6 papers
Mono-X Signal Characterization from Two-component Dark Matter Using a Convolutional Neural Network
Max Fusté Costa, Max Fusté Costa, Yong Sheng Koay +1
We assess the scope of a Convolutional Neural Network (CNN) in characterizing potential signals of two-component Dark Matter (DM) arising at the Large Hadron Collider (LHC) from mo…
Glimpses of the X17 from coherent elastic neutrino nucleus scattering
Johan Rathsman, Joakim Cederkäll, Yasar Hicyilmaz +2
We show that the process of Coherent Elastic neutrino (ν) Nucleus Scattering (CEνNS) at nuclear reactor experiments has significant sensitivity to the so-called X17 particle, whi…
The X17 Existence Hinted at by Nuclear Reactor Neutrinos
Johan Rathsman, Joakim Cederkäll, Yasar Hicyilmaz +2
We show that by exploiting the process of Coherent Elastic neutrino (v) Nucleus Scattering (CEvNS), neutrino measurements by nuclear reactor experiments appear to corroborate the e…
A quantum algorithm for the n-gluon MHV scattering amplitude
Erik Bashore, Stefano Moretti, Timea Vitos
We propose a quantum algorithm for computing the n-gluon maximally helicity violating (MHV) tree-level scattering amplitude. We revisit a newly proposed method for unitarisation of…
Hunting the elusive in CENS at the ESS
Joakim Cederkäll, YaÅar Hiçyılmaz, Else Lytken +2
The so-called particle has been proposed in order to explain a very significant resonant behaviour (in both the angular separation and invariant mass) of pairs produ…
Generating particle physics Lagrangians with transformers
Yong Sheng Koay, Rikard Enberg, Stefano Moretti +1
In physics, Lagrangians provide a systematic way to describe laws governing physical systems. In the context of particle physics, they encode the interactions and behavior of the f…