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Christian Kuehn

Researcher at Technische Universität München

Publications -  234
Citations -  4186

Christian Kuehn is an academic researcher from Technische Universität München. The author has contributed to research in topics: Dynamical systems theory & Ordinary differential equation. The author has an hindex of 25, co-authored 206 publications receiving 3233 citations. Previous affiliations of Christian Kuehn include Max Planck Society & Cornell University.

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Graphop mean-field limits and synchronization for the stochastic Kuramoto model.

TL;DR: In this article , a general mean-field theory for stochastic Kuramoto-type phase oscillator networks with heterogeneous connectivity and coupling weights is proposed. But the model is not suitable for graph structures that are sufficiently sparse.
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Introduction to Potential Theory via Applications

TL;DR: In this article, the Riesz decomposition theorem is proved for the complex plane and the Dirichlet problem is discussed, and the relation between potential theory and probability is discussed.
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Discretized Fast-Slow Systems with Canard Points in Two Dimensions

TL;DR: In this article, the authors studied the problem of preserving canard connections for time discretized fast-slow systems with canard fold points, and they showed that the structure preserving properties of the Kahan discretization imply a similar result as in continuous time, guaranteeing the occurrence of canard connection between attracting and repelling slow manifolds upon variation of a bifurcation parameter.
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Towards sample path estimates for fast–slow stochastic partial differential equations

TL;DR: In this article, it was shown that for a short-time period the probability for the corresponding sample path to leave a neighbourhood around the stable slow manifold of the system is exponentially small.
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A General View on Double Limits in Differential Equations

TL;DR: In this article, a general conceptual framework for singularly perturbed differential equations with multiple small parameters is proposed, where the setting and restrictions of the differential equation problem are specified and the relevant small parameters are identified.