Pith Number
pith:XF3I56QH
pith:2025:XF3I56QH6KYLN7LMHYC5LHDD6X
not attested
not anchored
not stored
refs pending
MultiPDENet: PDE-embedded Learning with Multi-time-stepping for Accelerated Flow Simulation
arxiv:2501.15987 v1 · 2025-01-27 · math.NA · cs.AI · cs.NA
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{XF3I56QH6KYLN7LMHYC5LHDD6X}
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
Author claim
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claim
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T10:05:53.414884Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b9768efa07f2b0b6fd6c3e05d59c63f5f9f9be139150cd6283e9106d25acb80c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/XF3I56QH6KYLN7LMHYC5LHDD6X \
| 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: b9768efa07f2b0b6fd6c3e05d59c63f5f9f9be139150cd6283e9106d25acb80c
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "39bcda3ae8bac498a1e57ce151faa35f8f1df49a8e8b2144eb9e42cc9aa1e52a",
"cross_cats_sorted": [
"cs.AI",
"cs.NA"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "math.NA",
"submitted_at": "2025-01-27T12:15:51Z",
"title_canon_sha256": "a297f69631b34fc0982268b4216c2bed97a798f0d0bf265495f3dd2bdf7ee9a7"
},
"schema_version": "1.0",
"source": {
"id": "2501.15987",
"kind": "arxiv",
"version": 1
}
}