pith:3LNA6NI5
A Parallel and Adaptive Mesh-Free method for Heterogeneous Porous Media
Normalized radial basis functions with Shepard stabilization approximate discontinuous step functions to arbitrarily small L1 error.
arxiv:2605.16564 v1 · 2026-05-15 · math.NA · cs.NA
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{3LNA6NI5KSNEX4BVIX7JGYJDYW}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
Claims
We provide a theoretical analysis showing that the proposed normalized RBF framework achieves arbitrarily small L^1 error in approximating discontinuous step functions.
Shepard normalization stabilizes the RBF approximation near sharp interfaces so that sparse regression can produce robust continuous representations of the original discontinuous data.
PAM is a mesh-independent RBF framework with Shepard normalization, sparse regression, adaptive refinement, and subdomain parallelism that approximates discontinuous data with arbitrarily small L1 error for step functions.
References
Formal links
Receipt and verification
| First computed | 2026-05-20T00:02:29.349903Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
dada0f351d549a4bf03545fe936123c5b6e8902dd8c50da22a641654a3c1b217
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3LNA6NI5KSNEX4BVIX7JGYJDYW \
| 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: dada0f351d549a4bf03545fe936123c5b6e8902dd8c50da22a641654a3c1b217
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "8909193c6ae15b737e76e871ac2ca76f527ae6ef0526ffac47d58576cbb70a06",
"cross_cats_sorted": [
"cs.NA"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "math.NA",
"submitted_at": "2026-05-15T19:07:29Z",
"title_canon_sha256": "918b6cd8ecd61bf121411e5e004de059e570b52a021c8b52ba4e74091708d2c0"
},
"schema_version": "1.0",
"source": {
"id": "2605.16564",
"kind": "arxiv",
"version": 1
}
}