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Andreas Lind

Publications and source records attributed to Andreas Lind.

4 recordsLinked to original sources
arXiv2025

Embedded topological triviality of separable families of singularities

Understanding how singularities behave under small perturbations is a central theme in singularity theory. In this paper we establish sufficient conditions for families of analytic function-germs on a germ of a complex analytic space to admit an embedded topological trivialization. Our results extend previous work of the third author and collaborators, moving from abstract triviality to the embedded setting. As an application, we obtain new instances of topological stability, including a broad class of $\mu$-constant deformations. These findings provide a new insight into the long-standing $\mu$-constant conjecture, one of the major open problems in the field.

math.AG↗
arXiv2022

Holomorphic Lie Group Actions on Danielewski Surfaces

We prove that any Lie subgroup $G$ (with finitely many connected components) of an infinite-dimensional topological group $\mathcal G$ which is an amalgamated product of two closed subgroups, can be conjugated to one factor. We apply this result to classify Lie group actions on Danielewski surfaces by elements of the overshear group (up to conjugation).

math.CV↗
arXiv2013

The Dynamical Functional Particle Method

We present a new algorithm which is named the Dynamical Functional Particle Method, DFPM. It is based on the idea of formulating a finite dimensional damped dynamical system whose stationary points are the solution to the original equations. The resulting Hamiltonian dynamical system makes it possible to apply efficient symplectic integrators. Other attractive properties of DFPM are that it has an exponential convergence rate, automatically includes a sparse formulation and in many cases can solve nonlinear problems without any special treatment. We study the convergence and convergence rate of DFPM. It is shown that for the discretized symmetric eigenvalue problems the computational complexity is given by $\mathcal{O}(N^{(d+1)/{d}})$, where \emph{d} is the dimension of the problem and \emph{N} is the vector size. An illustrative example of this is made for the 2-dimensional Schr\"odinger equation. Comparisons are made with the standard numerical libraries ARPACK and LAPACK. The conjugated gradient method and shifted power method are tested as well. It is concluded that DFPM is both versatile and efficient.

math.NA↗