Approaches to the Optimal Nonlinear Analysis of Microcalorimeter Pulses

TL;DR

This paper introduces a method for analyzing microcalorimeter pulses nonlinearly while maintaining the benefits of linear optimal filtering, demonstrated by accurately computing the Joule energy as an estimator of photon energy.

Contribution

The paper presents a novel approach to nonlinear analysis of microcalorimeter pulses that preserves linear filtering advantages, specifically applied to Joule energy estimation.

Findings

Successfully computed Joule energy as a nonlinear estimator

Preserved signal-to-noise ratio advantages of linear filtering

Demonstrated applicability to photon energy measurement

Abstract

We consider how to analyze microcalorimeter pulses for quantities that are nonlinear in the data, while preserving the signal-to-noise advantages of lin- ear optimal filtering. We successfully apply our chosen approach to compute the electrothermal feedback energy deficit (the "Joule energy") of a pulse, which has been proposed as a linear estimator of the deposited photon energy.