pith. sign in
Pith Number

pith:VLB4AVWQ

pith:2026:VLB4AVWQ43SSWXCNR3AEWKSAFX
not attested not anchored not stored refs resolved

Flow Field Reconstruction with Sensor Placement Policy Learning

Guancheng Wan, Haixin Wang, Ruoyan Li, Wei Wang, Xiao Luo, Yizhou Sun, Zijie Huang, Zixiao Liu

A directional transport-aware GNN paired with constrained PPO jointly optimizes flow reconstruction and sensor placement under realistic conditions.

arxiv:2605.14137 v1 · 2026-05-13 · cs.CE

Add to your LaTeX paper
\usepackage{pith}
\pithnumber{VLB4AVWQ43SSWXCNR3AEWKSAFX}

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

Together, they achieve significant improvements over existing methods.

C2weakest assumption

The directional transport-aware GNN and Two-Step Constrained PPO will maintain performance gains when applied to truly realistic 3D flows without the simplifying assumptions of prior work.

C3one line summary

A directional GNN combined with constrained PPO jointly improves flow-field reconstruction accuracy and sensor layout selection in realistic fluid dynamics settings.

References

26 extracted · 26 resolved · 2 Pith anchors

[1] COMSOL Multiphysics® · doi:10.1002/aic.690480510
[2] Asymptotic accuracy of the saddlepoint approximation for maximum likelihood estimation.The Annals of Statistics, 50(4):2021–2046, 2021
[3] URL https://doi.org/10.1214/22-AOS2169 · doi:10.1214/22-aos2169
[4] doi: 10.1063/1.2393436 · doi:10.1063/1.2393436
[5] doi: 10.1063/5.0097688 · doi:10.1063/5.0097688

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-05-17T23:39:11.729372Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

aac3c056d0e6e52b5c4d8ec04b2a402de7812bb20636e6646d900321f3e0e57b

Aliases

arxiv: 2605.14137 · arxiv_version: 2605.14137v1 · doi: 10.48550/arxiv.2605.14137 · pith_short_12: VLB4AVWQ43SS · pith_short_16: VLB4AVWQ43SSWXCN · pith_short_8: VLB4AVWQ
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/VLB4AVWQ43SSWXCNR3AEWKSAFX \
  | 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: aac3c056d0e6e52b5c4d8ec04b2a402de7812bb20636e6646d900321f3e0e57b
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "8f47ab965166c265c9c5f677836ba09a5c7de41e871c0206ce78100e22764d73",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CE",
    "submitted_at": "2026-05-13T21:41:29Z",
    "title_canon_sha256": "0bbcad029c40a183201c9213f95e2332a0b3dcbbbd031b61e90e4e30c6239cba"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14137",
    "kind": "arxiv",
    "version": 1
  }
}