasing the measured DM fraction. Therefore, lower DM
fractions observed at high redshift with respect to local galaxies such as reported for instance in
Lang et al. (2017), Genzel et al. (2017, 2020), Sharma et al. (2021), or Price et al. (2021) are not
necessarily inconsistent with the current model of galaxy formation and evolution as long as the
radius where the DM fraction is estimated is properly taken into account (for a discussion on the
topic, see also Sect. 4.4 of Förster Schreiber & Wuyts 2020).

1.3.3 Impact of galaxies’s environment

As discussed in Sect. 1.3.2, galaxies follow their own secular evolution driven by the accretion of cold gas that is transformed into new stars and regulated by feedback processes. This picture combined with more violent events such as galaxy mergers is supposed to drive their evolution over long timescales in terms of physical properties (e.g. stellar mass, metallicity, SFR, etc.), morphology (build-up of the Hubble sequence with the formation of disks and ellipticals), and kinematics (increase in the fraction of rotationally supported disk systems with large amounts of DM). Nevertheless, the secular evolution of galaxies is not sufficient in itself to explain their observed properties. Indeed, it has now become clear that a major component of galaxy evolution is the impact of their host environment at both low and high redshift. Studies that discuss the effect of the environment focus on four main types: (i) galaxy clusters that are the most massive virialised structures in the Universe (e.g. Muzzin et al. 2009; Balogh et al. 2017), (ii) galaxy groups (e.g. More et al. 2012; Abril-Melgarejo et al. 2021; Mercier et al. 2022), an intermediate type of structure that is smaller than galaxy clusters and that can either be isolated or a substructure of clusters, (iii) the cosmic web that is made of galaxy clusters and groups but also of filaments linking the clusters together (e.g. Umehata et al. 2019; Bacon et al. 2021; Daddi et al. 2021), and (iv) the field, that is the remaining space where there is no detected structures.
Ideally, field galaxies would be located in low-density regions called cosmic voids, but in practice
it depends upon how the classification between field, groups, clusters, or filaments, was done. Among the four types of environment, the cosmic web is the most difficult of all to observe because of its low surface-brightness emission (e.g. Bacon et al. 2021) and was therefore until recently mostly a prediction from cosmological simulations without clear observational counterparts (e.g. Haider et al. 2016; Galárraga-Espinosa et al. 2020), except from the large-scale distribution of galaxies in large spectroscopic surveys such as the SDSS (e.g. Chen et al. 2015; Krolewski et al. 2019; Darragh Ford et al. 2019; Sarron et al. 2019). Throughout recent years, efforts have also been pushed into observing and characterising the properties of the progenitors of low redshift galaxy clusters, called proto-clusters, before they virialised (e.g. Darvish et al. 2020; Champagne et al. 2021).

As discussed further below, based on observational and theoretical arguments, it has been discussed that galaxy clusters could play an important role in quenching star formation and morphologically transforming galaxies. The two main channels through which a galaxy is likely to be affected by the galaxy cluster it is infalling into are (i) through hydrodynamical mechanisms between the relatively cold gas found in the ISM and in the circum-galactic medium (CGM) of the galaxy and the much hotter intra-cluster medium (ICM) and (ii) through gravitational interactions with one or multiple galaxies already located or infalling into the cluster, or directly with the cluster’s gravitational potential (for a review on the topic, see Cortese et al. 2021). The former mechanisms have been proposed to offer pathways through which galaxies can suffer from starvation (also called strangulation), that is the cessation of cold gas accretion from the CGM, which is a prerequisite to quench star formation. The typical physical mechanisms that have been suggested are (i) ram-pressure stripping (Gunn & Gott 1972) which removes the gas located in galaxies because of the pressure exerted by the ICM. Its effect is more efficient for low-mass galaxies, denser structures (i.e. for clusters more than groups), and in the outer parts of galaxies. And (ii) thermal evaporation (Cowie & Songaila 1977) where the cold gas found in a galaxy is heated by the hot ICM which allows it to evaporate and fill the CGM. Such hydrodynamical mechanisms have been predominantly observed in the local Universe (e.g. Boselli et al. 2006; Boissier et al. 2012; Longobardi et al. 2020), though there has been quite recently a first serendipitous discovery at $z \sim 0.7$ in the MUSE-gAlaxy Groups In Cosmos (MAGIC) survey (Boselli et al. 2019), and they are thought to be the driving mechanisms behind the formation of the so-called jellyfish galaxies (e.g. Mercer et al. 2007; Smith et al. 2010; Ebeling et al. 2014; McPartland et al. 2016; Poggianti et al. 2017). On the other hand, gravitational interactions can be summarised into the so-called galaxy harassment effect which is the combined effect of tidal gravitational interactions between an infalling galaxy, the cluster, and the other galaxies found therein across multiple fly-bys. Gravitational mechanisms are important, in particular to account for the morphological transition seen in clusters and to explain the higher fraction of irregular galaxies found in these structures. Note that the aforementioned mechanisms can also affect galaxies in groups. However, some of these mechanisms that can be predominant in galaxy clusters (e.g. ram-pressure stripping) can become marginal in groups because of the groups’ lower gas density and/or shallower gravitational potential. This might be different in proto-clusters where, according to current simulations (e.g. Chiang et al. 2017), galaxy groups are expected to affect the properties (e.g. SFR) of their galaxy members before the clusters formed (i.e. pre-processing; see for instance Fujita 2004).

Multiple studies have tried to detect a visible impact of the environment on galaxies’ physical properties in order to discriminate between different underlying mechanisms. For instance, the stellar mass function (SMF) has been compared between galaxies located in clusters and galaxies
found in the field. Such studies at both low and high redshift have highlighted from the shape of
the galaxy stellar mass function that galaxy clusters contain an excess of massive galaxies and
tend to be depleted in low-mass galaxies (e.g. Peng et al. 2010; van der Burg et al. 2020)
compared to field galaxies at the same redshift. At the same time, galaxies in clusters have on
average systematically lower SFR values at fixed stellar mass (e.g. Calvi et al. 2018; Old et al.
2020b,a; Mercier et al. 2022) and nearly all massive galaxies found in the inner parts of galaxy
clusters are quenched. These facts have therefore raised the question of whether quenching is
environmentally or stellar mass driven in clusters. In the local Universe, it has been shown (e.g.
Peng et al. 2010) that the stellar mass is the driving mechanism for massive galaxies but that
environmental quenching becomes more important for low-mass galaxies. Still, there is a
significant population of star-forming galaxies in clusters and in groups and some of the quenched
galaxies are not located far below the MS. Therefore, this suggests that, if the environment does
help in quenching star formation, it must have happened on relatively short timescales (e.g.
Muzzin et al. 2012; Mercier et al. 2022). Similarly, recent intermediate redshift studies such as
McNab et al. (2021) or Baxter et al. (2022) have shown that massive galaxies at $z \sim 1$ were
certainly quenched prior to their infall into the cluster and that it was also the case for lower-mass
galaxies, though they also suffered from additional quenching by their cluster during their infall.
Furthermore, higher redshift studies ($z \sim 3$) such as those of Sarron & Conselice (2021) and
Lemaux et al. (2022) have rather found that the fraction of quenched galaxies in groups and
clusters decreases with increasing redshift and that the global SFR of these galaxies at fixed
stellar mass increases with increasing redshift. These last contradictory results can be reconciled
with what is observed in the local Universe by remarking that most high-redshift clusters are not
virialised yet. Hence, these studies show that the environment seems to mostly affect the
evolution of galaxies prior to the virialisation of the structures, that is through pre-processing in
high-redshift groups that will assemble into the clusters seen at low redshift.

