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Complex_L2.thy
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Complex_L2.thy
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section \<open>\<open>Complex_L2\<close> -- Hilbert space of square-summable functions\<close>
(*
Authors:
Dominique Unruh, University of Tartu, unruh@ut.ee
Jose Manuel Rodriguez Caballero, University of Tartu, jose.manuel.rodriguez.caballero@ut.ee
*)
theory Complex_L2
imports
Complex_Bounded_Linear_Function
"HOL-Analysis.L2_Norm"
"HOL-Library.Rewrite"
"HOL-Analysis.Infinite_Sum"
begin
unbundle cblinfun_notation
unbundle no_notation_blinfun_apply
subsection \<open>l2 norm of functions\<close>
definition "has_ell2_norm (x::_\<Rightarrow>complex) \<longleftrightarrow> (\<lambda>i. (x i)\<^sup>2) abs_summable_on UNIV"
lemma has_ell2_norm_bdd_above: \<open>has_ell2_norm x \<longleftrightarrow> bdd_above (sum (\<lambda>xa. norm ((x xa)\<^sup>2)) ` Collect finite)\<close>
by (simp add: has_ell2_norm_def abs_summable_bdd_above)
lemma has_ell2_norm_L2_set: "has_ell2_norm x = bdd_above (L2_set (norm o x) ` Collect finite)"
proof (rule iffI)
have \<open>mono sqrt\<close>
using monoI real_sqrt_le_mono by blast
assume \<open>has_ell2_norm x\<close>
then have *: \<open>bdd_above (sum (\<lambda>xa. norm ((x xa)\<^sup>2)) ` Collect finite)\<close>
by (subst (asm) has_ell2_norm_bdd_above)
have \<open>bdd_above ((\<lambda>F. sqrt (sum (\<lambda>xa. norm ((x xa)\<^sup>2)) F)) ` Collect finite)\<close>
using bdd_above_image_mono[OF \<open>mono sqrt\<close> *]
by (auto simp: image_image)
then show \<open>bdd_above (L2_set (norm o x) ` Collect finite)\<close>
by (auto simp: L2_set_def norm_power)
next
define p2 where \<open>p2 x = (if x < 0 then 0 else x^2)\<close> for x :: real
have \<open>mono p2\<close>
by (simp add: monoI p2_def)
have [simp]: \<open>p2 (L2_set f F) = (\<Sum>i\<in>F. (f i)\<^sup>2)\<close> for f and F :: \<open>'a set\<close>
by (smt (verit) L2_set_def L2_set_nonneg p2_def power2_less_0 real_sqrt_pow2 sum.cong sum_nonneg)
assume *: \<open>bdd_above (L2_set (norm o x) ` Collect finite)\<close>
have \<open>bdd_above (p2 ` L2_set (norm o x) ` Collect finite)\<close>
using bdd_above_image_mono[OF \<open>mono p2\<close> *]
by auto
then show \<open>has_ell2_norm x\<close>
apply (simp add: image_image has_ell2_norm_def abs_summable_bdd_above)
by (simp add: norm_power)
qed
definition ell2_norm :: \<open>('a \<Rightarrow> complex) \<Rightarrow> real\<close> where \<open>ell2_norm x = sqrt (\<Sum>\<^sub>\<infinity>i. norm (x i)^2)\<close>
lemma ell2_norm_SUP:
assumes \<open>has_ell2_norm x\<close>
shows "ell2_norm x = sqrt (SUP F\<in>{F. finite F}. sum (\<lambda>i. norm (x i)^2) F)"
using assms apply (auto simp add: ell2_norm_def has_ell2_norm_def)
apply (subst infsum_nonneg_is_SUPREMUM_real)
by (auto simp: norm_power)
lemma ell2_norm_L2_set:
assumes "has_ell2_norm x"
shows "ell2_norm x = (SUP F\<in>{F. finite F}. L2_set (norm o x) F)"
proof-
have "sqrt (\<Squnion> (sum (\<lambda>i. (cmod (x i))\<^sup>2) ` Collect finite)) =
(SUP F\<in>{F. finite F}. sqrt (\<Sum>i\<in>F. (cmod (x i))\<^sup>2))"
proof (subst continuous_at_Sup_mono)
show "mono sqrt"
by (simp add: mono_def)
show "continuous (at_left (\<Squnion> (sum (\<lambda>i. (cmod (x i))\<^sup>2) ` Collect finite))) sqrt"
using continuous_at_split isCont_real_sqrt by blast
show "sum (\<lambda>i. (cmod (x i))\<^sup>2) ` Collect finite \<noteq> {}"
by auto
show "bdd_above (sum (\<lambda>i. (cmod (x i))\<^sup>2) ` Collect finite)"
using has_ell2_norm_bdd_above[THEN iffD1, OF assms] by (auto simp: norm_power)
