Genetic Algorithms for Interior Comparative Optimization of Standard BCS Parameters in Selected Superconductors and High-Temperature Superconductors

Standards Pub Date : 2022-09-16 DOI:10.3390/standards2030029
F. Casesnoves
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引用次数: 3

Abstract

Inverse least squares numerical optimization, 3D/4D interior optimization, and 3D/4D graphical optimization software and algorithm programming have been presented in a series of previous articles on the applications of the BCS theory of superconductivity and TC dual/multiobjective optimizations. This study deals with the comparison/validation of the optimization results using several different methods, namely, classical inverse least squares (ILS), genetic algorithms (GA), 3D/4D interior optimization, and 2D/3D/4D graphical optimization techniques. The results comprise Tikhonov regularization algorithms and mathematical methods for all the research subjects. The findings of the mathematical programming for optimizing type I chrome isotope superconductors are validated with the genetic algorithms and compared to previous results of 3D/4D interior optimization. Additional rulings present a hypothesis of the new ‘molecular effect’ model/algorithm intended to be proven for Hg-cuprate-type high-temperature superconductors. In molecular effect optimization, inverse least squares and inverse least squares polynomial methods are applied with acceptable numerical and 2D graphical optimization solutions. For the BCS isotope effect and molecular effect, linearization logarithmic transformations for model formula software are implemented in specific programs. The solutions show accuracy with low programming residuals and confirm these findings. The results comprise two strands, the modeling for the isotope effect and molecular effect hypotheses and the development of genetic algorithms and inverse least squares-improved programming methods. Electronic physics applications in superconductors and high-temperature superconductors emerged from the rulings. Extrapolated applications for new modeling for the theory of superconductivity emerged from the numerical and image data obtained.
选定超导体和高温超导体中标准BCS参数内部比较优化的遗传算法
逆最小二乘数值优化、3D/4D内部优化和3D/4D图形优化软件和算法编程在BCS超导理论和TC双/多目标优化中的应用已经在之前的一系列文章中进行了介绍。本研究采用经典的逆最小二乘(ILS)、遗传算法(GA)、3D/4D内部优化和2D/3D/4D图形优化技术,对优化结果进行了比较和验证。结果包括吉洪诺夫正则化算法和所有研究对象的数学方法。利用遗传算法验证了I型铬同位素超导体优化数学规划的结果,并与之前的3D/4D内部优化结果进行了比较。额外的裁决提出了一个新的“分子效应”模型/算法的假设,旨在证明氢铜型高温超导体。在分子效应优化中,采用逆最小二乘和逆最小二乘多项式方法,得到了可接受的数值和二维图形优化解。对于BCS同位素效应和分子效应,在具体程序中实现了模型公式软件的线性化对数变换。该解决方案具有较低的编程残差,并证实了这些发现。研究结果包括同位素效应和分子效应假设的建模,以及遗传算法和逆最小二乘改进规划方法的发展。电子物理在超导体和高温超导体中的应用从这些裁决中涌现出来。所获得的数值和图像数据为超导理论的新建模提供了外推应用。
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