Finally, galaxy clusters and galaxy groups might also affect the dynamics of galaxies but the
evidence is rather scarce for the moment. From a theoretical perspective, there have been some
claims that gravitational interactions between galaxies in the outskirts of clusters might strip
them of a significant fraction of their stellar content and produce DM dominated dwarfs that are
observed in the local Universe (D'Onghia et al. 2009). If there is a significant fraction of irregular
galaxies found in clusters, then we may expect to find imprints in their gas and stellar kinematics
either by increasing the velocity dispersion or by producing out-of-equilibrium motions with
respect to the bulk rotation of the galaxy. As already discussed before, it is true that samples of
galaxies at higher redshift have a larger fraction of objects with large velocity dispersion or no
clear signs of rotation in their gas kinematics (kinematically disturbed objects, e.g. Förster
Schreiber et al. 2006b, 2009a; Epinat et al. 2009; Law et al. 2009; Contini et al. 2012; Epinat et al.
2012; Contini et al. 2016). However, it is less clear whether this is due to the galaxies still being in
a transitional dynamical state, or whether this is due to merger events that happened recently in
their past, or whether the galaxies' environment plays a significant role through the
aforementioned physical mechanisms associated to galaxy clusters and galaxy groups (e.g. Mendes
de Oliveira et al. 1998; Epinat et al. 2009; Feng et al. 2020). Large surveys specifically designed to
target galaxies in the field, in groups, and in clusters at intermediate and/or high redshift and
with resolved kinematics information, such as the MAGIC survey (Epinat et al., see also
Chapter 3), will certainly help to answer such questions. Ordered rotation in galaxies might also
be affected by their environment, for instance through the removal of their gas or stellar content
(ram-pressure stripping, gas evaporation, etc.; for a review on the topic see Cortese et al. 2021),
by suppressing feedback processes (and therefore affecting the shape of DM haloes in their inner
parts, e.g. Freundlich et al. 2020), or by changing the distribution of baryons (e.g. asymmetric
features or contraction of the distribution, Maltby et al. 2010; Kuchner et al. 2017; Matharu et al.
2019; Mercier et al. 2022). An ideal scaling relation to investigate this effect is the TFR since it
links the stellar and the dynamical contents of galaxies. Indeed, if the environment affects the gas
or stellar kinematics of the galaxies through one of the aforementioned mechanisms then the effect
should be visible in the TFR when comparing galaxies located in low- and high-density
environments. However, until recently only a handful of studies had tried to do so, probably
because of the difficulty to assemble large representative spectroscopic samples of galaxies both in
the field and in clusters or group of galaxies with resolved kinematics data. A few notable
exceptions are the first analysis performed by Pelliccia et al. (2019) using long-slit spectroscopy
and our two analyses presented in Abril-Melgarejo et al. (2021) and Mercier et al. (2022). Though
results may seem conflicting, our current interpretation based on our latest results is that there is
no discernable impact of the environment on the TFR at $z \sim 0.7$, hence at this redshift galaxies in
galaxy clusters or large groups exhibit neither lower nor higher mass fractions of baryons than in
the field. Perhaps even more importantly, our two analyses (Abril-Melgarejo et al. 2021; Mercier
et al. 2022) have shown how systematic effects induced by the comparison carried out between
different surveys can propagate to the dynamical analysis and strongly impact the conclusions if
not carefully taken into account. In this regard, MAGIC with its unique design combined with
the powerful capabilities of Multi-Unit Spectroscopic Explorer (MUSE) (see Sect. 2.2.3) is the
ideal survey to reduce these systematics to their minimum and to provide the best constraints on
the impact of the environment on galaxies’ dynamics at intermediate redshift.

1.4 The Dark Matter enigma

A particularly important quantity that is needed to explain observations in extragalactic astrophysics and in cosmology is DM. Indeed, current estimates of the cosmological parameters find that nearly 85% of the total mass in the Universe, thus excluding dark energy that dominates the energy budget, is composed of DM (Planck Collaboration et al. 2020, 2021). At the same time, DM has become a key component in dynamical models of galaxies and galaxy clusters without which it is nearly impossible to explain the large velocities of the gas and the stars in the galaxies or the amplitude of the gravitational lensing visible in massive galaxy clusters (a typical textbook example would be the bullet cluster, e.g. in Clowe et al. 2004). Furthermore, our current model of galaxy formation and evolution greatly makes use of DM to explain the early formation of DM dominated structures onto which baryons would be accreted to form proto-galaxies and then galaxies (e.g. for an early model of this type see White & Rees 1978b). Thus, DM seems ubiquitous in our current understanding of the Universe and yet its nature still remains a mystery. An opposite view of this “missing mass problem” is to rather consider it as a proof of the limits of the current laws of physics, especially concerning gravity. Throughout the years, various theories have thus been proposed to modify Newtonian gravity on the scales of galaxies and galaxy clusters but their difficulty to conciliate DM-dominated systems (e.g. dwarf or low-surface brightness galaxies, see de Blok & McGaugh 1997; Boldrini 2021) with seemingly DM-poor systems (e.g. Mancera Piña et al. 2022) has raised doubts as to whether such models are sufficient to explain DM.
1.4.1 Dark Matter or modified gravity ?

Historically speaking, early proofs of the gravitational effect of DM came from the pioneering
work of Fritz Zwicky on the Coma Cluster (Zwicky 1933, 1937). His argument was that, based on
the virial theorem and on the measurement of the radial velocities of the galaxies located in the
cluster, there was just not enough luminous mass (by a factor of roughly 400, though
overestimated because he was not aware at the time of the existence of hot gas located between
galaxies) in the galaxies to explain the apparently large velocity dispersion. Hence, he concluded
that there must be some invisible matter that must dominate the mass budget. During the 1970s,
multiple kinematics studies of local galaxies using Hα and cold gas (HI, e.g. Rogstad & Shostak
1972; Roberts & Rots 1973; Rubin et al. 1978a,b, 1980; Bosma 1978, 1981a,b) and of the Milky
Way using dwarf companions (e.g. Ostriker et al. 1974) shed light on the fact that the rotation
curves of galaxies remain constant beyond a certain point, indicating the presence of large amount
of unseen mass. Beside their rotation curves, the galaxy disks were also found to be cold, that is
with very little velocity dispersion. It was shown by Ostriker & Peebles (1973) that such disks
could not remain stable alone in numerical simulations over a Hubble time (i.e. a characteristic
time-scale of the Universe) and that they built-up bar instabilities unless a large spherical halo
with a mass at least equal to that of the disk was added. Though the evidence had become clear,
the nature of this invisible mass was not yet elucidated. For instance, Ostriker et al. (1974)
suggested that it was due to a large number of very faint stars that extended well beyond the
optical radius seen in photographic plates, but other theories were proposed based on white
dwarfs, black holes, or massive baryonic particles. Throughout the 1980s, the leading theory was
that this missing mass was composed of massive neutrinos but disagreements between
observations and simulations and the impossibility to measure a neutrino mass consistent with the
required cosmological value led to a loss of interest. In parallel, a set of new theories where the
missing mass would be made of non-baryonic massive particles were developed. These theories
were labelled as Warm Dark Matter (WDM) and Cold Dark Matter (CDM) and had the
advantage to much better match the temperature fluctuations seen in the CMB and the observed
clustering of galaxies (e.g. Davis & Djorgovski 1985). Nevertheless, there were still discrepancies
and to match even better the clustering new models were developed, among those was suggested
the idea of adding a cosmological constant to the CDM model. Definite proof of the accelerated
expansion of the Universe through the observations of type Ia supernovae and thus of the need of
a non-zero cosmological constant (Riess 1998; Perlmutter et al. 1999) further strengthened the
theory and led to the establishment of our current standard model of cosmology (ΛCDM).
It has become clear from the large amount of rotation curves and 2D velocity fields that have
been studied in the literature, such as the Spitzer Photometry and Accurate Rotation Curves
(SPARCS), Calar Alto Legacy Integral Field Area Survey (CALIFA), or Sydney-AAO
Multi-object Integral field spectrograph (SAMI) samples in the local Universe (Lelli et al. 2016;
Sánchez et al. 2016; Croom et al. 2012) or the Mass Assembly Survey with SINFONI in VVDS
(MASSIV) described in Contini et al. (2012) at high redshift, that nearly every galaxy contains
significant amounts of DM even at high redshift. In parallel, further evidence for the presence of
an invisible mass in galaxy clusters has been found in various ways. For instance this was done
through the measurement of the velocity dispersion of galaxies moving through clusters (as
Zwicky did), which requires enough unseen mass for the galaxies to remain gravitationally bound
to the structure, through the measurement of the temperature of the hot X-ray emitting gas
located in the ICM, which requires enough mass so that the gas remains in hydrostatic
equilibrium, or through the gravitational lensing effect of some clusters on background sources
(e.g. Richard et al. 2021). More historical details about evidence for the missing mass problem
can be found for instance in Sanders (2010). Alternatively to the development of the DM theory,
other alternative theories of gravity started to be developed during the 1980s, the most famons
being the Modified Newtonian dynamics (MOND) first described in Milgrom (1983). A common
feature in such theories is that they describe the missing mass problem by changing the laws of
gravity and thus the dynamics of a system. This introduces a typical acceleration $a_0$ that acts as
an additional constant above which Newtonian dynamics is recovered and below which the
effective acceleration that appears in Newton’s first law of gravity is proportional to the square of
the intrinsic acceleration (i.e. for $a \ll a_0$ we have $F \propto ma^2$, with $m$ the gravitational mass and $a$
the intrinsic acceleration). Thus, for any mass distribution which can be reduced to a point mass
when seen sufficiently far away we find that $GM/r^2 \propto a^2 \propto V^4/r^2$, which corresponds to a flat
rotation curve at large radii. Despite the clear appeal of alternative theories of gravity there have
been a few difficulties that have slowed down their development. A first point that needs to be
taken into account is that they must be applicable on scales for which DM is necessary. This
includes galaxies and galaxy clusters but also cosmological scales since DM is required to produce
the large scale structure of the Universe, the so-called cosmic web. A second important point is
that, by construction, such theories predict that the dynamics of the systems is tightly linked to
their baryonic content (stars, gas, dust, etc.). Hence, there must be an additional effort made to
explain outliers where such links are not observed such as, for instance, the recent DM-poor
galaxy presented in Mancera Piña et al. (2022)<fnref n="2" /> or the bullet cluster whose observed mass
distribution does not match the total mass distribution derived with gravitational lensing.
Therefore, for the time being the leading theory has remained that the missing mass in galaxies
and galaxy clusters is linked to DM. Nevertheless, this does not mean that a compelling
alternative theory of gravity might hypothetically emerge in the near-future and provide us with
an answer to mystery that is DM from a dynamical standpoint.

