Modeling Accelerated Growth of Bacteria Population Through Feynman Diagrams

Descripción del Articulo

In Quantum Physics normally the well-known Feynman Diagrams are used to calculate transition probabilities by which we can estimate predictions as to the expected measurement of a certain physical variables. In this paper we use this technique to estimate quantitative measurements of the rapid growt...

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Detalles Bibliográficos
Autor: Nieto-Chaupis, Huber
Formato: artículo
Fecha de Publicación:2020
Institución:Universidad Autónoma del Perú
Repositorio:AUTONOMA-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.autonoma.edu.pe:20.500.13067/1720
Enlace del recurso:https://hdl.handle.net/20.500.13067/1720
https://doi.org/10.1109/ETCM48019.2019.9014865
Nivel de acceso:acceso restringido
Materia:Microorganisms
Mathematical model
Photonics
Sociology
Statistics
Acceleration
https://purl.org/pe-repo/ocde/ford#2.02.04
Descripción
Sumario:In Quantum Physics normally the well-known Feynman Diagrams are used to calculate transition probabilities by which we can estimate predictions as to the expected measurement of a certain physical variables. In this paper we use this technique to estimate quantitative measurements of the rapid growth of a bacteria population dictated by binary fission as well as to make predictions to anticipate and tackle down their possible scenarios of aggregation. We have used the theory of the Feynman diagrams in conjunction to the propagator. The resulting probabilities are interpreted as the ones that allows us to measure the growth of the population under certain physical conditions. Once the formalism is defined, we pass to calculate amplitudes of probability in taking the example 2→2 processes. With the types: termophile and mesophile, we provide various master equations in order to compute the net number of bacteria for a time of up to 20 hours. The final error of the model has been of order of 7.5%. Mainly of the uncertainty comes from the lack of interpretation of the parameters brought from the physics model.
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