December 11, 2025 Bachelor Thesis Open Access

Tim Leidel

MARC21 XML Export

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    <subfield code="a">&lt;p&gt;Precision tracking of charged particles is a key ingredient for the physics programme of the Belle~II experiment at the SuperKEKB.&lt;br&gt;
In particular, decays in flight of charged kaons and pions, such as&amp;nbsp;$K^{+} \to \mu^{+} \nu_\mu$ and $\pi^{+} \to \mu^{+} \nu_\mu$ and their charge conjugates, pose a challenge for standard track-finding algorithms.&lt;br&gt;
These tracks, hereafter referred to as tricky tracks, exhibit a kink topology with a change of momentum and direction at a displaced decay vertex.&lt;br&gt;
They are relevant for a range of flavour-physics and new-physics analyses, since a successful reconstruction leads to an improvement in the particle identification and $\text{d}E/\text{d}x$ calibration.&lt;br&gt;
A successful reconstruction of tricky tracks would also make new processes measurable.&lt;/p&gt;

&lt;p&gt;This thesis studies the reconstruction of tricky tracks using the CDC AI Track Finder, called CATFinder, a graph neural network-based track-finding algorithm for the central drift chamber, and a dedicated configuration for tricky tracks.&lt;br&gt;
The focus is on kink topologies from $K^{+} \to \mu^{+} \nu_\mu$ and $\pi^{+} \to \mu^{+} \nu_\mu$ decays, where both the mother and daughter tracks are reconstructable in the central drift chamber.&lt;br&gt;
To this end, simulated Monte Carlo samples are used that combine realistic physics events with specialised particle-gun configurations.&lt;/p&gt;

&lt;p&gt;On the algorithmic side, the CATFinder is extended with two additional binary classifiers trained to identify mother and daughter particles in tricky tracks.&lt;br&gt;
Three training strategies are explored that differ in the relative weight assigned to the new classifier terms in the loss function and in whether a pretraining phase is used without these terms.&lt;br&gt;
The performance of the resulting models is evaluated on prompt pion samples and mixed $B$ events.&lt;br&gt;
The evaluation considers general tracking metrics, kink-specific metrics, momentum resolution, hit-based metrics, and classifier-quality measures such as receiver operating characteristic curves.&lt;br&gt;
Comparing the training strategies provides insight into the trade-offs between generic tracking performance and specialised sensitivity to tricky tracks.&lt;/p&gt;</subfield>
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    <subfield code="a">Torben Ferber</subfield>
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    <subfield code="a">Giacomo De Pietro</subfield>
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    <subfield code="a">Tricky Tracks with the CATFinder at Belle II</subfield>
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    <subfield code="c">2025-12-11</subfield>
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    <subfield code="a">Tim Leidel</subfield>
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