1.4.2 Current questions regarding Dark Matter

Even if ΛCDM and therefore DM have become nowadays the leading theories, this does not mean
that there are no remaining questions concerning them for which we do not have definite answers
yet. The most obvious unanswered question regarding DM is concerning its nature itself. If DM is
indeed composed of still undetected new particles, then the answer is ultimately likely to come
from particle physics. Nevertheless, extragalactic astrophysics remains a privileged laboratory
that can be used to put constraints on which type of particles might be appropriate for DM. The
details how this is achieved actually go beyond the scope of this Thesis, and also to some degree
of my current understanding, but I can nevertheless mention one survey that I am aware of,
MUSE-FAINT (Zoutendijk et al. 2020), that used observations of ultra-faint dwarf galaxies to put
constraints on various models of DM: massive astrophysical compact halo object (MACHOs),
self-interacting and fuzzy DM, and axion-like particles (Zoutendijk et al. 2020, 2021a,b; Regis
et al. 2021). However, current questions regarding DM do not reduce solely to its nature. For
instance, one of such key question is whether structure formation happened quicker than what
ΛCDM predicts. Evidence that it might be so are the too large number of very luminous galaxies

<footnote n="2">²Note that some galaxies may seem to be outliers not because of the theory used but because of uncertainties propagating to the dynamical modelling, including the galaxy inclination, the distribution of stars and gas, or the mass-to-light ratio of the various baryonic components in the galaxy (e.g. stellar disk, stellar bulge, cold gas disk, etc.).</footnote>
in the Local Volume and a too low number of galaxies in the Local Void, as well as the existence
of massive clusters at high redshifts (e.g. Mortonson et al. 2011). Another current challenge is
concerning the missing satellite problem of the Milky Way which states that there may be not
enough (low-mass) satellites around it compared to predictions from ΛCDM simulations (Moore
et al. 1999; Strigari & Wechsler 2012).

There exist other discrepancies between observations and ΛCDM simulations, in particular
towards the formation of bulgeless and low-surface brightness galaxies, but one question that is
particularly important with respect to my field of expertise is regarding the cusp-core problem.
This is a long-standing issue between observations and predictions from DM-only simulations that
do not agree on the slope of the DM profiles in the inner parts. Early simulations of the collapse
of DM haloes such as those performed by Navarro et al. (1997) clearly showed that the inner
logarithmic slope (d log ρ/d log r, with ρ the density) could be fitted by a universal value of minus
unity which led to the establishment of the now famous Navarro-Frenk-White (NFW) profile.
Thus, simulations predicted that DM haloes are cuspy. On the other hand, early mass models
performed on the rotation curves of local galaxies showed that they must have a constant density
in the inner parts, hence that they have a core (e.g. Moore 1994; Burkert & Silk 1997; Salucci
2001). This result still holds nowadays with nevertheless some measurements that might point out
towards cuspy DM haloes but still with a shallower slope than what ΛCDM predicts (e.g. Chemin
et al. 2011), though more recent results would suggest that core profiles are preferred over cuspy
ones (e.g. Korsaga et al. 2018, 2019a,b). At higher redshift, the picture is more complex because of
stronger instrumental effects that affect kinematics observations (see Sect. 5.2.4.5 for a discussion
on that topic with our data). Still, a few years back a seminal analysis performed by Genzel et al.
(2020) using rotation curves showed evidence that galaxies at z ≈ 2 host core DM profiles. During
the following year, we further strengthened this evidence in Bouché et al. (2022) by performing
mass models on 2D velocity fields of z ≈ 1 galaxies using data from the MUSE Extremely Deep
Field (MXDF). The current explanation that is given to solve the apparent discrepancy in the
inner slope is that DM haloes are originally cuspy by nature, but that there must exist at least
one mechanism that sufficiently heats the halo so that it removes some DM particles in the inner
parts, thus transforming the cuspy initial profile into a core one. Suggested physical processes
that can heat DM particles enough are (i) dynamical friction induced by the passage of, for
instance, a satellite galaxy, a globular cluster, or even just a collection of gas clouds (e.g. El-Zant
et al. 2001; Romano-Díaz et al. 2008; Nipoti & Binney 2014) or (ii) feedback processes from
supernovae, from an AGN, or from stellar winds (e.g. Read & Gilmore 2005; Madau et al. 2014;
El-Zant et al. 2016; Dutton et al. 2016; Freundlich et al. 2020). Hence, even if we have
fundamentally found some plausible solutions to the cusp-core problem, the questions of which
mechanism plays a leading role and whether these explanations are enough at high redshift where
DM profiles have had less time to be affected by baryonic processes are still a matter of debate.
Chapter 2

Spectroscopy in extragalactic
astronomy

There are two main types of observations (in terms of electromagnetic radiation) that can be
carried out in extragalactic astronomy: imaging and spectroscopy. Both are actually two pieces of
the same puzzle. Imaging can be seen as providing spatial information over a spectrum that has
been integrated over a sufficiently large spectral window, whereas spectroscopy can rather be seen
as the opposite, that is as a spectrum that is spectrally resolved but spatially integrated over a
given aperture. Because the various constituents of a galaxy (e.g. stars, gas, dust, etc.) do not
emit in the same way, we can recover their spectral signatures and infer from them some physical
properties such as the presence of some chemical species, their relative abundance, the amount of
extinction due to dust, or the gas and/or stellar velocity just to cite a few. Therefore, spectra are
key observations because they are fundamental to extract major physical quantities useful to
study the evolution of galaxies that would otherwise be very difficult, if not impossible at all, to
obtain. Furthermore, the spectra of galaxies are also affected by their motion and by the
expansion of the Universe. Thus, they are also key observations to derive, when possible, precise
cosmological redshifts that are in turn useful to correctly derive galaxies' physical properties that
depend on their distance to us such as their stellar masse or SFR.

In this section, I therefore give a brief overview of spectroscopy as it is used in extragalactic
astronomy. I will restrict the discussion to the optical and IR since these are the parts of the
spectrum that I have worked with during this Thesis. In particular, I will focus on integral field
spectroscopy which is the observing technique that I have been using the most during this Thesis.
I begin in Sect. 2.1 with a description of the fundamental principles behind modern spectroscopy
such as how spectra are currently obtained and I give a brief overview of the physics behind the
main spectroscopic features seen in galaxy spectra. Then, in Sect. 2.2 I focus on integral field
spectroscopy. I give an historical overview of the development of the discipline, from the early
instruments to the current and next generation instruments that are or shall be installed on future
telescopes. In particular, I focus my discussion on MUSE which is the main instrument that I
have been using during this Thesis.
## 2.1 Principles of spectroscopy

The first astronomical application of spectroscopy was performed by J. R. von Fraunhofer at the beginning of the nineteenth century by observing the Sun and then other stars which led him to discover the presence of absorption lines now known as Fraunhofer lines. Since then, the field of spectroscopy has greatly changed and is now not limited to the sole study of nearby stars. Historically, spectroscopic studies such as the one performed by J. R. von Fraunhofer were limited to integrated spectra, that is spectra taken within a given aperture. These had the advantage of allowing to observe relatively faint objects since their total light was integrated but at the cost of a loss of spatial information. The core concept of spectroscopy is to disperse the incoming light but there are multiple techniques that allow doing so. The oldest one is through the use of a prism that will disperse the light in different directions because of the variation of the prism's material index of refraction with wavelength. A second technique is to use a dispersion grating which is an optical component made of a series of equally spaced ridges (reflective grating) or slits (transmissive grating) that will diffract the incoming light when passing through a slit or when being reflected on a ridge. The result is a diffraction pattern due to the superposition of the waves from each slit/ridge with a succession of light intensity peaks and valleys. The important point is that the position of the peaks and valleys (defined by their order) are determined by the distance between each slit/ridge in the grating and by the wavelength of the incoming light. Thus, gratings act as dispersive systems and produce a spectrum for each order (except the zeroth one). However, there are two caveats with such systems: (i) consecutive orders will partially overlap with each other because of the wavelength dependence of the dispersion and (ii) for a given order, there is a maximum wavelength beyond which the light cannot be dispersed any more by the grating. Dispersion gratings that are optimised to focus the light for a given order and central wavelength are called blazed or echelette gratings. A last technique that uses both previous concepts is called a grism. It corresponds to a prism with one of its face manufactured as a dispersion grating.

The lack of spatial resolution in integrated spectra quickly led astronomers to use dispersive systems in combination with slits. This technique, called long-slit spectroscopy, consists in placing a slit before the dispersive system so that the resulting spectrum is dispersed onto the detector perpendicular to the slit orientation. This way, it is possible to obtain some spatial information but only in 1D. Despite their relative simplicity compared to more complex designs discussed below, long-slit spectrographs have been and are still widely used, as is the case for instance with the DEep Imaging Multi-Object Spectrograph (DEIMOS) described in Faber et al. (2003) and used for the Observations of Redshift Evolution in Large-Scale Environments (ORELSE) survey (Lubin et al. 2009). The main difficulty with long-slit spectroscopy when observing galaxies is that one must place the slit in advance on the target which requires to know its position and the slit orientation. For instance, to measure the velocities within a galaxy the ideal case is when the slit is positioned along the galaxy's major axis to minimise projection effects, which therefore requires to have this information prior to placing the slit. Historically, one way to circumvent this issue and to produce spatially resolved observations of galaxies with long-slit spectroscopy was to scan the slit along a given direction while keeping the same orientation. However, such observations lacked precision and were laborious, thus not very efficient. In the mean-time, two other scanning methods had been developed that relied on the principle of interference rather than diffraction: Fourier Transform Spectroscopy (FTS) and Fabry-Pérot spectroscopy. The former uses a Michelson interferometer to make the incoming light interfere with itself which produces an interference pattern on the detector. By varying the distance between the two arms
of the instrument and recording the interference pattern, one recovers an output signal at each position in the field that is the Fourier transform of the input spectrum. The latter technique uses two parallel semi-reflective blades that only let pass through wavelengths that are in resonance with the distance between the two blades, thus selecting only a fraction of the full spectrum. By changing the distance between the blades, it is thus possible to scan the full spectrum. During the 1980s and 1990s, new optical designs were suggested to overcome the issues imposed by scanning devices. These designs that involved the use of fibres coupled with arrays of micro-lenses or image slicers would become what is nowadays called integral field spectroscopy. An historical overview of these new instruments is given in Sect. 2.2.

