CZ+SK HEP Workshop 2026

Session

Block 6

11 Sept 2026, 11:00

Academy of Science, Sál Dvořák (Prague)

40. Transverse-momentum dependent effects in semi-inclusive DIS at COMPASS

Vendula Benesova (Charles University (CZ))

11/09/2026, 11:00

COMPASS experiment at CERN had a wide physics programme. One of its cornerstones were studies of hadron production in deep inelastic scattering (DIS), which can be interpreted in the transverse-momentum-dependent (TMD) factorisation framework, allowing to access the distributions of polarisation and transverse momentum of quarks within the nucleon in the language of TMD PDFs, and the...

22. Angular analysis of B0 → K*0 μ+ μ- decays with the ATLAS detector

Gokul Duraikandan (Charles University (CZ))

11/09/2026, 11:18

Rare flavour-changing neutral-current decays are powerful probes of the Standard Model and of possible new physics, as they are suppressed in the Standard Model and can receive contributions from virtual heavy particles. The decay $B^0 \to K^{*0}\mu^+\mu^-$ provides a particularly rich channel through its multidimensional angular distribution, from which observables sensitive to the $b \to...

14. Performance and Internal Stability of the ATLAS Timepix3 Detector Network during the 2025 van der Meer Scans

Catalina Lesmes Ramirez (Czech Technical University in Prague (CZ))

11/09/2026, 11:36

The Timepix3 detector network installed inside the ATLAS cavern [1] has demonstrated reliable performance for measuring particle fluxes and monitoring luminosity during LHC operations [2, 4]. Comprising fourteen operational detectors distributed throughout the ATLAS experiment, the network is exposed to diverse radiation fields and flux levels. Detectors closer to the interaction point provide...

25. FastFrames - multithreaded analysis framework used by ATLAS collaboration

Michal Dubovsky (Comenius University (SK))

11/09/2026, 11:54

The talk will give an overview of an multithreaded (multiple CPU cores), physics framework FastFrames, used by the ATLAS collaboration. The goal of FastFrames is to enable analysis teams to efficiently scale their analysis specific code to multiple CPU cores, thus significantly speeding up physics analysis timescale by reducing computational time.

The talk will describe key problems that...

31. Benchmarking Machine Learning Architectures for ttH Multilepton Signal Sensitivity

Lukáš Viceník (Czech Technical University in Prague (CZ))

11/09/2026, 12:12

Machine-learning benchmarks for signal--background separation in high-energy physics are often confounded by inconsistent feature definitions, training procedures, and evaluation metrics. We present a controlled comparison of six architectures for ttH multilepton classification, from XGBoost to Lorentz-equivariant graph networks, under standardised hyperparameter optimisation across a...