Subspace-Iteration CTMRG - #422
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This PR adds one more CTMRG projector algorithm
SubspaceIterationProjector, introduced in https://arxiv.org/abs/2607.15158.The basic idea is that, after constructing the full-infinite environment
M, one use QR/LQ to obtain "rangefinder" tensorsX, Yto project it toY M Xwhich lives in a much smaller "oversampling" space. This space is intentionally chosen to be still larger than the target environment space χ. It then greatly reduces the cost to do SVD, resulting in significant speed up especially on GPU.According to the paper, one can achieve over 100x speedup for D = 6, χ = 144 on GPU. So it appears to be quite a worthwhile addition.
The rangefinders
X,Ymay be reused during CTMRG iterations, thus a caching mechanism has to be introduced.TODO
Since
SubspaceIterationProjectorcontains parameters beyondtrunc, it is a bit difficult to just specify it with a symbol. We need to introduce more API flexibility in defining an CTMRG / projector algorithm.The initial implementation is restricted to fixed-space truncation, trivial symmetry sectors (it is not straightforward to efficiently determine the charges in the oversampling space) and non-differentiated forward CTMRG contractions. Missing features will be gradually added back in follow-up commits.