## 2.2 The rise of Integral Field Spectroscopy

In what follows, I provide a short historical overview of the development of the field of Integral Field Spectroscopy from early proof of concepts with the development of the Traitement Intégral des Galaxies par l'Etude de leurs Raies (TIGER) spectrograph, going through the different generations of instruments, to MUSE that is discussed in Sect. 2.2.3. I conclude this section by mentioning other current valuable Integral Field Spectrograph (IFS) instruments and what might be expected from the next generation that will be installed on the future Extremely Large Telescopes (ELTs).

### 2.2.1 Pioneering concepts: TIGER, OASIS, and SAURON

The early concept of Integral Field Spectroscopy was suggested by George Courtès in 1980 during the “Premier colloque national du comité francais du télescope spatial: Applications de la photométrie bidimensionnele à l’Astrophysique” (First colloquium of the french committee of the space telescope: applications from 2D photometry to Astrophysics) in Toulouse (Lachieze-Rey 1980). A second publication, in English this time and much easier to find, was published in 1982 (Courtès 1982) where two IFS designs were presented, both implementing an array of lenses. The first design uses an array of lenses located at the focus of the telescope that splits the field-of-view (FoV) into multiple parts. After passing through an optical system composed of a prism or a grism, the spectra are cast onto a detector. The second design is an improved version of a previous concept that was proposed and developed by Vanderriest (1980). The idea is to use optical fibres, to split the FoV, whose ends are re-arranged into a line that feeds a slit spectrograph. George Courtès noticed that because of the fibres’ design a significant fraction of the incoming flux is lost with this system and he therefore improved it by adding an array of lenses before the fibres. This way, each lens focuses the light onto the central parts of the fibres where the flux loss is marginal. During the 1980s, the first design was developed by a collaboration between the observatories of Lyon and Marseille. This first prototype, named TIGER<fnref n="1" />, was run for the first time at the CFHT in 1987 (Bacon et al. 1995) and operated on a regular basis from 1990 to 1996. TIGER was truly the first operational IFS instrument in the world that integrated George Courtès’ idea. It acted as the first proof-of-concept that showed to the world the feasibility and the powerful capabilities of such an instrument compared to already existing devices (long-slit scanning, Fabry-Pérot, etc.) and it therefore paved the way for the

<footnote n="1">¹As explained in Bacon et al. (1995) the name is actually a pun since the instrument shared the same cage as another instrument named PUMA.</footnote>
development of modern 3D spectroscopy. It had a quite small FoV of either 7" × 7" or 10" × 10"
in spectrographic mode and observed in the visible part of the spectrum with a spectral resolving
power varying from R ~ 350 to R ~ 2000 depending on the filter used. Thus, TIGER was mainly
used to study compact objects such as galactic nuclei (e.g. Bacon et al. 1994; Durret et al. 1994),
though science topics diversified throughout the years (T Tauri stars, quasars, gravitational
lenses, etc.) as the design of the instrument and its associated reduction software converged to
their final forms (see Emsellem 1999).

<figure><img src="image_7.png" /><figcaption>Figure 2.1: Original design of the TIGER Integral Field Spectrograph from Bacon et al. (1988) based on a first concept proposed by Courtes (1982). The combination of an array of micro-lenses with a grism allows to split the FoV and produce one spectrum per spatial element.</figcaption></figure>

The development of the Adaptive Optics (AO) bonnette for the CFHT and the requirements to
collect a large number of spectra on a small FoV with a large spatial sampling led to the
decommissioning of TIGER that was replaced by the Optically Adaptive System for Imaging
Spectroscopy (OASIS) spectrograph. This new IFS instrument built by the observatory of Lyon
under the supervision of Roland Bacon was specifically designed to be used with the bonnette.
After preliminary tests at the Observatory of Haute-Provence (OHP), the instrument was shipped
to Hawaii where it ran for the first time in 1997 and in 1998 for the beginning of the scientific
phase where it observed among other things T Tauri stars (e.g. Lavalley 2000), the stellar
dynamics of galactic nuclei and bars (e.g. Emsellem 1999; Bacon et al. 2001), radio galaxies (e.g.
Rocca-Volmerange et al. 2000), as well as quasars (e.g. Ledoux et al. 1998). In 2002, the
instrument was decommissioned and brought back to Lyon before being installed on the William Herschel Telescope (CFHT) in 2003 (Rutten 2000). When installed on the CFHT, its hexagonal FoV varied from 2.7" × 3.7" to 12" × 16.7" over roughly 1100 spatial elements with a spectral resolving power going from $R \sim 1100$ to $R \sim 4300$ (depending on the spectral configuration) in the optical.

<figure><img src="image_8.png" /><figcaption>Figure 2.2: Examples of early velocity fields from TIGER ([NII] gas kinematics for M51, Bacon et al. 1988), OASIS (stellar kinematics for NGC 4621, Wernli et al. 2002), and SAURON (stellar kinematics for NGC 3377, Bacon et al. 2001). We can see the variation in spectral resolution and the transition from the small FoV IFS instruments, TIGER and OASIS, to a larger FoV with SAURON.</figcaption></figure>

Following the conception of TIGER and OASIS a collaboration between the observatories of Lyon, Leiden, and the University of Durham decided to build another IFS instrument in the footsteps of OASIS but dedicated to the study of the stellar and gas dynamics of nearby galaxies. Indeed, even if OASIS could study galaxy kinematics, its small FoV limited it to the inner regions such as the nucleus or the bar. Thus, the Spectroscopic Area Unit for Research on Optical Nebulae (SAURON) instrument was commissioned on the WHT early 1999 (Miller et al. 2000; Bacon et al. 2001) and operated until 2014. It was a large FoV and quite high throughput (about 35% for the optics, 14% in total) IFS instrument also using an array of 1520 square micro-lenses. Two observing modes were provided by the instrument: (i) a low spatial resolution mode with spatial pixels (spaxels) of nearly 1" × 1" spanning a large FoV of 33" × 41" and (ii) a high spatial resolution mode with spaxels of 0.26" × 0.26" spanning a smaller FoV of 9" × 11". Even though the optics were optimised to observe between 4500 Å and 7000 Å, it was commissioned with a single filter in the range 4180 Å – 5400 Å which contains bright emission and absorption lines for nearby galaxies such as Hβ or [OIII]λ5007. Because it was specifically designed to study the galaxies' kinematics, the instrument also had low spectral sampling of nearly 1 Å per spectral pixel (spexel) and a Line Spread Function - LSF Full Width at Half Maximum (FWHM) of nearly three spaxels. As a comparison, this is equivalent to the spectral sampling of OASIS in its high spectral resolution configuration which had a spectral coverage twice narrower (or equivalently a sampling twice lower than that of the medium resolution configuration which had roughly the same spectral coverage as SAURON). Its main science objective was the dynamical analysis of a sample of 72 nearby spiral, lenticular, and elliptical galaxies that led to the SAURON project with, as of December 2022, roughly 70 papers starting with Bacon et al. (2001) and including the
ATLAS<sup>3D</sup> series (e.g. see Cappellari et al. 2011a).

Examples of early velocity fields for the three instruments are shown in Fig. 2.2 (left: TIGER, middle: OASIS, and right: SAURON). The leftmost velocity field was obtained from the first observations made with TIGER on the nucleus of M51 (Bacon et al. 1988), the middle one from Wernli et al. (2002) was observed a few years after the beginning of the observing runs with OASIS and shows the existence of a counter-rotating core with respect to the rotation of the galaxy’s disk in NGC 4621, and the rightmost velocity field was an early result for the first observations carried out with SAURON on NGC 3377 (Bacon et al. 2001). Apart from a clear variation in spectral resolution, we can also see how the instruments evolved from small FoVs focussed on the nuclear regions of galaxies to larger FoVs that can observe the larger disk kinematics.

