Online energy reconstruction for calorimeters under high pile-up conditions using deconvolutional techniques

Abstract

High-energy calorimeters operating at high data acquisition rates may suffer from signal superposition (pile-up) in their electronic readout. This issue arises when the time interval between two consecutive incoming physics signals is shorter than the front-end electronics latency. Signal pile-up can significantly degrade online energy estimation, and some palliative approaches treat pile-up as an additional noise source to preserve the well-established Optimal Filter theory as the baseline for signal estimation. To enable actual online compensation for pile-up effects, the method proposed in this paper models the front-end electronics as a linear transmission channel whose transfer function can be equalized (deconvolved). For experiments in which the acquisition rate is synchronized with the collision clock, the equalizer output allows direct energy estimation per bunch-crossing (BC). Optimal approximations for the equalizer design are proposed using both FIR (Finite Impulse Response) filters and an iterative method. The latter provides improved reconstruction performance (i.e., smaller errors), but at the cost of higher computational complexity and additional data-flow circuitry for online implementation. Toy simulation data, based on typical calorimeter front-end responses, are used to evaluate the performance of the proposed methods.