Pith Number
pith:SEJW4DW2
pith:2024:SEJW4DW2BTE45FOMKFXSBKICNR
not attested
not anchored
not stored
refs pending
Can Geometric Quantum Machine Learning Lead to Advantage in Barcode Classification?
arxiv:2409.01496 v1 · 2024-09-02 · quant-ph · cond-mat.dis-nn · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{SEJW4DW2BTE45FOMKFXSBKICNR}
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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.
Cited by
Receipt and verification
| First computed | 2026-07-05T09:02:29.748789Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
91136e0eda0cc9ce95cc516f20a9026c4a77b7ad5e5219b4dddb56d795b431fc
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/SEJW4DW2BTE45FOMKFXSBKICNR \
| 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: 91136e0eda0cc9ce95cc516f20a9026c4a77b7ad5e5219b4dddb56d795b431fc
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "647988c291e2e4f41b0ebfd7a1d231800ec8714510a675cf43b2c54ce358b52f",
"cross_cats_sorted": [
"cond-mat.dis-nn",
"cs.CV"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "quant-ph",
"submitted_at": "2024-09-02T23:34:52Z",
"title_canon_sha256": "b6838480584b7e38d1cbb531f20dec85203d8e0333e7b2742e15b6fc62c8c2cb"
},
"schema_version": "1.0",
"source": {
"id": "2409.01496",
"kind": "arxiv",
"version": 1
}
}