## 2.2.2 First-generation instruments

The forefathers of the IFS instruments showed how promising integral field spectroscopy could become using the design with an array of micro-lenses. At the same time, improvements in the conception of fibre bundles and the development of MOS such as the VIsible Multi-Object Spectrograph (VIMOS), presented in Le Fevre et al. (1998), also motivated the scientific community to install a first generation of IFS instruments on large telescopes such as the Very Large Telescope (VLT), the KECK telescopes or the Gemini Observatory (Gemini). In addition, independently of the work achieved by the teams in Lyon and Marseille, another one at the Max-Planck-Institut für extraterrestrische Physik (MPE) developed a new design, observing in the IR, and based on the concept of an image slicer that, as the name suggests, slices the FoV into stripes that are then fed into a long-slit grism spectrograph. This instrument, named 3D-MPE, was deployed as early as 1993 in various locations from the WHT to the 2.2 m MPG-ESO telescope in La Silla, Chile (Cameron et al. 1993; Krabbe et al. 1995) and was the foundation for the modern SINFONI instrument. SINFONI was a first-generation IFS instrument in collaboration between MPE and ESO that was installed on the UT4 platform of the VLT. The instrument made use of the image slicing technique and of its own natural guide star AO system (applicable for the 3" and 0.8" modes only, see below). It was specifically designed to individually study distant objects and therefore it observed in the IR with a narrow FoV of either 8" × 8", 3" × 3", or 0.8" × 0.8" (pixel scale of 125 × 250 mas, 50 × 100 mas, or 12.5 × 25 mas, respectively; see Thatte et al. 1998). It led to significant surveys such as the Spectroscopic Imaging survey in the Near-infrared with SINFONI (SINS) and the zCOSMOS-SINFONI (zC-SINF) survey that studied the dynamics of a sample of high redshift (e.g. Förster Schreiber et al. 2006a, 2009b, 2014, 2018; Cresci et al. 2009; Shapiro et al. 2009; Mancini et al. 2011; Newman et al. 2012, 2014; Tacchella et al. 2015), the MASSIV that probed 84 star-forming galaxies in the range 0.9 ≤ z ≤ 1.8 (e.g. Epinat et al. 2009; Contini et al. 2012; Epinat et al. 2012; Vergani et al. 2012; López-Sanjuan et al. 2013b; Divoy et al. 2014), and the Lyman-break galaxies Stellar populations and Dynamics (LSD) and Assessing the Mass-Abundance redshift[-Z] Evolution (AMAZE) surveys that were designed to study the chemical content of high redshift (z ≥ 3) Lyman-break galaxies (LBGs) (e.g. Maiolino et al. 2008; Mannucci et al. 2009; Gnerucci et al. 2011).

Another first-generation instrument that hosts an IFS but this time on the UT2 platform is the Fibre Large Array Multi-Element Spectrograph (FLAMES). FLAMES is a fibre facility installed in 2002 (Pasquini et al. 2002) whose goal was to perform MOS spectroscopy over a large FoV of 25' in diameter. It hosts two different spectrographs, one of which is GIRAFFE, a medium to
high-resolution spectrograph that observes in the visible but with three different modes:
(i) MEDUSA that performs spectroscopy for 132 targets simultaneously over the entire FoV,
(ii) the IFU mode that can perform integral field spectroscopy for 15 different targets using deployable Integral Field Units (IFUs) but with small FoVs of roughly 3" × 3", and
(iii) ARGUS, a single IFU with a larger FoV of 12" × 7" (Pasquini et al. 2000). The IFU mode of FLAMES-GIRAFFE is particularly interesting because it used for the first time multiple IFUs to probe a larger FoV (Flores et al. 2004). Both the IFU and ARGUS modes nevertheless provide low spatial sampling with only 20 spaxels for the former and 14 × 22 spaxels for the latter. Its most significant survey is the Intermediate MAss Galaxy Evolution Sequence (IMAGES) survey that probed 63 galaxies at $0.4 < z < 0.75$ to study their dynamics (e.g. Flores et al. 2004, 2006; Puech et al. 2006a,b, 2007, 2008b, 2010, 2014; Yang et al. 2008; Neichel et al. 2008; Rodrigues et al. 2008).

One last first-generation instruments that has also contributed significantly to the field of extragalactic astrophysics and to integral field spectroscopy is OH-Suppressing Infra-Red Imaging Spectrograph (OSIRIS). It is an IFS instrument specifically designed to be used on the KECK telescopes with its AO system. It saw its first light in 2005 and operated in the IR. Its design is similar to most of the other IFS instruments in the sense that it also uses an array of micro-lenses with fibre bundles. Its FoV is not larger than any other IFS instrument in operation at the time but the fact that it is used at the KECK telescopes with its AO system makes the observations diffraction limited. Thus, it provided high resolution observations with a spatial sampling varying from 0.1" per spaxel for the coarsest mode to 0.02" per spaxel for the finest one (Larkin et al. 2000, 2006) and with a Point Spread Function - PSF FWHM of about 0.1" (e.g. Wright et al. 2007). For instance, Wright et al. (2007); Law et al. (2009); Wright et al. (2009, 2010); Law et al. (2018) used it to study the spatially resolved kinematics of a small sample of $z \sim 2-3$ galaxies as a function of their morphology and AGN activity.

### 2.2.3 The MUSE revolution

After the success of the first generation of IFS instruments installed on large telescopes there was a need for a second generation with improved capacities in terms of FoV and sensitivity to study statistically significant samples of intermediate and high redshift galaxies. These new instruments, such as the K-band Multi Object Spectrograph (KMOS) and MUSE, were designed in a context where large photometric and spectro-photometric surveys such as the The Two Micron All Sky Survey (2MASS) (Skrutskie et al. 2006), the All-Wavelength Extended Groth Strip International Survey (AEGIS) (Davis et al. 2007), the Great Observatories Origins Deep Survey (GOODS) (Dickinson et al. 2003), the Cosmic Evolution Survey (COSMOS) (Scoville et al. 2007), or the SDSS (Gunn & Knapp 1993) had already shed light on the large scale structure of the Universe. Similarly, these surveys had already started probing the global properties of galaxies as a function of redshift and environment. Nevertheless, the study of the physical processes taking place on resolved scales were still limited to relatively small samples of galaxies from previous IFS instruments. Thus, in the course of 2001, ESO defined four main scientific objectives that required specific instruments, two of which were (i) a near-infrared (NIR) MOS instrument to study high-redshift galaxies and (ii) a 3D spectrograph with a large FoV. The former instrument that was selected for this call is KMOS (see Sect. 2.2.4) and the latter is MUSE, which was suggested by Roland Bacon (Monnet 2002).

MUSE is a multi-IFU IFS instrument with a FoV of 1' × 1' in wide-field mode and a high
<figure><img src="image_9.png" /><figcaption>Figure 2.3: Illustration of the field splitting and image slicing for MUSE taken from Weilbacher et al. (2020). The original FoV is shown on the left-hand side, the field splitting in 24 parts in the middle, and the final image slicing in 48 parts that is done for each of the 24 IFUs on the right-hand side. Each slice is then fed to a spectrograph and its resulting spectrum is imaged on the corresponding CCD.</figcaption></figure>

sensitivity that was designed to study large samples of intermediate and high redshift galaxies. It was built by the MUSE consortium that gathers the Leibniz Institute for Astrophysics Potsdam (AIP), Centre de Recherche Astrophysique de Lyon (CRAL), Eidgenössische Technische Hochschule Zürich (ETH), Institut de Recherche en Astrophysique et Planétologie (IRAP), Institute for Astrophysics and Geophysics (IAG), Leiden University, and ESO. Similarly to SINFONI, it also implements an image slicer rather than an array of micro-lenses to feed the FoV into multiple spectrographs (Henault et al. 2003). Its large FoV which is one of the key characteristics of the instrument is further achieved through the use of a field splitter and 24 IFUs as illustrated in Fig. 2.3. The way this is done is roughly speaking as follows: 1. the FoV is split into 24 sub-fields that are each fed to a single IFU, 2. each sub-field is cut into 48 slices following the pattern shown in Fig. 2.3, and 3. each slice is sent into the spectrograph that disperses its light vertically into the corresponding Charged-Coupled Device (CCD). These steps produce 24 output images of 4224 × 4240 pixels as shown on the left-hand side of Fig. 2.4. Each image has the 48 spectra dispersed vertically into four quadrants. The cross splitting the quadrants in the middle corresponds to the overscan region of the CCD whereas the two strips on both sides are pre-scan regions. Both are required by the CCD to read the data. Such raw data cannot be used directly and a full reduction pipeline must be applied to go from these 24 images to the final data cube (see the right-hand side of Fig. 2.4 for a narrow-band image around $H\alpha$ for the same observation). Since I directly worked on already reduced MUSE data and that I never performed the reduction steps myself during this Thesis, I will not discuss it further and I will redirect the interested reader to Weilbacher et al. (2020) where the latest reduction pipeline is described in details. Technically, MUSE can operate in two modes: wide-field and narrow-field mode. The difference
between the two is that the narrow-field mode operates over a narrower FoV of 7.5" × 7.5" with a spatial sampling of 25 mas per spaxel that is similar to space-based optical observations. This mode can be interesting for observations that require a finer spatial scale without a higher spectral resolving power over a narrower FoV but with the high sensitivity of MUSE and its IFS instrument capacities (e.g. to study AGNs such as in Winkel et al. 2022). Nevertheless, the most widely used mode is the wide-field one which is what I have been using. Therefore, in what follows, I will not discuss further the narrow-field mode. The output of the wide-field mode is a data cube of 1' × 1' with a spatial sampling equal to 0.2" per spaxel, spanning a wavelength range that goes from 4650 Å to 9300 Å with a spectral sampling of 1.25 Å per spaxel.

