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,
author = {Brehmer, Paul and Herbst, Michael F. and Wessel, Stefan and Rizzi, Matteo and Stamm, Benjamin},
title = {Reduced basis surrogates for quantum spin systems based on tensor networks},
url = {http://arxiv.org/abs/2304.13587v2},
eprint = {2304.13587v2},
month = {Apr},
year = {2023},
}