Flow, Wind, and Stochastic Connectivity Modeling Infectious Diseases

We study in this paper the trends of the evolution of different infections using a SIR flow (first-order ODE system), completed by a differential inclusion, a geodesic motion in a gyroscopic field of forces, and a stochastic SIR perturbation of the flow (Itô ODE system). We are interested in mathematical analysis, bringing new results on studied evolutionary models: infection flow together with a differential inclusion, bounds of evolution, dual description of disease evolution, log-optimal and rapid path, epidemic wind (geometric dynamics), stochastic equations of evolution, and stochastic connectivity. We hope that the paper will be a guideline for strategizing optimal sociopolitical countermeasures to mitigate infectious diseases.

Geometric Dynamics on Riemannian Manifolds

The purpose of this paper is threefold: (i) to highlight the second order ordinary differential equations (ODEs) as generated by flows and Riemannian metrics (decomposable single-time dynamics); (ii) to analyze the second order partial differential equations (PDEs) as generated by multi-time flows and pairs of Riemannian metrics (decomposable multi-time dynamics); (iii) to emphasise second order PDEs as generated by m-distributions and pairs of Riemannian metrics (decomposable multi-time dynamics). We detail five significant decomposed dynamics: (i) the motion of the four outer planets relative to the sun fixed by a Hamiltonian, (ii) the motion in a closed Newmann economical system fixed by a Hamiltonian, (iii) electromagnetic geometric dynamics, (iv) Bessel motion generated by a flow together with an Euclidean metric (created motion), (v) sinh-Gordon bi-time motion generated by a bi-flow and two Euclidean metrics (created motion). Our analysis is based on some least squares Lagrangians and shows that there are dynamics that can be split into flows and motions transversal to the flows.

Geometric Spectral Algorithms for the Simulation of Rigid Bodies

Lie group methods are an excellent choice for simulating differential equations evolving on Lie groups or homogeneous manifolds, as they can preserve the underlying geometric structures of the corresponding manifolds. Spectral methods are a popular choice for constructing numerical approximations for smooth problems, as they can converge geometrically. In this paper, we focus on developing numerical methods for the simulation of geometric dynamics and control of rigid body systems. Practical algorithms, which combine the advantages of Lie group methods and spectral methods, are given and they are tested both in a geometric dynamic system and a geometric control system.

Geometric Dynamics Used in the Study of Mechanical Methods

In this paper some methods for obtaining the Lagrange functions are pointed out. These methods can be used in general dynamical systems but they are especially useful in the study of autonomous systems. The obtained Lagrange functions is used in dynamical systems with applications in mechanics.