(* Author: L C Paulson, University of Cambridge
Author: Amine Chaieb, University of Cambridge
Author: Robert Himmelmann, TU Muenchen
Author: Brian Huffman, Portland State University
*)
section \<open>Elementary Normed Vector Spaces\<close>
theory Elementary_Normed_Spaces
imports
"HOL-Library.FuncSet"
Elementary_Metric_Spaces
Connected
begin
subsection\<^marker>\<open>tag unimportant\<close> \<open>Various Lemmas Combining Imports\<close>
lemma countable_PiE:
"finite I \<Longrightarrow> (\<And>i. i \<in> I \<Longrightarrow> countable (F i)) \<Longrightarrow> countable (Pi\<^sub>E I F)"
by (induct I arbitrary: F rule: finite_induct) (auto simp: PiE_insert_eq)
lemma open_sums:
fixes T :: "('b::real_normed_vector) set"
assumes "open S \<or> open T"
shows "open (\<Union>x\<in> S. \<Union>y \<in> T. {x + y})"
using assms
proof
assume S: "open S"
show ?thesis
proof (clarsimp simp: open_dist)
fix x y
assume "x \<in> S" "y \<in> T"
with S obtain e where "e > 0" and e: "\<And>x'. dist x' x < e \<Longrightarrow> x' \<in> S"
by (auto simp: open_dist)
then have "\<And>z. dist z (x + y) < e \<Longrightarrow> \<exists>x\<in>S. \<exists>y\<in>T. z = x + y"
by (metis \<open>y \<in> T\<close> diff_add_cancel dist_add_cancel2)
then show "\<exists>e>0. \<forall>z. dist z (x + y) < e \<longrightarrow> (\<exists>x\<in>S. \<exists>y\<in>T. z = x + y)"
using \<open>0 < e\<close> \<open>x \<in> S\<close> by blast
qed
next
assume T: "open T"
show ?thesis
proof (clarsimp simp: open_dist)
fix x y
assume "x \<in> S" "y \<in> T"
with T obtain e where "e > 0" and e: "\<And>x'. dist x' y < e \<Longrightarrow> x' \<in> T"
by (auto simp: open_dist)
then have "\<And>z. dist z (x + y) < e \<Longrightarrow> \<exists>x\<in>S. \<exists>y\<in>T. z = x + y"
by (metis \<open>x \<in> S\<close> add_diff_cancel_left' add_diff_eq diff_diff_add dist_norm)
then show "\<exists>e>0. \<forall>z. dist z (x + y) < e \<longrightarrow> (\<exists>x\<in>S. \<exists>y\<in>T. z = x + y)"
using \<open>0 < e\<close> \<open>y \<in> T\<close> by blast
qed
qed
subsection \<open>Support\<close>
definition (in monoid_add) support_on :: "'b set \<Rightarrow> ('b \<Rightarrow> 'a) \<Rightarrow> 'b set"
where "support_on s f = {x\<in>s. f x \<noteq> 0}"
lemma in_support_on: "x \<in> support_on s f \<longleftrightarrow> x \<in> s \<and> f x \<noteq> 0"
by (simp add: support_on_def)
lemma support_on_simps[simp]:
"support_on {} f = {}"
"support_on (insert x s) f =
(if f x = 0 then support_on s f else insert x (support_on s f))"
"support_on (s \<union> t) f = support_on s f \<union> support_on t f"
"support_on (s \<inter> t) f = support_on s f \<inter> support_on t f"
"support_on (s - t) f = support_on s f - support_on t f"
"support_on (f ` s) g = f ` (support_on s (g \<circ> f))"
unfolding support_on_def by auto
lemma support_on_cong:
"(\<And>x. x \<in> s \<Longrightarrow> f x = 0 \<longleftrightarrow> g x = 0) \<Longrightarrow> support_on s f = support_on s g"
by (auto simp: support_on_def)
lemma support_on_if: "a \<noteq> 0 \<Longrightarrow> support_on A (\<lambda>x. if P x then a else 0) = {x\<in>A. P x}"
by (auto simp: support_on_def)
lemma support_on_if_subset: "support_on A (\<lambda>x. if P x then a else 0) \<subseteq> {x \<in> A. P x}"
by (auto simp: support_on_def)
lemma finite_support[intro]: "finite S \<Longrightarrow> finite (support_on S f)"
unfolding support_on_def by auto
(* TODO: is supp_sum really needed? TODO: Generalize to Finite_Set.fold *)
definition (in comm_monoid_add) supp_sum :: "('b \<Rightarrow> 'a) \<Rightarrow> 'b set \<Rightarrow> 'a"
where "supp_sum f S = (\<Sum>x\<in>support_on S f. f x)"
lemma supp_sum_empty[simp]: "supp_sum f {} = 0"
unfolding supp_sum_def by auto
lemma supp_sum_insert[simp]:
"finite (support_on S f) \<Longrightarrow>
supp_sum f (insert x S) = (if x \<in> S then supp_sum f S else f x + supp_sum f S)"
by (simp add: supp_sum_def in_support_on insert_absorb)
lemma supp_sum_divide_distrib: "supp_sum f A / (r::'a::field) = supp_sum (\<lambda>n. f n / r) A"
by (cases "r = 0")
(auto simp: supp_sum_def sum_divide_distrib intro!: sum.cong support_on_cong)
subsection \<open>Intervals\<close>
lemma image_affinity_interval:
fixes c :: "'a::ordered_real_vector"
shows "((\<lambda>x. m *\<^sub>R x + c) ` {a..b}) =
(if {a..b}={} then {}
else if 0 \<le> m then {m *\<^sub>R a + c .. m *\<^sub>R b + c}
else {m *\<^sub>R b + c .. m *\<^sub>R a + c})"
(is "?lhs = ?rhs")
proof (cases "m=0")
case True
then show ?thesis
by force
next
case False
show ?thesis
proof
show "?lhs \<subseteq> ?rhs"
by (auto simp: scaleR_left_mono scaleR_left_mono_neg)
show "?rhs \<subseteq> ?lhs"
proof (clarsimp, intro conjI impI subsetI)
show "\<lbrakk>0 \<le> m; a \<le> b; x \<in> {m *\<^sub>R a + c..m *\<^sub>R b + c}\<rbrakk>
\<Longrightarrow> x \<in> (\<lambda>x. m *\<^sub>R x + c) ` {a..b}" for x
apply (rule_tac x="inverse m *\<^sub>R (x-c)" in rev_image_eqI)
using False apply (auto simp: le_diff_eq pos_le_divideRI)
using diff_le_eq pos_le_divideR_eq by force
show "\<lbrakk>\<not> 0 \<le> m; a \<le> b; x \<in> {m *\<^sub>R b + c..m *\<^sub>R a + c}\<rbrakk>
\<Longrightarrow> x \<in> (\<lambda>x. m *\<^sub>R x + c) ` {a..b}" for x
apply (rule_tac x="inverse m *\<^sub>R (x-c)" in rev_image_eqI)
apply (auto simp add: neg_le_divideR_eq not_le)
apply (auto simp: field_simps)
apply (metis (no_types, lifting) add_diff_cancel_left' add_le_imp_le_right diff_add_cancel inverse_eq_divide neg_le_divideR_eq neg_le_iff_le scale_minus_right)
done
qed
qed
qed
subsection \<open>Limit Points\<close>
lemma islimpt_ball:
fixes x y :: "'a::{real_normed_vector,perfect_space}"
shows "y islimpt ball x e \<longleftrightarrow> 0 < e \<and> y \<in> cball x e"
(is "?lhs \<longleftrightarrow> ?rhs")
proof
show ?rhs if ?lhs
proof
{
assume "e \<le> 0"
then have *: "ball x e = {}"
using ball_eq_empty[of x e] by auto
have False using \<open>?lhs\<close>
unfolding * using islimpt_EMPTY[of y] by auto
}
then show "e > 0" by (metis not_less)
show "y \<in> cball x e"
using closed_cball[of x e] islimpt_subset[of y "ball x e" "cball x e"]
ball_subset_cball[of x e] \<open>?lhs\<close>
unfolding closed_limpt by auto
qed
show ?lhs if ?rhs
proof -
from that have "e > 0" by auto
{
fix d :: real
assume "d > 0"
have "\<exists>x'\<in>ball x e. x' \<noteq> y \<and> dist x' y < d"
proof (cases "d \<le> dist x y")
case True
then show "\<exists>x'\<in>ball x e. x' \<noteq> y \<and> dist x' y < d"
proof (cases "x = y")
case True
then have False
using \<open>d \<le> dist x y\<close> \<open>d>0\<close> by auto
then show "\<exists>x'\<in>ball x e. x' \<noteq> y \<and> dist x' y < d"
by auto
next
case False
have "dist x (y - (d / (2 * dist y x)) *\<^sub>R (y - x)) =
norm (x - y + (d / (2 * norm (y - x))) *\<^sub>R (y - x))"
unfolding mem_cball mem_ball dist_norm diff_diff_eq2 diff_add_eq[symmetric]
by auto
also have "\<dots> = \<bar>- 1 + d / (2 * norm (x - y))\<bar> * norm (x - y)"
using scaleR_left_distrib[of "- 1" "d / (2 * norm (y - x))", symmetric, of "y - x"]
unfolding scaleR_minus_left scaleR_one
by (auto simp: norm_minus_commute)
also have "\<dots> = \<bar>- norm (x - y) + d / 2\<bar>"
unfolding abs_mult_pos[of "norm (x - y)", OF norm_ge_zero[of "x - y"]]
unfolding distrib_right using \<open>x\<noteq>y\<close> by auto
also have "\<dots> \<le> e - d/2" using \<open>d \<le> dist x y\<close> and \<open>d>0\<close> and \<open>?rhs\<close>
by (auto simp: dist_norm)
finally have "y - (d / (2 * dist y x)) *\<^sub>R (y - x) \<in> ball x e" using \<open>d>0\<close>
by auto
moreover
have "(d / (2*dist y x)) *\<^sub>R (y - x) \<noteq> 0"
using \<open>x\<noteq>y\<close>[unfolded dist_nz] \<open>d>0\<close> unfolding scaleR_eq_0_iff
by (auto simp: dist_commute)
