# Validation and extrapolation of atomic mass with physics-informed fully connected neural network

Source: [Validation and extrapolation of atomic mass with physics-informed fully connected neural network](<https://www.sota2.com/research/paper/68fa49a31e209131ce9386e6>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T07:25:33.376Z

Authors: Yiming Huang, Jinhui Chen, Jiangyong Jia, Lu-Meng Liu, Yu-Gang Ma, Chunjian Zhang

Published: 2025-01-02T17:07:13.000Z

## Abstract

Machine learning offers a powerful framework for validating and predicting atomic mass. We compare three improved neural network methods for representation and extrapolation for atomic mass prediction. The powerful method, adopting a macroscopic-microscopic approach and treating complex nuclear effects as output labels, achieves superior accuracy in AME2020, yielding a much lower root-mean-square deviation of 0.122 MeV in the test set, significantly lower than alternative methods. It also exhibits a better extrapolation performance when predicting AME2020 from AME2016, with a root-mean-square deviation of 0.191 MeV. We further conduct sensitivity analyses against the model inputs to verify interpretable alignment beyond statistical metrics. Incorporating theoretical predictions of magic numbers and masses, our fully connected neural networks reproduce key nuclear phenomena including nucleon pairing correlation and magic number effects. The extrapolation capability of the framework is discussed and the accuracy of predicting new mass measurements for isotope chains has also been tested.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Nuclear mass excess prediction on AME Experiment I 2020 (interpolation)](<https://www.sota2.com/research/sota/nuclear-mass-excess-prediction-on-ame-experiment-i-2020-interpolation.md>): Nuclear mass excess prediction; AME Experiment I 2020 (interpolation); IntRMSE (MeV): 0.122.

- [Nuclear mass prediction on AME 2020](<https://www.sota2.com/research/sota/nuclear-mass-prediction-on-ame-2020.md>): Nuclear mass prediction; AME 2020; ExtRMSE: 0.191.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2501.01352>)

[PDF](<https://arxiv.org/pdf/2501.01352.pdf>)