Estimating the redshift of galaxies from their photometric colors using machine learning methods
Tallennettuna:
| Tekijä: | |
|---|---|
| Aineistotyyppi: | artículo original |
| Tila: | Versión publicada |
| Julkaisupäivä: | 2020 |
| Kuvaus: | The determination of the redshift, a factor also known as z, is obtained from variations in the wavelength’s spectrum of galaxies or distant objects, such variation is basically the difference between the wavelength measure on Earth of the element present in the galaxy and the direct measure of the same element on the object by the use of spectroscopy. From the value z, it’s possible to obtain the values of the object’s distance and the speed at which it moves away from us. Obtaining spectroscopic data directly from astronomical objects, is not always an easy task to run and the use of color index become a more accessible alternative for many researchers. In this work we present the preliminary results of several machine learning methods, using regression based algorithms. The goal will be to obtain the value of z, from the photometric colors. |
| Maa: | Portal de Revistas TEC |
| Organisaatio: | Instituto Tecnológico de Costa Rica |
| Repositorio: | Portal de Revistas TEC |
| Kieli: | Inglés |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/5073 |
| Linkit: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/5073 |
| Sanahaku: | Universe expansion redshift galaxies svm decision trees ada boost random forest Universo expansión desplazamiento al rojo galaxias svm árboles de decisión bosque al azar |