moreover
have "dist (y - (d / (2 * dist y x)) *\<^sub>R (y - x)) y < d"
unfolding dist_norm
apply simp
unfolding norm_minus_cancel
using \<open>d > 0\<close> \<open>x\<noteq>y\<close>[unfolded dist_nz] dist_commute[of x y]
unfolding dist_norm
apply auto
done
ultimately show "\<exists>x'\<in>ball x e. x' \<noteq> y \<and> dist x' y < d"
apply (rule_tac x = "y - (d / (2*dist y x)) *\<^sub>R (y - x)" in bexI)
apply auto
done
qed
next
case False
then have "d > dist x y" by auto
show "\<exists>x' \<in> ball x e. x' \<noteq> y \<and> dist x' y < d"
proof (cases "x = y")
case True
obtain z where **: "z \<noteq> y" "dist z y < min e d"
using perfect_choose_dist[of "min e d" y]
using \<open>d > 0\<close> \<open>e>0\<close> by auto
show "\<exists>x'\<in>ball x e. x' \<noteq> y \<and> dist x' y < d"
unfolding \<open>x = y\<close>
using \<open>z \<noteq> y\<close> **
apply (rule_tac x=z in bexI)
apply (auto simp: dist_commute)
done
next
case False
then show "\<exists>x'\<in>ball x e. x' \<noteq> y \<and> dist x' y < d"
using \<open>d>0\<close> \<open>d > dist x y\<close> \<open>?rhs\<close>
apply (rule_tac x=x in bexI, auto)
done
qed
qed
}
then show ?thesis
unfolding mem_cball islimpt_approachable mem_ball by auto
qed
qed
lemma closure_ball_lemma:
fixes x y :: "'a::real_normed_vector"
assumes "x \<noteq> y"
shows "y islimpt ball x (dist x y)"
proof (rule islimptI)
fix T
assume "y \<in> T" "open T"
then obtain r where "0 < r" "\<forall>z. dist z y < r \<longrightarrow> z \<in> T"
unfolding open_dist by fast
(* choose point between x and y, within distance r of y. *)
define k where "k = min 1 (r / (2 * dist x y))"
define z where "z = y + scaleR k (x - y)"
have z_def2: "z = x + scaleR (1 - k) (y - x)"
unfolding z_def by (simp add: algebra_simps)
have "dist z y < r"
unfolding z_def k_def using \<open>0 < r\<close>
by (simp add: dist_norm min_def)
then have "z \<in> T"
using \<open>\<forall>z. dist z y < r \<longrightarrow> z \<in> T\<close> by simp
have "dist x z < dist x y"
unfolding z_def2 dist_norm
apply (simp add: norm_minus_commute)
apply (simp only: dist_norm [symmetric])
apply (subgoal_tac "\<bar>1 - k\<bar> * dist x y < 1 * dist x y", simp)
apply (rule mult_strict_right_mono)
apply (simp add: k_def \<open>0 < r\<close> \<open>x \<noteq> y\<close>)
apply (simp add: \<open>x \<noteq> y\<close>)
done
then have "z \<in> ball x (dist x y)"
by simp
have "z \<noteq> y"
unfolding z_def k_def using \<open>x \<noteq> y\<close> \<open>0 < r\<close>
by (simp add: min_def)
show "\<exists>z\<in>ball x (dist x y). z \<in> T \<and> z \<noteq> y"
using \<open>z \<in> ball x (dist x y)\<close> \<open>z \<in> T\<close> \<open>z \<noteq> y\<close>
by fast
qed
subsection \<open>Balls and Spheres in Normed Spaces\<close>
lemma mem_ball_0 [simp]: "x \<in> ball 0 e \<longleftrightarrow> norm x < e"
for x :: "'a::real_normed_vector"
by (simp add: dist_norm)
lemma mem_cball_0 [simp]: "x \<in> cball 0 e \<longleftrightarrow> norm x \<le> e"
for x :: "'a::real_normed_vector"
by (simp add: dist_norm)
lemma closure_ball [simp]:
fixes x :: "'a::real_normed_vector"
shows "0 < e \<Longrightarrow> closure (ball x e) = cball x e"
apply (rule equalityI)
apply (rule closure_minimal)
apply (rule ball_subset_cball)
apply (rule closed_cball)
apply (rule subsetI, rename_tac y)
apply (simp add: le_less [where 'a=real])
apply (erule disjE)
apply (rule subsetD [OF closure_subset], simp)
apply (simp add: closure_def, clarify)
apply (rule closure_ball_lemma)
apply simp
done
lemma mem_sphere_0 [simp]: "x \<in> sphere 0 e \<longleftrightarrow> norm x = e"
for x :: "'a::real_normed_vector"
by (simp add: dist_norm)
(* In a trivial vector space, this fails for e = 0. *)
lemma interior_cball [simp]:
fixes x :: "'a::{real_normed_vector, perfect_space}"
shows "interior (cball x e) = ball x e"
proof (cases "e \<ge> 0")
case False note cs = this
from cs have null: "ball x e = {}"
using ball_empty[of e x] by auto
moreover
have "cball x e = {}"
proof (rule equals0I)
fix y
assume "y \<in> cball x e"
then show False
by (metis ball_eq_empty null cs dist_eq_0_iff dist_le_zero_iff empty_subsetI mem_cball
subset_antisym subset_ball)
qed
then have "interior (cball x e) = {}"
using interior_empty by auto
ultimately show ?thesis by blast
next
case True note cs = this
have "ball x e \<subseteq> cball x e"
using ball_subset_cball by auto
moreover
{
fix S y
assume as: "S \<subseteq> cball x e" "open S" "y\<in>S"
then obtain d where "d>0" and d: "\<forall>x'. dist x' y < d \<longrightarrow> x' \<in> S"
unfolding open_dist by blast
then obtain xa where xa_y: "xa \<noteq> y" and xa: "dist xa y < d"
using perfect_choose_dist [of d] by auto
have "xa \<in> S"
using d[THEN spec[where x = xa]]
using xa by (auto simp: dist_commute)
then have xa_cball: "xa \<in> cball x e"
using as(1) by auto
then have "y \<in> ball x e"
proof (cases "x = y")
case True
then have "e > 0" using cs order.order_iff_strict xa_cball xa_y by fastforce
then show "y \<in> ball x e"
using \<open>x = y \<close> by simp
next
case False
have "dist (y + (d / 2 / dist y x) *\<^sub>R (y - x)) y < d"
unfolding dist_norm
using \<open>d>0\<close> norm_ge_zero[of "y - x"] \<open>x \<noteq> y\<close> by auto
then have *: "y + (d / 2 / dist y x) *\<^sub>R (y - x) \<in> cball x e"
using d as(1)[unfolded subset_eq] by blast
have "y - x \<noteq> 0" using \<open>x \<noteq> y\<close> by auto
hence **:"d / (2 * norm (y - x)) > 0"
unfolding zero_less_norm_iff[symmetric] using \<open>d>0\<close> by auto
have "dist (y + (d / 2 / dist y x) *\<^sub>R (y - x)) x =
norm (y + (d / (2 * norm (y - x))) *\<^sub>R y - (d / (2 * norm (y - x))) *\<^sub>R x - x)"
by (auto simp: dist_norm algebra_simps)
also have "\<dots> = norm ((1 + d / (2 * norm (y - x))) *\<^sub>R (y - x))"
by (auto simp: algebra_simps)
also have "\<dots> = \<bar>1 + d / (2 * norm (y - x))\<bar> * norm (y - x)"
using ** by auto
also have "\<dots> = (dist y x) + d/2"
using ** by (auto simp: distrib_right dist_norm)
finally have "e \<ge> dist x y +d/2"
using *[unfolded mem_cball] by (auto simp: dist_commute)
then show "y \<in> ball x e"
unfolding mem_ball using \<open>d>0\<close> by auto
qed
}
then have "\<forall>S \<subseteq> cball x e. open S \<longrightarrow> S \<subseteq> ball x e"
by auto
ultimately show ?thesis
using interior_unique[of "ball x e" "cball x e"]
using open_ball[of x e]
by auto
qed
lemma frontier_ball [simp]:
fixes a :: "'a::real_normed_vector"
shows "0 < e \<Longrightarrow> frontier (ball a e) = sphere a e"
by (force simp: frontier_def)
lemma frontier_cball [simp]:
fixes a :: "'a::{real_normed_vector, perfect_space}"
shows "frontier (cball a e) = sphere a e"
by (force simp: frontier_def)
corollary compact_sphere [simp]:
fixes a :: "'a::{real_normed_vector,perfect_space,heine_borel}"
shows "compact (sphere a r)"
using compact_frontier [of "cball a r"] by simp
corollary bounded_sphere [simp]:
fixes a :: "'a::{real_normed_vector,perfect_space,heine_borel}"
shows "bounded (sphere a r)"
by (simp add: compact_imp_bounded)
corollary closed_sphere [simp]:
fixes a :: "'a::{real_normed_vector,perfect_space,heine_borel}"
shows "closed (sphere a r)"
by (simp add: compact_imp_closed)
lemma image_add_ball [simp]:
fixes a :: "'a::real_normed_vector"
shows "(+) b ` ball a r = ball (a+b) r"
apply (intro equalityI subsetI)
apply (force simp: dist_norm)
apply (rule_tac x="x-b" in image_eqI)
apply (auto simp: dist_norm algebra_simps)
done
lemma image_add_cball [simp]:
fixes a :: "'a::real_normed_vector"
shows "(+) b ` cball a r = cball (a+b) r"
apply (intro equalityI subsetI)
apply (force simp: dist_norm)
apply (rule_tac x="x-b" in image_eqI)
apply (auto simp: dist_norm algebra_simps)
done
