moved theorems from AFP/Affine_Arithmetic and AFP/Ordinary_Differential_Equations
(* Title: HOL/Analysis/Bounded_Linear_Function.thy
Author: Fabian Immler, TU München
*)
section \<open>Bounded Linear Function\<close>
theory Bounded_Linear_Function
imports
Topology_Euclidean_Space
Operator_Norm
Uniform_Limit
begin
lemma onorm_componentwise:
assumes "bounded_linear f"
shows "onorm f \<le> (\<Sum>i\<in>Basis. norm (f i))"
proof -
{
fix i::'a
assume "i \<in> Basis"
hence "onorm (\<lambda>x. (x \<bullet> i) *\<^sub>R f i) \<le> onorm (\<lambda>x. (x \<bullet> i)) * norm (f i)"
by (auto intro!: onorm_scaleR_left_lemma bounded_linear_inner_left)
also have "\<dots> \<le> norm i * norm (f i)"
by (rule mult_right_mono)
(auto simp: ac_simps Cauchy_Schwarz_ineq2 intro!: onorm_le)
finally have "onorm (\<lambda>x. (x \<bullet> i) *\<^sub>R f i) \<le> norm (f i)" using \<open>i \<in> Basis\<close>
by simp
} hence "onorm (\<lambda>x. \<Sum>i\<in>Basis. (x \<bullet> i) *\<^sub>R f i) \<le> (\<Sum>i\<in>Basis. norm (f i))"
by (auto intro!: order_trans[OF onorm_sum_le] bounded_linear_scaleR_const
sum_mono bounded_linear_inner_left)
also have "(\<lambda>x. \<Sum>i\<in>Basis. (x \<bullet> i) *\<^sub>R f i) = (\<lambda>x. f (\<Sum>i\<in>Basis. (x \<bullet> i) *\<^sub>R i))"
by (simp add: linear_sum bounded_linear.linear assms linear_simps)
also have "\<dots> = f"
by (simp add: euclidean_representation)
finally show ?thesis .
qed
lemmas onorm_componentwise_le = order_trans[OF onorm_componentwise]
subsection \<open>Intro rules for @{term bounded_linear}\<close>
named_theorems bounded_linear_intros
lemma onorm_inner_left:
assumes "bounded_linear r"
shows "onorm (\<lambda>x. r x \<bullet> f) \<le> onorm r * norm f"
proof (rule onorm_bound)
fix x
have "norm (r x \<bullet> f) \<le> norm (r x) * norm f"
by (simp add: Cauchy_Schwarz_ineq2)
also have "\<dots> \<le> onorm r * norm x * norm f"
by (intro mult_right_mono onorm assms norm_ge_zero)
finally show "norm (r x \<bullet> f) \<le> onorm r * norm f * norm x"
by (simp add: ac_simps)
qed (intro mult_nonneg_nonneg norm_ge_zero onorm_pos_le assms)
lemma onorm_inner_right:
assumes "bounded_linear r"
shows "onorm (\<lambda>x. f \<bullet> r x) \<le> norm f * onorm r"
apply (subst inner_commute)
apply (rule onorm_inner_left[OF assms, THEN order_trans])
apply simp
done
lemmas [bounded_linear_intros] =
bounded_linear_zero
bounded_linear_add
bounded_linear_const_mult
bounded_linear_mult_const
bounded_linear_scaleR_const
bounded_linear_const_scaleR
bounded_linear_ident
bounded_linear_sum
bounded_linear_Pair
bounded_linear_sub
bounded_linear_fst_comp
bounded_linear_snd_comp
bounded_linear_inner_left_comp
bounded_linear_inner_right_comp
subsection \<open>declaration of derivative/continuous/tendsto introduction rules for bounded linear functions\<close>
attribute_setup bounded_linear =
\<open>Scan.succeed (Thm.declaration_attribute (fn thm =>
fold (fn (r, s) => Named_Theorems.add_thm s (thm RS r))
[
(@{thm bounded_linear.has_derivative}, @{named_theorems derivative_intros}),
(@{thm bounded_linear.tendsto}, @{named_theorems tendsto_intros}),
(@{thm bounded_linear.continuous}, @{named_theorems continuous_intros}),
(@{thm bounded_linear.continuous_on}, @{named_theorems continuous_intros}),
(@{thm bounded_linear.uniformly_continuous_on}, @{named_theorems continuous_intros}),
(@{thm bounded_linear_compose}, @{named_theorems bounded_linear_intros})
]))\<close>
attribute_setup bounded_bilinear =
\<open>Scan.succeed (Thm.declaration_attribute (fn thm =>
fold (fn (r, s) => Named_Theorems.add_thm s (thm RS r))
[
(@{thm bounded_bilinear.FDERIV}, @{named_theorems derivative_intros}),
(@{thm bounded_bilinear.tendsto}, @{named_theorems tendsto_intros}),
