Template-free Pulse Height Estimation of Microcalorimeter Responses with PCA

TL;DR

This paper introduces a PCA-based, template-free method for estimating pulse heights in microcalorimeter signals, significantly improving resolution in variable pulse-shape scenarios compared to traditional template-based filtering.

Contribution

The paper proposes a novel PCA-based approach for pulse height estimation that does not rely on predefined templates, enhancing resolution in variable pulse-shape microcalorimeter signals.

Findings

25% resolution improvement over standard methods

Effective for signals with high pulse-shape variation

Applicable to simulated microcalorimeter datasets

Abstract

We present a template-free method of estimating pulse height of micro-calorimeter signals based on principal component analysis (PCA). The method is shown to improve the resolution on a simulated dataset by 25\% compared to the standard filtering technique that uses the averaged pulse as an estimation for the signal template. This technique is useful for reconstruction of pulses in micro-calorimeters with a high degree of pulse-shape variation where finding the correct signal templates is difficult.