Rank-adaptive structure-preserving model order reduction of Hamiltonian systems
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A Hamiltonian formulation of the relativistic guiding center drifts is extended to anisotropic pressure plasmas. The magnetic coordinates devised by Boozer are adapted to the anisotropic pressure model and retain canonical properties for two-dimensional an ...
This paper develops the theory of affine Lie-Poisson reduction and applies this process to Yang-Mills and Hall magnetohydrodynamics for fluids and superfluids. As a consequence of this approach, the associated Poisson brackets are obtained by reduction of ...
For chaotic systems there is a theory for the decay of the survival probability, and for the parametric dependence of the local density of states. This theory leads to the distinction between 'perturbative' and 'non-perturbative' regimes, and to the observ ...
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels based on tangent vectors that take into account prior information on known invari ...
The Poisson induction and coinduction procedures are used to construct Banach Lie-Poisson spaces as well as related systems of integrals in involution. This general method applied to the Banach Lie-Poisson space of trace class operators leads to infinite H ...
This thesis deals with applications of Lie symmetries in differential geometry and dynamical systems. The first chapter of the thesis studies the singular reduction of symmetries of cosphere bundles, the conservation properties of contact systems and their ...
Very large mol. systems can be calcd. with the so called CNDOL approx. Hamiltonians that have been developed by avoiding oversimplifications and only using a priori parameters and formulas from the simpler NDO methods. A new diagonal monoelectronic term na ...
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels based on tangent vectors that take into account prior information on known invari ...