Advances in machine learning methods provide tools that have broad applicability in
scientific research. These techniques are being applied across the diversity of nuclear …

Abstract Machine learning (ML) is becoming a new paradigm for scientific research in
various research fields due to its exciting and powerful capability of modeling tools used for …

Background: The masses of ∼∼ 2500 nuclei have been measured experimentally;
however,> 7000 isotopes are predicted to exist in the nuclear landscape from H (Z= 1 Z= 1) …

Charge radius is one of the most fundamental properties of a nucleus. However, a precise
description of the evolution of charge radii along an isotopic chain is highly nontrivial, as …

Theoretical prediction shows that about 9000 nuclei could be bounded, of which the
properties will be hot topics in the new nuclear physics era opened by the new third …

A multi-task learning (MTL) framework, called gradient kernel ridge regression, for nuclear
masses and separation energies is developed by introducing gradient kernel functions to …

A feed-forward neural network model is trained to calculate the nuclear charge radii. The
model is trained with the input data set of proton and neutron number Z, N, the electric …

Accurate nuclear data provide an essential foundation for advances in a wide range of
fields, including nuclear energy, nuclear safety and security, safeguards, nuclear medicine …

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Menu Find a journal Publish with us Search Cart 1.Home 2.The European Physical Journal A …

We study the nature of the hidden charm pentaquarks, ie, the P c 4312, P c 4440 and P c
(4457), with a neural network approach in pionless effective field theory. In this framework …