subsection\<^marker>\<open>tag unimportant\<close> \<open>Various Lemmas on Normed Algebras\<close>
lemma closed_of_nat_image: "closed (of_nat ` A :: 'a::real_normed_algebra_1 set)"
by (rule discrete_imp_closed[of 1]) (auto simp: dist_of_nat)
lemma closed_of_int_image: "closed (of_int ` A :: 'a::real_normed_algebra_1 set)"
by (rule discrete_imp_closed[of 1]) (auto simp: dist_of_int)
lemma closed_Nats [simp]: "closed (\<nat> :: 'a :: real_normed_algebra_1 set)"
unfolding Nats_def by (rule closed_of_nat_image)
lemma closed_Ints [simp]: "closed (\<int> :: 'a :: real_normed_algebra_1 set)"
unfolding Ints_def by (rule closed_of_int_image)
lemma closed_subset_Ints:
fixes A :: "'a :: real_normed_algebra_1 set"
assumes "A \<subseteq> \<int>"
shows "closed A"
proof (intro discrete_imp_closed[OF zero_less_one] ballI impI, goal_cases)
case (1 x y)
with assms have "x \<in> \<int>" and "y \<in> \<int>" by auto
with \<open>dist y x < 1\<close> show "y = x"
by (auto elim!: Ints_cases simp: dist_of_int)
qed
subsection \<open>Filters\<close>
definition indirection :: "'a::real_normed_vector \<Rightarrow> 'a \<Rightarrow> 'a filter" (infixr "indirection" 70)
where "a indirection v = at a within {b. \<exists>c\<ge>0. b - a = scaleR c v}"
subsection \<open>Trivial Limits\<close>
lemma trivial_limit_at_infinity:
"\<not> trivial_limit (at_infinity :: ('a::{real_normed_vector,perfect_space}) filter)"
unfolding trivial_limit_def eventually_at_infinity
apply clarsimp
apply (subgoal_tac "\<exists>x::'a. x \<noteq> 0", clarify)
apply (rule_tac x="scaleR (b / norm x) x" in exI, simp)
apply (cut_tac islimpt_UNIV [of "0::'a", unfolded islimpt_def])
apply (drule_tac x=UNIV in spec, simp)
done
lemma at_within_ball_bot_iff:
fixes x y :: "'a::{real_normed_vector,perfect_space}"
shows "at x within ball y r = bot \<longleftrightarrow> (r=0 \<or> x \<notin> cball y r)"
unfolding trivial_limit_within
apply (auto simp add:trivial_limit_within islimpt_ball )
by (metis le_less_trans less_eq_real_def zero_le_dist)
subsection \<open>Limits\<close>
proposition Lim_at_infinity: "(f \<longlongrightarrow> l) at_infinity \<longleftrightarrow> (\<forall>e>0. \<exists>b. \<forall>x. norm x \<ge> b \<longrightarrow> dist (f x) l < e)"
by (auto simp: tendsto_iff eventually_at_infinity)
corollary Lim_at_infinityI [intro?]:
assumes "\<And>e. e > 0 \<Longrightarrow> \<exists>B. \<forall>x. norm x \<ge> B \<longrightarrow> dist (f x) l \<le> e"
shows "(f \<longlongrightarrow> l) at_infinity"
apply (simp add: Lim_at_infinity, clarify)
apply (rule ex_forward [OF assms [OF half_gt_zero]], auto)
done
lemma Lim_transform_within_set_eq:
fixes a l :: "'a::real_normed_vector"
shows "eventually (\<lambda>x. x \<in> s \<longleftrightarrow> x \<in> t) (at a)
\<Longrightarrow> ((f \<longlongrightarrow> l) (at a within s) \<longleftrightarrow> (f \<longlongrightarrow> l) (at a within t))"
by (force intro: Lim_transform_within_set elim: eventually_mono)
lemma Lim_null:
fixes f :: "'a \<Rightarrow> 'b::real_normed_vector"
shows "(f \<longlongrightarrow> l) net \<longleftrightarrow> ((\<lambda>x. f(x) - l) \<longlongrightarrow> 0) net"
by (simp add: Lim dist_norm)
lemma Lim_null_comparison:
fixes f :: "'a \<Rightarrow> 'b::real_normed_vector"
assumes "eventually (\<lambda>x. norm (f x) \<le> g x) net" "(g \<longlongrightarrow> 0) net"
shows "(f \<longlongrightarrow> 0) net"
using assms(2)
proof (rule metric_tendsto_imp_tendsto)
show "eventually (\<lambda>x. dist (f x) 0 \<le> dist (g x) 0) net"
using assms(1) by (rule eventually_mono) (simp add: dist_norm)
qed
lemma Lim_transform_bound:
fixes f :: "'a \<Rightarrow> 'b::real_normed_vector"
and g :: "'a \<Rightarrow> 'c::real_normed_vector"
assumes "eventually (\<lambda>n. norm (f n) \<le> norm (g n)) net"
and "(g \<longlongrightarrow> 0) net"
shows "(f \<longlongrightarrow> 0) net"
using assms(1) tendsto_norm_zero [OF assms(2)]
by (rule Lim_null_comparison)
lemma lim_null_mult_right_bounded:
fixes f :: "'a \<Rightarrow> 'b::real_normed_div_algebra"
assumes f: "(f \<longlongrightarrow> 0) F" and g: "eventually (\<lambda>x. norm(g x) \<le> B) F"
shows "((\<lambda>z. f z * g z) \<longlongrightarrow> 0) F"
proof -
have *: "((\<lambda>x. norm (f x) * B) \<longlongrightarrow> 0) F"
by (simp add: f tendsto_mult_left_zero tendsto_norm_zero)
have "((\<lambda>x. norm (f x) * norm (g x)) \<longlongrightarrow> 0) F"
apply (rule Lim_null_comparison [OF _ *])
apply (simp add: eventually_mono [OF g] mult_left_mono)
done
then show ?thesis
by (subst tendsto_norm_zero_iff [symmetric]) (simp add: norm_mult)
qed
lemma lim_null_mult_left_bounded:
fixes f :: "'a \<Rightarrow> 'b::real_normed_div_algebra"
assumes g: "eventually (\<lambda>x. norm(g x) \<le> B) F" and f: "(f \<longlongrightarrow> 0) F"
shows "((\<lambda>z. g z * f z) \<longlongrightarrow> 0) F"
proof -
have *: "((\<lambda>x. B * norm (f x)) \<longlongrightarrow> 0) F"
by (simp add: f tendsto_mult_right_zero tendsto_norm_zero)
have "((\<lambda>x. norm (g x) * norm (f x)) \<longlongrightarrow> 0) F"
apply (rule Lim_null_comparison [OF _ *])
apply (simp add: eventually_mono [OF g] mult_right_mono)
done
then show ?thesis
by (subst tendsto_norm_zero_iff [symmetric]) (simp add: norm_mult)
qed
lemma lim_null_scaleR_bounded:
assumes f: "(f \<longlongrightarrow> 0) net" and gB: "eventually (\<lambda>a. f a = 0 \<or> norm(g a) \<le> B) net"
shows "((\<lambda>n. f n *\<^sub>R g n) \<longlongrightarrow> 0) net"
proof
fix \<epsilon>::real
assume "0 < \<epsilon>"
then have B: "0 < \<epsilon> / (abs B + 1)" by simp
have *: "\<bar>f x\<bar> * norm (g x) < \<epsilon>" if f: "\<bar>f x\<bar> * (\<bar>B\<bar> + 1) < \<epsilon>" and g: "norm (g x) \<le> B" for x
proof -
have "\<bar>f x\<bar> * norm (g x) \<le> \<bar>f x\<bar> * B"
by (simp add: mult_left_mono g)
also have "\<dots> \<le> \<bar>f x\<bar> * (\<bar>B\<bar> + 1)"
by (simp add: mult_left_mono)
also have "\<dots> < \<epsilon>"
by (rule f)
finally show ?thesis .
qed
show "\<forall>\<^sub>F x in net. dist (f x *\<^sub>R g x) 0 < \<epsilon>"
apply (rule eventually_mono [OF eventually_conj [OF tendstoD [OF f B] gB] ])
apply (auto simp: \<open>0 < \<epsilon>\<close> divide_simps * split: if_split_asm)
done
qed
lemma Lim_norm_ubound:
fixes f :: "'a \<Rightarrow> 'b::real_normed_vector"
assumes "\<not>(trivial_limit net)" "(f \<longlongrightarrow> l) net" "eventually (\<lambda>x. norm(f x) \<le> e) net"
shows "norm(l) \<le> e"
using assms by (fast intro: tendsto_le tendsto_intros)
lemma Lim_norm_lbound:
fixes f :: "'a \<Rightarrow> 'b::real_normed_vector"
assumes "\<not> trivial_limit net"
and "(f \<longlongrightarrow> l) net"
and "eventually (\<lambda>x. e \<le> norm (f x)) net"
shows "e \<le> norm l"
using assms by (fast intro: tendsto_le tendsto_intros)
text\<open>Limit under bilinear function\<close>
lemma Lim_bilinear:
assumes "(f \<longlongrightarrow> l) net"
and "(g \<longlongrightarrow> m) net"
and "bounded_bilinear h"
shows "((\<lambda>x. h (f x) (g x)) \<longlongrightarrow> (h l m)) net"
using \<open>bounded_bilinear h\<close> \<open>(f \<longlongrightarrow> l) net\<close> \<open>(g \<longlongrightarrow> m) net\<close>
by (rule bounded_bilinear.tendsto)
lemma Lim_at_zero:
fixes a :: "'a::real_normed_vector"
and l :: "'b::topological_space"
shows "(f \<longlongrightarrow> l) (at a) \<longleftrightarrow> ((\<lambda>x. f(a + x)) \<longlongrightarrow> l) (at 0)"
using LIM_offset_zero LIM_offset_zero_cancel ..
subsection\<^marker>\<open>tag unimportant\<close> \<open>Limit Point of Filter\<close>
lemma netlimit_at_vector:
fixes a :: "'a::real_normed_vector"
shows "netlimit (at a) = a"
proof (cases "\<exists>x. x \<noteq> a")
case True then obtain x where x: "x \<noteq> a" ..
