477 citations · 6.1k across the 108 of their papers we have counts for
4 papers · 2 filters
Using Machine Learning to disentangle LHC signatures of Dark Matter candidates
C. K. Khosa, V. Sanz, M. Soughton
We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and pr…
Non-Resonant Searches for Axion-Like Particles at the LHC
M. B. Gavela, J. M. No, V. Sanz +1
We propose a new collider probe for axion-like particles (ALPs), and more generally for pseudo-Goldstone bosons: non-resonant searches which take advantage of the derivative nature…
Dynamical Axions and Gravitational Waves
Djuna Croon, Rachel Houtz, Veronica Sanz
In this paper we explore the possibility of observable gravitational waves as a manifestation of the QCD axion dynamics. In particular, we focus on dynamical axion models which sol…
Exploring SMEFT in VH with Machine Learning
Felipe F. Freitas, Charanjit K. Khosa, Verónica Sanz
In this paper we study the use of Machine Learning techniques to exploit kinematic information in VH, the production of a Higgs in association with a massive vector boson. We param…