A new linearized dynamics based on the anti-symmetric part of the stability matrix preserves phase space volume for non-Hamiltonian chaotic systems within a classical density matrix framework.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
MCBP detects boundaries by computing discrete mean curvature from k-nearest neighbor patches on the data manifold, then decomposes data into low-curvature smooth and high-curvature boundary subsets to improve clustering.
citing papers explorer
-
Phase space volume preserving dynamics for non-Hamiltonian systems
A new linearized dynamics based on the anti-symmetric part of the stability matrix preserves phase space volume for non-Hamiltonian chaotic systems within a classical density matrix framework.
-
A Mean Curvature Approach to Boundary Detection: Geometric Insights for Unsupervised Learning
MCBP detects boundaries by computing discrete mean curvature from k-nearest neighbor patches on the data manifold, then decomposes data into low-curvature smooth and high-curvature boundary subsets to improve clustering.