show "\<Squnion> (sqrt ` sum (\<lambda>i. (cmod (x i))\<^sup>2) ` Collect finite) = (SUP F\<in>Collect finite. sqrt (\<Sum>i\<in>F. (cmod (x i))\<^sup>2))"
by (metis image_image)
qed
thus ?thesis
using assms by (auto simp: ell2_norm_SUP L2_set_def)
qed
lemma has_ell2_norm_finite[simp]: "has_ell2_norm (x::'a::finite\<Rightarrow>_)"
unfolding has_ell2_norm_def by simp
lemma ell2_norm_finite:
"ell2_norm (x::'a::finite\<Rightarrow>complex) = sqrt (sum (\<lambda>i. (norm(x i))^2) UNIV)"
by (simp add: ell2_norm_def)
lemma ell2_norm_finite_L2_set: "ell2_norm (x::'a::finite\<Rightarrow>complex) = L2_set (norm o x) UNIV"
by (simp add: ell2_norm_finite L2_set_def)
lemma ell2_ket:
fixes a
defines \<open>f \<equiv> (\<lambda>i. if a = i then 1 else 0)\<close>
shows has_ell2_norm_ket: \<open>has_ell2_norm f\<close>
and ell2_norm_ket: \<open>ell2_norm f = 1\<close>
proof -
have \<open>(\<lambda>x. (f x)\<^sup>2) abs_summable_on {a}\<close>
apply (rule summable_on_finite) by simp
then show \<open>has_ell2_norm f\<close>
unfolding has_ell2_norm_def
apply (rule summable_on_cong_neutral[THEN iffD1, rotated -1])
unfolding f_def by auto
have \<open>(\<Sum>\<^sub>\<infinity>x\<in>{a}. (f x)\<^sup>2) = 1\<close>
apply (subst infsum_finite)
by (auto simp: f_def)
then show \<open>ell2_norm f = 1\<close>
unfolding ell2_norm_def
apply (subst infsum_cong_neutral[where T=\<open>{a}\<close> and g=\<open>\<lambda>x. (cmod (f x))\<^sup>2\<close>])
by (auto simp: f_def)
qed
lemma ell2_norm_geq0: \<open>ell2_norm x \<ge> 0\<close>
by (auto simp: ell2_norm_def intro!: infsum_nonneg)
lemma ell2_norm_point_bound:
assumes \<open>has_ell2_norm x\<close>
shows \<open>ell2_norm x \<ge> cmod (x i)\<close>
proof -
have \<open>(cmod (x i))\<^sup>2 = norm ((x i)\<^sup>2)\<close>
by (simp add: norm_power)
also have \<open>norm ((x i)\<^sup>2) = sum (\<lambda>i. (norm ((x i)\<^sup>2))) {i}\<close>
by auto
also have \<open>\<dots> = infsum (\<lambda>i. (norm ((x i)\<^sup>2))) {i}\<close>
by (rule infsum_finite[symmetric], simp)
also have \<open>\<dots> \<le> infsum (\<lambda>i. (norm ((x i)\<^sup>2))) UNIV\<close>
apply (rule infsum_mono_neutral)
using assms by (auto simp: has_ell2_norm_def)
also have \<open>\<dots> = (ell2_norm x)\<^sup>2\<close>
by (metis (no_types, lifting) ell2_norm_def ell2_norm_geq0 infsum_cong norm_power real_sqrt_eq_iff real_sqrt_unique)
finally show ?thesis
using ell2_norm_geq0 power2_le_imp_le by blast
qed
lemma ell2_norm_0:
assumes "has_ell2_norm x"
shows "(ell2_norm x = 0) = (x = (\<lambda>_. 0))"
proof
assume u1: "x = (\<lambda>_. 0)"
have u2: "(SUP x::'a set\<in>Collect finite. (0::real)) = 0"
if "x = (\<lambda>_. 0)"
by (metis cSUP_const empty_Collect_eq finite.emptyI)
show "ell2_norm x = 0"
unfolding ell2_norm_def
using u1 u2 by auto
next
assume norm0: "ell2_norm x = 0"
show "x = (\<lambda>_. 0)"
proof
fix i
have \<open>cmod (x i) \<le> ell2_norm x\<close>
using assms by (rule ell2_norm_point_bound)
also have \<open>\<dots> = 0\<close>
by (fact norm0)
finally show "x i = 0" by auto
qed
qed
lemma ell2_norm_smult:
assumes "has_ell2_norm x"
shows "has_ell2_norm (\<lambda>i. c * x i)" and "ell2_norm (\<lambda>i. c * x i) = cmod c * ell2_norm x"
proof -
have L2_set_mul: "L2_set (cmod \<circ> (\<lambda>i. c * x i)) F = cmod c * L2_set (cmod \<circ> x) F" for F
proof-
have "L2_set (cmod \<circ> (\<lambda>i. c * x i)) F = L2_set (\<lambda>i. (cmod c * (cmod o x) i)) F"
by (metis comp_def norm_mult)
also have "\<dots> = cmod c * L2_set (cmod o x) F"
by (metis norm_ge_zero L2_set_right_distrib)
finally show ?thesis .
