Study α decay and proton emission based on data-driven symbolic regression

IF 7.2 2区 物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

Abstract

α decay and proton emission were combined using symbolic regression to improve the accuracy of predicting their respective half-lives using two theoretical formulations: (1) adjustable parameters for the universal decay law and universal decay law for proton emission are obtained by regressions with fully-constrained symbolic regressions. (2) New theoretical formulas for calculating the half-life of proton emission and α decay are obtained using unconstrained symbolic regressions combined with nuclear data. Our computational analysis indicates that fully-constrained symbolic regressions and unconstrained symbolic regressions are reliable for specific and general nuclei, respectively, in terms of replicating experimental results, and are sufficiently robust to produce accurate half-life predictions. Unlike other machine learning methods that generate complex and opaque results, our approach integrates physics and machine learning to create interpretable formulas that provide intuitive parametric outcomes and transparent and dependable inferences of half-lives, even in areas with limited experimental data. The test results show that the equation yields accurate results, and can be easily applied to future α decay and proton emission studies.

基于数据驱动的符号回归研究α衰变和质子发射
利用符号回归法将α衰变和质子发射结合起来,以提高利用两种理论公式预测它们各自半衰期的准确性:(1)通过完全受约束的符号回归法获得质子发射的普遍衰变规律和普遍衰变规律的可调参数。(2)利用无约束符号回归结合核数据,获得计算质子发射半衰期和α衰变半衰期的新理论公式。我们的计算分析表明,全约束符号回归和无约束符号回归在复制实验结果方面分别对特定原子核和一般原子核是可靠的,并且具有足够的鲁棒性,可以产生准确的半衰期预测。与其他产生复杂而不透明结果的机器学习方法不同,我们的方法整合了物理学和机器学习,创建了可解释的公式,即使在实验数据有限的领域,也能提供直观的参数结果和透明可靠的半衰期推断。测试结果表明,该方程能得出准确的结果,并能轻松应用于未来的α衰变和质子发射研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computer Physics Communications
Computer Physics Communications 物理-计算机:跨学科应用
CiteScore
12.10
自引率
3.20%
发文量
287
审稿时长
5.3 months
期刊介绍: The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.
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