activity
20242026
most citedSymbolic regression for precision LHC physics

2 citations · 7 across the 9 of their papers we have counts for

collaborators

10 papers

hep-ph2026

PDF effects in high-mass Drell-Yan SMEFT analyses across flavour space

David Marzocca, Manuel Morales-Alvarado

High-mass Drell-Yan dilepton production provides one of the most sensitive probes of semileptonic four-fermion operators in the Standard Model Effective Field Theory (SMEFT), thank…

hep-ph2026★ 1 cited

Tailored PDFs for New Physics searches

Ella Cole, Mark N. Costantini, Elie Hammou +4

Given the non-negligible interplay between parton distribution functions (PDFs) at large x and potential New Physics (NP) effects in the high-energy tails of hadron collider observ…

hep-ph2025

Quark mixing from muon collider neutrinos

David Marzocca, Francesco Montagno, Manuel Morales-Alvarado +1

A high energy muon collider naturally produces a collimated beam of neutrinos for a fixed-target experiment at a dedicated far-forward facility. The high intensity and energy of th…

physics.acc-ph2025★ 2 cited

MuCol Milestone Report No. 7: Consolidated Parameters

Rebecca Taylor, Antoine Chancé, Dario Augusto Giove +459

This document is comprised of a collection of consolidated parameters for the key parts of the muon collider. These consolidated parameters follow on from the October 2024 Prelimin…

hep-ph2025

Foundation models for equation discovery in high energy physics

Manuel Morales-Alvarado

Foundation models, large machine learning models trained on broad, multimodal datasets, have been gaining increasing attention in scientific applications due to their strong perfor…

hep-ph2025

Angular Coefficients from Interpretable Machine Learning with Symbolic Regression

Josh Bendavid, Daniel Conde, Manuel Morales-Alvarado +2

We explore the use of symbolic regression to derive compact analytical expressions for angular observables relevant to electroweak boson production at the Large Hadron Collider (LH…