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

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.

本报告呈现了一种稳健的分析代码，该代码采用Python语言编写，并融合了ROOT数据分析框架的库，以应用于相位成像离子回旋共振（PI-ICR）这一先进的质谱方法。文中详细阐述了数据集构建与分析算法的步骤。该代码引入了一种新的相位确定方法，该方法能够将统计不确定性降低至原来的十分之一。这一统计不确定性的改进通过广泛的蒙特卡洛模拟得到了验证，并使得对奇特核质量的高精度研究成为可能，从而有助于检验标准模型（Standard Model）等粒子物理学领域的重要理论。