qed
from assms obtain M where M: "M \<ge> L2_set (cmod o x) F" if "finite F" for F
unfolding has_ell2_norm_L2_set bdd_above_def by auto
hence "cmod c * M \<ge> L2_set (cmod o (\<lambda>i. c * x i)) F" if "finite F" for F
unfolding L2_set_mul
by (simp add: ordered_comm_semiring_class.comm_mult_left_mono that)
thus has: "has_ell2_norm (\<lambda>i. c * x i)"
unfolding has_ell2_norm_L2_set bdd_above_def using L2_set_mul[symmetric] by auto
have "ell2_norm (\<lambda>i. c * x i) = (SUP F \<in> Collect finite. (L2_set (cmod \<circ> (\<lambda>i. c * x i)) F))"
by (simp add: ell2_norm_L2_set has)
also have "\<dots> = (SUP F \<in> Collect finite. (cmod c * L2_set (cmod \<circ> x) F))"
using L2_set_mul by auto
also have "\<dots> = cmod c * ell2_norm x"
proof (subst ell2_norm_L2_set)
show "has_ell2_norm x"
by (simp add: assms)
show "(SUP F\<in>Collect finite. cmod c * L2_set (cmod \<circ> x) F) = cmod c * \<Squnion> (L2_set (cmod \<circ> x) ` Collect finite)"
proof (subst continuous_at_Sup_mono [where f = "\<lambda>x. cmod c * x"])
show "mono ((*) (cmod c))"
by (simp add: mono_def ordered_comm_semiring_class.comm_mult_left_mono)
show "continuous (at_left (\<Squnion> (L2_set (cmod \<circ> x) ` Collect finite))) ((*) (cmod c))"
proof (rule continuous_mult)
show "continuous (at_left (\<Squnion> (L2_set (cmod \<circ> x) ` Collect finite))) (\<lambda>x. cmod c)"
by simp
show "continuous (at_left (\<Squnion> (L2_set (cmod \<circ> x) ` Collect finite))) (\<lambda>x. x)"
by simp
qed
show "L2_set (cmod \<circ> x) ` Collect finite \<noteq> {}"
by auto
show "bdd_above (L2_set (cmod \<circ> x) ` Collect finite)"
by (meson assms has_ell2_norm_L2_set)
show "(SUP F\<in>Collect finite. cmod c * L2_set (cmod \<circ> x) F) = \<Squnion> ((*) (cmod c) ` L2_set (cmod \<circ> x) ` Collect finite)"
by (metis image_image)
qed
qed
finally show "ell2_norm (\<lambda>i. c * x i) = cmod c * ell2_norm x".
qed
lemma ell2_norm_triangle:
assumes "has_ell2_norm x" and "has_ell2_norm y"
shows "has_ell2_norm (\<lambda>i. x i + y i)" and "ell2_norm (\<lambda>i. x i + y i) \<le> ell2_norm x + ell2_norm y"
proof -
have triangle: "L2_set (cmod \<circ> (\<lambda>i. x i + y i)) F \<le> L2_set (cmod \<circ> x) F + L2_set (cmod \<circ> y) F"
(is "?lhs\<le>?rhs")
if "finite F" for F
proof -
have "?lhs \<le> L2_set (\<lambda>i. (cmod o x) i + (cmod o y) i) F"
proof (rule L2_set_mono)
show "(cmod \<circ> (\<lambda>i. x i + y i)) i \<le> (cmod \<circ> x) i + (cmod \<circ> y) i"
if "i \<in> F"
for i :: 'a
using that norm_triangle_ineq by auto
show "0 \<le> (cmod \<circ> (\<lambda>i. x i + y i)) i"
if "i \<in> F"
for i :: 'a
using that
by simp
qed
also have "\<dots> \<le> ?rhs"
by (rule L2_set_triangle_ineq)
finally show ?thesis .
