Pith Number

pith:SEE6MEHK

pith:2021:SEE6MEHKND3WYNRMJUPH3WEY7F

not attested not anchored not stored refs pending

Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks

Dian Wu, Giuseppe Carleo, Riccardo Rossi

arxiv:2105.05650 v3 · 2021-05-12 · cond-mat.stat-mech · cond-mat.dis-nn · cs.LG · stat.ML

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{SEE6MEHKND3WYNRMJUPH3WEY7F}

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 open · sign in to claim

4 Citations open

5 Replications open

✓ 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

1 paper in Pith

Leveraging generative models to assist Monte Carlo sampling

Receipt and verification

First computed	2026-07-05T03:30:39.571679Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

9109e610ea68f76c362c4d1e7dd898f95b0998571533426794a8ad186946f40e

Aliases

arxiv: 2105.05650 · arxiv_version: 2105.05650v3 · doi: 10.48550/arxiv.2105.05650 · pith_short_12: SEE6MEHKND3W · pith_short_16: SEE6MEHKND3WYNRM · pith_short_8: SEE6MEHK

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/SEE6MEHKND3WYNRMJUPH3WEY7F \
  | 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: 9109e610ea68f76c362c4d1e7dd898f95b0998571533426794a8ad186946f40e

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "d004ecbf9da019a38c893e9c66e6897091cf667ee15dc2255806bbe1162887c2",
    "cross_cats_sorted": [
      "cond-mat.dis-nn",
      "cs.LG",
      "stat.ML"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cond-mat.stat-mech",
    "submitted_at": "2021-05-12T13:31:12Z",
    "title_canon_sha256": "97ef27a2436853ed1ee7f53c1b884fad158eafc86522d95adab33f46ffa920f0"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2105.05650",
    "kind": "arxiv",
    "version": 3
  }
}