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quant-ph2026
Implicit differentiation of tensor network algorithms
Lander Burgelman, Anna Francuz, Paul Brehmer +4
The current leading approach to the variational optimization of projected entangled-pair states (PEPS) is based on automatic differentiation, which allows for a convenient evaluati…
quant-ph2024★ 20 cited
Fermionic tensor network methods
Quinten Mortier, Lukas Devos, Lander Burgelman +5
We show how fermionic statistics can be naturally incorporated in tensor networks on arbitrary graphs through the use of graded Hilbert spaces. This formalism allows to use tensor…