Speaker
Description
The Cabibbo-Kobayashi-Maskawa (CKM) matrix describes the flavor-changing interactions of quarks. The matrix element |Vts| describes the coupling between the top and strange quark, but the decay of t→sW is not directly seen yet. A direct measurement of |Vts| can be performed by identifying the strange jets from top decays. However, the extremely low ratio of t→sW compared to the dominant t→bW, and the similarity of strange jets to other light jets, make identifying them a challenging task. In this study, we employ a deep learning approach called SAJA (Self-Attention for Jet Assignment), based on the self-attention mechanism, which can utilize the full event topology and all jet properties. The utilization of both the relationship between objects and jet properties within an event offers a significant advantage when identifying strange jets from top quark decays. We present the result of measurements of |Vts| using the SAJA model to identify jets decaying from t→sW.
