dc.contributor.author | Nieto-Chaupis, Huber | |
dc.date.accessioned | 2023-10-04T19:01:49Z | |
dc.date.available | 2023-10-04T19:01:49Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | https://hdl.handle.net/20.500.13067/2659 | |
dc.description.abstract | The principles of Machine Learning through the criteria of Mitchell are used to validate a concrete quantum-mechanics interpretation from a classical radiation scheme inside the framework of linear and nonlinear Compton scattering off a relativistic electron in a super-intense electromagnetic field. | es_PE |
dc.format | application/pdf | es_PE |
dc.language.iso | eng | es_PE |
dc.publisher | IEEE | es_PE |
dc.rights | info:eu-repo/semantics/restrictedAccess | es_PE |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | es_PE |
dc.subject | Quantum computing | es_PE |
dc.subject | Quantization (signal) | es_PE |
dc.subject | Electromagnetic scattering | es_PE |
dc.subject | Quantum mechanics | es_PE |
dc.subject | Machine learning | es_PE |
dc.subject | Mathematical models | es_PE |
dc.subject | Electromagnetic fields | es_PE |
dc.title | The Criteria of Mitchell to Interpret Classical Radiation as Compton Scattering | es_PE |
dc.type | info:eu-repo/semantics/article | es_PE |
dc.identifier.journal | 2022 IEEE 20th Biennial Conference on Electromagnetic Field Computation (CEFC) | es_PE |
dc.identifier.doi | https://doi.org/10.1109/CEFC55061.2022.9940776 | |
dc.subject.ocde | https://purl.org/pe-repo/ocde/ford#2.02.04 | es_PE |