We prove that if Σ A (N) is an irreducible Markov shift space over N and f : Σ A (N) → R is coercive with bounded variation then there exists a maximizing probability measure for f , whose support lies on a Markov subshift over a finite alphabet. Furthermore, the support of any maximizing measure is contained in this same compact subshift. To the best of our knowledge, this is the first proof beyond the finitely primitive case on the general irreducible non-compact setting. It's also noteworthy that our technique works for the full shift over positive real sequences.
In this work we show that, if L is a natural Lagrangian system such that the k-jet of the potential energy ensures it does not have a minimum at the equilibrium and such that its Hessian has rank at least n − 2, then there is an asymptotic trajectory to the associated equilibrium point and so the equilibrium is unstable. This applies, in particular, to analytic potentials with a saddle point and a Hessian with at most 2 null eigenvalues.The result is proven for Lagrangians in a specific form, and we show that the class of Lagrangians we are interested can be taken into this specific form by a subtle change of spatial coordinates. We also consider the extension of this results to systems subjected to gyroscopic forces.
The problemConsider the study of the Liapunov instability of equilibrium points of conservative Lagrangian systems in R 2n , with Lagrangians L(q,q) = T (q,q) − π(q), where π is the potential energy and T the kinetic energy.
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