[Feature] Degeneracy-aware truncation #101
Description
According to 2510.04756, in the context of CTMRG:
Then, we do singular value decomposition (SVD) as in Fig. 7(C). The diagonal
$S$ has$χ_0$ singular values sorted in the non-increasing order:$S_1 ≥ S_2 ≥ · · · ≥ S_{χ_0}$ . Instead of simply truncating$S$ to a predefined number of singular values, we noticed that$S$ has a multiplet structure that needs to be dealt with carefully when it comes to the truncation. To do this, we initially truncate S to$χ_i$ such that$χ_i$ is the largest number satisfying$S_{χ_i} / S_1 ≥ ϵ_C$ and$χ_i ≤ χ$ . Next, we find the largest$χ_f$ such that$χ_f ≥ χ_i$ and$1 − S_{χf} /S_{χi} < r_m$ . By including a complete multiplet during truncation, we improve the stability of CTMRG.
The idea is: Sometimes a hard truncrank(χ) cuts in the middle of a degenerate part of the singular value spectrum. It benefits to provide a truncation strategy that automatically increases χ (when these degenerate singular values are not too small) so that the entire degenerate part is kept.