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This is a Quantitative Study study.

Improving the accuracy of the tree-tensor network approach by optimization of network structure

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The algorithm enhances numerical accuracy for quantum many-body states by optimizing the tree-tensor network structure.
Performance improvements were particularly evident in the random XY model, where stochastic methods were notably effective.
In the Richardson model, the initial tree-tensor network and updating schemes significantly influence numerical accuracy outcomes.
The approach underscores the importance of tailored updating schemes to suit different quantum systems for optimal results.

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Algorithm improves numerical accuracy in quantum many-body systems using tree-tensor networks, suggesting structural optimization is crucial.

Hikihara et al. (2025) studied this question.

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Algorithm improves numerical accuracy in quantum many-body systems using tree-tensor networks, suggesting structural optimization is crucial.