29 citations · 67 across the 4 of their papers we have counts for
5 papers
Galaxy and Halo Assembly Bias in Alternative Dark Matter Models
Yikun Wang, Idit Zehavi, Sergio Contreras +6
The clustering of dark matter halos depends not only on halo mass but also on secondary halo properties, a phenomenon known as halo assembly bias. Coupled with variations in halo o…
Machine Learning Techniques for Astrophysics and Cosmology: Lyman- forest
Jonás Chaves-Montero
The Lyman- forest refers to the series of absorption features observed in the spectra of distant quasars that are produced by neutral hydrogen in the intergalactic medium. Obser…
Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z
Nesar Ramachandra, Jonás Chaves-Montero, Alex Alarcon +3
Photometric redshift estimation algorithms are often based on representative data from observational campaigns. Data-driven methods of this type are subject to a number of potentia…
The cosmological dependence of halo and galaxy assembly bias
Sergio Contreras, Jonás Chaves-Montero, Matteo Zennaro +1
One of the main predictions of excursion set theory is that the clustering of dark matter haloes only depends on halo mass. However, it has been long established that the clusterin…
A Differentiable Model of the Assembly of Individual and Populations of Dark Matter Halos
Andrew P. Hearin, Jonás Chaves-Montero, Matthew R. Becker +1
We present a new empirical model for the mass assembly of dark matter halos. We approximate the growth of individual halos as a simple power-law function of time, where the power-l…