Open AccessMATHEMATICAL OPTIMIZATION MOLECULAR EFFECT MODEL CRITICAL TEMPERATURE PREDICTIONS FOR HIGH TEMPERATURE SUPERCONDUCTORS WITH ELECTRONICS PHYSICS APPLICATIONS
Author(s) -
Francisco Casesnoves
Publication year - 2022
Publication title -
international journal of mathematics and computer research
Language(s) - English
Resource type - Journals
ISSN - 2320-7167
DOI - 10.47191/ijmcr/v10i4.05
Subject(s) - tikhonov regularization , inverse , inverse problem , regularization (linguistics) , least squares function approximation , statistical physics , mathematics , physics , computer science , mathematical analysis , geometry , statistics , artificial intelligence , estimator
In previous series of contributions, Inverse Least Squares (ILS) 2D Numerical/Graphical Optimization for primary Molecular Effect model were presented. This contribution deals with the Molecular Effect Model predictions for High Temperature Superconductors (HTSCs) group of [ Sn-Sb-Te-Ba-Mn-Cu-O ] . This group constitutes a recent materials innovation of HTSCs with TC > 0° with important recent/prospective electronics physics applications. For these optimization/simulations, 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. Findings for this Molecular Effect optimization, based on Inverse Least Squares and Inverse Least Squares polynomial methods show acceptable theoretical Numerical and 2D Graphical Optimization solutions and low residuals. Solutions comprise two parts, the modelling for TC Molecular Effect predictions, and the Inverse Least Squares improved programming methods with 95% confidence intervals and statistical images. Proposed Electronics Physics applications for Superconductors and High Temperature Superconductors turn up from numerical/graphical results.