Processing of non-constant baseline pulses: a matrix technique

TL;DR

This paper evaluates a matrix-based optimal filter technique for processing non-constant baseline pulses in high-activity experiments like HOLMES, using simulated data to assess its effectiveness.

Contribution

It introduces and tests a matrix technique specifically designed to handle non-constant baseline pulses in high-activity experimental data.

Findings

The matrix technique effectively processes non-constant baseline pulses.

Simulation results demonstrate improved pulse analysis accuracy.

The method shows potential for application in high-activity experiments.

Abstract

For a high source activity experiment, such as HOLMES, non-constant baseline pulses could constitute a great fraction of the data-set. We test the optimal filter matrix technique, proposed to process these pulses, on simulated responses of HOLMES microcalorimeters.