Reconstruction of Space-Points

This step is common for both ITR and OTR. The only difference is the input - clusters for the OTR and hits for the ITR.

In the framework of the CATS algorithm, the term space-point means a short 3D track segment inside a superlayer. The space-points are reconstructed by first searching for hit (cluster) multiplets in the $0^o$-layers and then attaching multiplets in the stereo layers. The parameters of $0^o$-multiplets are estimated using the Least Squares Method (LSM). The combined $0^o$- and stereo-multiplets are used as space-point candidates and are fitted by a Kalman parameter estimator (KPE). The KPE is a Kalman-type filter that estimates four $(x_0, y_0, t_x, t_y)$ parameters of a space-point at a given reference $z$-plane and also calculates the $\chi^2$ value for the space-point. Only space-points which successfully pass a cut on $\chi^2$ are used. An example of an event with reconstructed space-points is shown in Fig. 4.4.

Figure 4.4: Reconstruction of space-points -- short 3D track segments inside superlayers.