pith:CY3VJPLH
An improved boundary-focused adaptive quadtree algorithm for circle-polygon intersection area approximation
An adaptive quadtree algorithm approximates circle-polygon intersection areas in O(1/ε^{3/2}) time with O(ε) error.
arxiv:2605.15627 v1 · 2026-05-15 · cs.CG
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Claims
Theoretical analysis shows that the algorithm achieves O(1/ε^{3/2}) computational complexity while maintaining an O(ε) error bound, improving upon the O(1/ε²) complexity of classical Monte Carlo and uniform grid methods for the same error tolerance ε.
The curvature-multiplicity-guided adaptive sampling strategy, including the introduced minimum sample count and constant factor, correctly concentrates points on complex boundaries to achieve the stated O(ε) error without systematic bias or missed intersections in multi-circle cells.
An adaptive quadtree algorithm with curvature-guided Monte Carlo sampling for multi-circle polygon intersections achieves O(1/ε^{3/2}) complexity at O(ε) error, outperforming classical methods in experiments.
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Receipt and verification
| First computed | 2026-05-20T00:01:08.863803Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
163754bd677922c53c89375b9581d53eeb98c76ebf411f4f077546518e89a363
Aliases
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/CY3VJPLHPERMKPEJG5NZLAOVH3 \
| 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())"
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Canonical record JSON
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