# SMuK 2023 – wissenschaftliches Programm

## Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

# T: Fachverband Teilchenphysik

## T 7: Higgs, Di-Higgs I

### T 7.3: Vortrag

### Montag, 20. März 2023, 17:00–17:15, HSZ/0105

The reconstruction of the ττ invariant mass in H → ττ decays as a machine learning task — •Moritz Molch, Ulrich Husemann, Nikita Shadskiy, Lars Sowa, Michael Waßmer, and Roger Wolf — Institute of Experimental Particle Physics (ETP), Karlsruhe Institute of Technology

Analyses that deal with Higgs boson decays into a pair of τ leptons often rely on a good reconstruction of the ττ invariant mass. As the decay of two τ leptons involves at least two neutrinos, the reconstruction of m_{ττ} is a challenging part of such analyses.

In many analyses at the CMS experiment the SVfit algorithm, which is a likelihood method on an event-by-event basis, is utilized for that task. First studies have shown that m_{ττ} can also be reconstructed using a deep neural network.

In this talk the applicability of deep neural networks to reconstruct m_{ττ} is further investigated and a comparison to current methods is made.