The convergence crop-length of the polar-decomposition topological invariant in finite non-Hermitian chains is shown to be governed by skin-effect decay lengths, and is predicted by random-forest regression using root-derived features.
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Machine learning prediction of the convergence criterion for a topological invariant of finite non-Hermitian chains
The convergence crop-length of the polar-decomposition topological invariant in finite non-Hermitian chains is shown to be governed by skin-effect decay lengths, and is predicted by random-forest regression using root-derived features.