<figure><img src="image_10.png" /></figure>

Figure 2.4: Illustration of a raw (left-hand side) and fully processed (right-hand side) MUSE observation taken from Weilbacher et al. (2020). The raw image is the output of the tenth IFU’s CCD whereas the processed image corresponds to the entire FoV around the Hα wavelength. The central cross and the sides of the raw image correspond to the overscan and pre-scan of the CCD, respectively. There are 48 spectra aligned vertically in the raw image with the blue end at the bottom and the red end at the top.

Another interesting aspect of MUSE is that since summer 2017 it can operate with the AO module GALACSI (Ströbele et al. 2012) using four sodium laser guide-stars installed on the UT4 platform of the VLT. After being emitted, the light of the lasers will be absorbed and re-emitted by the sodium layer of the atmosphere that will be then observed by specific sensors on the ground. The wavefront distortion due to the turbulence in the lower parts of the atmosphere will then be computed so that a real-time correction is constantly applied to the primary mirror of the telescope. Without AO, MUSE already performs well with a PSF FWHM at around 6000 Å in good atmospheric conditions which is around 0.7". With AO and if the turbulence is mostly in the lower parts of the atmosphere, the PSF FWHM can reach around 0.4" at the same wavelength. Actually, the spatial resolution will be slightly worse at bluer wavelengths and slightly better at redder ones because of once again the turbulence that will more severely affect the blue part of the spectrum (see for instance Fig. 2 of Bacon et al. 2015). A second key characteristics of the instrument that has already been mentioned before is its high sensitivity. Combined with its large FoV, this gives MUSE the possibility to observe a large number of galaxies over relatively
short integration times and to probe low-mass galaxies down to $10^7 M_\odot$ that could hardly be observed and studied in a statistically significant manner with previous IFS instruments.

Furthermore MUSE observes continuously across its FoV, contrary to complementary instruments such as KMOS that rather observes galaxies individually over smaller FoVs but across a larger patrol field, which means one can perform blind source detection across the FoV without prior selection (except the field location) as was done for instance in the MUSE Hubble Ultra Deep Field (MUSE-HUDF) and in the MXDF respectively described in *Bacon et al.* (2017) and *Bacon et al.* (2021). All these characteristics therefore render MUSE a particularly powerful instrument to study the evolution of galaxies at intermediate to high redshift.

<figure><img src="image_11.png" /></figure>

Figure 2.5: Redshift interval for the main emission and absorption lines as well as spectral features detected with MUSE. The left-hand side plot shows the full redshift range over which detections can be made and the right-hand side plot focusses on the [O II] emitters range. The oxygen lines are shown in blue, the Balmer lines in black, the absorption lines in orange, and Lyα in red. The Balmer and Lyman breaks are also indicated with grey lines. The background color indicates whether no line (grey), a single line (red), two lines (orange), or three or more lines (blue) are available in the given spectral window. The background colors on the right-hand side are different because they only take into account emission lines whereas on the left-hand side the colors also take into account the absorption lines (but not the breaks). As an indication, the spectral window that is unavailable because of the sodium laser when the AO system is used is shown as the horizontal hatched yellow region.

MUSE is sensitive to two main types of galaxies: (i) those with a bright stellar continuum that are visible across the entire wavelength range and (ii) those with bright emission lines, independently of the continuum, that are usually associated to high star formation or to an AGN activity. A galaxy can obviously have both a strong continuum and emission lines at the same
time, so the two types are not mutually exclusive. Besides, those with a strong enough continuum
can also have stellar absorption lines and, in the right conditions, fainter emission or absorption
lines can also be detected. I do not show examples of MUSE spectra in this section because a few
that are relevant for the MAGIC survey are already presented and discussed in Chapter 3. In
practice, both emission and absorption lines, combined with a few spectroscopic features (e.g.
Balmer break) when they are visible, are used to derive a spectroscopic redshift. The details of
how this is done can be found in Sect. 3.2.2 for the MAGIC survey and in the relevant survey
papers (see below) for the others. Nevertheless, the reliability of the derived spectroscopic redshift
and the detection itself, especially in the case of emission line galaxies, highly depends on the
number of strong enough spectroscopic features that fall within the MUSE wavelength range.
Incidentally, such features being limited in number and located at fixed rest-frame wavelengths,
they restrict the redshift intervals within which galaxies might be securely detected. I show in
Fig. 2.5 the observed wavelength of the main emission and absorption lines, as well as the Balmer
break and the Lyman break, as a function of redshift. This figure therefore shows the redshift
window over which such features may be detected. At low and intermediate redshifts, the main
absorption lines are the Balmer lines, CaII H&lambda;3968.47, CaII K&lambda;3933.68, and the G-band from CH
molecules, and bright emission lines are also the Balmer lines, [OII]&lambda;&lambda;3727, 3729, and [OIII]. We
can see that the redshift range where most of the lines are detected is below z = 1.5. In
particular, when H&alpha; disappears the [OII] doublet enters the wavelength range around z &asymp; 0.2.
This interval (0.2 &le; z &le; 1.5) is what we will refer to in the next chapters as the [OII] emitters
redshift range since it is usually the brightest line available in this range that I used to model the
dynamics of galaxies (see Chapters 3 and 5 for more details). At higher redshift (z &ge; 3), Ly&alpha;
becomes detectable because it is a bright line with a complex and easily identifiable profile that
originates from the propagation of resonant Ly&alpha; photons in neutral gas within the interstellar
medium and/or in the vicinity of galaxies. However, between redshifts z = 1.5 and z &asymp; 3 we see
that there are neither bright emission nor absorption lines available which renders the
determination of secure spectroscopic redshifts difficult. This spectral window is referred to as the
MUSE redshift desert. A few fainter lines such as Mg II&lambda;&lambda;2796, 2803 and CIII]&lambda;&lambda;1907, 1909 are
nevertheless available, so it is still possible to measure a few redshifts in this range.

The powerful capabilities of MUSE compared to previous generations of IFS instruments have led to numerous studies on a plethora of topics since the instrument saw its first light in 2014 (Bacon et al. 2014). Thus, it would be beyond the scope of my current knowledge to give a full account of every subject that has been addressed using MUSE. Therefore, in what follows, I only cite a few important broad topics that have used both Guaranteed Time Observation (GTO) and non-GTO data. These topics include among many others: (i) probing the dust and gas structure of planetary nebulae (e.g Walsh et al. 2016; Monreal-Ibero & Walsh 2020), (ii) performing spectroscopy and studying the dynamics of a large number of stars found in globular clusters (e.g. Husser et al. 2016; Kamann et al. 2016, 2018; Voggel et al. 2016), (iii) studying the stellar kinematics of local and intermediate redshift galaxies (e.g. Emsellem et al. 2014; Krajnović et al. 2015, 2018; Guérou et al. 2016; Guérou et al. 2017), (iv) studying the dynamics and/or angular momentum of intermediate redshift galaxies (e.g. Contini et al. 2016; Swinbank et al. 2017; Bouché et al. 2021), (v) probing the evolution of galaxy mergers across cosmic time (e.g. Ventou et al. 2017, 2019), (vi) constraining the low-mass end of the galaxy MS relation (e.g. Boogaard et al. 2018), (vii) studying inflows and outflows in galaxies using background quasars (e.g. Bouché et al. 2016; Schroetter et al. 2016, 2019, 2021; Zabl et al. 2019, 2021), (viii) putting constraints on the nature of dark matter (e.g Zoutendijk et al. 2020, 2021a; Bouché et al. 2022), (ix) studying
Lyα haloes at high redshift (e.g. Swinbank et al. 2015; Wisotzki et al. 2016; Patrício et al. 2016; Diener et al. 2017; Leclercq et al. 2017; Matthee et al. 2020; Maseda et al. 2020; Kusakabe et al. 2020), (x) the serendipitous discovery of a giant ionised gas structure in the COSMOS field (Epinat et al. 2018), (xi) using galaxy clusters as magnifying lenses to study background galaxies (e.g. Richard et al. 2015, 2021; Karman et al. 2015, 2017; Bina et al. 2016; Lagattuta et al. 2017; Mahler et al. 2018; de La Vieuville et al. 2019), (xii) looking at the effect of environment on small samples of galaxies (e.g. Fossati et al. 2016; Sheen et al. 2017; Consolandi et al. 2017; Boselli et al. 2019), (xiii) studying gas-stripping in a statistically significant sample of local galaxies (e.g. Poggianti et al. 2017; Bellhouse et al. 2017; Fritz et al. 2017, and subsequent papers of the series), or (xiv) probing the impact of the environment on the dynamics of a large sample of intermediate redshift galaxies (Abril-Melgarejo et al. 2021; Mercier et al. 2022). Furthermore, several important GTO and non-GTO surveys carried out extragalactic observations with MUSE, including for instance the MUSE Hubble Deep Field South (MUSE-HDFS), MUSE-HUDF, MXDF, or MUSE-WIDE designed to study galaxy evolution at intermediate and high redshift, or more importantly the MAGIC survey (see Chapter 3) that was designed to probe the effect of the environment on galaxy dynamical properties at intermediate redshift (see Appendix A for a more complete and detailed list of major MUSE survey as of December 2022).

