Pith Number
pith:23O37WBC
pith:2025:23O37WBCUILQYVBNPJ4J6DTX4X
not attested
not anchored
not stored
refs pending
Symmetry- and Gradient-enhanced Gaussian Process Regression for the Active Learning of Potential Energy Surfaces in Porous Materials
arxiv:2501.16475 v1 · 2025-01-27 · physics.chem-ph · cond-mat.mtrl-sci · physics.comp-ph
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{23O37WBCUILQYVBNPJ4J6DTX4X}
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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.
Receipt and verification
| First computed | 2026-07-05T10:06:48.032586Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d6ddbfd822a2170c542d7a789f0e77e5e44b3d9ee0b3801c841e17d668713816
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/23O37WBCUILQYVBNPJ4J6DTX4X \
| 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: d6ddbfd822a2170c542d7a789f0e77e5e44b3d9ee0b3801c841e17d668713816
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c7843ad0f174228159bc166e363effdc093ef27d7e0243b4360a211c4eda1a95",
"cross_cats_sorted": [
"cond-mat.mtrl-sci",
"physics.comp-ph"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "physics.chem-ph",
"submitted_at": "2025-01-27T20:08:33Z",
"title_canon_sha256": "aab9ea1bfcca97e207f45aa19df02f0c168ec5a6f5e17d1d70ad023c5b3ed6b6"
},
"schema_version": "1.0",
"source": {
"id": "2501.16475",
"kind": "arxiv",
"version": 1
}
}