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arXiv 1212.2007nucl-th
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用神经网络建立~(38- 66)Ti同位素potential energy曲线的经验物理公式

Empirical physical formula for potential energy curves of 38-66Ti isotopes by using neural networks

S. Akkoyun, T. Bayram, S. O. Kara, N. Yildiz

摘要:

在过去的十年里,核形状转变一直是研究的热点。特别是从微观的角度来理解这一现象是非常重要的。基于这个原因,人们在相对论和非相对论平均场模型下,利用势能曲线研究了核的形状相变。本文采用分层前馈神经网络(LFNN),对采用Hartree-Fock-Bogoliubov(HFB)方法计算的38- 66 Ti合金在SLy 4 Skyrme力作用下的PEC建立了一致的经验物理公式(EPFs)。结果表明,用神经网络方法得到的PEC与HFB计算的PEC是一致的。

英文摘要:

Nuclear shape transition has been actively studied in the past decade. In particular, the understanding of this phenomenon from a microscopic point of view is of great importance. Because of this reason, many works have been employed to investigate shape phase transition in nuclei within the relativistic and non-relativistic mean field models by examining potential energy curves (PECs). In this paper, by using layered feed-forward neural networks (LFNNs), we have constructed consistent empirical physical formulas (EPFs) for the PECs of 38-66Ti calculated in Hartree-Fock-Bogoliubov (HFB) method with SLy4 Skyrme forces. It has been seen that the PECs obtained by neural network method are compatible with those of HFB calculations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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