Belle II Document Server 16 records found  1 - 10next  jump to record: Search took 0.00 seconds. 
1. Improving the Belle II Neural Track Trigger with Deep Neural Networks / Timo Forsthofer ; Prof. Christian Kiesling [BELLE2-MTHESIS-2024-020] Presented on 30 06 2024 MSc
2024
Max-Planck-Intitute for Physics / Garching
In order to provide accurate measurements of Standard Model parameters and search for new physics at the precision frontier [1], the Belle II experiments aims to reach an instantaneous luminosity of 6 × 1035 cm−2s−1 [2]. [...]
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2. Upgrade of Belle II's Neural Network Trigger by Track Finding in Three-Dimensional Hough Space / Simon Hiesl ; Prof. Dr. Christian Kiesling [BELLE2-MTHESIS-2024-018] Presented on 12 04 2024 MSc
2024
Max-Planck-Institute for Physics / Munich
The target luminosity of the Belle II experiment, located at the SuperKEKB electron-positron collider in Tsukuba, Japan, is 6x10^{35} cm^{-2}s^{-1}. [...]
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3. Slow Pion Identification using the Pixel Detector of Belle II / Mariangela Varela ; Prof. Dr. Christian Kiesling [BELLE2-MTHESIS-2024-001] Presented on 07 09 2023 MSc
2023
Max-Planck-Intitute for Physics / Munich, Germany
Charged pions coming from D∗ decays are very useful to tag the flavor of neutral B mesons. [...]
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4. Ecient Physics Signal Selectors for the First Trigger Level of the Belle II Experiment based on Machine Learning / Sebastian Skambraks ; Christian Kiesling [BELLE2-PTHESIS-2023-015] Presented on 22 11 2021 PhD
2021
Ludwig-Maximilians-University / Munich
A neural network based z-vertex trigger is developed for the first level trigger of the upgraded flavor physics experiment Belle II at the high luminosity B factory SuperKEKB in Tsukuba, Japan. [...]
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5. Analysis on the Lepton Flavor Violating Decay τ -> μ π0 in Belle II / Marton Nemeth-Csoka ; Christian Kiesling [BELLE2-MTHESIS-2023-036] Presented on 27 11 2021 MSc
2021
Ludwig-Maximilians-University / Munich
This work focuses on the lepton flavor violating decay τ → μπ0 with the goal to explore the prospects of finding New Physics in this particular channel. [...]
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6. Developing a Displaced Vertex Trigger for Dark Matter Searches at the Belle II Experiment / Elia Schmidt ; Prof. Dr. Christian Kiesling [BELLE2-MTHESIS-2023-021] Presented on 13 03 2023 MSc
2023
Max-Planck-Institute for Physics / Munich
For many well-motivated dark matter models, discovery potential is predicted at highintensity particle colliders such as the Belle II experiment. [...]
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7. Background Analysis for $B^0$ Lifetime and Oscillation Frequency Measurement using Hadronic $B^0\rightarrow D^{(*)-}\pi^+$ Channels at Belle II / Caspar Schmitt ; Christian Kiesling ; Thibaud Humair [BELLE2-MTHESIS-2021-076] Presented on 13 09 2021 MSc
2021
Max-Planck Institute for Physics / Munich
To explain the origin of the observed matter-antimatter asymmetry in the universe, new sources of charge-parity (CP) symmetry violation beyond the standard model of particle physics are required. [...]
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8. SM Compatibility of B to K*)pi Measurements and Ongoing Analysis on B+ to K*(892)+ pi0 in Belle II / Oskar Tittel ; Christian Kiesling [BELLE2-MTHESIS-2021-004] Presented on 15 03 2021 MSc
2021
Max-Planck-Institut für Physik / Munich
In 2001, the BaBar and Belle experiments have convincingly confirmed the CP violation within the B meson system as predicted by the Standard Model (SM). [...]
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9. Search for the LFV-Decay τ→ μπ⁰ / Marton Nemeth-Csoka ; Felix Meggendorfer ; Christian Kiesling [BELLE2-TALK-CONF-2021-007] 12 Minutes
10 March 2021
/ DPG Spring 2021
With the start of data taking using the Belle II detector at the SuperKEKB electron-positron collider a new era in searches for New Physics is on the horizon. [...]
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10. Optimization of the z-Vertex Neural Network Trigger for the Belle II Experiment / Sara McCarney ; Christian Kiesling [BELLE2-MTHESIS-2020-004] Presented on 08 08 2019 MSc
2019
Max-Planck-Institute for Physics / Munich
For the Belle II experiment at the SuperKEKB asymmetric electron-positron (e+/e-)collider (KEK, Japan) the concept of a first level (L1) track trigger, realized by neural networks, is presented [...]
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