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Scalable Pseudospectral Analysis via Low-Rank Approximations of Dynamical Systems
Pseudospectral analysis is fundamental for quantifying the sensitivity and transient behavior of nonnormal matrices, yet its computational cost scales cubically with dimension, rendering it prohibitive for large-scale systems. While existing research on scalable pseudospectral computation has focuse
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