Fractional dynamics and recurrence analysis in cancer model
Enrique C. Gabrick, Matheus R. Sales, Elaheh Sayari, Jos\'e Trobia,, Ervin K. Lenzi, Fernando da S. Borges, Jos\'e D. Szezech Jr., Kelly C., Iarosz, Ricardo L. Viana, Iber\^e L. Caldas, Antonio M. Batista

TL;DR
This study explores how fractional derivatives influence chaotic dynamics in a cancer model, revealing transitions from chaos to periodicity as the fractional order decreases, with RQA effectively characterizing these changes.
Contribution
It introduces the application of recurrence quantification analysis to fractional cancer models, demonstrating how fractional order affects system dynamics and transitions.
Findings
Chaotic motion is suppressed as fractional order decreases.
System transitions from chaos to fixed points around fractional order 0.9966.
Exponential relationship between fractional order and tumor growth parameter.
Abstract
In this work, we analyze the effects of fractional derivatives in the chaotic dynamics of a cancer model. We begin by studying the dynamics of a standard model, {\it i.e.}, with integer derivatives. We study the dynamical behavior by means of the bifurcation diagram, Lyapunov exponents, and recurrence quantification analysis (RQA), such as the recurrence rate (RR), the determinism (DET), and the recurrence time entropy (RTE). We find a high correlation coefficient between the Lyapunov exponents and RTE. Our simulations suggest that the tumor growth parameter () is associated with a chaotic regime. Our results suggest a high correlation between the largest Lyapunov exponents and RTE. After understanding the dynamics of the model in the standard formulation, we extend our results by considering fractional operators. We fix the parameters in the chaotic regime and investigate the…
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Taxonomy
TopicsMathematical Biology Tumor Growth · Gene Regulatory Network Analysis · Microtubule and mitosis dynamics
