Pith Number
pith:YFSWPA7J
pith:2025:YFSWPA7JHN3PUCPV6IAAP7RXQX
not attested
not anchored
not stored
refs pending
Deep Learning-Enabled Supercritical Flame Simulation at Detailed Chemistry and Real-Fluid Accuracy Towards Trillion-Cell Scale
arxiv:2508.18969 v1 · 2025-08-26 · cs.DC
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{YFSWPA7JHN3PUCPV6IAAP7RXQX}
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
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claim
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 | 2026-07-05T11:59:34.694128Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c1656783e93b76fa09f5f20007fe3785f08fc9a7ca85b73ff6862b9a63143594
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YFSWPA7JHN3PUCPV6IAAP7RXQX \
| 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: c1656783e93b76fa09f5f20007fe3785f08fc9a7ca85b73ff6862b9a63143594
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "3696e1069b3a925ee2377baea6263e23ddf1c4ecc2f8b52897104678dae75a00",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.DC",
"submitted_at": "2025-08-26T12:13:17Z",
"title_canon_sha256": "5db5bc6bb3aa68e998d269b2b5e4931bee66d5efe8c0afbfe191970b03f84c27"
},
"schema_version": "1.0",
"source": {
"id": "2508.18969",
"kind": "arxiv",
"version": 1
}
}