To study rare processes, such as the formation of exotic particles, the PANDA experiment has been set up. To process the large dataflow, the subsystems preprocess the data. One example is the algorithm to search online for clusters in the data of the calorimeter, developed in this thesis. Due to the high interaction rates, the time is important. Optima have been determined to assign the data to (time)bunches (257, 97, and 15 ns) and hits to clusters (282, 122, and 40 ns), for interaction rates of 200 kHz and less, 2 MHz, and 20 MHz, respectively, and each hit must have a minimal energy of 3 MeV. Using these optima, the efficiencies for the investigated two- and seven-photon channels are 70-80% and 9-20%, respectively, depending on the interaction rate. In addition, it was investigated if the algorithm can run on the readout system, making use of the processing power in the data concentrators and the nodes in the data collection network. This was found to be possible, and, furthermore, the processing time using this approach is much lower. An important note to the efficiencies is that there were problems in creating the time stamps for the hits, which may cause the obtained results to deviate from reality. In addition, another step needs to be added to the reconstruction, where the event selection takes place, to determine the final efficiencies. It is recommended to proceed with the development of the cluster finding algorithm, as it delivers good performance at low costs.

The Endcap Disc DIRC has been developed to provide an excellent particle identification for the future PANDA experiment by separating pions and kaons up to a momentum of 4 GeV/c with a separation power of 3 standard deviations in the polar angle region from 5 ◦ to 22 ◦ . This goal will be achieved using dedicated particle identification algorithms based on likelihood methods and will be applied in an offline analysis and online event filtering. This paper evaluates the resulting PID performance using Monte-Carlo simulations to study basic single track PID as well as the analysis of complex physics channels. The online reconstruction algorithm has been tested with a Virtex4 FGPA card and optimized regarding the resulting constraints.

The PANDA detector at the future FAIR facility at GSI is planned as a fixed- target experiment for proton-antiproton collisions at momenta between 1.5 and 15 GeV/c. It will be used to address open questions in hadronic physics. In order to achieve a sufficient particle identification, two different DIRC detector concepts have been developed. This talk will cover the Endcap Disc DIRC detector which is placed at the forward endcap of the PANDA target spectrometer and will provide a 3σ separation of pions and kaons up to a momentum of 4 GeV/c for polar angles from 5° to 22°. The most important component of the DIRC detector is a 2 cm thin fused silica radiator plate that is divided into 4 identical quadrants. The surfaces are polished with high precision in order to guarantee little photon losses by total reflection and conserve the Cherenkov angle during propagation through the optical system. Intrinsic chromatic errors will be minimized by the implementation of an optical filter. The readout system consists of 96 readout elements with focusing optics and attached MCP-PMTs to focus the photons that are produced by the Cherenkov cone of the traversing particle and acquire their position and timing information. This new detector concept requires the development of dedicated reconstruction and particle identification algorithms which permit an efficient analysis of the measured time-correlated photon patterns. Time and event based simulations with dedicated Monte-Carlo simulation frameworks have been used to validate the PID requirements of the DIRC counter. Additionally, the Monte-Carlo simulations have been used to estimate the radiation dose in different detector volumes in order to compare these values with actual measurement results.