Bachelor Thesis Open Access
Tim Leidel
{
"abstract": "<p>Precision tracking of charged particles is a key ingredient for the physics programme of the Belle~II experiment at the SuperKEKB.<br>\nIn particular, decays in flight of charged kaons and pions, such as $K^{+} \\to \\mu^{+} \\nu_\\mu$ and $\\pi^{+} \\to \\mu^{+} \\nu_\\mu$ and their charge conjugates, pose a challenge for standard track-finding algorithms.<br>\nThese tracks, hereafter referred to as tricky tracks, exhibit a kink topology with a change of momentum and direction at a displaced decay vertex.<br>\nThey 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.<br>\nA successful reconstruction of tricky tracks would also make new processes measurable.</p>\n\n<p>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.<br>\nThe 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.<br>\nTo this end, simulated Monte Carlo samples are used that combine realistic physics events with specialised particle-gun configurations.</p>\n\n<p>On the algorithmic side, the CATFinder is extended with two additional binary classifiers trained to identify mother and daughter particles in tricky tracks.<br>\nThree 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.<br>\nThe performance of the resulting models is evaluated on prompt pion samples and mixed $B$ events.<br>\nThe evaluation considers general tracking metrics, kink-specific metrics, momentum resolution, hit-based metrics, and classifier-quality measures such as receiver operating characteristic curves.<br>\nComparing the training strategies provides insight into the trade-offs between generic tracking performance and specialised sensitivity to tricky tracks.</p>",
"author": [
{
"family": "Tim Leidel"
}
],
"id": "22381",
"issued": {
"date-parts": [
[
2025,
12,
11
]
]
},
"language": "eng",
"title": "Tricky Tracks with the CATFinder at Belle II",
"type": "thesis"
}