The International Linear Collider (ILC) is one of the best candidates for the future of the high energy physics to explore many unknown phenomena such as dark matter and the physics beyond the Standard Model. The ILC has two detectors. The International Large Detector (ILD) is one of these detectors and a Time Projection Chamber (TPC) is a tracker detector foreseen for the ILD. The main goal of the TPC is to measure the momentum of tracks and the energy loss of charged particles in order to reach high precision physics observables. Many different technologies are considered for this purpose.
GridPix, i.e. a combination of a micropattern gaseous detector and pixelized
readout, one of the candidate readouts for the ILD TPC, is under investigation in this thesis. The result of this combination is that there are many hits along a track causing a better spatial resolution compared with other readout systems. This property is essential to measure the momentum more precisely. In addition, the huge amount of the hits along a track improves the energy loss measurement. However, the pattern recognition (track finding) for the GridPix is very challenging due to a large number of hits and diffusion effects in the TPC in addition to the noise in the readout system.
A novel algorithm for the track finding has been developed to solve this difficulty. This algorithm first tries to find a segment of a track in a small area, called tracklet, based on the Hough Transform and using a bivariate normal distribution to improve collecting relevant hits of a tracklet. After finding all tracklets in all regions, the relevant tracklets are merged in order to have the full track. A successful performance of this algorithm for both simulated and experimental data shows that it is promising for the future.