Sample with tracker hit information for tracking algorithm ML studies TTbar_13TeV_PU50_PixelSeeds

These can be used in ML studies of particle tracking algorithms. Particle tracking is the process of clustering the recorded hits into groups of points arranged along an helix. </p> <p> One of the first steps of the track finding workflow is the creation of track seeds, i.e. compatible pairs of hits from different detector layers, that are subsequently fed to to higher level pattern recognition steps.

The compatibility between two hits is evaluated only on the basis of geometrical considerations, such as cuts in $\eta$, $\phi$ and $r$, and these doublets define the building blocks for further tracks. However the set of compatible hit pairs is highly affected by combinatorial background resulting in the next steps of the tracking algorithm to process a significant fraction of fake doublets. For each event an $O(10^6)$ doublets are produced while only an $O(10^3)$ are genuine resulting in a fake ratio of $O(10^3)$. </p> <p> Each doublet in this dataset is charcaterised by a set of features, such as its coordinates and the charge released in ther Pixel Detector, and the pixel cluster shape, projected on 2D histogram.