Continuous Front-End Signal Flow Simulation in Nuclear Instrumentation Using the Lorenzetti Framework

Abstract

Particle detector simulators, such as the Lorenzetti framework, are essential tools for studying and designing new acquisition architectures for nuclear instrumentation. Generally, these simulators encompass the entire readout chain, from pulse digitization to sample storage. Although well-established, this event-driven simulation philosophy presents limitations when studying first-level (L1) trigger algorithms, which operate heavily on continuous data streams. Currently, it is not possible to use standard simulators to effectively analyze this type of real-time processing. To bridge this gap, this work proposes a reinterpretation of Minimum Bias simulation data, transforming it into a continuous sequence of collisions. The proposed method enables the generation of continuous data in a free-running regime, providing a robust framework for the design, testing, and development of real-time calorimetry data processing systems, specifically targeting low-level trigger algorithms within the Lorenzetti environment.