have "\<not> trivial_limit (at a)"
unfolding trivial_limit_def eventually_at dist_norm
apply clarsimp
apply (rule_tac x="a + scaleR (d / 2) (sgn (x - a))" in exI)
apply (simp add: norm_sgn sgn_zero_iff x)
done
then show ?thesis
by (rule Lim_ident_at [of a UNIV])
qed simp
subsection \<open>Boundedness\<close>
lemma continuous_on_closure_norm_le:
fixes f :: "'a::metric_space \<Rightarrow> 'b::real_normed_vector"
assumes "continuous_on (closure s) f"
and "\<forall>y \<in> s. norm(f y) \<le> b"
and "x \<in> (closure s)"
shows "norm (f x) \<le> b"
proof -
have *: "f ` s \<subseteq> cball 0 b"
using assms(2)[unfolded mem_cball_0[symmetric]] by auto
show ?thesis
by (meson "*" assms(1) assms(3) closed_cball image_closure_subset image_subset_iff mem_cball_0)
qed
lemma bounded_pos: "bounded S \<longleftrightarrow> (\<exists>b>0. \<forall>x\<in> S. norm x \<le> b)"
unfolding bounded_iff
by (meson less_imp_le not_le order_trans zero_less_one)
lemma bounded_pos_less: "bounded S \<longleftrightarrow> (\<exists>b>0. \<forall>x\<in> S. norm x < b)"
apply (simp add: bounded_pos)
apply (safe; rule_tac x="b+1" in exI; force)
done
lemma Bseq_eq_bounded:
fixes f :: "nat \<Rightarrow> 'a::real_normed_vector"
shows "Bseq f \<longleftrightarrow> bounded (range f)"
unfolding Bseq_def bounded_pos by auto
lemma bounded_linear_image:
assumes "bounded S"
and "bounded_linear f"
shows "bounded (f ` S)"
proof -
from assms(1) obtain b where "b > 0" and b: "\<forall>x\<in>S. norm x \<le> b"
unfolding bounded_pos by auto
from assms(2) obtain B where B: "B > 0" "\<forall>x. norm (f x) \<le> B * norm x"
using bounded_linear.pos_bounded by (auto simp: ac_simps)
show ?thesis
unfolding bounded_pos
proof (intro exI, safe)
show "norm (f x) \<le> B * b" if "x \<in> S" for x
by (meson B b less_imp_le mult_left_mono order_trans that)
qed (use \<open>b > 0\<close> \<open>B > 0\<close> in auto)
qed
lemma bounded_scaling:
fixes S :: "'a::real_normed_vector set"
shows "bounded S \<Longrightarrow> bounded ((\<lambda>x. c *\<^sub>R x) ` S)"
apply (rule bounded_linear_image, assumption)
apply (rule bounded_linear_scaleR_right)
done
lemma bounded_scaleR_comp:
fixes f :: "'a \<Rightarrow> 'b::real_normed_vector"
assumes "bounded (f ` S)"
shows "bounded ((\<lambda>x. r *\<^sub>R f x) ` S)"
using bounded_scaling[of "f ` S" r] assms
by (auto simp: image_image)
lemma bounded_translation:
fixes S :: "'a::real_normed_vector set"
assumes "bounded S"
shows "bounded ((\<lambda>x. a + x) ` S)"
proof -
from assms obtain b where b: "b > 0" "\<forall>x\<in>S. norm x \<le> b"
unfolding bounded_pos by auto
{
fix x
assume "x \<in> S"
then have "norm (a + x) \<le> b + norm a"
using norm_triangle_ineq[of a x] b by auto
}
then show ?thesis
unfolding bounded_pos
using norm_ge_zero[of a] b(1) and add_strict_increasing[of b 0 "norm a"]
by (auto intro!: exI[of _ "b + norm a"])
qed
lemma bounded_translation_minus:
fixes S :: "'a::real_normed_vector set"
shows "bounded S \<Longrightarrow> bounded ((\<lambda>x. x - a) ` S)"
using bounded_translation [of S "-a"] by simp
lemma bounded_uminus [simp]:
fixes X :: "'a::real_normed_vector set"
shows "bounded (uminus ` X) \<longleftrightarrow> bounded X"
by (auto simp: bounded_def dist_norm; rule_tac x="-x" in exI; force simp: add.commute norm_minus_commute)
lemma uminus_bounded_comp [simp]:
fixes f :: "'a \<Rightarrow> 'b::real_normed_vector"
shows "bounded ((\<lambda>x. - f x) ` S) \<longleftrightarrow> bounded (f ` S)"
using bounded_uminus[of "f ` S"]
by (auto simp: image_image)
lemma bounded_plus_comp:
fixes f g::"'a \<Rightarrow> 'b::real_normed_vector"
assumes "bounded (f ` S)"
assumes "bounded (g ` S)"
shows "bounded ((\<lambda>x. f x + g x) ` S)"
proof -
{
fix B C
assume "\<And>x. x\<in>S \<Longrightarrow> norm (f x) \<le> B" "\<And>x. x\<in>S \<Longrightarrow> norm (g x) \<le> C"
then have "\<And>x. x \<in> S \<Longrightarrow> norm (f x + g x) \<le> B + C"
by (auto intro!: norm_triangle_le add_mono)
} then show ?thesis
using assms by (fastforce simp: bounded_iff)
qed
lemma bounded_plus:
fixes S ::"'a::real_normed_vector set"
assumes "bounded S" "bounded T"
shows "bounded ((\<lambda>(x,y). x + y) ` (S \<times> T))"
using bounded_plus_comp [of fst "S \<times> T" snd] assms
by (auto simp: split_def split: if_split_asm)
lemma bounded_minus_comp:
"bounded (f ` S) \<Longrightarrow> bounded (g ` S) \<Longrightarrow> bounded ((\<lambda>x. f x - g x) ` S)"
for f g::"'a \<Rightarrow> 'b::real_normed_vector"
using bounded_plus_comp[of "f" S "\<lambda>x. - g x"]
by auto
lemma bounded_minus:
fixes S ::"'a::real_normed_vector set"
assumes "bounded S" "bounded T"
shows "bounded ((\<lambda>(x,y). x - y) ` (S \<times> T))"
using bounded_minus_comp [of fst "S \<times> T" snd] assms
by (auto simp: split_def split: if_split_asm)
lemma not_bounded_UNIV[simp]:
"\<not> bounded (UNIV :: 'a::{real_normed_vector, perfect_space} set)"
proof (auto simp: bounded_pos not_le)
obtain x :: 'a where "x \<noteq> 0"
using perfect_choose_dist [OF zero_less_one] by fast
fix b :: real
assume b: "b >0"
have b1: "b +1 \<ge> 0"
using b by simp
with \<open>x \<noteq> 0\<close> have "b < norm (scaleR (b + 1) (sgn x))"
by (simp add: norm_sgn)
then show "\<exists>x::'a. b < norm x" ..
qed
corollary cobounded_imp_unbounded:
fixes S :: "'a::{real_normed_vector, perfect_space} set"
shows "bounded (- S) \<Longrightarrow> \<not> bounded S"
using bounded_Un [of S "-S"] by (simp add: sup_compl_top)
subsection\<^marker>\<open>tag unimportant\<close>\<open>Relations among convergence and absolute convergence for power series\<close>
lemma summable_imp_bounded:
fixes f :: "nat \<Rightarrow> 'a::real_normed_vector"
shows "summable f \<Longrightarrow> bounded (range f)"
by (frule summable_LIMSEQ_zero) (simp add: convergent_imp_bounded)
lemma summable_imp_sums_bounded:
"summable f \<Longrightarrow> bounded (range (\<lambda>n. sum f {..<n}))"
by (auto simp: summable_def sums_def dest: convergent_imp_bounded)
lemma power_series_conv_imp_absconv_weak:
fixes a:: "nat \<Rightarrow> 'a::{real_normed_div_algebra,banach}" and w :: 'a
assumes sum: "summable (\<lambda>n. a n * z ^ n)" and no: "norm w < norm z"
shows "summable (\<lambda>n. of_real(norm(a n)) * w ^ n)"
proof -
obtain M where M: "\<And>x. norm (a x * z ^ x) \<le> M"
using summable_imp_bounded [OF sum] by (force simp: bounded_iff)
then have *: "summable (\<lambda>n. norm (a n) * norm w ^ n)"
by (rule_tac M=M in Abel_lemma) (auto simp: norm_mult norm_power intro: no)
show ?thesis
apply (rule series_comparison_complex [of "(\<lambda>n. of_real(norm(a n) * norm w ^ n))"])
apply (simp only: summable_complex_of_real *)
apply (auto simp: norm_mult norm_power)
done
qed
subsection \<open>Normed spaces with the Heine-Borel property\<close>
lemma not_compact_UNIV[simp]:
fixes s :: "'a::{real_normed_vector,perfect_space,heine_borel} set"
shows "\<not> compact (UNIV::'a set)"
by (simp add: compact_eq_bounded_closed)
lemma not_compact_space_euclideanreal [simp]: "\<not> compact_space euclideanreal"
by (simp add: compact_space_def)
text\<open>Representing sets as the union of a chain of compact sets.\<close>
lemma closed_Union_compact_subsets:
fixes S :: "'a::{heine_borel,real_normed_vector} set"
assumes "closed S"
obtains F where "\<And>n. compact(F n)" "\<And>n. F n \<subseteq> S" "\<And>n. F n \<subseteq> F(Suc n)"
"(\<Union>n. F n) = S" "\<And>K. \<lbrakk>compact K; K \<subseteq> S\<rbrakk> \<Longrightarrow> \<exists>N. \<forall>n \<ge> N. K \<subseteq> F n"
proof
show "compact (S \<inter> cball 0 (of_nat n))" for n
using assms compact_eq_bounded_closed by auto
next
show "(\<Union>n. S \<inter> cball 0 (real n)) = S"
by (auto simp: real_arch_simple)
next
fix K :: "'a set"
assume "compact K" "K \<subseteq> S"
then obtain N where "K \<subseteq> cball 0 N"
by (meson bounded_pos mem_cball_0 compact_imp_bounded subsetI)
then show "\<exists>N. \<forall>n\<ge>N. K \<subseteq> S \<inter> cball 0 (real n)"
by (metis of_nat_le_iff Int_subset_iff \<open>K \<subseteq> S\<close> real_arch_simple subset_cball subset_trans)
qed auto
subsection \<open>Intersecting chains of compact sets and the Baire property\<close>
proposition bounded_closed_chain:
fixes \<F> :: "'a::heine_borel set set"
assumes "B \<in> \<F>" "bounded B" and \<F>: "\<And>S. S \<in> \<F> \<Longrightarrow> closed S" and "{} \<notin> \<F>"
and chain: "\<And>S T. S \<in> \<F> \<and> T \<in> \<F> \<Longrightarrow> S \<subseteq> T \<or> T \<subseteq> S"
shows "\<Inter>\<F> \<noteq> {}"
proof -
have "B \<inter> \<Inter>\<F> \<noteq> {}"
proof (rule compact_imp_fip)
show "compact B" "\<And>T. T \<in> \<F> \<Longrightarrow> closed T"
by (simp_all add: assms compact_eq_bounded_closed)
show "\<lbrakk>finite \<G>; \<G> \<subseteq> \<F>\<rbrakk> \<Longrightarrow> B \<inter> \<Inter>\<G> \<noteq> {}" for \<G>
proof (induction \<G> rule: finite_induct)
case empty
with assms show ?case by force
next
case (insert U \<G>)
then have "U \<in> \<F>" and ne: "B \<inter> \<Inter>\<G> \<noteq> {}" by auto
then consider "B \<subseteq> U" | "U \<subseteq> B"
using \<open>B \<in> \<F>\<close> chain by blast
then show ?case
proof cases
case 1
then show ?thesis
using Int_left_commute ne by auto
next
case 2
have "U \<noteq> {}"
using \<open>U \<in> \<F>\<close> \<open>{} \<notin> \<F>\<close> by blast
