Pith Number
pith:Q7QPDHMK
pith:2025:Q7QPDHMKSCUGO6VVFDDPA6VNJZ
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An Adaptive Framework for Autoregressive Forecasting in CFD Using Hybrid Modal Decomposition and Deep Learning
arxiv:2505.01531 v1 · 2025-05-02 · physics.flu-dyn · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{Q7QPDHMKSCUGO6VVFDDPA6VNJZ}
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Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
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4
Citations
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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 | 2026-07-05T10:57:59.556972Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
87e0f19d8a90a8677ab528c6f07aad4e71d7407d914d33f61221aa2b6a54ce3d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/Q7QPDHMKSCUGO6VVFDDPA6VNJZ \
| 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: 87e0f19d8a90a8677ab528c6f07aad4e71d7407d914d33f61221aa2b6a54ce3d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "6834922c03d5ba100f7bdddfe719b71bdbea7b73b4a4f03434a533c7863a5406",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
"primary_cat": "physics.flu-dyn",
"submitted_at": "2025-05-02T18:33:41Z",
"title_canon_sha256": "650f6342895b1474781163c5d8a741205ca79e7b0c3bae571423ee084235987e"
},
"schema_version": "1.0",
"source": {
"id": "2505.01531",
"kind": "arxiv",
"version": 1
}
}