pith:OGNQBC4V
A Practical Introduction to Tensor Network Renormalization with TNRKit.jl
TNRKit extracts universal conformal data directly from fixed-point tensors in tensor network renormalization.
arxiv:2604.06922 v4 · 2026-04-08 · cond-mat.str-el · cond-mat.stat-mech · cs.MS · quant-ph
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Claims
TNRKit enables the extraction of universal conformal data -- including scaling dimensions and the central charge -- directly from fixed-point tensors.
The implemented coarse-graining routines produce fixed-point tensors whose eigenvalues and eigenvectors faithfully encode the universal data of the underlying model without significant truncation artifacts or symmetry-breaking errors.
TNRKit is a symmetry-aware Julia package that implements TRG, HOTRG, and LoopTNR to coarse-grain tensor networks and extract conformal data such as scaling dimensions and central charge from fixed-point tensors.
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| First computed | 2026-06-09T02:07:26.108859Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
719b008b9587f4a06243084c50b990c68b11f8cb68c39aaa23c1bb5d14eb99ff
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/OGNQBC4VQ72KAYSDBBGFBOMQY2 \
| jq -c '.canonical_record' \
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Canonical record JSON
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