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Applications of the Hausdorff distance in normed spaces #

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Riesz's lemma, stated for a normed space over a normed field: for any closed proper subspace F of E, there is a nonzero x such that ‖x - F‖ is at least r * ‖x‖ for any r < 1. This is riesz_lemma.

In a nontrivially normed field (with an element c of norm > 1) and any R > ‖c‖, one can guarantee ‖x‖ ≤ R and ‖x - y‖ ≥ 1 for any y in F. This is riesz_lemma_of_norm_lt.

A further lemma, metric.closed_ball_inf_dist_compl_subset_closure, finds a closed ball within the closure of a set s of optimal distance from a point in x to the frontier of s.

theorem riesz_lemma {𝕜 : Type u_1} [normed_field 𝕜] {E : Type u_2} [normed_add_comm_group E] [normed_space 𝕜 E] {F : subspace 𝕜 E} (hFc : is_closed F) (hF : (x : E), x F) {r : } (hr : r < 1) :
(x₀ : E), x₀ F (y : E), y F r * x₀ x₀ - y

Riesz's lemma, which usually states that it is possible to find a vector with norm 1 whose distance to a closed proper subspace is arbitrarily close to 1. The statement here is in terms of multiples of norms, since in general the existence of an element of norm exactly 1 is not guaranteed. For a variant giving an element with norm in [1, R], see riesz_lemma_of_norm_lt.

theorem riesz_lemma_of_norm_lt {𝕜 : Type u_1} [normed_field 𝕜] {E : Type u_2} [normed_add_comm_group E] [normed_space 𝕜 E] {c : 𝕜} (hc : 1 < c) {R : } (hR : c < R) {F : subspace 𝕜 E} (hFc : is_closed F) (hF : (x : E), x F) :
(x₀ : E), x₀ R (y : E), y F 1 x₀ - y

A version of Riesz lemma: given a strict closed subspace F, one may find an element of norm ≤ R which is at distance at least 1 of every element of F. Here, R is any given constant strictly larger than the norm of an element of norm > 1. For a version without an R, see riesz_lemma.

Since we are considering a general nontrivially normed field, there may be a gap in possible norms (for instance no element of norm in (1,2)). Hence, we can not allow R arbitrarily close to 1, and require R > ‖c‖ for some c : 𝕜 with norm > 1.