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Yingying Li - Fermilab - : Jet or Event? ---- Physics at Future e+e- Colliders

E 188 (Building 362)

E 188

Building 362

Information loss caused by dimensionality reduction in jet clustering is one of the major limitations for improving the precision of measuring hadronic events at future e−e+ colliders. Such measurements are key for probing, e.g., the nature of Higgs boson, since the hadronic events are dominant in Higgs data. We show that this difficulty could be well- addressed using the machine-learning (ML) techniques at event-level. For this purpose, a comparative ML-based study is pursued between jet-level and event-level analyses. We explore how the precision of the benchmark measurements gets improved with the assistance of the information beyond jet level. As an application of this method, we analyse the precision of measuring the Higgs total width at e−e+ colliders with 5ab−1@240GeV and its dependence on the detector resolution. We expect that the proposed method can be broadly applied to many other hadronic-event measurements at future e−e+ colliders.
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