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The linear nature of MPS makes them most appropriate for tridiagonal matrices (1d neighbor connections). We can permute the site indices to better approximate a 1d system.
I can see why the permutation is NP, as solving tridiagonal QUBOs with TensorNetworks is in P https://arxiv.org/abs/2309.10509
In the reference you provide there are some references, but their algorithm is the most straightforward in my opinion
iagoleal
changed the title
Implement Q-matrix permutation
Preprocessing: Implement Q-matrix permutation
Jan 8, 2025
The linear nature of MPS makes them most appropriate for tridiagonal matrices (1d neighbor connections). We can permute the site indices to better approximate a 1d system.
This is itself an NP problem, but perhaps the ideas here could help (Appendix III.A.4):
https://arxiv.org/pdf/2403.00910
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