(@{thm bounded_bilinear.continuous}, @{named_theorems continuous_intros}),
(@{thm bounded_bilinear.continuous_on}, @{named_theorems continuous_intros}),
(@{thm bounded_linear_compose[OF bounded_bilinear.bounded_linear_left]},
@{named_theorems bounded_linear_intros}),
(@{thm bounded_linear_compose[OF bounded_bilinear.bounded_linear_right]},
@{named_theorems bounded_linear_intros}),
(@{thm bounded_linear.uniformly_continuous_on[OF bounded_bilinear.bounded_linear_left]},
@{named_theorems continuous_intros}),
(@{thm bounded_linear.uniformly_continuous_on[OF bounded_bilinear.bounded_linear_right]},
@{named_theorems continuous_intros})
]))\<close>
subsection \<open>type of bounded linear functions\<close>
typedef (overloaded) ('a, 'b) blinfun ("(_ \<Rightarrow>\<^sub>L /_)" [22, 21] 21) =
"{f::'a::real_normed_vector\<Rightarrow>'b::real_normed_vector. bounded_linear f}"
morphisms blinfun_apply Blinfun
by (blast intro: bounded_linear_intros)
declare [[coercion
"blinfun_apply :: ('a::real_normed_vector \<Rightarrow>\<^sub>L'b::real_normed_vector) \<Rightarrow> 'a \<Rightarrow> 'b"]]
lemma bounded_linear_blinfun_apply[bounded_linear_intros]:
"bounded_linear g \<Longrightarrow> bounded_linear (\<lambda>x. blinfun_apply f (g x))"
by (metis blinfun_apply mem_Collect_eq bounded_linear_compose)
setup_lifting type_definition_blinfun
lemma blinfun_eqI: "(\<And>i. blinfun_apply x i = blinfun_apply y i) \<Longrightarrow> x = y"
by transfer auto
lemma bounded_linear_Blinfun_apply: "bounded_linear f \<Longrightarrow> blinfun_apply (Blinfun f) = f"
by (auto simp: Blinfun_inverse)
subsection \<open>type class instantiations\<close>
instantiation blinfun :: (real_normed_vector, real_normed_vector) real_normed_vector
begin
lift_definition norm_blinfun :: "'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> real" is onorm .
lift_definition minus_blinfun :: "'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b"
is "\<lambda>f g x. f x - g x"
by (rule bounded_linear_sub)
definition dist_blinfun :: "'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> real"
where "dist_blinfun a b = norm (a - b)"
definition [code del]:
"(uniformity :: (('a \<Rightarrow>\<^sub>L 'b) \<times> ('a \<Rightarrow>\<^sub>L 'b)) filter) = (INF e:{0 <..}. principal {(x, y). dist x y < e})"
definition open_blinfun :: "('a \<Rightarrow>\<^sub>L 'b) set \<Rightarrow> bool"
where [code del]: "open_blinfun S = (\<forall>x\<in>S. \<forall>\<^sub>F (x', y) in uniformity. x' = x \<longrightarrow> y \<in> S)"
lift_definition uminus_blinfun :: "'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b" is "\<lambda>f x. - f x"
by (rule bounded_linear_minus)
lift_definition zero_blinfun :: "'a \<Rightarrow>\<^sub>L 'b" is "\<lambda>x. 0"
by (rule bounded_linear_zero)
lift_definition plus_blinfun :: "'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b"
is "\<lambda>f g x. f x + g x"
by (metis bounded_linear_add)
lift_definition scaleR_blinfun::"real \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b" is "\<lambda>r f x. r *\<^sub>R f x"
by (metis bounded_linear_compose bounded_linear_scaleR_right)
definition sgn_blinfun :: "'a \<Rightarrow>\<^sub>L 'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b"
where "sgn_blinfun x = scaleR (inverse (norm x)) x"
instance
apply standard
unfolding dist_blinfun_def open_blinfun_def sgn_blinfun_def uniformity_blinfun_def
apply (rule refl | (transfer, force simp: onorm_triangle onorm_scaleR onorm_eq_0 algebra_simps))+
done
end
declare uniformity_Abort[where 'a="('a :: real_normed_vector) \<Rightarrow>\<^sub>L ('b :: real_normed_vector)", code]
lemma norm_blinfun_eqI:
assumes "n \<le> norm (blinfun_apply f x) / norm x"
assumes "\<And>x. norm (blinfun_apply f x) \<le> n * norm x"
assumes "0 \<le> n"
