Enhancing Spatial Resolution in Hybrid Pixel Detectors Through Optimized Charge Transport Simulation
Recent advancements in hybrid pixel detector technology have been reported in a paper titled "Optimizing Charge Transport Simulation for Hybrid Pixel Detectors" by X. Xie and 25 co-authors. The research focuses on enhancing the spatial resolution of the MÖNCH 25 µm pitch hybrid pixel detector through the application of deep learning models that utilize both simulation and measurement data.
The study identifies significant challenges when comparing simulation-based models to those derived from actual measurements, particularly for electrons. The findings indicate that the spatial resolution achieved via simulations is notably lower than that obtained from measurements. Additionally, discrepancies were noted when comparing X-ray simulations with actual measurements, especially concerning the spectral output of individual pixels. These issues suggest a need for optimization in current simulation methodologies.
To address these challenges, the authors conducted a Monte Carlo simulation to model the dynamics of charge carriers within the silicon sensor. This simulation aims to refine the modeling of charge transport, encompassing various processes such as the initial generation of the charge cloud, its drift, diffusion, repulsion, and the impact of electronic noise. The results from this simulation were validated against measurements from the MÖNCH detector for X-rays, showing a marked improvement in agreement when accounting for charge repulsion effects.
This research is significant as it lays the groundwork for future enhancements in detector technology, which could lead to improved imaging capabilities in various applications, including medical imaging and particle physics experiments. The findings are prepared for submission to the Journal of Instrumentation as part of the proceedings for the 25th International Workshops on Radiation Imaging Detectors.
For further details, the paper can be accessed at arXiv:2407.20841.