Analysis methods and code for very high-precision mass measurements of unstable isotopes

TL;DR

This paper introduces a Python-based analysis code for PI-ICR mass spectrometry, significantly reducing statistical uncertainties and enabling high-precision measurements of exotic nuclear masses.

Contribution

The paper presents a new phase-determination method integrated into analysis software, improving statistical precision by up to ten times for mass spectrometry of unstable isotopes.

Findings

Up to 10 times reduction in statistical uncertainties.

Validation through extensive Monte-Carlo simulations.

Enables high-precision nuclear mass measurements.

Abstract

We present a robust analysis code developed in the Python language and incorporating libraries of the ROOT data analysis framework for the state-of-the-art mass spectrometry method called phase-imaging ion-cyclotron-resonance (PI-ICR). A step-by-step description of the dataset construction and analysis algorithm is given. The code features a new phase-determination approach that offers up to 10 times smaller statistical uncertainties. This improvement in statistical uncertainty is confirmed using extensive Monte-Carlo simulations and allows for very high-precision studies of exotic nuclear masses to test, among others, the standard model of particle physics.