pith:QZ4VRXSI
Lebesgue measure of distance sets with regular pins and multi-scale Mizohata-Takeuchi-type estimates
If dim E >1, dim E + dim F >2 and F has equal Hausdorff and packing dimension, then some pinned distance set Delta_y(E) has positive Lebesgue measure.
arxiv:2603.15328 v3 · 2026-03-16 · math.CA · math.AP · math.CO
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\pithnumber{QZ4VRXSIAA4STUOOSEBVVXNK4L}
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Record completeness
Claims
There exists y∈F such that Δ_y(E) has positive Lebesgue measure, given dim_H E>1, dim_H E + dim_H F>2, and F has equal Hausdorff and packing dimension.
The assumption that F has equal Hausdorff and packing dimensions, which enables the multi-scale Good-Bad decomposition and Mizohata-Takeuchi estimates to control the distance set without extra losses.
Under dim_H E >1, dim_H E + dim_H F >2 and F regular (equal Hausdorff and packing dimensions), there exists y in F such that the pinned distance set Δ_y(E) has positive Lebesgue measure.
Receipt and verification
| First computed | 2026-07-17T01:20:47.501936Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
867958de48003929d1ce91035addaae2c6087fdf775af57f7d8f9c31367db6d0
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QZ4VRXSIAA4STUOOSEBVVXNK4L \
| 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: 867958de48003929d1ce91035addaae2c6087fdf775af57f7d8f9c31367db6d0
Canonical record JSON
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"license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
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"submitted_at": "2026-03-16T14:20:56Z",
"title_canon_sha256": "aaeac579701ef0901db5c42e7ddcc17f7745974c1258dc414029b64a2387e36c"
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