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Theory of machine learning based on nonrelativistic quantum mechanics
(World Scientific, 2021)
The goal of this paper is the presentation of the elementary procedures that normally are done in nonrelativistic Quantum Mechanics in terms of the principles of Machine Learning. In essence, this paper discusses Mitchell's ...
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Machine Learning to Assess Urbanistic Development in the South Pole of Lima City
(Springer, 2022-01-01)
We employ Machine Learning through the Mitchell’s criteria to carry out an assessment on the potential spatial configurations at the south pole of Lima city, at Perú. Based at both qualitative and quantitative facts, an ...
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Data Analysis of Particle Physics Experiments Based on Machine Learning and the Mitchell’s Criteria
(Springer, 2020)
Commonly the searching and identification of new particles, requires to reach highest efficiencies and purities as well. It demands to apply a chain of cuts that reject the background substantially. In most cases the ...
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Testing Machine Learning at Classical Electrodynamics
(Institute of Electrical and Electronics Engineers, 2021-10-22)
Like physics or another laws-based basic science, machine learning might also be a firm methodology to solve physics problems by the which a kind of optimization and minimization of energy are needed. Expressed at the ...
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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 ...
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Machine Learning Algorithms for Producing Equations in Physics
(IEEE, 2025-02-26)
Based at the prospective scenario that computers might to replace humans, emerge the idea that them can carry out jobs as a scientist does. Thus, one might to expect that for example machine learning can be a serious ...
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Machine Learning as Mediator of Classical Electrodynamics and Quantum Mechanics
(IEEE, 2025-03-13)
Machine Learning has been used as part of a closed-form operation that allows to link classical physics to quantum mechanics of a free electron radiating photons inside superintese laser field. To accomplish this an ...
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Can Artificial Intelligence do Autonomous Research?: An Example of Using the Mitchell Criteria
(IEEE, 2023)
Nowadays, media and scientific literature have shown capabilities of Artificial Intelligence (AI) to carry out autonomous activities with the same efficiency as a human being are presented. It is clear that AI can support ...
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The Quantum Mechanics Propagator as the Machine Learning Performance in Space-Time Displacements
(Institute of Electrical and Electronics Engineers, 2021-12)
The role of evolution operator is to provide the time displacement of wave function through the Hamiltonian of the system. The usage of coordinates representation gives the well-known propagator that is the Green’s function. ...
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Theory and Simulation of Electromagnetic Systems Governed by Machine Learning Principles
(IEEE, 2022)
This paper proposes the idea that electromagnetic systems can be formulated through probabilities once the system has been understood by the classical physics. With this, several physical observables are estimated. Also, ...
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