Machine Learning as a Tool to Teach Quantum Mechanics

Nieto-Chaupis H. · 2026 IEEE/ACIS 24th International Conference on Software Engineering Research, Management and Applications, SERA 2026 (2026) · DOI: 10.1109/sera69989.2026.11618656

Resumen

With the imminent arrival and establishment of quantum technologies in our society, it is expected that prospective engineers will assume a crucial role to manage and keep the quantum applications to a broad spectrum of sectors. Thus, the teaching and learning of quantum mechanics might to be done in the first two years of some programs. Clearly, the complexity of quantum theory might be an important trouble to capture their most relevant parts and applications, even in the first years of undergraduate program. Because this, this paper explores well-known methodologies from machine learning, such as artificial neural network to overcome all these inherent difficulties in the side of student to incorporate in the package of learning, the fundamental and basic applications of quantum mechanics. Essentially, the present paper makes usage of basic unit of artificial neural network known as perceptron in the form of simple and multilayer in order to present the basic postulates and implications of quantum mechanics.

Instituciones: Universidad Autónoma del Perú