pith:RXNYAVUY
Pro-Tensor Network
Pro-tensor networks categorify tensor networks to study many-many-body theories without semisimplicity or finiteness.
arxiv:2605.06661 v2 · 2026-05-07 · cond-mat.str-el · hep-th · math-ph · math.CT · math.MP · math.QA
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\pithnumber{RXNYAVUYBP45MV4QCSG4J2JNBQ}
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Record completeness
Claims
We introduce the pro-tensor network, a categorification of the tensor network, as a fully rigorous yet graphically transparent framework for studying the collection of many many-body theories, which we dub many-many-body theory.
That a well-defined pro-tensor network can be constructed and used for physical calculations while dispensing with the assumptions of semisimplicity, finiteness, and rigidity.
Pro-tensor networks form a categorified framework for many-many-body theories that recovers the Levin-Wen model and characterizes particles as modules over promonads without requiring semisimplicity, finiteness or rigidity.
Receipt and verification
| First computed | 2026-05-20T01:06:09.814883Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
8ddb8056980bf9d65790148dc4e92d0c1f465adbd122f2fef45e1f8964c26afb
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/RXNYAVUYBP45MV4QCSG4J2JNBQ \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 8ddb8056980bf9d65790148dc4e92d0c1f465adbd122f2fef45e1f8964c26afb
Canonical record JSON
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"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
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"submitted_at": "2026-05-07T17:58:40Z",
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