Pith Number
pith:VGSI3G7Y
pith:2023:VGSI3G7YFGKPWNUWSYDX4BMAYG
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Hybrid Neural-Network FEM Approximation of Diffusion Coefficient in Elliptic and Parabolic Problems
arxiv:2302.10773 v1 · 2023-02-21 · math.NA · cs.NA
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{VGSI3G7YFGKPWNUWSYDX4BMAYG}
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Record completeness
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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 | 2026-07-05T05:44:21.577222Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
a9a48d9bf82994fb369696077e0580c18667a6682a2a0e59d7b79d98d235ead9
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/VGSI3G7YFGKPWNUWSYDX4BMAYG \
| 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: a9a48d9bf82994fb369696077e0580c18667a6682a2a0e59d7b79d98d235ead9
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "a45dca448e2007c3a9de0b5663d13c956e72fbd043de1f77e210c15b5d4d54f4",
"cross_cats_sorted": [
"cs.NA"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "math.NA",
"submitted_at": "2023-02-21T16:08:40Z",
"title_canon_sha256": "4c193325a91538bd4cb1acca6d36de04e24c7dcf971e4d76c00a4297c26c65b4"
},
"schema_version": "1.0",
"source": {
"id": "2302.10773",
"kind": "arxiv",
"version": 1
}
}