Pith Number
pith:MWNTJXBF
pith:2024:MWNTJXBFNUKK3SGBMYDZVQ3GU4
not attested
not anchored
not stored
refs pending
Training Large-Scale Optical Neural Networks with Two-Pass Forward Propagation
arxiv:2408.08337 v1 · 2024-08-15 · cs.LG · physics.optics
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{MWNTJXBFNUKK3SGBMYDZVQ3GU4}
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
· sign in to
claim
4
Citations
5
Replications
✓
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 | 2026-07-05T08:55:52.771331Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
659b34dc256d14adc8c166079ac366a722ab6b6777c073088c5c722ad0756594
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MWNTJXBFNUKK3SGBMYDZVQ3GU4 \
| 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: 659b34dc256d14adc8c166079ac366a722ab6b6777c073088c5c722ad0756594
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "cd3a0ed09c0196ef41dc30f7eb1092119da996640c5079e76c58306e7bb69d5b",
"cross_cats_sorted": [
"physics.optics"
],
"license": "http://creativecommons.org/publicdomain/zero/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-08-15T11:27:01Z",
"title_canon_sha256": "18fbef2f89bb4c4c3e77a5d9118537fe1aa3f78103c7d57f4d6c4c70878d7c01"
},
"schema_version": "1.0",
"source": {
"id": "2408.08337",
"kind": "arxiv",
"version": 1
}
}