Adding infrared data to photometric redshift estimation in the Dark Energy Survey
The Dark Energy Survey (DES) is a comological project that uses the Dark Energy Camera (DECam), located at the Cerro Tololo Inter-American Observatory (CTIO) in Chile, covering 5000 square degrees of the southern sky between 2013 and 2019. The resulting catalogues contain hundreds of millions of gal...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/121897 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/121897 |
| Access Level: | acceso abierto |
| Palabra clave: | 52 Galaxies-general Galaxies-redshifts Infrared Dark Energy Survey Techniques-photometry Catalogues Surveys Methods-data analysis Galaxias-general Galaxias-redshifts Infrarrojo Técnicas-fotometría Catálogos Cartografiados Métodos-análisis de datos Astrofísica 21 Astronomía y Astrofísica |
| Sumario: | The Dark Energy Survey (DES) is a comological project that uses the Dark Energy Camera (DECam), located at the Cerro Tololo Inter-American Observatory (CTIO) in Chile, covering 5000 square degrees of the southern sky between 2013 and 2019. The resulting catalogues contain hundreds of millions of galaxies with photometric redshifts (photo-zs) estimated from these optical measurements, supporting a broad range of extragalactic and cosmological studies. This work investigates improvements in photometric redshift estimation achieved by combining DES optical data with infrared measurements from the VISTA Hemisphere Survey (VHS) and the Wide-field Infrared Survey Explorer (WISE). Using the Angular Neighbourhood Fitting (ANF) machine learning algorithm applied to a spectroscopic subsample, we find that adding infrared data reduces all the metrics (scatter, bias and outlier fraction) in photo-z estimates, particularly at intermediate and high redshifts. The inclusion of WISE data provides more accurate photo-zs than VHS, while combining both infrared datasets with DES results in only marginal additional improvements compared to what is achieved with DES+WISE. We also compare our results with those obtained by Banerji et al. (2015), confirming the benefits of incorporating infrared photometry for improved photo-z estimation. This study opens the way for building a comprehensive, high-quality photometric redshift catalogue that will benefit upcoming wide-area surveys such as the Legacy Survey of Space and Time (LSST) and Euclid, as well as future cosmological and astrophysical analyses. |
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