arXiv subjects

B. B. Jiao

Publications and source records attributed to B. B. Jiao.

3 recordsLinked to original sources

arXiv2020

Nuclear binding energy predictions based on BP neural network

Nuclear masses are of great importance in nuclear physics and astrophysics. Descriptive experimental data on nuclear masses and the prediction of unknown masses based on residual proton-neutron interactions are a focus in nuclear physics. The accuracy of the residual interaction determines the accuracy of the nuclear mass values, so the study of residual interactions is essential. Before we carry out this study, there are many papers using artificial neural networks in nuclear physics. But no one uses BP neural network to study residual interactions. In this paper, we obtained a description and prediction model for residual interactions based on BP neural network. By combining experimental values with residual interactions model, we successfully calculate the nuclear masses of $A\geq100$. Results demonstrate that the differences between our calculated values and experimental values (AME2003, AME2012 and AME2016) show that the root-mean-squared deviations (RMSDs) are small (comparing with AME2003, the odd-A nuclei RMSD and the even-A nuclei RMSD are 112 keV and 128 keV; comparing with AME2012, the odd-A nuclei RMSD and the even-A nuclei RMSD are 103 keV and 121 keV; comparing with AME2016, the RMSD of odd-A nuclei and even-A nuclei are 106 keV and 122 keV, respectively). In addition, we obtained some predicted masses based on AME2003 and AME2012, the predicted values have good accuracy and compared well with experimental values (AME2012 and AME2016). The results show that the study of residual interactions using the proposed BP neural network method is feasible and accurate. This method is helpful for analyzing and extracting useful information from a large number of experimental values and then providing a reference for discovering physical laws and support for physical experiments.

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arXiv2020

Description and prediction of even-A nuclear masses based on residual proton-neutron interactions

The odd-even staggering of neighboring nuclear masses is very useful in calculating local mass relations and nucleon-pair correlations. During the past decades, there has been an increasing interest in the odd-even features of the mass relations and related quantities exhibited in masses of neighboring nuclei. In this work, after choosing a nucleus, we made an analysis of its neighboring nuclei on the upper left corner and the lower right corner respectively. We empirically obtained a new residual interaction formula of even-$A$ ($A$ is the mass number) nuclei, and it is an revision based on the existing empirical local formula of the proton-neutron interactions between the last proton and the last neutron ($δV_{1p-1n}$). We then calculated the even-$A$ nuclear masses. The differences between our calculated values and the AME2012 database show that the root-mean-squared deviations (RMSD) are small (for even-$A$ nuclei: $A$ $\geq$ 42, RMSD $\approx$ 161 keV; $A$ $\geq$ 100, RMSD $\approx$ 125 keV), while for heavy nuclei, some of our calculated values can reach an accuracy of a few tens of keV. With our residual interaction formula including one parameter, we have successfully predicted some unknown masses. Some of our predicted values compared well with the experimental values (AME2016). In addition, the accuracy and simplicity of our predicted masses for medium and heavy nuclei are comparable to those of the AME2012 (AME2016) extrapolations.

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arXiv2020

The study of Nuclear binding energy for $A\geq100$ based on Odd-Even staggering of nuclear masses

The existing nuclear masses formula and nuclear masses model has undoubtedly achieved very good results, but it is still not satisfactory for some nuclear masses. Although there are many studies in Odd-Even staggering (OES) of nuclear masses, but the research on nuclear masses by using the systematicness of OES is indeed very few. Our purpose in this paper is to describe an empirical formula for Odd-Even staggering of nuclear masses that can be useful in describing and predicting nuclear masses. We empirically obtained the formula of odd-Z (odd-N) nuclei and even-Z (even-N) nuclei based on studying the OES of nuclear masses (AME2012). With the proton (neutron) empirical pairing gap from the OES of the binding energies and AME2012 database, the root-mean-square deviation of even-Z nuclei and odd-Z nuclei that we have successfully obtained 208 keV and 238 keV, respectively. The RMSD of even-N nuclei and odd-N nuclei is 222 keV and 240 keV. The result shows that our predicted values are compared well with values in AME2016, and some predicted values agree better with the experimental values. These results demonstrate that our empirical formulas have good accuracy and reliability. Another advantage of these formulas is that they use less known nuclear masses to predict unknown nuclear masses. In addition, this paper also uses BP neural network to study proton Odd-Even staggering of nuclear masses (even-Z and odd-Z nuclei) and neutron Odd-Even staggering of nuclear masses (even-N and odd-N nuclei). The RMSD of even-Z and odd-Z nuclei is 141 keV and 159 keV; the RMSD of even-N and odd-N nuclei is 150 keV and 160 keV. The results show that the RMSD of nuclear masses based on neural network 60-80 keV decrease than that based on empirical formula (the accuracy is increased by about 32%). Accurate nuclear mass is helpful to the research of nuclear physics, nuclear technology and astrophysics.

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