Subset-Sum Norm Inequality
ProvedFunctionalInequalities.Analysis.Tensor.sum_norm_sq_le_sum_norm_sq_sum_subset_readablefunctional-inequalitieskls-conjecturekls-modularkls-readablelog-concave
This is the inequality form of the BKL subset-sum estimate.
Let be a real inner-product space, let be finite with , and let be assigned to every -element subset . Then
This inequality is the norm estimate extracted from the exact subset-sum identity and is used in the representation-theoretic symmetrization bound.
Original Lean declaration header
Within namespace FunctionalInequalities.Analysis.Tensor. Shown in its original module context. Proof omitted.
theorem sum_norm_sq_le_sum_norm_sq_sum_subset (U : Finset α) {d : ℕ} (hU : U.card = 3 * d)
(x : Finset α → V) :
∑ F ∈ U.powersetCard d, ‖x F‖ ^ 2 ≤
∑ E ∈ U.powersetCard (2 * d), ‖∑ F ∈ E.powersetCard d, x F‖ ^ 2
Module navigation
Module: Analysis/Tensor/Symmetrization.
Supporting theorems: sum_norm_sq_sum_subset_eq.
Previous: sum_norm_sq_sum_subset_eq · Next: exists_mem_fixingOutside_image_eq.
Source excerpt, lines 401–404 · Frozen source 408915f.
Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_Tensor_Symmetrization
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
variable {α : Type*} [DecidableEq α]
Formal statement
theorem FunctionalInequalities.Analysis.Tensor.sum_norm_sq_le_sum_norm_sq_sum_subset_readable (U : Finset α) {d : ℕ} (hU : U.card = 3 * d)
(x : Finset α → V) :
∑ F ∈ U.powersetCard d, ‖x F‖ ^ 2 ≤
∑ E ∈ U.powersetCard (2 * d), ‖∑ F ∈ E.powersetCard d, x F‖ ^ 2 := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/Tensor/Symmetrization.lean#L399-L458 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.Tensor.Symmetrization`, declaration `FunctionalInequalities.Analysis.Tensor.sum_norm_sq_le_sum_norm_sq_sum_subset`; the repository is private at upload time).