shows "norm f = n"
by (auto simp: norm_blinfun_def
intro!: antisym onorm_bound assms order_trans[OF _ le_onorm]
bounded_linear_intros)
lemma norm_blinfun: "norm (blinfun_apply f x) \<le> norm f * norm x"
by transfer (rule onorm)
lemma norm_blinfun_bound: "0 \<le> b \<Longrightarrow> (\<And>x. norm (blinfun_apply f x) \<le> b * norm x) \<Longrightarrow> norm f \<le> b"
by transfer (rule onorm_bound)
lemma bounded_bilinear_blinfun_apply[bounded_bilinear]: "bounded_bilinear blinfun_apply"
proof
fix f g::"'a \<Rightarrow>\<^sub>L 'b" and a b::'a and r::real
show "(f + g) a = f a + g a" "(r *\<^sub>R f) a = r *\<^sub>R f a"
by (transfer, simp)+
interpret bounded_linear f for f::"'a \<Rightarrow>\<^sub>L 'b"
by (auto intro!: bounded_linear_intros)
show "f (a + b) = f a + f b" "f (r *\<^sub>R a) = r *\<^sub>R f a"
by (simp_all add: add scaleR)
show "\<exists>K. \<forall>a b. norm (blinfun_apply a b) \<le> norm a * norm b * K"
by (auto intro!: exI[where x=1] norm_blinfun)
qed
interpretation blinfun: bounded_bilinear blinfun_apply
by (rule bounded_bilinear_blinfun_apply)
lemmas bounded_linear_apply_blinfun[intro, simp] = blinfun.bounded_linear_left
context bounded_bilinear
begin
named_theorems bilinear_simps
lemmas [bilinear_simps] =
add_left
add_right
diff_left
diff_right
minus_left
minus_right
scaleR_left
scaleR_right
zero_left
zero_right
sum_left
sum_right
end
instance blinfun :: (real_normed_vector, banach) banach
proof
fix X::"nat \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b"
assume "Cauchy X"
{
fix x::'a
{
fix x::'a
assume "norm x \<le> 1"
have "Cauchy (\<lambda>n. X n x)"
proof (rule CauchyI)
fix e::real
assume "0 < e"
from CauchyD[OF \<open>Cauchy X\<close> \<open>0 < e\<close>] obtain M
where M: "\<And>m n. m \<ge> M \<Longrightarrow> n \<ge> M \<Longrightarrow> norm (X m - X n) < e"
by auto
show "\<exists>M. \<forall>m\<ge>M. \<forall>n\<ge>M. norm (X m x - X n x) < e"
proof (safe intro!: exI[where x=M])
fix m n
assume le: "M \<le> m" "M \<le> n"
have "norm (X m x - X n x) = norm ((X m - X n) x)"
by (simp add: blinfun.bilinear_simps)
also have "\<dots> \<le> norm (X m - X n) * norm x"
by (rule norm_blinfun)
also have "\<dots> \<le> norm (X m - X n) * 1"
using \<open>norm x \<le> 1\<close> norm_ge_zero by (rule mult_left_mono)
also have "\<dots> = norm (X m - X n)" by simp
also have "\<dots> < e" using le by fact
finally show "norm (X m x - X n x) < e" .
qed
qed
hence "convergent (\<lambda>n. X n x)"
by (metis Cauchy_convergent_iff)
} note convergent_norm1 = this
define y where "y = x /\<^sub>R norm x"
have y: "norm y \<le> 1" and xy: "x = norm x *\<^sub>R y"
by (simp_all add: y_def inverse_eq_divide)
have "convergent (\<lambda>n. norm x *\<^sub>R X n y)"
by (intro bounded_bilinear.convergent[OF bounded_bilinear_scaleR] convergent_const
convergent_norm1 y)
also have "(\<lambda>n. norm x *\<^sub>R X n y) = (\<lambda>n. X n x)"
by (subst xy) (simp add: blinfun.bilinear_simps)
finally have "convergent (\<lambda>n. X n x)" .
}
then obtain v where v: "\<And>x. (\<lambda>n. X n x) \<longlonglongrightarrow> v x"
unfolding convergent_def
by metis
have "Cauchy (\<lambda>n. norm (X n))"
proof (rule CauchyI)
fix e::real
assume "e > 0"
from CauchyD[OF \<open>Cauchy X\<close> \<open>0 < e\<close>] obtain M
where M: "\<And>m n. m \<ge> M \<Longrightarrow> n \<ge> M \<Longrightarrow> norm (X m - X n) < e"
by auto
show "\<exists>M. \<forall>m\<ge>M. \<forall>n\<ge>M. norm (norm (X m) - norm (X n)) < e"
proof (safe intro!: exI[where x=M])
fix m n assume mn: "m \<ge> M" "n \<ge> M"
have "norm (norm (X m) - norm (X n)) \<le> norm (X m - X n)"
by (metis norm_triangle_ineq3 real_norm_def)
also have "\<dots> < e" using mn by fact
finally show "norm (norm (X m) - norm (X n)) < e" .
