A new error decomposition framework for scaled Hermite spectral methods shows that balancing spatial and frequency truncation errors via scaling recovers geometric convergence and doubles algebraic convergence orders.
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Scaling Optimized Hermite Approximation Methods
A new error decomposition framework for scaled Hermite spectral methods shows that balancing spatial and frequency truncation errors via scaling recovers geometric convergence and doubles algebraic convergence orders.