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Given the importance of nuclear mass predictions, numerous models have been developed to extrapolate the measured data into unknown regions. While neural networks -- the core of modern artificial intelligence -- have been recently suggested…

Nuclear Theory · Physics 2025-07-11 C. H. Kim , K. Y. Chae , M. S. Smith

We show that the Liquid Drop Model is best suited to describe the masses of prolate deformed nuclei than of spherical nuclei. To this end three Liquid Drop Mass formulas are employed to describe nuclear masses of eight sets of nuclei with…

Nuclear Theory · Physics 2015-05-30 Jorge G. Hirsch , Cesar Barbero , Alejandro E. Mariano

Volume-filling cross-diffusion equations for the components of a tissue structure are formally derived from mass conservation laws and force balances for the interphase pressures and viscous drag forces in a multiphase approach. The…

Analysis of PDEs · Mathematics 2026-04-03 Ansgar Jüngel , Cordula Reisch , Sara Xhahysa

We present a theoretical framework to quantify statistical uncertainties in covariant density functional theory (CDFT) for both nuclear matter and finite nuclei, based on a relativistic point-coupling energy density functional (EDF). By…

Nuclear Theory · Physics 2026-04-10 X. Zhang , C. C. Wang , C. R. Ding , J. M. Yao

Twelve physics-informed machine learning models have been trained to model binding energy residuals. Our approach begins with determining the difference between measured experimental binding energies and three different mass models. Then…

Nuclear Theory · Physics 2025-03-12 Ian Bentley , James Tedder , Marwan Gebran , Ayan Paul

For recently constructed classes of D6-brane models, yielding the Standard Model fermion spectrum and gauge symmetry, we compute lower bounds on the masses of new U(1) fields that such models predict in addition to the hypercharge $U(1)_Y$.…

High Energy Physics - Phenomenology · Physics 2011-03-23 D. M. Ghilencea

Properties of 8,979 nuclei ranging from oxygen-16 to Z = 136, A = 339 and extending from the proton drip line to the neutron drip line have been calculated by use of the 1992 version of the finite-range droplet model. The calculated…

Nuclear Theory · Physics 2007-05-23 J. Rayford Nix , Peter Moller

The sources of theoretical uncertainties in the prediction of the two-neutron drip line are analyzed in the framework of covariant density functional theory. We concentrate on single-particle and pairing properties as potential sources of…

Nuclear Theory · Physics 2015-08-25 A. V. Afanasjev , S. E. Agbemava , D. Ray , P. Ring

The nucleon separation energies and shell gaps in nuclei over the whole nuclear chart are systematically studied with eight global nuclear mass models. For unmeasured neutron-rich and super-heavy regions, the uncertainty of the predictions…

Nuclear Theory · Physics 2015-06-22 Qiuhong Mo , Min Liu , Ning Wang

Based on Monte Carlo approach and conventional error analysis theory, taking the heaviest doubly magic nucleus $^{208}$Pb as an example, we firstly evaluate the propagated uncertainties of universal potential parameters for three typical…

Nuclear Theory · Physics 2021-02-02 Zhen-Zhen Zhang , Hua-Lei Wang , Hai-Yan Meng , Min-Liang Liu

Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical…

Nuclear Theory · Physics 2017-03-01 A. E. Lovell , F. M. Nunes , J. Sarich , S. M. Wild

Nuclear masses are calculated using the modified Bethe-Weizsacker mass formula in which the isotonic shifts have been incorporated. The results are compared with the improved liquid drop model with isotonic shift. Mass excesses predicted by…

Nuclear Theory · Physics 2009-11-10 P. Roy Chowdhury , C. Samanta , D. N. Basu

Uncertainty estimation, which provides a means of building explainable neural networks for medical imaging applications, have mostly been studied for single deep learning models that focus on a specific task. In this paper, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Leonhard F. Feiner , Martin J. Menten , Kerstin Hammernik , Paul Hager , Wenqi Huang , Daniel Rueckert , Rickmer F. Braren , Georgios Kaissis

When propagating uncertainty in the data of differential equations, the probability laws describing the uncertainty are typically themselves subject to uncertainty. We present a sensitivity analysis of uncertainty propagation for…

Probability · Mathematics 2022-03-01 Oliver G. Ernst , Alois Pichler , Björn Sprungk

New superheavy nuclei are often identified through their characteristic $\alpha$-decay energies, which requires accurate calculations of $Q_{\alpha}$ values. While many $Q_{\alpha}$ predictions are available, little is known about their…

Nuclear Theory · Physics 2019-01-30 Erik Olsen , Witold Nazarewicz

Information about the physical properties of astrophysical objects cannot be measured directly but is inferred by interpreting spectroscopic observations in the context of atomic physics calculations. Ratios of emission lines, for example,…

This study proposes a linear approach for propagating uncertainties in the multiline thru-reflect-line (TRL) calibration method for vector network analyzers. The multiline TRL formulation we are proposing applies the law of uncertainty…

Signal Processing · Electrical Eng. & Systems 2023-07-19 Ziad Hatab , Michael Ernst Gadringer , Wolfgang Bösch

In many time-dependent problems of practical interest the parameters and/or initial conditions entering the equations describing the evolution of the various quantities exhibit uncertainty. One way to address the problem of how this…

Numerical Analysis · Mathematics 2018-03-09 Jing Li , Panos Stinis

Some general features of the Bethe-Weizsacker mass formula recently extended to light nuclei have been explored. Though this formula improves fits to the properties of light nuclei and it does seem to work well in delineating the positions…

Nuclear Theory · Physics 2009-11-10 D. N. Basu

In many time-dependent problems of practical interest the parameters entering the equations describing the evolution of the various quantities exhibit uncertainty. One way to address the problem of how this uncertainty impacts the solution…

Numerical Analysis · Mathematics 2012-11-20 Panagiotis Stinis