Tesis profesional presentada por Paulina Contreras Miranda [paulina.contrerasma@udlap.mx]

Licenciatura en Física. Departamento de Actuaría, Física y Matemáticas. Escuela de Ciencias, Universidad de las Américas Puebla.

Jurado Calificador

Asesor: Dr. Daniel Grün
Asesor: Dr. Luca Tortorelli
Asesora: Dra. Milagros Zeballos Rebaza

Cholula, Puebla, México a 30 de noviembre de 2023.

Resumen

Spectral Energy Distributions (SEDs) represent how the energy of an object is arranged considering different wavelengths. These are useful in astronomical research, as are known as the object?s fingerprints that bring insights to the characteristics of, e.g. galaxies. This study focuses on building a self-organizing map (SOM) to bring order to a set of restframe galaxy SEDs. The aim is to find patterns within thie galaxy zoo, providing insights and techniques that are crucial for photometric redshifts. Morevoer, the SOM's outcomes are expected to contribute to the construction of a comprehensive model for the galaxy population, aiming to provide insights and techniques that will be useful for photometric redshifts and more generally to build a model of the galaxy population useful for future cosmological galaxy surveys. Through this work, we intent to offer alternative methods for interpreting and categorizing galaxy spectral profiles.

Keywords: Spectral Energy Distribution, Galaxy, Variarional Autoencoder, Self Organizing Map.

Table of content

Portada

Agradecimientos

Índices

Capítulo 1. Introduction

  • 1.1 Photometry
  • 1.2 Spectroscopy
  • 1.3 Galaxy Population
  • 1.4 Star-formation in galaxies
  • 1.5 Spectral energy distributions
  • 1.6 Stellar population synthesis models
  • 1.7 Dust in galaxies
  • 1.8 Photometric redshifts
  • 1.9 Justification

Capítulo 2. Models and numerical tools

  • 2.1 FSPS
  • 2.2 Auto Encoders
  • 2.3 Self Organizing Maps (SOM)

Capítulo 3. Results and analysis

  • 3.1 Autoencoder implementation
  • 3.2 Clustering implementation
  • 3.3 SOM implementation

Capítulo 4. Conclusions

Referencias

Contreras Miranda, P. 2023. Mapping the Zoo of Rest-Frame Galaxy SEDs using Unsupervised Machine Learning. Tesis Licenciatura. Física. Departamento de Actuaría, Física y Matemáticas, Escuela de Ciencias, Universidad de las Américas Puebla. Noviembre. Derechos Reservados © 2023.