Incorporation of LCFIPlus vertexing module in FCCAnalyses

Numerous studies and measurements planned at the FCC-ee rely on efficient and accurate jet flavour tagging algorithms, which in turn heavily rely on secondary vertex reconstruction as b and c jets contain long-lived hadrons that decay hundreds of microns from the collision point. At the same time, vertex reconstruction is also an important tool to test the performance of different vertex detector designs.LCFIPlus is a flavour tagging framework developed for linear colliders that includes a vertexing module. Here, we present the incorporation of this vertexing module into the FCCAnalyses framework. The flexible and configurable implementation consists of reconstructing the primary, the secondary vertices, and longer-lived V0s, which have been adapted both for rejection and to identify V0s. We show the performance of the vertex finding module and present the potential refining techniques that can be incorporated

Strange jet tagging at the FCC-ee using a transformer NN architecture and K short reconstruction

The successful identification of strange quark jets at the FCC-ee would enable the study of a multitude of largely unexplored processes, including the first ever study of Z->ss production, rare Higgs boson decays and the strange Yukawa coupling, CKM matrix elements via W decays, and BSM physics scenarios such as FCNCs. Due to the challenging nature of distinguishing these medium-mass quarks, strange tagging is a topic that has up to now received considerably less attention than its heavy flavour counterparts, or indeed gluon tagging. A multiclassifier neural network using a transformer-based architecture is coupled with secondary vertexing and a novel implementation of K short reconstruction at the FCC-ee to discriminate strange quark initiated jets. This poster presents a state-of-the-art strange quark tagger at the FCC-ee, with a focus on light quark discrimination at the Z pole