Coordinate systems and distributional embeddings in Bourgain-Rosenthal-Schechtman spaces: a framework for operator reduction
Abstract
For every 1≤ α<ω1, we construct an explicit unconditional finite-dimensional decomposition (FDD) (Xλ)λ∈Tα of the Bourgain-Rosenthal-Schechtman space Rαp,0 by blocking its standard martingale difference sequence (MDS) basis. This FDD has strong reproducing properties and supports a theory of distributional representations between the spaces Rαp,0, 1≤ α<ω1. We use this framework to prove an approximate orthogonal reduction: every bounded linear operator on a limit space Rαp,0 is, via a distributional embedding and up to arbitrary precision, reduced to a scalar FDD-diagonal operator. As a consequence, the standard MDS bases of the limit spaces Rαp,0 satisfy the factorization property.
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.