Compactness, convexity, and translate containment of the closed fold
ProvedKomlos.closedConvexFold_geometrybanaszczykconvex-geometry
Let be compact and convex and let . For the closed fold defined by the retained fibers of length at least ,
This assertion holds for every vector , including zero, and requires no Gaussian measure hypothesis. It supplies the geometric part of the folding step in vector balancing.
Preamble
import Definitions.Def_Komlos_convex_fold import Mathlib.Probability.Distributions.Gaussian.Multivariate open Set MeasureTheory ProbabilityTheory open scoped Pointwise set_option autoImplicit false
Formal statement
theorem Komlos.closedConvexFold_geometry (m : ℕ) (K : Set (EuclideanSpace ℝ (Fin m)))
(hconv : Convex ℝ K) (hcomp : IsCompact K) (u : EuclideanSpace ℝ (Fin m)) :
Convex ℝ (Komlos.closedConvexFold m K u) ∧
IsCompact (Komlos.closedConvexFold m K u) ∧
∀ x ∈ Komlos.closedConvexFold m K u, x + u ∈ K ∨ x - u ∈ K := by sorry
Source
Shashwat Garg, Algorithms for Combinatorial Discrepancy, TU Eindhoven PhD thesis (2018), Chapter 3, Definition 14 and following convexity observation, printed p. 18. https://pure.tue.nl/ws/files/107722737/20181010_Garg.pdf . The closed-fold definition expresses the retained fibers using endpoints y,y+2u; compactness is recorded explicitly for compact K.