In a Recent Work (Koc Et Al., SIAM J. Numer. Anal. 59(4), 2163–2196, 2021), the Authors Showed that Including Difference Quotients (DQs) is Necessary in Order to Prove Optimal Pointwise in Time Error Bounds for Proper Orthogonal Decomposition (POD) Reduced Order Models of the Heat Equation. in This Work, We Introduce a New Approach to Including DQs in the POD Procedure. Instead of Computing the POD Modes using All of the Snapshot Data and DQs, We Only Use the First Snapshot Along with All of the DQs and Special POD Weights. We Show that This Approach Retains All of the Numerical Analysis Benefits of the Standard POD DQ Approach, while using a POD Data Set that Has Approximately Half the Number of Snapshots as the Standard POD DQ Approach, I.e., the New Approach Requires Less Computational Effort. We Illustrate Our Theoretical Results with Numerical Experiments.
S. L. Eskew and J. R. Singler, "A New Approach to Proper Orthogonal Decomposition with Difference Quotients," Advances in Computational Mathematics, vol. 49, no. 2, article no. 13, Springer, Apr 2023.
The definitive version is available at https://doi.org/10.1007/s10444-023-10011-9
Mathematics and Statistics
Keywords and Phrases
Approximation theory; Difference quotients; Projections; Proper orthogonal decomposition; Reduced order models
International Standard Serial Number (ISSN)
Article - Journal
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01 Apr 2023
National Science Foundation, Grant 2111421