Studies of seeding algorithms in future particle collider experiments

This study focus is on the implementation and effects of 4-dimensional (4D) tracking technology in the ATLAS experiment at CERN's High Luminosity Large Hadron Collider (HL-LHC). It addresses the computational challenges posed by the expected increase in simultaneous collisions (pile-up) and the need for efficient tracking algorithms in the upgraded detector environment. The study explores the potential of seeding algorithms, which are crucial for track reconstruction, to utilize timing information alongside spatial coordinates to discriminate between particle tracks. It investigates the implications of incorporating time information into the ATLAS ITk silicon inner tracker detector during event reconstruction. The report also examines the broader application of such algorithms in future particle collider experiments, suggesting that time information can drastically reduce complexity and enhance particle identification, particularly in high pile-up scenarios. In a simulation study of the ODD (Open Data Detector) a significant improvement in CPU timing, a reduction in the number of fake seeds, and consequently, a more efficient event reconstruction process was achieved, after the implementation of time information in the seeding algorithm. The findings highlight the necessity of temporal resolution in seeding algorithms and propose a methodology for their assessment and improvement, setting a foundation for future research in the field of temporal seeding for particle colliders.