pith. sign in
Pith Number

pith:UDTFEBXB

pith:2026:UDTFEBXBTWBUSFLNZWJGPRB7MY
not attested not anchored not stored refs pending

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots

Kirill Neklyudov, Lazar Atanackovic, Vincent Guan

Wasserstein Lagrangian Mechanics learns second-order population dynamics directly from observed marginals without specifying the Lagrangian.

arxiv:2605.08550 v3 · 2026-05-08 · cs.LG · stat.ML

Add to your LaTeX paper
\usepackage{pith}
\pithnumber{UDTFEBXBTWBUSFLNZWJGPRB7MY}

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.

Claims

C1strongest claim

WLM is the first algorithm that learns these second-order dynamics from observed marginals, without specifying the Lagrangian.

C2weakest assumption

That population dynamics of interest can be accurately described as minimizing a population-level action under a damped Wasserstein Lagrangian.

C3one line summary

Wasserstein Lagrangian Mechanics learns second-order population dynamics from observed marginals without specifying the Lagrangian and outperforms gradient flow methods on periodic dynamics like vortex motion and flocking.

Receipt and verification
First computed 2026-05-20T00:03:15.291626Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

a0e65206e19d8349156dcd9267c43f661e6bc259fe80b7d4233824f69c6cb24c

Aliases

arxiv: 2605.08550 · arxiv_version: 2605.08550v3 · doi: 10.48550/arxiv.2605.08550 · pith_short_12: UDTFEBXBTWBU · pith_short_16: UDTFEBXBTWBUSFLN · pith_short_8: UDTFEBXB
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/UDTFEBXBTWBUSFLNZWJGPRB7MY \
  | 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: a0e65206e19d8349156dcd9267c43f661e6bc259fe80b7d4233824f69c6cb24c
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "a6c75cadde9fda76efe73c240afb120e90fc11055778cb8b6a39ecb8df7af207",
    "cross_cats_sorted": [
      "stat.ML"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-08T23:21:17Z",
    "title_canon_sha256": "0e2e0c5b3586732c24850c70092404de1885fdf22d04331e593d3f0538b663c3"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.08550",
    "kind": "arxiv",
    "version": 3
  }
}