Sparse domination implies convex body domination

Aapo Laukkarinen, Emiel Lorist

The AI-associated dyadic randomization step underlies Theorem A: for 1≤r,s<∞ with 1/r+1/s>1, a bilinear form on compactly supported bounded scalar functions with an (r,s)-sparse bound has a convex-body sparse bound for its coordinate-wise C^n extension, with stated n^(1+1/r+1/s) and η^−1 dependence. Theorem 2.6 proves a dyadic version; the non-dyadic extension and final theorem were completed by the human authors.

Sources for this record

What was already known

Nazarov–Petermichl–Treil–Volberg introduced convex-body domination and conjectured the general implication from scalar sparse domination. Earlier work proved an implication only under a stronger generic estimate arising in typical sparse-domination proofs.

AI involvement AI-centered

Aapo Laukkarinen and Emiel Lorist co-developed an initial commutator approach with ChatGPT 5.6, then suggested Rademacher randomization. ChatGPT helped find a rough dyadic proof; the authors developed, verified and explained the complete theorem.

The model co-developed a rough central dyadic proof, while humans supplied the Rademacher pivot and completed the final theorem.

Importance Notable

The final theorem proves the conjectured implication from scalar sparse bounds to convex-body sparse bounds.

Limitations

The human authors supplied the Rademacher pivot and completed the non-dyadic theorem. The rough model-generated dyadic proof is unavailable for direct comparison with the final proof.

Technical verification Formal (human)

The authors explicitly state that they fully developed and verified the final proof; the reported check covers the dyadic AI-associated step and its final use.

Human understanding Full

The authors explain and complete the randomization and stopping-time mechanism.

Correction and publication history

2026-10-18 · publication

The final theorem proves the conjectured implication from scalar sparse bounds to convex-body sparse bounds.

Read this published revision