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

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.

arXiv comment14 pages, 6 figures, 1 table, code available via Zenodo/GitHub (https://doi.org/10.5281/zenodo.4553515)

References in corpus (9)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• Array Programming with NumPy
• High-precision measurement of the atomic mass of the electron
• Separated Oscillatory Fields for High-Precision Penning Trap Mass Spectrometry
• Direct Measurement of the Mass Difference of Ho163 and Dy163 Solves the Q-Value Puzzle for the Neutrino Mass Determination
• First glimpse of the $N=82$ shell closure below $Z=50$ from masses of neutron-rich cadmium isotopes and isomers
• Q-Value and Half-Lives for the Double-Beta-Decay Nuclide 110Pd
• Position-sensitive ion detection in precision Penning trap mass spectrometry
• Direct decay-energy measurement as a route to the neutrino mass

Cited by in corpus (1)

• Gaussian mixture model clustering algorithms for the analysis of high-precision mass measurements