### 2.2.4 Miscellaneous current and next-generation instruments

MUSE is not the only second-generation IFS instrument currently observing in the world. Other instruments with their own key characteristics also exist and it is fair that I mention them before finishing this chapter by discussing the next-generation of such instruments that will be installed on the future ELTs. As already quickly discussed, KMOS is a second-generation IFS instrument operating in the IR that was built by various institutes in the United Kingdom and in Germany in collaboration with ESO. It was commissioned in 2012 and is installed on the UT1 platform of the VLT. Similarly to MUSE, it uses the image slicing technique but its particularity is that it builds upon the concept first introduced with GIRAFFE of using deployable IFUs to observe multiple galaxies at the same time in a large FoV of 7.2' in diameter (Tomono et al. 2003; Sharples et al. 2004). Its wavelength range makes it perfect to study the resolved physical processes taking place in intermediate and high redshift galaxies. At the same time, its design with deployable IFUs allows to study the impact of the environment on galaxies in a wide variety of environments by simultaneously probing galaxies in the inner parts of galaxy groups or galaxy clusters and in their outskirts (Sharples et al. 2005). KMOS was one of the first IFS instruments to provide large surveys of galaxies with resolved spectroscopic data such as K-band Multi Object Spectrograph 3D (KMOS3D) (Wisnioski et al. 2015, 2019) and KMOS Redshift One Survey (KROSS) (Stott et al. 2016) which have led to important studies concerning the dynamics of galaxies, including the evolution of angular momentum across cosmic time (e.g. Burkert et al. 2016; Swinbank et al. 2017; Harrison et al. 2017) or the redshift evolution of the Tully-Fisher relation (e.g. Übler et al. 2017; Tiley et al. 2019a, 2021). Another current IFS instrument is Mapping Nearby Galaxies at APO (MANGA) that provides the eponymous survey (Bundy et al. 2015) and which is operational since the fourth data release of the SDSS. It is composed of 17 IFUs made of fibre bundles that observe local galaxies in the SDSS from the UV to the NIR with medium spectral resolving power. The quality of its data product and the ever-increasing number of observed galaxies has led to numerous studies, in particular regarding galaxy evolution (e.g. Jin et al. 2016; Belfiore et al. 2017; Graham et al. 2018; Law et al. 2022). Similarly to MANGA, another current
instrument dedicated to providing integral field spectroscopy for thousands of galaxies at low-redshift is SAMI, first described in Croom et al. (2012). It is composed of 13 different IFUs that use fibre bundles to observed galaxies over 15" FoVs in diameter. Its current eponymous survey targets galaxies located in groups and in the field and is thus ideal to probe the impact of the environment in the local Universe (e.g. Allen et al. 2015; Green et al. 2018; Scott et al. 2018; Croom et al. 2021).

Even more recently, the James Webb Space Telescope (JWST) was finally launched and as of July 2022 is fully operational and working. Among the on-board instruments are found JWST Mid-Infrared Instrument (MIRI) (Wright et al. 2004) and JWST Near-Infrared Spectrograph (NIRSPEC) that both include an integral field spectroscopic mode (Rieke et al. 2015). MIRI provides observations between roughly 5 µm and 28 µm using four IFUs that split the wavelength range in four sections and each section is further split in three gratings. The four IFUs observe at the same time but with a single grating, thus three observations of the same source are required to have a complete wavelength coverage. It has a small FoV that varies between 3.2" × 3.7" (~0.2" per spaxel) for the shortest wavelengths and 6.6" × 7.6" (~0.3" per spaxel) for the longest ones (Wells et al. 2015). On the other hand, NIRSPEC contains a single IFU that operates between 0.6 µm (~0.9 µm for medium spectral resolution) and 5.3 µm and always observes a 3" × 3" (0.1" per spaxel). For the low spectral resolution mode ($R \sim 100$) the full wavelength range is recorded, but for the two medium-resolution modes ($R > 1000$) the wavelength range is split in four different gratings (Closs et al. 2008).

Integral field spectroscopy having already had a tremendous impact on the field of extragalactic astrophysics it seems logical to expect that next-generation IFS instruments should be planned to be located on the future ELTs operational around the 2030s and 2040s. For instance, ESO has plans to incorporate IFS instruments on its future Extremely Large Telescope (ELT), first through its first-light instrument High Angular Resolution Monolithic Optical and Near-infrared Integral field spectrograph (HARMONI), described in Tecza et al. (2009) and Thatte et al. (2010), and then through a second generation MOS instrument with IFS capabilities called MOSAIC (Evans et al. 2014). HARMONI will be an IFU operating in the visible and in the NIR through various spectral channels with medium or high spectral resolving power. Combined with powerful AO systems specifically designed for the ELT, it will be optimised to obtain high-resolution diffraction-limited observations of high redshift galaxies. On the other hand, MOSAIC will be a second-generation MOS instrument that will also observe in the optical and in the NIR. Similarly to GIRAFFE and KMOS it will also host multiple IFUs that can be arranged in a 40 arcmin² FoV. Similarly, IFS instruments are also planned on the future Thirty Meter Telescope (TMT). One of the first light instruments will be Infrared Imaging Spectrograph (IRIS) that will observe in the NIR with medium spectral resolving power and over a relatively large FoV of 34" × 34" (Larkin et al. 2010). Thanks to the TMT and the use of a specific AO system, it shall provide diffraction-limited observations similar to what HARMONI will achieve. Apart from the ELTs, the VLTs will also be updated in the near-future with new-generation instruments including IFS instruments. To begin with, the current plan at ESO is to install onto one of the four telescopes of the VLT a new MUSE-like instrument optimised to observe in the blue part of the spectrum between roughly 350 nm and 600 nm: BLUEMUSE (Richard et al. 2019). The point of this instrument that will greatly benefit from the design of MUSE is to probe the part missing in MUSE data over a larger FoV and with a medium spectral resolving power. Finally, there is also a new spectrograph currently installed on the VLT with IFS capabilities that will soon start science operations in April 2023. This instrument, called Enhanced Resolution
Imager and Spectrograph (ERIS) (Davies et al. 2018), will observe in the IR and has an integral field spectroscopic observing mode called ERIS-SPIFFIER that is an upgraded version of SPIFFI, the IFU of SINFONI. Combined with powerful AO modes and two resolving powers (medium at R ~ 5000 and high at R ~ 10 000), the instrument shall be able to probe the dynamics of individual high-redshift galaxies (z ≳ 5) with high spatial and spectral resolutions using emission lines such as [OII], [OIII], or Hβ, as well as the optical disk of intermediate redshift galaxies using Hα with better spatial sampling and spatial and spectral resolution than MUSE.<fnref n="2" />

<footnote n="2">²Further plans for future fibre-based IFS instruments include for instance HECTOR on the Anglo-Australian Telescope (Bryant et al. 2016) or SPECTEL, a project for a dedicated large FoV 10 m-class telescope for dedicated 3D spectroscopic observations (Ellis & Dawson 2019).</footnote>
# Chapter 3

# The MAGIC survey

The data used in Abril-Melgarejo et al. (2021) and Mercier et al. (2022) (see also Chapter 6) and in the analysis of the angular momentum presented in Chapter 7 are all part of the MAGIC survey. Therefore, before delving into the analysis of the impact of the environment on galaxy scaling relations at $z \sim 0.7$ in Chapter 6 and on their angular momentum in Chapter 7, we briefly present in this section the survey design, the main characteristic of the observed structures and of their galaxies, and we refer the reader to Epinat et al. (in prep.) for a complete description of the survey.