qed
qed
then obtain K where K: "(\<lambda>n. norm (X n)) \<longlonglongrightarrow> K"
unfolding Cauchy_convergent_iff convergent_def
by metis
have "bounded_linear v"
proof
fix x y and r::real
from tendsto_add[OF v[of x] v [of y]] v[of "x + y", unfolded blinfun.bilinear_simps]
tendsto_scaleR[OF tendsto_const[of r] v[of x]] v[of "r *\<^sub>R x", unfolded blinfun.bilinear_simps]
show "v (x + y) = v x + v y" "v (r *\<^sub>R x) = r *\<^sub>R v x"
by (metis (poly_guards_query) LIMSEQ_unique)+
show "\<exists>K. \<forall>x. norm (v x) \<le> norm x * K"
proof (safe intro!: exI[where x=K])
fix x
have "norm (v x) \<le> K * norm x"
by (rule tendsto_le[OF _ tendsto_mult[OF K tendsto_const] tendsto_norm[OF v]])
(auto simp: norm_blinfun)
thus "norm (v x) \<le> norm x * K"
by (simp add: ac_simps)
qed
qed
hence Bv: "\<And>x. (\<lambda>n. X n x) \<longlonglongrightarrow> Blinfun v x"
by (auto simp: bounded_linear_Blinfun_apply v)
have "X \<longlonglongrightarrow> Blinfun v"
proof (rule LIMSEQ_I)
fix r::real assume "r > 0"
define r' where "r' = r / 2"
have "0 < r'" "r' < r" using \<open>r > 0\<close> by (simp_all add: r'_def)
from CauchyD[OF \<open>Cauchy X\<close> \<open>r' > 0\<close>]
obtain M where M: "\<And>m n. m \<ge> M \<Longrightarrow> n \<ge> M \<Longrightarrow> norm (X m - X n) < r'"
by metis
show "\<exists>no. \<forall>n\<ge>no. norm (X n - Blinfun v) < r"
proof (safe intro!: exI[where x=M])
fix n assume n: "M \<le> n"
have "norm (X n - Blinfun v) \<le> r'"
proof (rule norm_blinfun_bound)
fix x
have "eventually (\<lambda>m. m \<ge> M) sequentially"
by (metis eventually_ge_at_top)
hence ev_le: "eventually (\<lambda>m. norm (X n x - X m x) \<le> r' * norm x) sequentially"
proof eventually_elim
case (elim m)
have "norm (X n x - X m x) = norm ((X n - X m) x)"
by (simp add: blinfun.bilinear_simps)
also have "\<dots> \<le> norm ((X n - X m)) * norm x"
by (rule norm_blinfun)
also have "\<dots> \<le> r' * norm x"
using M[OF n elim] by (simp add: mult_right_mono)
finally show ?case .
qed
have tendsto_v: "(\<lambda>m. norm (X n x - X m x)) \<longlonglongrightarrow> norm (X n x - Blinfun v x)"
by (auto intro!: tendsto_intros Bv)
show "norm ((X n - Blinfun v) x) \<le> r' * norm x"
by (auto intro!: tendsto_upperbound tendsto_v ev_le simp: blinfun.bilinear_simps)
qed (simp add: \<open>0 < r'\<close> less_imp_le)
thus "norm (X n - Blinfun v) < r"
by (metis \<open>r' < r\<close> le_less_trans)
qed
qed
thus "convergent X"
by (rule convergentI)
qed
subsection \<open>On Euclidean Space\<close>
lemma Zfun_sum:
assumes "finite s"
assumes f: "\<And>i. i \<in> s \<Longrightarrow> Zfun (f i) F"
shows "Zfun (\<lambda>x. sum (\<lambda>i. f i x) s) F"
using assms by induct (auto intro!: Zfun_zero Zfun_add)
lemma norm_blinfun_euclidean_le:
fixes a::"'a::euclidean_space \<Rightarrow>\<^sub>L 'b::real_normed_vector"
shows "norm a \<le> sum (\<lambda>x. norm (a x)) Basis"
apply (rule norm_blinfun_bound)
apply (simp add: sum_nonneg)
apply (subst euclidean_representation[symmetric, where 'a='a])
apply (simp only: blinfun.bilinear_simps sum_distrib_right)
apply (rule order.trans[OF norm_sum sum_mono])
apply (simp add: abs_mult mult_right_mono ac_simps Basis_le_norm)
done
lemma tendsto_componentwise1:
fixes a::"'a::euclidean_space \<Rightarrow>\<^sub>L 'b::real_normed_vector"
and b::"'c \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b"
assumes "(\<And>j. j \<in> Basis \<Longrightarrow> ((\<lambda>n. b n j) \<longlongrightarrow> a j) F)"
shows "(b \<longlongrightarrow> a) F"
proof -
have "\<And>j. j \<in> Basis \<Longrightarrow> Zfun (\<lambda>x. norm (b x j - a j)) F"
using assms unfolding tendsto_Zfun_iff Zfun_norm_iff .
