Simulating Light Dark Matter Signals at SHiP

Abstract

Dark matter remains one of the most compelling mysteries in modern physics, with a wide range of astrophysical and cosmological observations providing strong evidence for its existence. Among the many proposed candidates, light dark matter, with masses below the GeV scale, has gained increasing interest, partly due to its accessibility in current and next-generation accelerator-based experiments. An interesting framework for light dark matter involves a massive dark photon mediator A′, which kinetically mixes with the Standard Model photon, enabling interactions between the visible and dark sectors. This thesis focuses on the sensitivity of the SHiP (Search for Hidden Particles) experiment – a planned proton beam-dump experiment at the CERN Super-Proton- Synchrotron (SPS) – to light dark matter scenarios. This experiment is designed to probe feebly interacting particles and is expected to significantly extend the parameter space coverage for light dark sector particles. The analysis adopts a benchmark model characterized by a minimal dark sector with a complex scalar dark matter candidate χ, a dark coupling αD = 0.1, and a mediator mass set to mA′ = 3mχ. Simulations are performed using two independent tools: BdNMC, a standalone dark matter Monte Carlo generator, and MadDump, a plugin for the Mad- Graph5_aMC@NLO framework tailored for beam dump and fixed-target experiments. A comparative analysis of these tools is conducted in the context of the complex scalar model, highlighting methodological differences and their impact on predicted signal rates. Furthermore, the sensitivity studies for the SHiP experiment are extended to fermionic dark matter scenarios, including both Dirac and Majorana candidates, resulting in updated exclusion contours and emphasizing the experiment’s discovery potential across these different dark matter hypotheses.