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20202026
most citedConstraining Light Thermal Inelastic Dark Matter with NA64

23 citations · 61 across the 13 of their papers we have counts for

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hep-ph2023★ 4 cited

A panorama of new-physics explanations to the MiniBooNE excess

Asli M. Abdullahi, Jaime Hoefken Zink, Matheus Hostert +2

The MiniBooNE low-energy excess stands as an unexplained anomaly in short-baseline neutrino oscillation experiments. It has been shown that it can be explained in the context of da…

hep-ph2023★ 1 cited

Dark matter in the Higgs resonance region

Mattia Di Mauro, Chiara Arina, Nicolao Fornengo +2

The singlet scalar Higgs portal model provides one of the simplest explanations of dark matter in our Universe. Its Higgs resonant region, , has gained pa…

hep-ph2023★ 23 cited

Constraining Light Thermal Inelastic Dark Matter with NA64

Martina Mongillo, Asli Abdullahi, Benjamin Banto Oberhauser +5

A vector portal between the Standard Model and the dark sector is a predictive and compelling framework for thermal dark matter. Through co-annihilations, models of inelastic dark…

hep-ph2023★ 1 cited

Semi-Visible Dark Photon Phenomenology at the GeV Scale

Asli M. Abdullahi, Matheus Hostert, Daniele Massaro +1

In rich dark sector models, dark photons heavier than tens of MeV can behave as semi-visible particles: their decays contain both visible and invisible final states. We present mod…

hep-ph2022

DarkNews: a Python-based event generator for heavy neutral lepton production in neutrino-nucleus scattering

Asli M. Abdullahi, Jaime Hoefken Zink, Matheus Hostert +2

We introduce DarkNews, a lightweight Python-based Monte-Carlo generator for beyond-the-Standard-Model neutrino-nucleus scattering. The generator handles the production and decay of…

hep-ph2021★ 17 cited

Indirect dark-matter detection with MadDM v3.2 -- Lines and Loops

Chiara Arina, Jan Heisig, Fabio Maltoni +2

Automated tools for the computation of particle physics' processes have become the backbone of phenomenological studies beyond the standard model. Here, we present MadDM v3.2. This…

hep-ph2020★ 4 cited

Studying dark matter with MadDM 3.1: a short user guide

Chiara Arina, Jan Heisig, Fabio Maltoni +4

MadDM is an automated numerical tool for the computation of dark-matter observables for generic new physics models. We announce version 3.1 and summarize its features. Notably, the…