Abstract: The measured branching fractions of B-mesons into leptonic final states derived by the LHCb, Belle and BaBar collaborations hint towards the breakdown of lepton flavour universality. In this work we take at face value the so-called R-D(()*()) observables that are defined as the ratios of neutral B-meson charged-current decays into a D-(*())-meson, a charged lepton and a neutrino final state in the tau and light lepton channels. A well-studied and simple solution to this charged current anomaly is to introduce a scalar leptoquark S-1 that couples to the second and third generation of fermions. We investigate how S-1 can also serve as a mediator between the Standard Model and a dark sector. We study this scenario in detail and estimate the constraints arising from collider searches for leptoquarks, collider searches for missing energy signals, direct detection experiments and the dark matter relic abundance. We stress that the production of a pair of leptoquarks that decays into different final states (i.e. the commonly called “mixed” channels) provides critical information for identifying the underlying dynamics, and we exemplify this by studying the t tau b nu and the resonant S-1 plus missing energy channels. We find that direct detection data provides non-negligible constraints on the leptoquark coupling to the dark sector, which in turn affects the relic abundance. We also show that the correct relic abundance can not only arise via standard freeze-out, but also through conversion-driven freeze-out. We illustrate the rich phenomenology of the model with a few selected benchmark points, providing a broad stroke of the interesting connection between lepton flavour universality violation and dark matter.

Abstract: We study the LHC discovery potential in the search for heavy neutral leptons (HNL) with a new signature: a displaced shower in the CMS muon detector, giving rise to a large cluster of hits forming a displaced shower. A new Delphes module is used to model the CMS detector response for such displaced decays. We reinterpret a dedicated CMS search for neutral long-lived particles decaying in the CMS muon endcap detectors for the minimal HNL scenario. We demonstrate that this new strategy is particularly sensitive to active-sterile mixings with tau leptons, due to hadronic tau decays. HNL masses between similar to 1-6 GeV can be accessed for mixings as low as vertical bar V-tau N vertical bar(2) similar to 10(-7), probing unique regions of parameter space in the tau sector.

Abstract: The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods.