3 papers
hep-ph2026
Physically Consistent Parameter Inference: Transparent Machine Learning Emulation in High Energy Physics and Cosmology
Jorge Alda, Jacobo Asorey, Alejandro Mir +1
Global fits in high energy physics and cosmology often face the challenge of exploring high-dimensional parameter spaces with computationally expensive or topologically complex lik…
hep-ph2025
B-Meson Anomalies: Effective Field Theory Meets Machine Learning
Alejandro Mir, Jorge Alda, Siannah Penaranda
Discrepancies between experimental measurements and Standard Model predictions in -meson decays, especially in lepton flavor universality ratios like , an…
hep-ph2024
Flavour Anomalies: A comparative analysis using a machine learning algorithm
Jorge Alda, Alejandro Mir, Siannah Penaranda
We present an analysis on flavour anomalies in semileptonic rare -meson decays using an effective field theory approach and assuming that new physics affects only one generation…