Closed pbrehmer closed 1 year ago
Also fix the cut off axes labels on this occasion. (The locally generated docs do not have this problem, only the deployed only version.)
We also should describe the choice of the training grid somewhere, and in particular, the importance of the first snapshot point in some models with symmetries (e.g. the XXZ model with discrete $M$-plateaus where $[H_\text{XXZ},M]=0$).
Before diving into explicit code examples, a introduction to the theoretical reduced basis framework as well as the application to quantum spin systems would be nice.
On the one hand many readers might not be familiar with reduced basis methods but also people outside of physics probably find many body Hamiltonians confusing at first glance. The reduced basis part would consider general parametrized eigenvalue problems and explain the basics of the greedy algorithm. The construction of the spin Hamiltonians could already be shifted to this introduction, such that the beginning of the "The reduced basis workflow" example doesn't have to deal with introducing spin physics first.