moreover
have False if "\<And>x. x \<in> U \<Longrightarrow> \<exists>Y\<in>\<G>. x \<notin> Y"
proof -
have "\<And>x. x \<in> U \<Longrightarrow> \<exists>Y\<in>\<G>. Y \<subseteq> U"
by (metis chain contra_subsetD insert.prems insert_subset that)
then obtain Y where "Y \<in> \<G>" "Y \<subseteq> U"
by (metis all_not_in_conv \<open>U \<noteq> {}\<close>)
moreover obtain x where "x \<in> \<Inter>\<G>"
by (metis Int_emptyI ne)
ultimately show ?thesis
by (metis Inf_lower subset_eq that)
qed
with 2 show ?thesis
by blast
qed
qed
qed
then show ?thesis by blast
qed
corollary compact_chain:
fixes \<F> :: "'a::heine_borel set set"
assumes "\<And>S. S \<in> \<F> \<Longrightarrow> compact S" "{} \<notin> \<F>"
"\<And>S T. S \<in> \<F> \<and> T \<in> \<F> \<Longrightarrow> S \<subseteq> T \<or> T \<subseteq> S"
shows "\<Inter> \<F> \<noteq> {}"
proof (cases "\<F> = {}")
case True
then show ?thesis by auto
next
case False
show ?thesis
by (metis False all_not_in_conv assms compact_imp_bounded compact_imp_closed bounded_closed_chain)
qed
lemma compact_nest:
fixes F :: "'a::linorder \<Rightarrow> 'b::heine_borel set"
assumes F: "\<And>n. compact(F n)" "\<And>n. F n \<noteq> {}" and mono: "\<And>m n. m \<le> n \<Longrightarrow> F n \<subseteq> F m"
shows "\<Inter>(range F) \<noteq> {}"
proof -
have *: "\<And>S T. S \<in> range F \<and> T \<in> range F \<Longrightarrow> S \<subseteq> T \<or> T \<subseteq> S"
by (metis mono image_iff le_cases)
show ?thesis
apply (rule compact_chain [OF _ _ *])
using F apply (blast intro: dest: *)+
done
qed
text\<open>The Baire property of dense sets\<close>
theorem Baire:
fixes S::"'a::{real_normed_vector,heine_borel} set"
assumes "closed S" "countable \<G>"
and ope: "\<And>T. T \<in> \<G> \<Longrightarrow> openin (top_of_set S) T \<and> S \<subseteq> closure T"
shows "S \<subseteq> closure(\<Inter>\<G>)"
proof (cases "\<G> = {}")
case True
then show ?thesis
using closure_subset by auto
next
let ?g = "from_nat_into \<G>"
case False
then have gin: "?g n \<in> \<G>" for n
by (simp add: from_nat_into)
show ?thesis
proof (clarsimp simp: closure_approachable)
fix x and e::real
assume "x \<in> S" "0 < e"
obtain TF where opeF: "\<And>n. openin (top_of_set S) (TF n)"
and ne: "\<And>n. TF n \<noteq> {}"
and subg: "\<And>n. S \<inter> closure(TF n) \<subseteq> ?g n"
and subball: "\<And>n. closure(TF n) \<subseteq> ball x e"
and decr: "\<And>n. TF(Suc n) \<subseteq> TF n"
proof -
have *: "\<exists>Y. (openin (top_of_set S) Y \<and> Y \<noteq> {} \<and>
S \<inter> closure Y \<subseteq> ?g n \<and> closure Y \<subseteq> ball x e) \<and> Y \<subseteq> U"
if opeU: "openin (top_of_set S) U" and "U \<noteq> {}" and cloU: "closure U \<subseteq> ball x e" for U n
proof -
obtain T where T: "open T" "U = T \<inter> S"
using \<open>openin (top_of_set S) U\<close> by (auto simp: openin_subtopology)
with \<open>U \<noteq> {}\<close> have "T \<inter> closure (?g n) \<noteq> {}"
using gin ope by fastforce
then have "T \<inter> ?g n \<noteq> {}"
using \<open>open T\<close> open_Int_closure_eq_empty by blast
then obtain y where "y \<in> U" "y \<in> ?g n"
using T ope [of "?g n", OF gin] by (blast dest: openin_imp_subset)
moreover have "openin (top_of_set S) (U \<inter> ?g n)"
using gin ope opeU by blast
ultimately obtain d where U: "U \<inter> ?g n \<subseteq> S" and "d > 0" and d: "ball y d \<inter> S \<subseteq> U \<inter> ?g n"
by (force simp: openin_contains_ball)
show ?thesis
proof (intro exI conjI)
show "openin (top_of_set S) (S \<inter> ball y (d/2))"
by (simp add: openin_open_Int)
show "S \<inter> ball y (d/2) \<noteq> {}"
using \<open>0 < d\<close> \<open>y \<in> U\<close> opeU openin_imp_subset by fastforce
have "S \<inter> closure (S \<inter> ball y (d/2)) \<subseteq> S \<inter> closure (ball y (d/2))"
using closure_mono by blast
also have "... \<subseteq> ?g n"
using \<open>d > 0\<close> d by force
finally show "S \<inter> closure (S \<inter> ball y (d/2)) \<subseteq> ?g n" .
have "closure (S \<inter> ball y (d/2)) \<subseteq> S \<inter> ball y d"
proof -
have "closure (ball y (d/2)) \<subseteq> ball y d"
using \<open>d > 0\<close> by auto
then have "closure (S \<inter> ball y (d/2)) \<subseteq> ball y d"
by (meson closure_mono inf.cobounded2 subset_trans)
then show ?thesis
by (simp add: \<open>closed S\<close> closure_minimal)
qed
also have "... \<subseteq> ball x e"
using cloU closure_subset d by blast
finally show "closure (S \<inter> ball y (d/2)) \<subseteq> ball x e" .
show "S \<inter> ball y (d/2) \<subseteq> U"
using ball_divide_subset_numeral d by blast
qed
qed
let ?\<Phi> = "\<lambda>n X. openin (top_of_set S) X \<and> X \<noteq> {} \<and>
S \<inter> closure X \<subseteq> ?g n \<and> closure X \<subseteq> ball x e"
have "closure (S \<inter> ball x (e / 2)) \<subseteq> closure(ball x (e/2))"
by (simp add: closure_mono)
also have "... \<subseteq> ball x e"
using \<open>e > 0\<close> by auto
finally have "closure (S \<inter> ball x (e / 2)) \<subseteq> ball x e" .
moreover have"openin (top_of_set S) (S \<inter> ball x (e / 2))" "S \<inter> ball x (e / 2) \<noteq> {}"
using \<open>0 < e\<close> \<open>x \<in> S\<close> by auto
ultimately obtain Y where Y: "?\<Phi> 0 Y \<and> Y \<subseteq> S \<inter> ball x (e / 2)"
using * [of "S \<inter> ball x (e/2)" 0] by metis
show thesis
proof (rule exE [OF dependent_nat_choice [of ?\<Phi> "\<lambda>n X Y. Y \<subseteq> X"]])
show "\<exists>x. ?\<Phi> 0 x"
using Y by auto
show "\<exists>Y. ?\<Phi> (Suc n) Y \<and> Y \<subseteq> X" if "?\<Phi> n X" for X n
using that by (blast intro: *)
qed (use that in metis)
qed
have "(\<Inter>n. S \<inter> closure (TF n)) \<noteq> {}"
proof (rule compact_nest)
show "\<And>n. compact (S \<inter> closure (TF n))"
by (metis closed_closure subball bounded_subset_ballI compact_eq_bounded_closed closed_Int_compact [OF \<open>closed S\<close>])
show "\<And>n. S \<inter> closure (TF n) \<noteq> {}"
by (metis Int_absorb1 opeF \<open>closed S\<close> closure_eq_empty closure_minimal ne openin_imp_subset)
show "\<And>m n. m \<le> n \<Longrightarrow> S \<inter> closure (TF n) \<subseteq> S \<inter> closure (TF m)"
by (meson closure_mono decr dual_order.refl inf_mono lift_Suc_antimono_le)
qed
moreover have "(\<Inter>n. S \<inter> closure (TF n)) \<subseteq> {y \<in> \<Inter>\<G>. dist y x < e}"
proof (clarsimp, intro conjI)
fix y
assume "y \<in> S" and y: "\<forall>n. y \<in> closure (TF n)"
then show "\<forall>T\<in>\<G>. y \<in> T"
by (metis Int_iff from_nat_into_surj [OF \<open>countable \<G>\<close>] subsetD subg)
show "dist y x < e"
by (metis y dist_commute mem_ball subball subsetCE)
qed
ultimately show "\<exists>y \<in> \<Inter>\<G>. dist y x < e"
by auto
qed
qed
subsection \<open>Continuity\<close>
subsubsection\<^marker>\<open>tag unimportant\<close> \<open>Structural rules for uniform continuity\<close>
lemma (in bounded_linear) uniformly_continuous_on[continuous_intros]:
fixes g :: "_::metric_space \<Rightarrow> _"
assumes "uniformly_continuous_on s g"
shows "uniformly_continuous_on s (\<lambda>x. f (g x))"
using assms unfolding uniformly_continuous_on_sequentially
unfolding dist_norm tendsto_norm_zero_iff diff[symmetric]
by (auto intro: tendsto_zero)
lemma uniformly_continuous_on_dist[continuous_intros]:
fixes f g :: "'a::metric_space \<Rightarrow> 'b::metric_space"
assumes "uniformly_continuous_on s f"
and "uniformly_continuous_on s g"
shows "uniformly_continuous_on s (\<lambda>x. dist (f x) (g x))"
proof -
{
fix a b c d :: 'b
have "\<bar>dist a b - dist c d\<bar> \<le> dist a c + dist b d"
using dist_triangle2 [of a b c] dist_triangle2 [of b c d]
using dist_triangle3 [of c d a] dist_triangle [of a d b]
by arith
} note le = this
{
fix x y
assume f: "(\<lambda>n. dist (f (x n)) (f (y n))) \<longlonglongrightarrow> 0"
assume g: "(\<lambda>n. dist (g (x n)) (g (y n))) \<longlonglongrightarrow> 0"
have "(\<lambda>n. \<bar>dist (f (x n)) (g (x n)) - dist (f (y n)) (g (y n))\<bar>) \<longlonglongrightarrow> 0"
by (rule Lim_transform_bound [OF _ tendsto_add_zero [OF f g]],
simp add: le)
}
then show ?thesis
using assms unfolding uniformly_continuous_on_sequentially
unfolding dist_real_def by simp
qed
lemma uniformly_continuous_on_norm[continuous_intros]:
fixes f :: "'a :: metric_space \<Rightarrow> 'b :: real_normed_vector"
assumes "uniformly_continuous_on s f"
shows "uniformly_continuous_on s (\<lambda>x. norm (f x))"
unfolding norm_conv_dist using assms
by (intro uniformly_continuous_on_dist uniformly_continuous_on_const)
lemma uniformly_continuous_on_cmul[continuous_intros]:
fixes f :: "'a::metric_space \<Rightarrow> 'b::real_normed_vector"
assumes "uniformly_continuous_on s f"
shows "uniformly_continuous_on s (\<lambda>x. c *\<^sub>R f(x))"
using bounded_linear_scaleR_right assms
by (rule bounded_linear.uniformly_continuous_on)
lemma dist_minus:
fixes x y :: "'a::real_normed_vector"
shows "dist (- x) (- y) = dist x y"
unfolding dist_norm minus_diff_minus norm_minus_cancel ..
lemma uniformly_continuous_on_minus[continuous_intros]:
fixes f :: "'a::metric_space \<Rightarrow> 'b::real_normed_vector"
shows "uniformly_continuous_on s f \<Longrightarrow> uniformly_continuous_on s (\<lambda>x. - f x)"
unfolding uniformly_continuous_on_def dist_minus .