hence "Zfun (\<lambda>x. \<Sum>j\<in>Basis. norm (b x j - a j)) F"
by (auto intro!: Zfun_sum)
thus ?thesis
unfolding tendsto_Zfun_iff
by (rule Zfun_le)
(auto intro!: order_trans[OF norm_blinfun_euclidean_le] simp: blinfun.bilinear_simps)
qed
lift_definition
blinfun_of_matrix::"('b::euclidean_space \<Rightarrow> 'a::euclidean_space \<Rightarrow> real) \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b"
is "\<lambda>a x. \<Sum>i\<in>Basis. \<Sum>j\<in>Basis. ((x \<bullet> j) * a i j) *\<^sub>R i"
by (intro bounded_linear_intros)
lemma blinfun_of_matrix_works:
fixes f::"'a::euclidean_space \<Rightarrow>\<^sub>L 'b::euclidean_space"
shows "blinfun_of_matrix (\<lambda>i j. (f j) \<bullet> i) = f"
proof (transfer, rule, rule euclidean_eqI)
fix f::"'a \<Rightarrow> 'b" and x::'a and b::'b assume "bounded_linear f" and b: "b \<in> Basis"
then interpret bounded_linear f by simp
have "(\<Sum>j\<in>Basis. \<Sum>i\<in>Basis. (x \<bullet> i * (f i \<bullet> j)) *\<^sub>R j) \<bullet> b
= (\<Sum>j\<in>Basis. if j = b then (\<Sum>i\<in>Basis. (x \<bullet> i * (f i \<bullet> j))) else 0)"
using b
by (simp add: inner_sum_left inner_Basis if_distrib cong: if_cong) (simp add: sum.swap)
also have "\<dots> = (\<Sum>i\<in>Basis. (x \<bullet> i * (f i \<bullet> b)))"
using b by (simp add: sum.delta)
also have "\<dots> = f x \<bullet> b"
by (metis (mono_tags, lifting) Linear_Algebra.linear_componentwise linear_axioms)
finally show "(\<Sum>j\<in>Basis. \<Sum>i\<in>Basis. (x \<bullet> i * (f i \<bullet> j)) *\<^sub>R j) \<bullet> b = f x \<bullet> b" .
qed
lemma blinfun_of_matrix_apply:
"blinfun_of_matrix a x = (\<Sum>i\<in>Basis. \<Sum>j\<in>Basis. ((x \<bullet> j) * a i j) *\<^sub>R i)"
by transfer simp
lemma blinfun_of_matrix_minus: "blinfun_of_matrix x - blinfun_of_matrix y = blinfun_of_matrix (x - y)"
by transfer (auto simp: algebra_simps sum_subtractf)
lemma norm_blinfun_of_matrix:
"norm (blinfun_of_matrix a) \<le> (\<Sum>i\<in>Basis. \<Sum>j\<in>Basis. \<bar>a i j\<bar>)"
apply (rule norm_blinfun_bound)
apply (simp add: sum_nonneg)
apply (simp only: blinfun_of_matrix_apply sum_distrib_right)
apply (rule order_trans[OF norm_sum sum_mono])
apply (rule order_trans[OF norm_sum sum_mono])
apply (simp add: abs_mult mult_right_mono ac_simps Basis_le_norm)
done
lemma tendsto_blinfun_of_matrix:
assumes "\<And>i j. i \<in> Basis \<Longrightarrow> j \<in> Basis \<Longrightarrow> ((\<lambda>n. b n i j) \<longlongrightarrow> a i j) F"
shows "((\<lambda>n. blinfun_of_matrix (b n)) \<longlongrightarrow> blinfun_of_matrix a) F"
proof -
have "\<And>i j. i \<in> Basis \<Longrightarrow> j \<in> Basis \<Longrightarrow> Zfun (\<lambda>x. norm (b x i j - a i j)) F"
using assms unfolding tendsto_Zfun_iff Zfun_norm_iff .
hence "Zfun (\<lambda>x. (\<Sum>i\<in>Basis. \<Sum>j\<in>Basis. \<bar>b x i j - a i j\<bar>)) F"
by (auto intro!: Zfun_sum)
thus ?thesis
unfolding tendsto_Zfun_iff blinfun_of_matrix_minus
by (rule Zfun_le) (auto intro!: order_trans[OF norm_blinfun_of_matrix])
qed
lemma tendsto_componentwise:
fixes a::"'a::euclidean_space \<Rightarrow>\<^sub>L 'b::euclidean_space"
and b::"'c \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b"
shows "(\<And>i j. i \<in> Basis \<Longrightarrow> j \<in> Basis \<Longrightarrow> ((\<lambda>n. b n j \<bullet> i) \<longlongrightarrow> a j \<bullet> i) F) \<Longrightarrow> (b \<longlongrightarrow> a) F"
apply (subst blinfun_of_matrix_works[of a, symmetric])
apply (subst blinfun_of_matrix_works[of "b x" for x, symmetric, abs_def])
by (rule tendsto_blinfun_of_matrix)
lemma
continuous_blinfun_componentwiseI:
fixes f:: "'b::t2_space \<Rightarrow> 'a::euclidean_space \<Rightarrow>\<^sub>L 'c::euclidean_space"
assumes "\<And>i j. i \<in> Basis \<Longrightarrow> j \<in> Basis \<Longrightarrow> continuous F (\<lambda>x. (f x) j \<bullet> i)"
shows "continuous F f"
using assms by (auto simp: continuous_def intro!: tendsto_componentwise)
lemma
continuous_blinfun_componentwiseI1:
fixes f:: "'b::t2_space \<Rightarrow> 'a::euclidean_space \<Rightarrow>\<^sub>L 'c::real_normed_vector"