## 3.1 Survey design and observing strategy

The MAGIC survey is a MUSE GTO observing program (PI: T. Contini) whose goal is to study the impact of the environment on the morpho-dynamical properties of galaxies, including their dynamics, around redshift $z \approx 0.7$. To this end, 17 deep MUSE observations were carried out in the COSMOS field (Scoville et al. 2007), or more specifically in the area covered by the spectroscopic survey zCOSMOS (Lilly et al. 2007), each centred on at least one already known structure. Each observation was obtained during dark nights and under good seeing conditions with a PSF FWHM below 0.8". The locations of the fields were chosen so as to maximise the number of dense groups in each FoV based on the zCOSMOS group catalogue of Knobel et al. (2009, 2012) (groups between $z \approx 0.25$ and $z \approx 0.85$), and further refined with the COSMOS2015 photometric catalogue of Laigle et al. (2016) and the COSMOS-WALL catalogue of Iovino et al. (2016). Targeting structures already detected in previous works was necessary in order to maximise the detection rate and the sample statistics since blind observations with MUSE would have been otherwise too costly and much less efficient given the size of its FoV. Thus, there were 14 galaxy groups that were chosen for target selection of the 17 MUSE fields for a total on-source exposure time of 67 h, half of which were carried out in wide-field mode with the new ESO VLT Ground Layer Adaptive Optics (GLAO) facility GALACSI (La Penna et al. 2016).
In this Thesis and in Epinat et al. (2018); Boselli et al. (2019); Abril-Melgarejo et al. (2021); Mercier et al. (2022); Epinat et al. (in prep.) each MUSE field was labelled after the name of the main targeted group given in the last version of the zCOSMOS group catalogue of Knobel et al. (2012). Their label writes CGRXXX, where XXX is the number of the group, which is the contraction of COSMOS GROUP NUMBER XXX. Similarly, we will label galaxies as
<figure><img src="image_12.png" /><figcaption>Figure 3.1: HST image of the MUSE observation CGR23. The main MUSE FoV is represented as a square with dimensions roughly equal to 1' × 1', with north and east pointing up and left, respectively. The galaxies observed in the FoV are colour-coded according to their MUSE spectroscopic redshift. Field galaxies are shown with crosses whereas each structure is shown with its own marker (see the top left part of the main plot). Field galaxies with low redshift confidence flag (CONFID) are shown with smaller markers (by definition there are no such galaxies in the structures). On the top is shown the redshift histogram for field galaxies, segregated between low (black dashed line) and high (black solid line) CONFID value. The structures are shown with vertical lines with the same colour as that of the galaxies in the main plot and below each line is shown the corresponding symbol used in the main plot.</figcaption></figure>
<table><caption>Table 3.1: Summary of the main characteristics of each MUSE field from Epinat et al. (in prep.).</caption><thead><tr><th>Field<br>(1)</th><th>R.A.<br>J2000<br>(2)</th><th>Dec.<br>J2000<br>(3)</th><th>θ<br>°<br>(4)</th><th>Exposure<br>h<br>(5)</th><th>FWHM<sub>7000</sub><br>"<br>(6)</th><th>∂FWHM<sub>PSF</sub>/∂λ<br>"/µm<br>(7)</th><th>β<sub>PSF</sub><br>(8)</th></tr></thead><tbody><tr><td>CGR23</td><td>149°47′34″</td><td>2°10′7″</td><td>0</td><td>1.00</td><td>0.615</td><td>-0.342</td><td>2.592</td></tr><tr><td>CGR26</td><td>150°29′30″</td><td>2°4′16″</td><td>35</td><td>1.00</td><td>0.586</td><td>-0.270</td><td>2.707</td></tr><tr><td>CGR28</td><td>150°13′32″</td><td>1°48′45″</td><td>-10</td><td>4.35</td><td>0.569</td><td>-0.368</td><td>2.594</td></tr><tr><td>CGR30</td><td>150°8′30″</td><td>2°3′60″</td><td>0</td><td>9.75</td><td>0.588</td><td>-0.282</td><td>2.606</td></tr><tr><td>CGR32-M1</td><td>149°55′14″</td><td>2°31′53″</td><td>30</td><td>4.35</td><td>0.480</td><td>-0.405</td><td>2.206</td></tr><tr><td>CGR32-M2</td><td>149°56′4″</td><td>2°31′24″</td><td>30</td><td>4.35</td><td>0.490</td><td>-0.406</td><td>2.037</td></tr><tr><td>CGR32-M3</td><td>149°55′10″</td><td>2°30′49″</td><td>30</td><td>4.35</td><td>0.546</td><td>-0.498</td><td>2.241</td></tr><tr><td>CGR34</td><td>149°51′24″</td><td>2°29′26″</td><td>-4</td><td>5.25</td><td>0.571</td><td>-0.236</td><td>2.825</td></tr><tr><td>CGR35</td><td>150°0′21″</td><td>2°27′23″</td><td>30</td><td>4.69</td><td>0.555</td><td>-0.447</td><td>2.448</td></tr><tr><td>CGR51</td><td>149°58′52″</td><td>1°47′55″</td><td>-30</td><td>1.00</td><td>0.577</td><td>-0.339</td><td>2.714</td></tr><tr><td>CGR61</td><td>149°43′34″</td><td>1°55′8″</td><td>-40</td><td>1.00</td><td>0.596</td><td>-0.344</td><td>3.320</td></tr><tr><td>CGR79</td><td>149°49′7″</td><td>1°49′19″</td><td>-20</td><td>4.35</td><td>0.501</td><td>-0.345</td><td>2.474</td></tr><tr><td>CGR84-M1</td><td>150°3′3″</td><td>2°35′48″</td><td>0</td><td>5.25</td><td>0.532</td><td>-0.249</td><td>2.568</td></tr><tr><td>CGR84-M2</td><td>150°3′35″</td><td>2°36′46″</td><td>0</td><td>4.35</td><td>0.608</td><td>-0.526</td><td>2.068</td></tr><tr><td>CGR87</td><td>150°1′31″</td><td>2°21′29″</td><td>-20</td><td>2.68</td><td>0.540</td><td>-0.368</td><td>2.191</td></tr><tr><td>CGR114</td><td>149°59′55″</td><td>2°15′32″</td><td>-15</td><td>4.38</td><td>0.588</td><td>-0.400</td><td>2.340</td></tr><tr><td>CGR172</td><td>150°10′16″</td><td>2°31′24″</td><td>0</td><td>4.69</td><td>0.481</td><td>-0.483</td><td>2.074</td></tr></tbody></table>

**Notes:** (1) MUSE field name, (2) equatorial right ascension (J2000), (3) equatorial declination (J2000), (4) FoV rotation angle with respect to the North (positive towards East), (5) total on-source exposure time, (6) FWHM at 7000 Å for a Moffat PSF, (7) linear gradient of the PSF FWHM with wavelength, and (8) beta parameter of the Moffat PSF profile.

YYY_CGRXXX, where YYY corresponds to the galaxy's ID. However, there are actually five slight exceptions to this rule when it was decided to do a mosaic of potentially extended groups. The first set of exception comes from the fact that one of the observed structures is not a dense group but a galaxy cluster: CGR32 (more than 100 members). This structure therefore required three MUSE FoVs to map it entirely and these individual fields are labelled as CGR32-MX with X running from one to three and where M stands for mosaic. Nevertheless, unless specified otherwise, their galaxy labels will always write YYY_CGR32 independently of which field they belong to (IDs are unique for the three combined MUSE fields so that there are no duplicates). The second set of exceptions is for CGR84. Indeed, similarly to CGR32, it was found that the density measured from the COSMOS2015 catalogue was high well beyond the structure's location so that a mosaic of two fields was used. The northernmost one was labelled CGR84-M1 and the southernmost CGR84-M2. In Abril-Melgarejo et al. (2021) and Mercier et al. (2022), and therefore in Chapter 6 as well, these two fields were labelled as CGR84 and CGR84-N instead (previous nomenclature) for the southern and northern structures, respectively.

An example of a MUSE field (CGR23) observed as part of the MAGIC survey is shown in Fig. 3.1 and the remaining of the fields are illustrated in Appendix B (see Fig. B.1 to B.14). The main MUSE FoV (or FoVs in the case of CGR32 and CGR84) is represented for each field as a black
square with north and east respectively oriented up and left. Field objects (galaxies and stars), that is those not associated to any structure (see Sect. 3.3 for how the structures were detected), are always represented as crosses and galaxies in structures are shown with various symbols (one symbol per structure, see the legend on the top left corner of each figure). Field galaxies are further separated between low confidence flag for the redshift estimate (CONFID, see Sect. 3.2.2 below) represented with small crosses and high CONFID value with large crosses (by definition there are only high CONFID galaxies in the structures, see Sect. 3.3). Furthermore, galaxies are colour-coded according to their redshift with the maximum value set to $z = 1.56$ to highlight the distribution of [OII] emitters, being the main population of galaxies studied in the MAGIC survey and in this Thesis<fnref n="1" />. However, let us keep in mind that galaxies above $z = 1.56$ can be distributed well beyond this value, among which are found Lyα emitters located beyond redshift $z = 2.9$. Additionally, on top of each figure is shown the redshift histograms for the objects found in the FoVs. Field objects with high CONFID are represented with a black solid line whereas low CONFID objects are shown with a black dashed line. On the other hand, structures are represented as vertical lines with the same colour as that associated to their redshift. Furthermore, to help the reader easily identify the structures, below each vertical line is shown the symbol used to represent the corresponding structure in the HST image. As can be seen from Fig. B.1 to B.14, a large variety of structures can be found in the different MUSE fields. Field galaxies that are [OII] emitters tend to be spread out quite evenly between $z \approx 0.2$ and $z \approx 1.5$ for the majority of the fields, whereas galaxies in structures are mostly located in large structures in the redshift range $0.5 \le z \le 0.9$. Nevertheless, smaller structures (less than ten members or so) are also found above and below this range. We will go back in more details to the structure identification and their main characteristics in Sect. 3.3.

## 3.2 MUSE data and main survey properties

In this section, we briefly describe the data reduction process which was done for most of the MUSE fields before the start of this Thesis. We also quickly discuss in Sect. 3.2.2 how spectroscopic redshifts were determined from the MUSE spectra and how they are distributed for field galaxies and those located in structures.

### 3.2.1 MUSE data for the MAGIC sample

At the start of this Thesis, data reduction had already been done for 14 out the 17 MUSE fields. The last observations of CGR35, CGR87, and CGR172 being obtained in the first few months of this work, the data reduction was performed quickly afterwards so that science-ready data cubes for these fields were available as early as the beginning of the year 2020. Similarly to what was done in the MUSE-HDFS survey (Bacon et al. 2015), the final data cube for each field was obtained by combining Observing Blocks (OBs) composed of four 900 s exposures. Between each exposure a small dithering pattern and a 90° rotation of the FoV were performed so that every pixel, except perhaps those near the centre, would fall into different channels (see Sect. 2.2.3). Among the 17 MUSE fields, 12 have integration times larger than

<footnote n="1">¹Note that in this Thesis [OII] emitters refer to galaxies whose redshift falls in the $0.2 \le z \le 1.5$ range where the [OII] doublet could theoretically be detected. Thus, it includes galaxies for which the [OII] doublet is indeed detected as well as galaxies that do not possess it in their spectrum. For instance, this includes quenched galaxies at $0.2 \le z \le 1.5$ whose redshift is determined from their absorption lines and features.</footnote>