lemma uniformly_continuous_on_add[continuous_intros]:
fixes f g :: "'a::metric_space \<Rightarrow> 'b::real_normed_vector"
assumes "uniformly_continuous_on s f"
and "uniformly_continuous_on s g"
shows "uniformly_continuous_on s (\<lambda>x. f x + g x)"
using assms
unfolding uniformly_continuous_on_sequentially
unfolding dist_norm tendsto_norm_zero_iff add_diff_add
by (auto intro: tendsto_add_zero)
lemma uniformly_continuous_on_diff[continuous_intros]:
fixes f :: "'a::metric_space \<Rightarrow> 'b::real_normed_vector"
assumes "uniformly_continuous_on s f"
and "uniformly_continuous_on s g"
shows "uniformly_continuous_on s (\<lambda>x. f x - g x)"
using assms uniformly_continuous_on_add [of s f "- g"]
by (simp add: fun_Compl_def uniformly_continuous_on_minus)
subsection\<^marker>\<open>tag unimportant\<close> \<open>Topological properties of linear functions\<close>
lemma linear_lim_0:
assumes "bounded_linear f"
shows "(f \<longlongrightarrow> 0) (at (0))"
proof -
interpret f: bounded_linear f by fact
have "(f \<longlongrightarrow> f 0) (at 0)"
using tendsto_ident_at by (rule f.tendsto)
then show ?thesis unfolding f.zero .
qed
lemma linear_continuous_at:
assumes "bounded_linear f"
shows "continuous (at a) f"
unfolding continuous_at using assms
apply (rule bounded_linear.tendsto)
apply (rule tendsto_ident_at)
done
lemma linear_continuous_within:
"bounded_linear f \<Longrightarrow> continuous (at x within s) f"
using continuous_at_imp_continuous_within[of x f s] using linear_continuous_at[of f] by auto
lemma linear_continuous_on:
"bounded_linear f \<Longrightarrow> continuous_on s f"
using continuous_at_imp_continuous_on[of s f] using linear_continuous_at[of f] by auto
subsection\<^marker>\<open>tag unimportant\<close> \<open>Arithmetic Preserves Topological Properties\<close>
lemma open_scaling[intro]:
fixes s :: "'a::real_normed_vector set"
assumes "c \<noteq> 0"
and "open s"
shows "open((\<lambda>x. c *\<^sub>R x) ` s)"
proof -
{
fix x
assume "x \<in> s"
then obtain e where "e>0"
and e:"\<forall>x'. dist x' x < e \<longrightarrow> x' \<in> s" using assms(2)[unfolded open_dist, THEN bspec[where x=x]]
by auto
have "e * \<bar>c\<bar> > 0"
using assms(1)[unfolded zero_less_abs_iff[symmetric]] \<open>e>0\<close> by auto
moreover
{
fix y
assume "dist y (c *\<^sub>R x) < e * \<bar>c\<bar>"
then have "norm ((1 / c) *\<^sub>R y - x) < e"
unfolding dist_norm
using norm_scaleR[of c "(1 / c) *\<^sub>R y - x", unfolded scaleR_right_diff_distrib, unfolded scaleR_scaleR] assms(1)
assms(1)[unfolded zero_less_abs_iff[symmetric]] by (simp del:zero_less_abs_iff)
then have "y \<in> (*\<^sub>R) c ` s"
using rev_image_eqI[of "(1 / c) *\<^sub>R y" s y "(*\<^sub>R) c"]
using e[THEN spec[where x="(1 / c) *\<^sub>R y"]]
using assms(1)
unfolding dist_norm scaleR_scaleR
by auto
}
ultimately have "\<exists>e>0. \<forall>x'. dist x' (c *\<^sub>R x) < e \<longrightarrow> x' \<in> (*\<^sub>R) c ` s"
apply (rule_tac x="e * \<bar>c\<bar>" in exI, auto)
done
}
then show ?thesis unfolding open_dist by auto
qed
lemma minus_image_eq_vimage:
fixes A :: "'a::ab_group_add set"
shows "(\<lambda>x. - x) ` A = (\<lambda>x. - x) -` A"
by (auto intro!: image_eqI [where f="\<lambda>x. - x"])
lemma open_negations:
fixes S :: "'a::real_normed_vector set"
shows "open S \<Longrightarrow> open ((\<lambda>x. - x) ` S)"
using open_scaling [of "- 1" S] by simp
lemma open_translation:
fixes S :: "'a::real_normed_vector set"
assumes "open S"
shows "open((\<lambda>x. a + x) ` S)"
proof -
{
fix x
have "continuous (at x) (\<lambda>x. x - a)"
by (intro continuous_diff continuous_ident continuous_const)
}
moreover have "{x. x - a \<in> S} = (+) a ` S"
by force
ultimately show ?thesis
by (metis assms continuous_open_vimage vimage_def)
qed
lemma open_neg_translation:
fixes s :: "'a::real_normed_vector set"
assumes "open s"
shows "open((\<lambda>x. a - x) ` s)"
using open_translation[OF open_negations[OF assms], of a]
by (auto simp: image_image)
lemma open_affinity:
fixes S :: "'a::real_normed_vector set"
assumes "open S" "c \<noteq> 0"
shows "open ((\<lambda>x. a + c *\<^sub>R x) ` S)"
proof -
have *: "(\<lambda>x. a + c *\<^sub>R x) = (\<lambda>x. a + x) \<circ> (\<lambda>x. c *\<^sub>R x)"
unfolding o_def ..
have "(+) a ` (*\<^sub>R) c ` S = ((+) a \<circ> (*\<^sub>R) c) ` S"
by auto
then show ?thesis
using assms open_translation[of "(*\<^sub>R) c ` S" a]
unfolding *
by auto
qed
lemma interior_translation:
"interior ((+) a ` S) = (+) a ` (interior S)" for S :: "'a::real_normed_vector set"
proof (rule set_eqI, rule)
fix x
assume "x \<in> interior ((+) a ` S)"
then obtain e where "e > 0" and e: "ball x e \<subseteq> (+) a ` S"
unfolding mem_interior by auto
then have "ball (x - a) e \<subseteq> S"
unfolding subset_eq Ball_def mem_ball dist_norm
by (auto simp: diff_diff_eq)
then show "x \<in> (+) a ` interior S"
unfolding image_iff
apply (rule_tac x="x - a" in bexI)
unfolding mem_interior
using \<open>e > 0\<close>
apply auto
done
next
fix x
assume "x \<in> (+) a ` interior S"
then obtain y e where "e > 0" and e: "ball y e \<subseteq> S" and y: "x = a + y"
unfolding image_iff Bex_def mem_interior by auto
{
fix z
have *: "a + y - z = y + a - z" by auto
assume "z \<in> ball x e"
then have "z - a \<in> S"
using e[unfolded subset_eq, THEN bspec[where x="z - a"]]
unfolding mem_ball dist_norm y group_add_class.diff_diff_eq2 *
by auto
then have "z \<in> (+) a ` S"
unfolding image_iff by (auto intro!: bexI[where x="z - a"])
}
then have "ball x e \<subseteq> (+) a ` S"
unfolding subset_eq by auto
then show "x \<in> interior ((+) a ` S)"
unfolding mem_interior using \<open>e > 0\<close> by auto
qed
lemma interior_translation_subtract:
"interior ((\<lambda>x. x - a) ` S) = (\<lambda>x. x - a) ` interior S" for S :: "'a::real_normed_vector set"
using interior_translation [of "- a"] by (simp cong: image_cong_simp)
lemma compact_scaling:
fixes s :: "'a::real_normed_vector set"
assumes "compact s"
shows "compact ((\<lambda>x. c *\<^sub>R x) ` s)"
proof -
let ?f = "\<lambda>x. scaleR c x"
have *: "bounded_linear ?f" by (rule bounded_linear_scaleR_right)
show ?thesis
using compact_continuous_image[of s ?f] continuous_at_imp_continuous_on[of s ?f]
using linear_continuous_at[OF *] assms
by auto
qed
lemma compact_negations:
fixes s :: "'a::real_normed_vector set"
assumes "compact s"
shows "compact ((\<lambda>x. - x) ` s)"
using compact_scaling [OF assms, of "- 1"] by auto
lemma compact_sums:
fixes s t :: "'a::real_normed_vector set"
assumes "compact s"
and "compact t"
shows "compact {x + y | x y. x \<in> s \<and> y \<in> t}"
proof -
have *: "{x + y | x y. x \<in> s \<and> y \<in> t} = (\<lambda>z. fst z + snd z) ` (s \<times> t)"
apply auto
unfolding image_iff
apply (rule_tac x="(xa, y)" in bexI)
apply auto
done
have "continuous_on (s \<times> t) (\<lambda>z. fst z + snd z)"
unfolding continuous_on by (rule ballI) (intro tendsto_intros)
then show ?thesis
unfolding * using compact_continuous_image compact_Times [OF assms] by auto
qed
lemma compact_differences:
fixes s t :: "'a::real_normed_vector set"
assumes "compact s"
and "compact t"
shows "compact {x - y | x y. x \<in> s \<and> y \<in> t}"
proof-
have "{x - y | x y. x\<in>s \<and> y \<in> t} = {x + y | x y. x \<in> s \<and> y \<in> (uminus ` t)}"
apply auto
apply (rule_tac x= xa in exI, auto)
done
then show ?thesis
using compact_sums[OF assms(1) compact_negations[OF assms(2)]] by auto
qed
lemma compact_translation:
"compact ((+) a ` s)" if "compact s" for s :: "'a::real_normed_vector set"
proof -
have "{x + y |x y. x \<in> s \<and> y \<in> {a}} = (\<lambda>x. a + x) ` s"
by auto
then show ?thesis
using compact_sums [OF that compact_sing [of a]] by auto
qed
lemma compact_translation_subtract:
"compact ((\<lambda>x. x - a) ` s)" if "compact s" for s :: "'a::real_normed_vector set"
using that compact_translation [of s "- a"] by (simp cong: image_cong_simp)
lemma compact_affinity:
fixes s :: "'a::real_normed_vector set"
assumes "compact s"
shows "compact ((\<lambda>x. a + c *\<^sub>R x) ` s)"
proof -
have "(+) a ` (*\<^sub>R) c ` s = (\<lambda>x. a + c *\<^sub>R x) ` s"
by auto
then show ?thesis
using compact_translation[OF compact_scaling[OF assms], of a c] by auto
qed
lemma closed_scaling:
fixes S :: "'a::real_normed_vector set"
assumes "closed S"
shows "closed ((\<lambda>x. c *\<^sub>R x) ` S)"
proof (cases "c = 0")
case True then show ?thesis
by (auto simp: image_constant_conv)
next
case False
from assms have "closed ((\<lambda>x. inverse c *\<^sub>R x) -` S)"
by (simp add: continuous_closed_vimage)
also have "(\<lambda>x. inverse c *\<^sub>R x) -` S = (\<lambda>x. c *\<^sub>R x) ` S"
using \<open>c \<noteq> 0\<close> by (auto elim: image_eqI [rotated])
finally show ?thesis .
