SHiP is a proposed high-intensity beam dump experiment set to operate at the CERN SPS. It is expected to have an unprecedented sensitivity to a variety of models containing feebly interacting particles, such as Heavy Neutral Leptons (HNLs). Two HNLs or more could successfully explain the observed neutrino masses through the seesaw mechanism. If, in addition, they are quasi-degenerate, they could be responsible for the baryon asymmetry of the Universe. Depending on their mass splitting, HNLs can have very different phenomenologies: they can behave as Majorana fermions - with lepton number violating (LNV) signatures, such as same-sign dilepton decays - or as Dirac fermions with only lepton number conserving (LNC) signatures. In this work, we quantitatively demonstrate that LNV processes can be distinguished from LNC ones at SHiP, using only the angular distribution of the HNL decay products. Accounting for spin correlations in the simulation and using boosted decision trees for discrimination, we show that SHiP will be able to distinguish Majorana-like and Dirac-like HNLs in a significant fraction of the currently unconstrained parameter space. If the mass splitting is of order 10(-6) eV, SHiP could even be capable of resolving HNL oscillations, thus providing a direct measurement of the mass splitting. This analysis highlights the potential of SHiP to not only search for feebly interacting particles, but also perform model selection.
Rakesh Chawla, Andrea Rizzi, Matthias Finger, Federica Legger, Matteo Galli, Sun Hee Kim, João Miguel das Neves Duarte, Tagir Aushev, Hua Zhang, Alexis Kalogeropoulos, Yixing Chen, Tian Cheng, Ioannis Papadopoulos, Gabriele Grosso, Valérie Scheurer, Meng Xiao, Qian Wang, Michele Bianco, Varun Sharma, Joao Varela, Marko Stamenkovic, Sourav Sen, Ashish Sharma, Seungkyu Ha, David Vannerom, Csaba Hajdu, Sanjeev Kumar, Sebastiana Gianì, Kun Shi, Abhisek Datta, Siyuan Wang, Anton Petrov, Jian Wang, Yi Zhang, Muhammad Ansar Iqbal, Yong Yang, Xin Sun, Muhammad Ahmad, Donghyun Kim, Matthias Wolf, Anna Mascellani, Paolo Ronchese, , , , , , , , , , , , , , , , , , , , ,