3 papers
nlin.CD2026
Ordinal-pattern transition networks as a symbolic substrate for reservoir computing
Max Potratzki, Thomas G. de Jong, Michael Small +1
Reservoir computing has established itself as a computationally efficient alternative to fully trained recurrent neural networks using a fixed high-dimensional nonlinear substrate…
nlin.CD2025
Quantifying the irregularity of a time series
Max Potratzki, Manuel Adams, Timo Bröhl +1
We introduce circulance, a scalar measure for classifying time series of dynamical systems. Circulance captures the extent of temporal regularity or irregularity that is encoded in…
physics.soc-ph2024
Synchronization dynamics of phase oscillators on power grid models
Max Potratzki, Timo Bröhl, Thorsten Rings +1
We investigate topological and spectral properties of models of European and US-American power grids and of paradigmatic network models as well as their implications for the synchr…