## 2 Overview of Data Processing in Modern Particle Detectors  
The physics analysis conducted in the modern HEP field starts with a particle accelerator. In the case of LHC, two streams of proton particles are accelerated up to 0.9999999\(c\) and collide at four specific detection points. The LHCb experiment is placed in one of these four locations and has a subset of eight dedicated detectors to acquire data from the particles generated in the collisions. The electromagnetic calorimeter is one of them. Complementing the previous definition, the calorimeter detector's general structure is segmented in three different rectangular-shaped regions, as can be seen in Figure 1.  
Although all modules have the same size of 12 \(\times\) 12 cm, the number of readout cells on a module depends on the region. The inner region is the closest to the accelerator pipe and has nine readout cells of 4 \(\times\) 4 cm per module. It has the highest granularity among the three regions since it is the region with the highest occupancy of incident particles. The middle region surrounds the inner and has four readout cells of 6 \(\times\) 6 cm per module, and the outer region has a single readout cell of 12 \(\times\) 12 cm per module. Since the occupancy decreases with the distance from the accelerator pipe, the shape of the readout cells for middle and outer regions is increased following a trade-off between precision and cost. Regarding the size of the inner readout cells, it is calculated following the _Moliere_ radius. Therefore, a particle is expected to deposit all of its energy in one inner readout cell if it falls on its center. However, to ensure that all the energy from a particle is captured, and to simplify the reconstruction algorithm, the definition of a calorimeter cluster stands for a 3 \(\times\) 3 block of readout cells around an energy peak. Some studies have been done regarding the cluster shapes [14] where 2 \(\times\) 2 clusters show promising performance for high luminosity, although the 3 \(\times\) 3 cluster is used as a base for masking other shapes on clusters. Therefore, for simplicity in the reconstruction process, the definition of 3 \(\times\) 3 readout cell clusters is maintained through all the regions of the detector. Since in this approach we focus on improving the reconstruction performance rather than particle identification, we can only evaluate comparisons between the reconstruction results and simulation data. In all particle physics experiments, data are not analyzed directly from the detector readout, what is called raw data. Instead, domain experts need information of what happened inside the detectors in order to make the physics' analysis. This information is extracted through the reconstruction process. In the case of the calorimeter detector, a sample of raw data contains the list of readout cells that have an energy deposit from  
Figure 1: The electromagnetic calorimeter 3d-view from behind the detector towards the interaction point [5]. one collision. This needs to be reconstructed as all the groups of \(3\times 3\) readout cells with the energy, belonging to the same particle colliding into the calorimeter. Up until now, the amount of data generated by all the detectors at LHCb reached the order of 35 GB/s. However, the processing rate of each datum sample was decreased by a factor 40 to a throughput of 1 MHz using a hardware selector known as level 0 trigger [15]. In the upcoming upgrade of the experiment, the data processing rate is going to increase to 30 MHz, meaning the full 35 GB/s will be processed. Since this throughput rate cannot be stored with current technology, the trigger system will be upgraded into a full software trigger called the high level trigger (HLT), where complete data reconstruction needs to take place. Even so, since the number of collisions will also increase in the upgrade, the occupancy of the LHCb detector is going to increase in a factor five.