Mathematical-Computational Optimization Methods on Primary Molecular Effect Model for Selected High Temperature Superconductors with Electronics Physics Applications

Abstract

In previous series of contributions, Inverse Least Squares (ILS) Numerical Optimization, 3D/4D Interior Optimization, 3D/4D Graphical Optimization software and algorithms-programming were presented. The BCS theory Isotope Effect applications on superconductors TC dual/multiobjective optimization was the main subject. This contribution deals with the Molecular Effect Model for High Temperature Superconductors (HTSCs), in primary hypothesis stages. Selected group of HTSCs is Sn-Sb-Te-Ba-Mn-Cu-O . Namely, classical Inverse Least Squares, 2D Interior Optimization, and 2D Graphical Optimization techniques are applied. Results comprise Tikhonov Regularization algorithms and mathematical methods for this HTSCs group. Mathematical-programming findings to optimize this Type II HTSCs are presented with ILS outcoming data in Matlab and GNU-Octave. Rulings present an hypothesis of new ‘Molecular Effect’ model/algorithm, intended be proven for this HTSCs group. In this Molecular Effect optimization, Inverse Least Squares and Inverse Least Squares polynomial methods are applied with acceptable Numerical and 2D Graphical Optimization solutions. Results show accuracy with low programming residuals that confirm these findings. Solutions comprise two strands, the modelling for Molecular Effect, and the Inverse Least Squares improved programming methods with confidence intervals and statistical images. Hypothesis in Electronics Physics applications for Superconductors and High Temperature Superconductors emerge from findings. Modelling-hypothesis applications in Superconductor Theory turn up from the numerical and imaging data obtained.