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Quantization of Energies with Machine Learning Without Quantum Mechanics
(IEEE, 2025-02-26)
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 ...
Acceso restringido
Machine Learning for Identification of Quantum Effects in Dirac-Lorentz Electrodynamics
(IEEE, 2025-03-13)
A computational methodology based at Machine Learning in order to identify quantum effects at Dirac-Lorentz electrodynamics, is proposed. Essentially, the present contribution is based in an algorithm that employs the ...
Acceso restringido
Perturbed Perceptron's Input to Derive Schrödinger Equation in Artificial Neural Networks
(IEEE, 2025-04-21)
With the arrival of powerful computers and advanced algorithms, the searching of new fundamental equations describing our universe, is expected. In this manner, artificial intelligence might to be able to reproduce known ...
Acceso restringido
Canonical Commutation Relation Derived from Witt Algebra
(MDPI, 2025-06-07)
From an arbitrary definition of operators inspired by oscillators of Virasoro, an algebra is derived. It fits the structure of Virasoro algebra with null central charge or Witt algebra. The resulting formalism has yielded ...
Acceso abierto
Bayesian Synapse Driven by Quantum Hamiltonian and Electrical Interactions
(IEEE, 2025-04-21)
A probabilistic model of Synapse is proposed. In concrete, synapse is proposed as a Bayesian probability that requires the quantum probabilities for both: the interaction of Calcium 2+ in axon area, and the releasing of ...
Acceso restringido





