activity
20082026
most citedData-driven model reduction and transfer operator approximation

267 citations · 1.1k across the 40 of their papers we have counts for

collaborators
Showing 2019Show all

7 papers · 1 filter

math.DS2019

Targets and Holes

P. Giulietti, P. Koltai, S. Vaienti

We address the extreme value problem of a one-dimensional dynamical system approaching a fixed target while constrained to avoid a fixed set which can be thought of as a small hole…

physics.flu-dyn2019★ 12 cited

Lagrangian coherent sets in turbulent Rayleigh-Bénard convection

Christiane Schneide, Martin Stahn, Ambrish Pandey +4

Coherent circulation rolls and their relevance for the turbulent heat transfer in a two-dimensional Rayleigh--Bénard convection model are analyzed. The flow is in a closed cell of…

math.DS2019

Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds

Andreas Bittracher, Stefan Klus, Boumediene Hamzi +2

We present a novel kernel-based machine learning algorithm for identifying the low-dimensional geometry of the effective dynamics of high-dimensional multiscale stochastic systems.…

math.DS2019★ 1 cited

Revealing the intrinsic geometry of finite dimensional invariant sets of infinite dimensional dynamical systems

Raphael Gerlach, Péter Koltai, Michael Dellnitz

Embedding techniques allow the approximations of finite dimensional attractors and manifolds of infinite dimensional dynamical systems via subdivision and continuation methods. The…

math.DS2019

Computation and optimal perturbation of finite-time coherent sets for aperiodic flows without trajectory integration

Gary Froyland, Péter Koltai, Martin Stahn

Understanding the macroscopic behavior of dynamical systems is an important tool to unravel transport mechanisms in complex flows. A decomposition of the state space into coherent…

math.DS2019

Spectral Properties of Effective Dynamics from Conditional Expectations

Feliks Nüske, Péter Koltai, Lorenzo Boninsegna +1

The reduction of high-dimensional systems to effective models on a smaller set of variables is an essential task in many areas of science. For stochastic dynamics governed by diffu…