assumes "\<And>i. i \<in> Basis \<Longrightarrow> continuous F (\<lambda>x. f x i)"
shows "continuous F f"
using assms by (auto simp: continuous_def intro!: tendsto_componentwise1)
lemma
continuous_on_blinfun_componentwise:
fixes f:: "'d::t2_space \<Rightarrow> 'e::euclidean_space \<Rightarrow>\<^sub>L 'f::real_normed_vector"
assumes "\<And>i. i \<in> Basis \<Longrightarrow> continuous_on s (\<lambda>x. f x i)"
shows "continuous_on s f"
using assms
by (auto intro!: continuous_at_imp_continuous_on intro!: tendsto_componentwise1
simp: continuous_on_eq_continuous_within continuous_def)
lemma bounded_linear_blinfun_matrix: "bounded_linear (\<lambda>x. (x::_\<Rightarrow>\<^sub>L _) j \<bullet> i)"
by (auto intro!: bounded_linearI' bounded_linear_intros)
lemma continuous_blinfun_matrix:
fixes f:: "'b::t2_space \<Rightarrow> 'a::real_normed_vector \<Rightarrow>\<^sub>L 'c::real_inner"
assumes "continuous F f"
shows "continuous F (\<lambda>x. (f x) j \<bullet> i)"
by (rule bounded_linear.continuous[OF bounded_linear_blinfun_matrix assms])
lemma continuous_on_blinfun_matrix:
fixes f::"'a::t2_space \<Rightarrow> 'b::real_normed_vector \<Rightarrow>\<^sub>L 'c::real_inner"
assumes "continuous_on S f"
shows "continuous_on S (\<lambda>x. (f x) j \<bullet> i)"
using assms
by (auto simp: continuous_on_eq_continuous_within continuous_blinfun_matrix)
lemma continuous_on_blinfun_of_matrix[continuous_intros]:
assumes "\<And>i j. i \<in> Basis \<Longrightarrow> j \<in> Basis \<Longrightarrow> continuous_on S (\<lambda>s. g s i j)"
shows "continuous_on S (\<lambda>s. blinfun_of_matrix (g s))"
using assms
by (auto simp: continuous_on intro!: tendsto_blinfun_of_matrix)
lemma mult_if_delta:
"(if P then (1::'a::comm_semiring_1) else 0) * q = (if P then q else 0)"
by auto
lemma compact_blinfun_lemma:
fixes f :: "nat \<Rightarrow> 'a::euclidean_space \<Rightarrow>\<^sub>L 'b::euclidean_space"
assumes "bounded (range f)"
shows "\<forall>d\<subseteq>Basis. \<exists>l::'a \<Rightarrow>\<^sub>L 'b. \<exists> r::nat\<Rightarrow>nat.
strict_mono r \<and> (\<forall>e>0. eventually (\<lambda>n. \<forall>i\<in>d. dist (f (r n) i) (l i) < e) sequentially)"
by (rule compact_lemma_general[where unproj = "\<lambda>e. blinfun_of_matrix (\<lambda>i j. e j \<bullet> i)"])
(auto intro!: euclidean_eqI[where 'a='b] bounded_linear_image assms
simp: blinfun_of_matrix_works blinfun_of_matrix_apply inner_Basis mult_if_delta sum.delta'
scaleR_sum_left[symmetric])
lemma blinfun_euclidean_eqI: "(\<And>i. i \<in> Basis \<Longrightarrow> blinfun_apply x i = blinfun_apply y i) \<Longrightarrow> x = y"
apply (auto intro!: blinfun_eqI)
apply (subst (2) euclidean_representation[symmetric, where 'a='a])
apply (subst (1) euclidean_representation[symmetric, where 'a='a])
apply (simp add: blinfun.bilinear_simps)
done
lemma Blinfun_eq_matrix: "bounded_linear f \<Longrightarrow> Blinfun f = blinfun_of_matrix (\<lambda>i j. f j \<bullet> i)"
by (intro blinfun_euclidean_eqI)
(auto simp: blinfun_of_matrix_apply bounded_linear_Blinfun_apply inner_Basis if_distrib
cond_application_beta sum.delta' euclidean_representation
cong: if_cong)
text \<open>TODO: generalize (via \<open>compact_cball\<close>)?\<close>
instance blinfun :: (euclidean_space, euclidean_space) heine_borel
proof
fix f :: "nat \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'b"
assume f: "bounded (range f)"
then obtain l::"'a \<Rightarrow>\<^sub>L 'b" and r where r: "strict_mono r"
and l: "\<forall>e>0. eventually (\<lambda>n. \<forall>i\<in>Basis. dist (f (r n) i) (l i) < e) sequentially"
using compact_blinfun_lemma [OF f] by blast
{
fix e::real
let ?d = "real_of_nat DIM('a) * real_of_nat DIM('b)"
assume "e > 0"
hence "e / ?d > 0" by (simp add: DIM_positive)
with l have "eventually (\<lambda>n. \<forall>i\<in>Basis. dist (f (r n) i) (l i) < e / ?d) sequentially"
by simp
moreover
{
fix n
assume n: "\<forall>i\<in>Basis. dist (f (r n) i) (l i) < e / ?d"
have "norm (f (r n) - l) = norm (blinfun_of_matrix (\<lambda>i j. (f (r n) - l) j \<bullet> i))"
unfolding blinfun_of_matrix_works ..