qed
lemma closed_negations:
fixes S :: "'a::real_normed_vector set"
assumes "closed S"
shows "closed ((\<lambda>x. -x) ` S)"
using closed_scaling[OF assms, of "- 1"] by simp
lemma compact_closed_sums:
fixes S :: "'a::real_normed_vector set"
assumes "compact S" and "closed T"
shows "closed (\<Union>x\<in> S. \<Union>y \<in> T. {x + y})"
proof -
let ?S = "{x + y |x y. x \<in> S \<and> y \<in> T}"
{
fix x l
assume as: "\<forall>n. x n \<in> ?S" "(x \<longlongrightarrow> l) sequentially"
from as(1) obtain f where f: "\<forall>n. x n = fst (f n) + snd (f n)" "\<forall>n. fst (f n) \<in> S" "\<forall>n. snd (f n) \<in> T"
using choice[of "\<lambda>n y. x n = (fst y) + (snd y) \<and> fst y \<in> S \<and> snd y \<in> T"] by auto
obtain l' r where "l'\<in>S" and r: "strict_mono r" and lr: "(((\<lambda>n. fst (f n)) \<circ> r) \<longlongrightarrow> l') sequentially"
using assms(1)[unfolded compact_def, THEN spec[where x="\<lambda> n. fst (f n)"]] using f(2) by auto
have "((\<lambda>n. snd (f (r n))) \<longlongrightarrow> l - l') sequentially"
using tendsto_diff[OF LIMSEQ_subseq_LIMSEQ[OF as(2) r] lr] and f(1)
unfolding o_def
by auto
then have "l - l' \<in> T"
using assms(2)[unfolded closed_sequential_limits,
THEN spec[where x="\<lambda> n. snd (f (r n))"],
THEN spec[where x="l - l'"]]
using f(3)
by auto
then have "l \<in> ?S"
using \<open>l' \<in> S\<close>
apply auto
apply (rule_tac x=l' in exI)
apply (rule_tac x="l - l'" in exI, auto)
done
}
moreover have "?S = (\<Union>x\<in> S. \<Union>y \<in> T. {x + y})"
by force
ultimately show ?thesis
unfolding closed_sequential_limits
by (metis (no_types, lifting))
qed
lemma closed_compact_sums:
fixes S T :: "'a::real_normed_vector set"
assumes "closed S" "compact T"
shows "closed (\<Union>x\<in> S. \<Union>y \<in> T. {x + y})"
proof -
have "(\<Union>x\<in> T. \<Union>y \<in> S. {x + y}) = (\<Union>x\<in> S. \<Union>y \<in> T. {x + y})"
by auto
then show ?thesis
using compact_closed_sums[OF assms(2,1)] by simp
qed
lemma compact_closed_differences:
fixes S T :: "'a::real_normed_vector set"
assumes "compact S" "closed T"
shows "closed (\<Union>x\<in> S. \<Union>y \<in> T. {x - y})"
proof -
have "(\<Union>x\<in> S. \<Union>y \<in> uminus ` T. {x + y}) = (\<Union>x\<in> S. \<Union>y \<in> T. {x - y})"
by force
then show ?thesis
using compact_closed_sums[OF assms(1) closed_negations[OF assms(2)]] by auto
qed
lemma closed_compact_differences:
fixes S T :: "'a::real_normed_vector set"
assumes "closed S" "compact T"
shows "closed (\<Union>x\<in> S. \<Union>y \<in> T. {x - y})"
proof -
have "(\<Union>x\<in> S. \<Union>y \<in> uminus ` T. {x + y}) = {x - y |x y. x \<in> S \<and> y \<in> T}"
by auto
then show ?thesis
using closed_compact_sums[OF assms(1) compact_negations[OF assms(2)]] by simp
qed
lemma closed_translation:
"closed ((+) a ` S)" if "closed S" for a :: "'a::real_normed_vector"
proof -
have "(\<Union>x\<in> {a}. \<Union>y \<in> S. {x + y}) = ((+) a ` S)" by auto
then show ?thesis
using compact_closed_sums [OF compact_sing [of a] that] by auto
qed
lemma closed_translation_subtract:
"closed ((\<lambda>x. x - a) ` S)" if "closed S" for a :: "'a::real_normed_vector"
using that closed_translation [of S "- a"] by (simp cong: image_cong_simp)
lemma closure_translation:
"closure ((+) a ` s) = (+) a ` closure s" for a :: "'a::real_normed_vector"
proof -
have *: "(+) a ` (- s) = - (+) a ` s"
by (auto intro!: image_eqI [where x = "x - a" for x])
show ?thesis
using interior_translation [of a "- s", symmetric]
by (simp add: closure_interior translation_Compl *)
qed
lemma closure_translation_subtract:
"closure ((\<lambda>x. x - a) ` s) = (\<lambda>x. x - a) ` closure s" for a :: "'a::real_normed_vector"
using closure_translation [of "- a" s] by (simp cong: image_cong_simp)
lemma frontier_translation:
"frontier ((+) a ` s) = (+) a ` frontier s" for a :: "'a::real_normed_vector"
by (auto simp add: frontier_def translation_diff interior_translation closure_translation)
lemma frontier_translation_subtract:
"frontier ((+) a ` s) = (+) a ` frontier s" for a :: "'a::real_normed_vector"
by (auto simp add: frontier_def translation_diff interior_translation closure_translation)
lemma sphere_translation:
"sphere (a + c) r = (+) a ` sphere c r" for a :: "'n::real_normed_vector"
by (auto simp: dist_norm algebra_simps intro!: image_eqI [where x = "x - a" for x])
lemma sphere_translation_subtract:
"sphere (c - a) r = (\<lambda>x. x - a) ` sphere c r" for a :: "'n::real_normed_vector"
using sphere_translation [of "- a" c] by (simp cong: image_cong_simp)
lemma cball_translation:
"cball (a + c) r = (+) a ` cball c r" for a :: "'n::real_normed_vector"
by (auto simp: dist_norm algebra_simps intro!: image_eqI [where x = "x - a" for x])
lemma cball_translation_subtract:
"cball (c - a) r = (\<lambda>x. x - a) ` cball c r" for a :: "'n::real_normed_vector"
using cball_translation [of "- a" c] by (simp cong: image_cong_simp)
lemma ball_translation:
"ball (a + c) r = (+) a ` ball c r" for a :: "'n::real_normed_vector"
by (auto simp: dist_norm algebra_simps intro!: image_eqI [where x = "x - a" for x])
lemma ball_translation_subtract:
"ball (c - a) r = (\<lambda>x. x - a) ` ball c r" for a :: "'n::real_normed_vector"
using ball_translation [of "- a" c] by (simp cong: image_cong_simp)
subsection\<^marker>\<open>tag unimportant\<close>\<open>Homeomorphisms\<close>
lemma homeomorphic_scaling:
fixes s :: "'a::real_normed_vector set"
assumes "c \<noteq> 0"
shows "s homeomorphic ((\<lambda>x. c *\<^sub>R x) ` s)"
unfolding homeomorphic_minimal
apply (rule_tac x="\<lambda>x. c *\<^sub>R x" in exI)
apply (rule_tac x="\<lambda>x. (1 / c) *\<^sub>R x" in exI)
using assms
apply (auto simp: continuous_intros)
done
lemma homeomorphic_translation:
fixes s :: "'a::real_normed_vector set"
shows "s homeomorphic ((\<lambda>x. a + x) ` s)"
unfolding homeomorphic_minimal
apply (rule_tac x="\<lambda>x. a + x" in exI)
apply (rule_tac x="\<lambda>x. -a + x" in exI)
using continuous_on_add [OF continuous_on_const continuous_on_id, of s a]
continuous_on_add [OF continuous_on_const continuous_on_id, of "plus a ` s" "- a"]
apply auto
done
lemma homeomorphic_affinity:
fixes s :: "'a::real_normed_vector set"
assumes "c \<noteq> 0"
shows "s homeomorphic ((\<lambda>x. a + c *\<^sub>R x) ` s)"
proof -
have *: "(+) a ` (*\<^sub>R) c ` s = (\<lambda>x. a + c *\<^sub>R x) ` s" by auto
show ?thesis
using homeomorphic_trans
using homeomorphic_scaling[OF assms, of s]
using homeomorphic_translation[of "(\<lambda>x. c *\<^sub>R x) ` s" a]
unfolding *
by auto
qed
lemma homeomorphic_balls:
fixes a b ::"'a::real_normed_vector"
assumes "0 < d" "0 < e"
shows "(ball a d) homeomorphic (ball b e)" (is ?th)
and "(cball a d) homeomorphic (cball b e)" (is ?cth)
proof -
show ?th unfolding homeomorphic_minimal
apply(rule_tac x="\<lambda>x. b + (e/d) *\<^sub>R (x - a)" in exI)
apply(rule_tac x="\<lambda>x. a + (d/e) *\<^sub>R (x - b)" in exI)
using assms
apply (auto intro!: continuous_intros
simp: dist_commute dist_norm pos_divide_less_eq mult_strict_left_mono)
done
show ?cth unfolding homeomorphic_minimal
apply(rule_tac x="\<lambda>x. b + (e/d) *\<^sub>R (x - a)" in exI)
apply(rule_tac x="\<lambda>x. a + (d/e) *\<^sub>R (x - b)" in exI)
using assms
apply (auto intro!: continuous_intros
simp: dist_commute dist_norm pos_divide_le_eq mult_strict_left_mono)
done
qed
lemma homeomorphic_spheres:
fixes a b ::"'a::real_normed_vector"
assumes "0 < d" "0 < e"
shows "(sphere a d) homeomorphic (sphere b e)"
unfolding homeomorphic_minimal
apply(rule_tac x="\<lambda>x. b + (e/d) *\<^sub>R (x - a)" in exI)
apply(rule_tac x="\<lambda>x. a + (d/e) *\<^sub>R (x - b)" in exI)
using assms
apply (auto intro!: continuous_intros
simp: dist_commute dist_norm pos_divide_less_eq mult_strict_left_mono)
done
lemma homeomorphic_ball01_UNIV:
"ball (0::'a::real_normed_vector) 1 homeomorphic (UNIV:: 'a set)"
(is "?B homeomorphic ?U")
proof
have "x \<in> (\<lambda>z. z /\<^sub>R (1 - norm z)) ` ball 0 1" for x::'a
apply (rule_tac x="x /\<^sub>R (1 + norm x)" in image_eqI)
apply (auto simp: divide_simps)
using norm_ge_zero [of x] apply linarith+
done
then show "(\<lambda>z::'a. z /\<^sub>R (1 - norm z)) ` ?B = ?U"
by blast
have "x \<in> range (\<lambda>z. (1 / (1 + norm z)) *\<^sub>R z)" if "norm x < 1" for x::'a
apply (rule_tac x="x /\<^sub>R (1 - norm x)" in image_eqI)
