Erlangen 2026 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 75: Higgs Physics VII
T 75.3: Vortrag
Donnerstag, 19. März 2026, 16:45–17:00, KH 01.019
Improving the event reconstruction and scalability of the Higgs self-coupling analysis at ILD — Mikael Berggren1, •Bryan Bliewert1,2, Jenny List1, Dimitris Ntounis3, Taikan Suehara4, Junping Tian4, Julie Munch Torndal1,2, and Caterina Vernieri3 — 1Deutsches Elektronen-Synchrotron DESY, Germany — 2Universität Hamburg, Germany — 3SLAC National Accelerator Laboratory, USA — 4University of Tokyo, Japan
The shape of the Higgs potential gives crucial insight into the Higgs mechanism. At future e+ e−-colliders and center-of-mass energies of ≥ 550 GeV, the Higgs potential can be probed directly by measuring the self-coupling λ through di-Higgs production. In an ongoing effort, the projected sensitivities for λ are updated assuming the ILD concept at an LCF 550-like facility. In our contribution, we discuss recent advancements in event reconstruction: First, we cover the identification and removal of low-pt hadrons (overlay) using machine learning (ML) and its effect on the di-jet invariant mass resolution. Second, we present how variables based on leading order matrix elements improve the event selection. Furthermore, we have designed our analysis using a modern distributed pipelining system (luigi/law) and present key concepts of this framework. It covers all steps from detector simulation to sensitivity extraction, greatly improving automation, reproducibility and scalability and producing results in a few hours for 150M events with o(1000) computing nodes. We conclude by showing the impact of the reconstruction advances on the measurement of the di-Higgs cross-section and the corresponding precision on λ.
Keywords: Higgs self-coupling; ILD; overlay removal; matrix element method