Reduced basis methods for parametrised eigenproblems
Author mfherbst
5 Stars
Updated Last
7 Months Ago
Started In
November 2022


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ReducedBasis.jl is a Julia package that uses the reduced basis method to accelerate the solution of a parametrized eigenvalue problems across the parameter domain.

In the RBM approach, a surrogate model is assembled by projecting the full problem onto a basis consisting of only a few tens of parameter snapshots. The package focuses on a greedy strategy that selects snapshots by maximally reducing the estimated error with each additional snapshot. Once the RBM surrogate is assembled, observables or post-processing can proceed at any parameter value with only a modest complexity scaling independently from the dimension of the initial eigenvalue problem.

For more details see our documentation.

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