Data-driven Koopman analysis of a bistable stochastic system recovers large deviation theory escape time statistics and basin structure via the subdominant mode.
Dynamical properties and mechanisms of metastability: a perspective in neuroscience
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Generalized saddle-node ghosts are defined for higher-dimensional systems with algorithms to detect ghost attractors, channels, and cycles, implemented in the PyGhostID Python package.
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Data-driven analysis of metastability in a stochastic bistable system
Data-driven Koopman analysis of a bistable stochastic system recovers large deviation theory escape time statistics and basin structure via the subdominant mode.
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Generalized saddle-node ghosts and their composite structures in dynamical systems
Generalized saddle-node ghosts are defined for higher-dimensional systems with algorithms to detect ghost attractors, channels, and cycles, implemented in the PyGhostID Python package.