also note norm_blinfun_of_matrix
also have "(\<Sum>i\<in>Basis. \<Sum>j\<in>Basis. \<bar>(f (r n) - l) j \<bullet> i\<bar>) <
(\<Sum>i\<in>(Basis::'b set). e / real_of_nat DIM('b))"
proof (rule sum_strict_mono)
fix i::'b assume i: "i \<in> Basis"
have "(\<Sum>j::'a\<in>Basis. \<bar>(f (r n) - l) j \<bullet> i\<bar>) < (\<Sum>j::'a\<in>Basis. e / ?d)"
proof (rule sum_strict_mono)
fix j::'a assume j: "j \<in> Basis"
have "\<bar>(f (r n) - l) j \<bullet> i\<bar> \<le> norm ((f (r n) - l) j)"
by (simp add: Basis_le_norm i)
also have "\<dots> < e / ?d"
using n i j by (auto simp: dist_norm blinfun.bilinear_simps)
finally show "\<bar>(f (r n) - l) j \<bullet> i\<bar> < e / ?d" by simp
qed simp_all
also have "\<dots> \<le> e / real_of_nat DIM('b)"
by simp
finally show "(\<Sum>j\<in>Basis. \<bar>(f (r n) - l) j \<bullet> i\<bar>) < e / real_of_nat DIM('b)"
by simp
qed simp_all
also have "\<dots> \<le> e" by simp
finally have "dist (f (r n)) l < e"
by (auto simp: dist_norm)
}
ultimately have "eventually (\<lambda>n. dist (f (r n)) l < e) sequentially"
using eventually_elim2 by force
}
then have *: "((f \<circ> r) \<longlongrightarrow> l) sequentially"
unfolding o_def tendsto_iff by simp
with r show "\<exists>l r. strict_mono r \<and> ((f \<circ> r) \<longlongrightarrow> l) sequentially"
by auto
qed
subsection \<open>concrete bounded linear functions\<close>
lemma transfer_bounded_bilinear_bounded_linearI:
assumes "g = (\<lambda>i x. (blinfun_apply (f i) x))"
shows "bounded_bilinear g = bounded_linear f"
proof
assume "bounded_bilinear g"
then interpret bounded_bilinear f by (simp add: assms)
show "bounded_linear f"
proof (unfold_locales, safe intro!: blinfun_eqI)
fix i
show "f (x + y) i = (f x + f y) i" "f (r *\<^sub>R x) i = (r *\<^sub>R f x) i" for r x y
by (auto intro!: blinfun_eqI simp: blinfun.bilinear_simps)
from _ nonneg_bounded show "\<exists>K. \<forall>x. norm (f x) \<le> norm x * K"
by (rule ex_reg) (auto intro!: onorm_bound simp: norm_blinfun.rep_eq ac_simps)
qed
qed (auto simp: assms intro!: blinfun.comp)
lemma transfer_bounded_bilinear_bounded_linear[transfer_rule]:
"(rel_fun (rel_fun (=) (pcr_blinfun (=) (=))) (=)) bounded_bilinear bounded_linear"
by (auto simp: pcr_blinfun_def cr_blinfun_def rel_fun_def OO_def
intro!: transfer_bounded_bilinear_bounded_linearI)
context bounded_bilinear
begin
lift_definition prod_left::"'b \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'c" is "(\<lambda>b a. prod a b)"
by (rule bounded_linear_left)
declare prod_left.rep_eq[simp]
lemma bounded_linear_prod_left[bounded_linear]: "bounded_linear prod_left"
by transfer (rule flip)
lift_definition prod_right::"'a \<Rightarrow> 'b \<Rightarrow>\<^sub>L 'c" is "(\<lambda>a b. prod a b)"
by (rule bounded_linear_right)
declare prod_right.rep_eq[simp]
lemma bounded_linear_prod_right[bounded_linear]: "bounded_linear prod_right"
by transfer (rule bounded_bilinear_axioms)
end
lift_definition id_blinfun::"'a::real_normed_vector \<Rightarrow>\<^sub>L 'a" is "\<lambda>x. x"
by (rule bounded_linear_ident)
lemmas blinfun_apply_id_blinfun[simp] = id_blinfun.rep_eq
lemma norm_blinfun_id[simp]:
"norm (id_blinfun::'a::{real_normed_vector, perfect_space} \<Rightarrow>\<^sub>L 'a) = 1"
by transfer (auto simp: onorm_id)
lemma norm_blinfun_id_le:
"norm (id_blinfun::'a::real_normed_vector \<Rightarrow>\<^sub>L 'a) \<le> 1"
by transfer (auto simp: onorm_id_le)
lift_definition fst_blinfun::"('a::real_normed_vector \<times> 'b::real_normed_vector) \<Rightarrow>\<^sub>L 'a" is fst
by (rule bounded_linear_fst)
lemma blinfun_apply_fst_blinfun[simp]: "blinfun_apply fst_blinfun = fst"
