66 citations · 133 across the 11 of their papers we have counts for
11 papers
Predicting galaxy bias using machine learning
Catalina Riveros-Jara, Antonio D. Montero-Dorta, Natália V. N. Rodrigues +6
Understanding how galaxies trace the underlying matter density field is essential for characterizing the influence of the large-scale structure on galaxy formation, being therefore…
The miniJPAS survey quasar selection V: combined algorithm
Ignasi Pérez-Ràfols, L. Raul Abramo, Ginés Martínez-Solaeche +27
Aims. Quasar catalogues from narrow-band photometric data are used in a variety of applications, including targeting for spectroscopic follow-up, measurements of supermassive black…
Exploring the halo-galaxy connection with probabilistic approaches
Natália V. N. Rodrigues, Natalí S. M. de Santi, L. Raul Abramo +1
The connection between galaxies and dark matter halos encompasses a range of processes and play a pivotal role in our understanding of galaxy formation and evolution. Traditionally…
The miniJPAS survey quasar selection IV: Classification and redshift estimation with SQUEzE
Ignasi Pérez-Ràfols, L. Raul Abramo, Ginés Martínez-Solaeche +24
We present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. This work is based on machine-learning clas…
The miniJPAS survey quasar selection III: Classification with artificial neural networks and hybridisation
G. Martínez-Solaeche, Carolina Queiroz, R. M. González Delgado +28
This paper is part of large effort within the J-PAS collaboration that aims to classify point-like sources in miniJPAS, which were observed in 60 optical bands over 1 deg$^2…
The miniJPAS survey quasar selection II: Machine learning classification with photometric measurements and uncertainties
Natália V. N. Rodrigues, L. Raul Abramo, Carolina Queiroz +23
Astrophysical surveys rely heavily on the classification of sources as stars, galaxies or quasars from multi-band photometry. Surveys in narrow-band filters allow for greater discr…
High-fidelity reproduction of central galaxy joint distributions with Neural Networks
Natália V. N. Rodrigues, Natalí S. M. de Santi, Antonio D. Montero-Dorta +1
The relationship between galaxies and haloes is central to the description of galaxy formation, and a fundamental step towards extracting precise cosmological information from gala…
The miniJPAS survey quasar selection I: Mock catalogues for classification
Carolina Queiroz, L. Raul Abramo, Natália V. N. Rodrigues +27
In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no r…
Mimicking the halo-galaxy connection using machine learning
Natalí S. M. de Santi, Natália V. N. Rodrigues, Antonio D. Montero-Dorta +3
Elucidating the connection between the properties of galaxies and the properties of their hosting haloes is a key element in galaxy formation. When the spatial distribution of obje…
Supernova lightCURVE POPulation Synthesis II: Validation against supernovae with an observed progenitor
J. J. Eldridge, N. -Y. Guo, N. Rodrigues +2
We use the results of a supernova light-curve population synthesis to predict the range of possible supernova light curves arising from a population of single-star progenitors that…
Supernova lightCURVE POPulation Synthesis I: including interacting binaries is key to understanding the diversity of type II supernova lightcurves
J. J. Eldridge, L. Xiao, E. R. Stanway +2
We present results of a supernova light-curve population synthesis, predicting the range of possible supernova lightcurves arising from a population of progenitor stars that includ…