ReducedBasis

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

In the RB 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 RB 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.

If you find this work useful, please cite:

@article{Brehmer2023,
  title = {Reduced basis surrogates for quantum spin systems based on tensor networks},
  author = {Brehmer, Paul and Herbst, Michael F. and Wessel, Stefan and Rizzi, Matteo and Stamm, Benjamin},
  journal = {Phys. Rev. E},
  volume = {108},
  issue = {2},
  pages = {025306},
  numpages = {14},
  year = {2023},
  month = {Aug},
  publisher = {American Physical Society},
  doi = {10.1103/PhysRevE.108.025306},
  url = {https://link.aps.org/doi/10.1103/PhysRevE.108.025306}
}