Tree tensor network states represent low-energy states faithfully
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866914288550019072 |
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| author | Barthel, Thomas |
| author_facet | Barthel, Thomas |
| contents | Extending corresponding results for matrix product states [Verstraete and Cirac, PRB 73, 094423 (2006); Schuch et al. PRL 100, 030504 (2008)], it is shown how the approximation error of tree tensor network states (TTNS) can be bounded using Schmidt spectra or Rényi entanglement entropies of the target quantum state. Conversely, one obtains bounds on TTNS bond dimensions needed to achieve a specific approximation accuracy. For tree lattices, the result implies that efficient TTNS approximations exist if $α<1$ Rényi entanglement entropies for single-branch cuts obey an area law, as in ground and low-energy states of certain gapped systems. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2512_20215 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Tree tensor network states represent low-energy states faithfully Barthel, Thomas Quantum Physics Statistical Mechanics Strongly Correlated Electrons Computational Physics Extending corresponding results for matrix product states [Verstraete and Cirac, PRB 73, 094423 (2006); Schuch et al. PRL 100, 030504 (2008)], it is shown how the approximation error of tree tensor network states (TTNS) can be bounded using Schmidt spectra or Rényi entanglement entropies of the target quantum state. Conversely, one obtains bounds on TTNS bond dimensions needed to achieve a specific approximation accuracy. For tree lattices, the result implies that efficient TTNS approximations exist if $α<1$ Rényi entanglement entropies for single-branch cuts obey an area law, as in ground and low-energy states of certain gapped systems. |
| title | Tree tensor network states represent low-energy states faithfully |
| topic | Quantum Physics Statistical Mechanics Strongly Correlated Electrons Computational Physics |
| url | https://arxiv.org/abs/2512.20215 |