Quality factor analysis and optimization of digital filtering signal reconstruction for liquid ionization calorimeters

TL;DR

This paper analyzes the impact of pulse shape residuals on the optimal filtering reconstruction in liquid ionization calorimeters and proposes an analysis method to correct these residuals, improving signal quality assessment.

Contribution

It introduces a new analysis method to evaluate and correct residual differences in pulse shapes, enhancing the accuracy of signal amplitude estimates in calorimeter data reconstruction.

Findings

Residuals affect the quality factor and amplitude estimates.

The correction preserves amplitude normalization.

Restores expected chi-squared behavior of the quality factor.

Abstract

The Optimal Filtering (OF) reconstruction of the sampled signals from a particle detector such as a liquid ionization calorimeter relies on the knowledge of the normalized pulse shapes. This knowledge is always imprecise, since there are residual differences between the true ionization pulse shapes and the predicted ones, whatever the method used to model or fit the particle--induced signals. The systematic error introduced by the residuals on the signal amplitude estimate is analyzed, as well as the effect on the quality factor provided by the OF reconstruction. An analysis method to evaluate the residuals from a sample of signals is developed and tested with a simulation tool. The correction obtained is showed to preserve the original amplitude normalization, while restoring the expected $\chi^2 $--like behavior of the quality factor.