LeanAide GPT-4 documentation

Module: Mathlib.Analysis.NormedSpace.Span


LinearEquiv.toSpanNonzeroSingleton_homothety

theorem LinearEquiv.toSpanNonzeroSingleton_homothety : āˆ€ (š•œ : Type u_1) {E : Type u_2} [inst : NormedDivisionRing š•œ] [inst_1 : SeminormedAddCommGroup E] [inst_2 : Module š•œ E] [inst_3 : BoundedSMul š•œ E] (x : E) (h : x ≠ 0) (c : š•œ), ‖(LinearEquiv.toSpanNonzeroSingleton š•œ E x h) c‖ = ‖x‖ * ‖c‖

This theorem states that for any type š•œ, normed division ring over š•œ, seminormed additive commutative group E, a module š•œ E, a bounded scalar multiplication of š•œ and E, and any non-zero element x of E, and any element c of š•œ, the norm of the element obtained by applying the linear equivalence `toSpanNonzeroSingleton` with arguments š•œ, E, x, h (where h is the condition that x ≠ 0) to the element c, is equal to the product of the norm of x and the norm of c. This theorem can be understood as stating the property that the norm of the projection of an element c in the span of a non-zero element x is proportional to the norm of x and the norm of c.

More concisely: For any normed division ring š•œ, seminormed additive commutative group E, module š•œ E, and bounded scalar multiplication, the norm of the product of a non-zero element x in E and any scalar c in š•œ, as defined by `toSpanNonzeroSingleton`, equals the product of the norms of x and c.