Pith Number
pith:QV6E5ZSB
pith:2026:QV6E5ZSB4Q77ZZGEYLP5HA3EWF
not attested
not anchored
not stored
refs pending
Multi-fidelity Machine Learning Interatomic Potentials for Charged Point Defects
arxiv:2603.05238 v2 · 2026-03-05 · cond-mat.mtrl-sci
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{QV6E5ZSB4Q77ZZGEYLP5HA3EWF}
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 | 2026-06-09T01:05:15.392933Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
857c4ee641e43ffce4c4c2dfd38364b14153a0102cde03525cee85fd943acccf
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QV6E5ZSB4Q77ZZGEYLP5HA3EWF \
| 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: 857c4ee641e43ffce4c4c2dfd38364b14153a0102cde03525cee85fd943acccf
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "38358837ce4d87b28cb23d213e8452a576a6abb0bc9bf80ae704df921ee6ca54",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cond-mat.mtrl-sci",
"submitted_at": "2026-03-05T14:54:29Z",
"title_canon_sha256": "e44a85d4c12223d2b73c1fc45a61b9a43b25241a5951a484d3a01e9b27bc55d2"
},
"schema_version": "1.0",
"source": {
"id": "2603.05238",
"kind": "arxiv",
"version": 2
}
}