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Marcilio Ferreira dos Santos

Publications and source records attributed to Marcilio Ferreira dos Santos.

3 recordsLinked to original sources

Causal Edge Rees Algebras for Spatiotemporal Graphs

Understanding the evolution of connectivity in spatiotemporal systems requires mathematical frameworks capable of encoding not only instantaneous interactions but also their cumulative causal structure. In this work, we introduce the \emph{Causal Edge Rees Algebra} (CERA), a new algebraic construction associated with causal spatiotemporal graphs. Given a temporal filtration induced by causal constraints, we associate a sequence of edge ideals whose Rees algebra encodes the full history of connectivity evolution in a single graded object. This construction establishes a bridge between dynamic graph topology and commutative algebra. In particular, we show that successive quotients of the filtration capture the emergence of new structural connections, allowing the identification of critical edges responsible for the fusion of previously disconnected components. This leads to the definition of temporal bridge modules and to a bridge detection theorem, which relates the dimension of these modules to the reduction in the number of connected components over time. Unlike existing algebraic approaches in topological data analysis, which are primarily based on geometric filtrations, the proposed framework is driven by intrinsic causal constraints. As a result, the CERA captures not only topological features but also their temporal organization and mechanisms of coalescence. The theory provides a new algebraic perspective on causal network dynamics, connecting edge ideals, Rees algebras, and temporal graphs. Beyond its theoretical significance, the framework opens new directions for the analysis of spatiotemporal systems, including epidemic networks, transport systems, and information propagation processes.

math.CO↗

Curvature-Weighted Contact Networks: Spectral Reduction and Global Stability in a Markovian SIR Model

We propose a new network-based SIR epidemic model in which transmission is modulated by a curvature-weighted contact matrix that encodes structural and geometric features of the underlying graph. The formulation encompasses both adjacency-driven and Markovian mixing, allowing heterogeneous interactions to be shaped by curvature-sensitive topological properties. We prove that the basic reproduction number satisfies \[ R_0=\fracβγλ_{\max}(M), \] where $M$ is the curvature-weighted transmission operator. Using Perron--Frobenius theory together with linear and nonlinear Lyapunov functionals, we establish: (i) global asymptotic stability of the disease-free equilibrium when $R_0<1$, and (ii) existence and global asymptotic stability of a unique endemic equilibrium when $R_0>1$. Our results show that curvature acts as a geometric regularizer of connectivity, lowering spectral radii, raising effective epidemic thresholds, and organizing the long-term dynamics through monotone contraction toward the endemic state. This framework generalizes classical network epidemiology by integrating geometric information directly into transmission operators, providing a rigorous foundation for epidemic dynamics on structurally heterogeneous networks.

math.DS↗

Deterministic Critical Community Size For The SIR System and Viral Strain Selection

In this paper the concept of Critical Community Size (CCS) for the deterministic SIR model is introduced and its consequences for the disease dynamics are stressed. The disease can fade out after an outburst. Also the principle of competitive exclusion holds no longer true. This is exemplified for the dynamics of two competing virus strains. The virus with higher R0 can be eradicated from the population.

q-bio.PE↗