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Seminar by John Singler
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    :bdg-primary-line:`Speaker`

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        John Singler (Missouri University of Science and Technology)

    :bdg-primary-line:`Title`

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        Data approximation capability of proper orthogonal decomposition

    :bdg-primary-line:`Date`

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        * February 14, 2023 16:00 CET+0100 (Europe/Rome)
        * February 14, 2023 10:00 EST-0500 (US/Eastern)
        * February 14, 2023 09:00 CST-0600 (US/Central)
        * February 14, 2023 07:00 PST-0800 (US/Pacific)

    :bdg-primary-line:`Abstract`

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        In the numerical analysis of Galerkin reduced order models (G-ROMs)
        based on proper orthogonal decomposition (POD), the data approximation
        capability of POD plays a crucial role. More specifically, existing
        approaches to deriving error bounds between the exact solution of the
        full order model (FOM) and the G-ROM rely on estimates involving the POD
        data approximation error, i.e., the error between the exact solution
        data and POD projections of that solution data. We survey advances in
        POD data approximation theory, and how these results have impacted the
        numerical analysis of POD G-ROMs for partial differential equations. We
        consider discrete and continuous data, and different measures of error.
        We also outline open questions.

    :bdg-primary-line:`Recording`

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        Watch the recording on `our YouTube channel <https://www.youtube.com/watch?v=3PsXX03ad88>`_.