3 papers
astro-ph.GA2025
Dark Matter profiles of "in silico" galaxies: deep learning inference
MartÃn de los Rios, Martín de los Rios, Serafina Di Gioia +2
Machine learning has the potential to improve the reconstruction of the dark matter profile of galaxies with respect to traditional methods, like rotation curves. We demonstrate on…
hep-ph2025
Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC
Ernesto Arganda, Marcela Carena, MartÃn de los Rios +4
The search for weakly interacting matter particles (WIMPs) is one of the main objectives of the High Luminosity Large Hadron Collider (HL-LHC). In this work we use Machine-Learning…
hep-ph2025
Bayesian technique to combine independently-trained Machine-Learning models applied to direct dark matter detection
David Cerdeno, Martin de los Rios, Andres D. Perez
We carry out a Bayesian analysis of dark matter (DM) direct detection data to determine particle model parameters using the Truncated Marginal Neural Ratio Estimation (TMNRE) machi…