Revisiting Macro-microscopic Mass Formula using Atomic Mass Evaluation-2020 Data

S. ., O. Sastri
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Abstract

Background: The macro-microscopic model has been succesful in nuclear mass predictionsand in obtaining various other properties of nuclear and nucleon matter. The present statusof generalised liquid drop model (GLDM) has been based on atomic mass evaluation (AME)-2003 data.Purpose: In this work, the co-efficients of most efficient mass formulae from Royer et.al.,have been re-optimised for 2451 selected nuclei from AME-2020 data.Methods: The root mean squared deviation (RMS) is minimized to optimize seven modelparameters that correspond to various terms in the nuclear binding energy that come inpowers of mass number A and square of relative neutron excess I = N −Z/A .Results: The RMS between the theoretical and experimental binding energies has beenobtained as 0.65 using both the formulae.Conclusions: The best possible formula for nuclear binding energy has been obtained usingAME-2020 data and it needs to be seen how this would effect the various nuclear propertiesand predictions.
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利用原子质量评估-2020数据重新审视宏观-微观质量公式
背景:宏观-微观模型在预测核质量以及获得核和核子物质的各种其他性质方面已经取得了成功。广义液滴模型(GLDM)的现状是基于2003年原子质量评估(AME)数据。目的:研究Royer等人最有效的质量公式的系数。,对AME-2020数据中选择的2451个核进行了重新优化。方法:利用最小均方根偏差(RMS)对7个模型参数进行优化,这些参数对应于质量数A和相对中子过剩量I的平方= N−Z/A的核结合能各项。结果:用这两个公式得到理论结合能与实验结合能的均方根偏差均为0.65。结论:利用ame -2020数据获得了核结合能的最佳公式,需要观察这将如何影响各种核性质和预测。
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