T 70: Experimental Methods (general) 3
Wednesday, March 23, 2022, 16:15–18:30, T-H29
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16:15 |
T 70.1 |
Calibration of the b-tagging mis-tag rate for charm jets based on W+c events at √s = 13 TeV with the ATLAS experiment — Johannes Erdmann and •Benedikt Gocke
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16:30 |
T 70.2 |
Convolutional Networks and Deep Learning at the Belle II Experiment — •Johannes Bilk, Sören Lange, Katharina Dort, Stephanie Käs, and Timo Schellhaas
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16:45 |
T 70.3 |
b-Tagging studies for the ATLAS experiment — •Eleonora Loiacono
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17:00 |
T 70.4 |
Extrapolation of flavour tagging calibrations to high transverse momenta — Arnulf Quadt, Elizaveta Shabalina, and •Sreelakshmi Sindhu
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17:15 |
T 70.5 |
Utilizing muons to tag b-jets in ATLAS — •Frederic Renner, Clara Elisabeth Leitgeb, and Cigdem Issever
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17:30 |
T 70.6 |
Signal efficiency corrections for boosted X→ bb tagger using Z→ bb events with the ATLAS experiment — •Daariimaa Battulga, Arely Cortes Gonzalez, and Cigdem Issever
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17:45 |
T 70.7 |
A machine-learning based method to improve isolation variables for photon identification with the ATLAS detector — Johannes Erdmann, Olaf Nackenhorst, and •Michael Windau
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18:00 |
T 70.8 |
Data-driven corrections to shower shape variables for photon identification at the ATLAS experiment with 13 TeV pp collision data — •Jan Lukas Späh, Björn Wendland, and Johannes Erdmann
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18:15 |
T 70.9 |
Towards tuning electromagnetic shower properties to data with AtlFast3 — •Joshua Beirer, Michael Duehrssen, and Stan Lai
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