Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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Noether symmetries of time-dependent damped nonlinear multidimensional wave equations produce conservation of linear and angular momentum, with the algebra enlarging to a conformal subalgebra for particular damping and nonlinearity forms.
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Learning Dynamic Stability Landscapes in Synchronization Networks
Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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Noether symmetries and conservation laws of a class of time-dependent multidimensional nonlinear wave equations
Noether symmetries of time-dependent damped nonlinear multidimensional wave equations produce conservation of linear and angular momentum, with the algebra enlarging to a conformal subalgebra for particular damping and nonlinearity forms.