using that apply (auto simp: divide_simps)
done
then show "(\<lambda>z::'a. z /\<^sub>R (1 + norm z)) ` ?U = ?B"
by (force simp: divide_simps dest: add_less_zeroD)
show "continuous_on (ball 0 1) (\<lambda>z. z /\<^sub>R (1 - norm z))"
by (rule continuous_intros | force)+
show "continuous_on UNIV (\<lambda>z. z /\<^sub>R (1 + norm z))"
apply (intro continuous_intros)
apply (metis le_add_same_cancel1 norm_ge_zero not_le zero_less_one)
done
show "\<And>x. x \<in> ball 0 1 \<Longrightarrow>
x /\<^sub>R (1 - norm x) /\<^sub>R (1 + norm (x /\<^sub>R (1 - norm x))) = x"
by (auto simp: divide_simps)
show "\<And>y. y /\<^sub>R (1 + norm y) /\<^sub>R (1 - norm (y /\<^sub>R (1 + norm y))) = y"
apply (auto simp: divide_simps)
apply (metis le_add_same_cancel1 norm_ge_zero not_le zero_less_one)
done
qed
proposition homeomorphic_ball_UNIV:
fixes a ::"'a::real_normed_vector"
assumes "0 < r" shows "ball a r homeomorphic (UNIV:: 'a set)"
using assms homeomorphic_ball01_UNIV homeomorphic_balls(1) homeomorphic_trans zero_less_one by blast
subsection\<^marker>\<open>tag unimportant\<close> \<open>Discrete\<close>
lemma finite_implies_discrete:
fixes S :: "'a::topological_space set"
assumes "finite (f ` S)"
shows "(\<forall>x \<in> S. \<exists>e>0. \<forall>y. y \<in> S \<and> f y \<noteq> f x \<longrightarrow> e \<le> norm (f y - f x))"
proof -
have "\<exists>e>0. \<forall>y. y \<in> S \<and> f y \<noteq> f x \<longrightarrow> e \<le> norm (f y - f x)" if "x \<in> S" for x
proof (cases "f ` S - {f x} = {}")
case True
with zero_less_numeral show ?thesis
by (fastforce simp add: Set.image_subset_iff cong: conj_cong)
next
case False
then obtain z where z: "z \<in> S" "f z \<noteq> f x"
by blast
have finn: "finite {norm (z - f x) |z. z \<in> f ` S - {f x}}"
using assms by simp
then have *: "0 < Inf{norm(z - f x) | z. z \<in> f ` S - {f x}}"
apply (rule finite_imp_less_Inf)
using z apply force+
done
show ?thesis
by (force intro!: * cInf_le_finite [OF finn])
qed
with assms show ?thesis
by blast
qed
subsection\<^marker>\<open>tag unimportant\<close> \<open>Completeness of "Isometry" (up to constant bounds)\<close>
lemma cauchy_isometric:\<comment> \<open>TODO: rename lemma to \<open>Cauchy_isometric\<close>\<close>
assumes e: "e > 0"
and s: "subspace s"
and f: "bounded_linear f"
and normf: "\<forall>x\<in>s. norm (f x) \<ge> e * norm x"
and xs: "\<forall>n. x n \<in> s"
and cf: "Cauchy (f \<circ> x)"
shows "Cauchy x"
proof -
interpret f: bounded_linear f by fact
have "\<exists>N. \<forall>n\<ge>N. norm (x n - x N) < d" if "d > 0" for d :: real
proof -
from that obtain N where N: "\<forall>n\<ge>N. norm (f (x n) - f (x N)) < e * d"
using cf[unfolded Cauchy_def o_def dist_norm, THEN spec[where x="e*d"]] e
by auto
have "norm (x n - x N) < d" if "n \<ge> N" for n
proof -
have "e * norm (x n - x N) \<le> norm (f (x n - x N))"
using subspace_diff[OF s, of "x n" "x N"]
using xs[THEN spec[where x=N]] and xs[THEN spec[where x=n]]
using normf[THEN bspec[where x="x n - x N"]]
by auto
also have "norm (f (x n - x N)) < e * d"
using \<open>N \<le> n\<close> N unfolding f.diff[symmetric] by auto
finally show ?thesis
using \<open>e>0\<close> by simp
qed
then show ?thesis by auto
qed
then show ?thesis
by (simp add: Cauchy_altdef2 dist_norm)
qed
lemma complete_isometric_image:
assumes "0 < e"
and s: "subspace s"
and f: "bounded_linear f"
and normf: "\<forall>x\<in>s. norm(f x) \<ge> e * norm(x)"
and cs: "complete s"
shows "complete (f ` s)"
proof -
have "\<exists>l\<in>f ` s. (g \<longlongrightarrow> l) sequentially"
if as:"\<forall>n::nat. g n \<in> f ` s" and cfg:"Cauchy g" for g
proof -
from that obtain x where "\<forall>n. x n \<in> s \<and> g n = f (x n)"
using choice[of "\<lambda> n xa. xa \<in> s \<and> g n = f xa"] by auto
then have x: "\<forall>n. x n \<in> s" "\<forall>n. g n = f (x n)" by auto
then have "f \<circ> x = g" by (simp add: fun_eq_iff)
then obtain l where "l\<in>s" and l:"(x \<longlongrightarrow> l) sequentially"
using cs[unfolded complete_def, THEN spec[where x=x]]
using cauchy_isometric[OF \<open>0 < e\<close> s f normf] and cfg and x(1)
by auto
then show ?thesis
using linear_continuous_at[OF f, unfolded continuous_at_sequentially, THEN spec[where x=x], of l]
by (auto simp: \<open>f \<circ> x = g\<close>)
qed
then show ?thesis
unfolding complete_def by auto
qed
subsection \<open>Connected Normed Spaces\<close>
lemma compact_components:
fixes s :: "'a::heine_borel set"
shows "\<lbrakk>compact s; c \<in> components s\<rbrakk> \<Longrightarrow> compact c"
by (meson bounded_subset closed_components in_components_subset compact_eq_bounded_closed)
lemma discrete_subset_disconnected:
fixes S :: "'a::topological_space set"
fixes t :: "'b::real_normed_vector set"
assumes conf: "continuous_on S f"
and no: "\<And>x. x \<in> S \<Longrightarrow> \<exists>e>0. \<forall>y. y \<in> S \<and> f y \<noteq> f x \<longrightarrow> e \<le> norm (f y - f x)"
shows "f ` S \<subseteq> {y. connected_component_set (f ` S) y = {y}}"
proof -
{ fix x assume x: "x \<in> S"
then obtain e where "e>0" and ele: "\<And>y. \<lbrakk>y \<in> S; f y \<noteq> f x\<rbrakk> \<Longrightarrow> e \<le> norm (f y - f x)"
using conf no [OF x] by auto
then have e2: "0 \<le> e / 2"
by simp
have "f y = f x" if "y \<in> S" and ccs: "f y \<in> connected_component_set (f ` S) (f x)" for y
apply (rule ccontr)
using connected_closed [of "connected_component_set (f ` S) (f x)"] \<open>e>0\<close>
apply (simp add: del: ex_simps)
apply (drule spec [where x="cball (f x) (e / 2)"])
apply (drule spec [where x="- ball(f x) e"])
apply (auto simp: dist_norm open_closed [symmetric] simp del: le_divide_eq_numeral1 dest!: connected_component_in)
apply (metis diff_self e2 ele norm_minus_commute norm_zero not_less)
using centre_in_cball connected_component_refl_eq e2 x apply blast
using ccs
apply (force simp: cball_def dist_norm norm_minus_commute dest: ele [OF \<open>y \<in> S\<close>])
done
moreover have "connected_component_set (f ` S) (f x) \<subseteq> f ` S"
by (auto simp: connected_component_in)
ultimately have "connected_component_set (f ` S) (f x) = {f x}"
by (auto simp: x)
}
with assms show ?thesis
by blast
qed
lemma continuous_disconnected_range_constant_eq:
"(connected S \<longleftrightarrow>
(\<forall>f::'a::topological_space \<Rightarrow> 'b::real_normed_algebra_1.
\<forall>t. continuous_on S f \<and> f ` S \<subseteq> t \<and> (\<forall>y \<in> t. connected_component_set t y = {y})
\<longrightarrow> f constant_on S))" (is ?thesis1)
and continuous_discrete_range_constant_eq:
"(connected S \<longleftrightarrow>
(\<forall>f::'a::topological_space \<Rightarrow> 'b::real_normed_algebra_1.
continuous_on S f \<and>
(\<forall>x \<in> S. \<exists>e. 0 < e \<and> (\<forall>y. y \<in> S \<and> (f y \<noteq> f x) \<longrightarrow> e \<le> norm(f y - f x)))
\<longrightarrow> f constant_on S))" (is ?thesis2)
and continuous_finite_range_constant_eq:
"(connected S \<longleftrightarrow>
(\<forall>f::'a::topological_space \<Rightarrow> 'b::real_normed_algebra_1.
continuous_on S f \<and> finite (f ` S)
\<longrightarrow> f constant_on S))" (is ?thesis3)
proof -
have *: "\<And>s t u v. \<lbrakk>s \<Longrightarrow> t; t \<Longrightarrow> u; u \<Longrightarrow> v; v \<Longrightarrow> s\<rbrakk>
\<Longrightarrow> (s \<longleftrightarrow> t) \<and> (s \<longleftrightarrow> u) \<and> (s \<longleftrightarrow> v)"
by blast
have "?thesis1 \<and> ?thesis2 \<and> ?thesis3"
apply (rule *)
using continuous_disconnected_range_constant apply metis
apply clarify
apply (frule discrete_subset_disconnected; blast)
apply (blast dest: finite_implies_discrete)
apply (blast intro!: finite_range_constant_imp_connected)
done
then show ?thesis1 ?thesis2 ?thesis3
by blast+
qed
lemma continuous_discrete_range_constant:
fixes f :: "'a::topological_space \<Rightarrow> 'b::real_normed_algebra_1"
assumes S: "connected S"
and "continuous_on S f"
and "\<And>x. x \<in> S \<Longrightarrow> \<exists>e>0. \<forall>y. y \<in> S \<and> f y \<noteq> f x \<longrightarrow> e \<le> norm (f y - f x)"
shows "f constant_on S"
using continuous_discrete_range_constant_eq [THEN iffD1, OF S] assms by blast
lemma continuous_finite_range_constant:
fixes f :: "'a::topological_space \<Rightarrow> 'b::real_normed_algebra_1"
assumes "connected S"
and "continuous_on S f"
and "finite (f ` S)"
shows "f constant_on S"
using assms continuous_finite_range_constant_eq by blast
end