qed
obtain Mx My where Mx: "Mx \<ge> L2_set (cmod o x) F" and My: "My \<ge> L2_set (cmod o y) F"
if "finite F" for F
using assms unfolding has_ell2_norm_L2_set bdd_above_def by auto
hence MxMy: "Mx + My \<ge> L2_set (cmod \<circ> x) F + L2_set (cmod \<circ> y) F" if "finite F" for F
using that by fastforce
hence bdd_plus: "bdd_above ((\<lambda>xa. L2_set (cmod \<circ> x) xa + L2_set (cmod \<circ> y) xa) ` Collect finite)"
unfolding bdd_above_def by auto
from MxMy have MxMy': "Mx + My \<ge> L2_set (cmod \<circ> (\<lambda>i. x i + y i)) F" if "finite F" for F
using triangle that by fastforce
thus has: "has_ell2_norm (\<lambda>i. x i + y i)"
unfolding has_ell2_norm_L2_set bdd_above_def by auto
have SUP_plus: "(SUP x\<in>A. f x + g x) \<le> (SUP x\<in>A. f x) + (SUP x\<in>A. g x)"
if notempty: "A\<noteq>{}" and bddf: "bdd_above (f`A)"and bddg: "bdd_above (g`A)"
for f g :: "'a set \<Rightarrow> real" and A
proof-
have xleq: "x \<le> (SUP x\<in>A. f x) + (SUP x\<in>A. g x)" if x: "x \<in> (\<lambda>x. f x + g x) ` A" for x
proof -
obtain a where aA: "a:A" and ax: "x = f a + g a"
using x by blast
have fa: "f a \<le> (SUP x\<in>A. f x)"
by (simp add: bddf aA cSUP_upper)
moreover have "g a \<le> (SUP x\<in>A. g x)"
by (simp add: bddg aA cSUP_upper)
ultimately have "f a + g a \<le> (SUP x\<in>A. f x) + (SUP x\<in>A. g x)" by simp
with ax show ?thesis by simp
qed
have "(\<lambda>x. f x + g x) ` A \<noteq> {}"
using notempty by auto
moreover have "x \<le> \<Squnion> (f ` A) + \<Squnion> (g ` A)"
if "x \<in> (\<lambda>x. f x + g x) ` A"
for x :: real
using that
by (simp add: xleq)
ultimately show ?thesis
by (meson bdd_above_def cSup_le_iff)
qed
have a2: "bdd_above (L2_set (cmod \<circ> x) ` Collect finite)"
by (meson assms(1) has_ell2_norm_L2_set)
have a3: "bdd_above (L2_set (cmod \<circ> y) ` Collect finite)"
by (meson assms(2) has_ell2_norm_L2_set)
have a1: "Collect finite \<noteq> {}"
by auto
have a4: "\<Squnion> (L2_set (cmod \<circ> (\<lambda>i. x i + y i)) ` Collect finite)
\<le> (SUP xa\<in>Collect finite.
