Monte-Carlo-based Signal Simulation of Silicon Drift Detectors

Abstract

Due to their excellent energy resolution and high count rate capability silicon drift detectors are state-of-the-art sensors for energy-dispersive detection of X-rays. X-ray energy spectra are acquired by signal processing of the detector output signals. Research in signal processing with silicon drift detectors targets signal throughput, detection of light elements, high-energy efficiency, energy resolution, pile-up rejection, and computing efficiency. For the investigation of signal processing with silicon drift detectors a simulation model is developed within this work. With this approach an alternative to the time-consuming and error-prone experimental analysis is developed. Benefits of the simulation are independence from hardware components and measurement conditions, due to software-based creation of signals with well-defined, configurable radiation and detector properties. Simulated time domain signal data is generated using a Monte-Carlo-based model of silicon drift detectors. Therefore, stochastic distributions for signal properties like pulse height, rise-time or signal timing are considered and implemented into the simulation tool. Simulated X-ray signals are superimposed with leakage current and time domain noise. For the description of detector noise a model based on an equivalent noise circuit is used. Applications for the simulation model are shown: Simulated detector signal data are used for offline investigations of signal processing algorithms allowing fast development of algorithms in a high-level programming language. Electrical signals of simulated detector data are generated using an arbitrary waveform generator for comparison and investigation of signal processing units in hardware. Furthermore, simulation-based design of analog circuits can be done using simulated signal data.