# On the closedness and geometry of tensor network state sets

@inproceedings{Barthel2021OnTC, title={On the closedness and geometry of tensor network state sets}, author={Thomas Barthel and Jianfeng Lu and Gero Friesecke}, year={2021} }

Tensor network states (TNS) are a powerful approach for the study of strongly correlated quantum matter. The curse of dimensionality is addressed by parametrizing the many-body state in terms of a network of partially contracted tensors. These tensors form a substantially reduced set of effective degrees of freedom. In practical algorithms, functionals like energy expectation values or overlaps are optimized over certain sets of TNS. Concerning algorithmic stability, it is important whether the… Expand

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