by transfer (rule refl)
lift_definition snd_blinfun::"('a::real_normed_vector \<times> 'b::real_normed_vector) \<Rightarrow>\<^sub>L 'b" is snd
by (rule bounded_linear_snd)
lemma blinfun_apply_snd_blinfun[simp]: "blinfun_apply snd_blinfun = snd"
by transfer (rule refl)
lift_definition blinfun_compose::
"'a::real_normed_vector \<Rightarrow>\<^sub>L 'b::real_normed_vector \<Rightarrow>
'c::real_normed_vector \<Rightarrow>\<^sub>L 'a \<Rightarrow>
'c \<Rightarrow>\<^sub>L 'b" (infixl "o\<^sub>L" 55) is "(o)"
parametric comp_transfer
unfolding o_def
by (rule bounded_linear_compose)
lemma blinfun_apply_blinfun_compose[simp]: "(a o\<^sub>L b) c = a (b c)"
by (simp add: blinfun_compose.rep_eq)
lemma norm_blinfun_compose:
"norm (f o\<^sub>L g) \<le> norm f * norm g"
by transfer (rule onorm_compose)
lemma bounded_bilinear_blinfun_compose[bounded_bilinear]: "bounded_bilinear (o\<^sub>L)"
by unfold_locales
(auto intro!: blinfun_eqI exI[where x=1] simp: blinfun.bilinear_simps norm_blinfun_compose)
lemma blinfun_compose_zero[simp]:
"blinfun_compose 0 = (\<lambda>_. 0)"
"blinfun_compose x 0 = 0"
by (auto simp: blinfun.bilinear_simps intro!: blinfun_eqI)
lift_definition blinfun_inner_right::"'a::real_inner \<Rightarrow> 'a \<Rightarrow>\<^sub>L real" is "(\<bullet>)"
by (rule bounded_linear_inner_right)
declare blinfun_inner_right.rep_eq[simp]
lemma bounded_linear_blinfun_inner_right[bounded_linear]: "bounded_linear blinfun_inner_right"
by transfer (rule bounded_bilinear_inner)
lift_definition blinfun_inner_left::"'a::real_inner \<Rightarrow> 'a \<Rightarrow>\<^sub>L real" is "\<lambda>x y. y \<bullet> x"
by (rule bounded_linear_inner_left)
declare blinfun_inner_left.rep_eq[simp]
lemma bounded_linear_blinfun_inner_left[bounded_linear]: "bounded_linear blinfun_inner_left"
by transfer (rule bounded_bilinear.flip[OF bounded_bilinear_inner])
lift_definition blinfun_scaleR_right::"real \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'a::real_normed_vector" is "( *\<^sub>R)"
by (rule bounded_linear_scaleR_right)
declare blinfun_scaleR_right.rep_eq[simp]
lemma bounded_linear_blinfun_scaleR_right[bounded_linear]: "bounded_linear blinfun_scaleR_right"
by transfer (rule bounded_bilinear_scaleR)
lift_definition blinfun_scaleR_left::"'a::real_normed_vector \<Rightarrow> real \<Rightarrow>\<^sub>L 'a" is "\<lambda>x y. y *\<^sub>R x"
by (rule bounded_linear_scaleR_left)
lemmas [simp] = blinfun_scaleR_left.rep_eq
lemma bounded_linear_blinfun_scaleR_left[bounded_linear]: "bounded_linear blinfun_scaleR_left"
by transfer (rule bounded_bilinear.flip[OF bounded_bilinear_scaleR])
lift_definition blinfun_mult_right::"'a \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'a::real_normed_algebra" is "( * )"
by (rule bounded_linear_mult_right)
declare blinfun_mult_right.rep_eq[simp]
lemma bounded_linear_blinfun_mult_right[bounded_linear]: "bounded_linear blinfun_mult_right"
by transfer (rule bounded_bilinear_mult)
lift_definition blinfun_mult_left::"'a::real_normed_algebra \<Rightarrow> 'a \<Rightarrow>\<^sub>L 'a" is "\<lambda>x y. y * x"
by (rule bounded_linear_mult_left)
lemmas [simp] = blinfun_mult_left.rep_eq
lemma bounded_linear_blinfun_mult_left[bounded_linear]: "bounded_linear blinfun_mult_left"
by transfer (rule bounded_bilinear.flip[OF bounded_bilinear_mult])
lemmas bounded_linear_function_uniform_limit_intros[uniform_limit_intros] =
bounded_linear.uniform_limit[OF bounded_linear_apply_blinfun]
bounded_linear.uniform_limit[OF bounded_linear_blinfun_apply]
bounded_linear.uniform_limit[OF bounded_linear_blinfun_matrix]
end