Pith Number
pith:GPPFELCQ
pith:2026:GPPFELCQYEPIDH55SPLU7FRD5Y
not attested
not anchored
not stored
refs pending
ND-TNN: Tensor-Neural-Network Approximation for High-Dimensional Nonlocal Diffusion Models
arxiv:2606.08685 v1 · 2026-06-07 · math.NA · cs.NA
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{GPPFELCQYEPIDH55SPLU7FRD5Y}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
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4
Citations
5
Replications
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Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-06-09T01:05:47.403365Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
33de522c50c11e819fbd93d74f9623ee0c5a7a2f8d12c9542b207a095ed37164
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GPPFELCQYEPIDH55SPLU7FRD5Y \
| 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: 33de522c50c11e819fbd93d74f9623ee0c5a7a2f8d12c9542b207a095ed37164
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "6a3a5e9a20e15904e0e226d318819abb1f22c9d8bf549cc79d92865935095f84",
"cross_cats_sorted": [
"cs.NA"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "math.NA",
"submitted_at": "2026-06-07T15:37:55Z",
"title_canon_sha256": "21271d7447c97d9c12972e0b416cb8ffb1b713f40816b2f8d4f6f1f3c343e635"
},
"schema_version": "1.0",
"source": {
"id": "2606.08685",
"kind": "arxiv",
"version": 1
}
}