Saltar al contenido
República del Perú · Observatorio de la producción científica universitaria
OApol.org Observatorio de Inteligencia Científica Universitaria del Perú
OApol.org
Inicio Universidades Publicaciones Investigadores
Repositorios
Tesis y trabajos académicosRevistas
Indicadores
Ranking trimestralRanking por carreraObjetivos de Desarrollo SostenibleReporte OCDERed neuronal 3D
Acerca
MetodologíaPrivacidad

Quantization of Energies with Machine Learning Without Quantum Mechanics

Nieto-Chaupis H. · 5th International Conference on Electrical, Communication and Computer Engineering, ICECCE 2024 (2024) · DOI: 10.1109/icecce63537.2024.10823608

Resumen

The field of Machine Learning through the technique of artificial neural network is used to determine in a straightforward manner the quantized energies of a particle in an infinite well. To accomplish this, unphysical mathematical assumptions have been applied. In essence, the opted method in this study aims to derive quantization without any knowledge of quantum mechanics of system. Moreover, the Schrödlnger equation has been reconstructed from the information of quantization derived from the usage of neural network. This procedure, although rather artificial might be exploited to derive other quantum mechanics equations without any knowledge to priori of system under study.

Instituciones: Universidad Autónoma del Perú