Pith Number
pith:PON2TYFV
pith:2019:PON2TYFVMCBAZL3TYBNDTAG6FQ
not attested
not anchored
not stored
refs pending
Monte Carlo algorithms are very effective in finding the largest independent set in sparse random graphs
arxiv:1904.02231 v1 · 2019-04-03 · cond-mat.dis-nn · cond-mat.stat-mech · cs.CC · cs.DS
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{PON2TYFVMCBAZL3TYBNDTAG6FQ}
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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 | 2026-05-17T23:41:09.148542Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
7b9ba9e0b560820caf73c05a3980de2c12b72a02be2efa5f83a597dcb36bb756
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/PON2TYFVMCBAZL3TYBNDTAG6FQ \
| 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: 7b9ba9e0b560820caf73c05a3980de2c12b72a02be2efa5f83a597dcb36bb756
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "cb5575f4ff076fd7214e6900617d494fdc5be812bf827e96d823d1cbd351ef7c",
"cross_cats_sorted": [
"cond-mat.stat-mech",
"cs.CC",
"cs.DS"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cond-mat.dis-nn",
"submitted_at": "2019-04-03T20:28:21Z",
"title_canon_sha256": "ef0075eafa9e215578419b68ae1e5f4bb2006fe3b1c2b8fd60e1c2173b4276a6"
},
"schema_version": "1.0",
"source": {
"id": "1904.02231",
"kind": "arxiv",
"version": 1
}
}