L2_set (cmod \<circ> x) xa + L2_set (cmod \<circ> y) xa)"
by (metis (mono_tags, lifting) a1 bdd_plus cSUP_mono mem_Collect_eq triangle)
have "\<forall>r. \<Squnion> (L2_set (cmod \<circ> (\<lambda>a. x a + y a)) ` Collect finite) \<le> r \<or> \<not> (SUP A\<in>Collect finite. L2_set (cmod \<circ> x) A + L2_set (cmod \<circ> y) A) \<le> r"
using a4 by linarith
hence "\<Squnion> (L2_set (cmod \<circ> (\<lambda>i. x i + y i)) ` Collect finite)
\<le> \<Squnion> (L2_set (cmod \<circ> x) ` Collect finite) +
\<Squnion> (L2_set (cmod \<circ> y) ` Collect finite)"
by (metis (no_types) SUP_plus a1 a2 a3)
hence "\<Squnion> (L2_set (cmod \<circ> (\<lambda>i. x i + y i)) ` Collect finite) \<le> ell2_norm x + ell2_norm y"
by (simp add: assms(1) assms(2) ell2_norm_L2_set)
thus "ell2_norm (\<lambda>i. x i + y i) \<le> ell2_norm x + ell2_norm y"
by (simp add: ell2_norm_L2_set has)
qed
lemma ell2_norm_uminus:
assumes "has_ell2_norm x"
shows \<open>has_ell2_norm (\<lambda>i. - x i)\<close> and \<open>ell2_norm (\<lambda>i. - x i) = ell2_norm x\<close>
using assms by (auto simp: has_ell2_norm_def ell2_norm_def)
subsection \<open>The type \<open>ell2\<close> of square-summable functions\<close>
typedef 'a ell2 = "{x::'a\<Rightarrow>complex. has_ell2_norm x}"
unfolding has_ell2_norm_def by (rule exI[of _ "\<lambda>_.0"], auto)
setup_lifting type_definition_ell2
instantiation ell2 :: (type)complex_vector begin
lift_definition zero_ell2 :: "'a ell2" is "\<lambda>_. 0" by (auto simp: has_ell2_norm_def)
lift_definition uminus_ell2 :: "'a ell2 \<Rightarrow> 'a ell2" is uminus by (simp add: has_ell2_norm_def)
lift_definition plus_ell2 :: "'a ell2 \<Rightarrow> 'a ell2 \<Rightarrow> 'a ell2" is "\<lambda>f g x. f x + g x"
by (rule ell2_norm_triangle)
lift_definition minus_ell2 :: "'a ell2 \<Rightarrow> 'a ell2 \<Rightarrow> 'a ell2" is "\<lambda>f g x. f x - g x"
apply (subst add_uminus_conv_diff[symmetric])
apply (rule ell2_norm_triangle)
by (auto simp add: ell2_norm_uminus)
lift_definition scaleR_ell2 :: "real \<Rightarrow> 'a ell2 \<Rightarrow> 'a ell2" is "\<lambda>r f x. complex_of_real r * f x"
by (rule ell2_norm_smult)
lift_definition scaleC_ell2 :: "complex \<Rightarrow> 'a ell2 \<Rightarrow> 'a ell2" is "\<lambda>c f x. c * f x"
by (rule ell2_norm_smult)
instance
proof
fix a b c :: "'a ell2"
show "((*\<^sub>R) r::'a ell2 \<Rightarrow> _) = (*\<^sub>C) (complex_of_real r)" for r
apply (rule ext) apply transfer by auto
show "a + b + c = a + (b + c)"
by (transfer; rule ext; simp)
show "a + b = b + a"
by (transfer; rule ext; simp)
show "0 + a = a"
by (transfer; rule ext; simp)
show "- a + a = 0"
by (transfer; rule ext; simp)
show "a - b = a + - b"
by (transfer; rule ext; simp)
show "r *\<^sub>C (a + b) = r *\<^sub>C a + r *\<^sub>C b" for r
apply (transfer; rule ext)
by (simp add: vector_space_over_itself.scale_right_distrib)
show "(r + r') *\<^sub>C a = r *\<^sub>C a + r' *\<^sub>C a" for r r'
apply (transfer; rule ext)
by (simp add: ring_class.ring_distribs(2))
show "r *\<^sub>C r' *\<^sub>C a = (r * r') *\<^sub>C a" for r r'
by (transfer; rule ext; simp)
show "1 *\<^sub>C a = a"
by (transfer; rule ext; simp)
qed
end
instantiation ell2 :: (type)complex_normed_vector begin
lift_definition norm_ell2 :: "'a ell2 \<Rightarrow> real" is ell2_norm .
declare norm_ell2_def[code del]
definition "dist x y = norm (x - y)" for x y::"'a ell2"
definition "sgn x = x /\<^sub>R norm x" for x::"'a ell2"
definition [code del]: "uniformity = (INF e\<in>{0<..}. principal {(x::'a ell2, y). norm (x - y) < e})"
definition [code del]: "open U = (\<forall>x\<in>U. \<forall>\<^sub>F (x', y) in INF e\<in>{0<..}. principal {(x, y). norm (x - y) < e}. x' = x \<longrightarrow> y \<in> U)" for U :: "'a ell2 set"
instance
proof
fix a b :: "'a ell2"
show "dist a b = norm (a - b)"
by (simp add: dist_ell2_def)
show "sgn a = a /\<^sub>R norm a"
by (simp add: sgn_ell2_def)
show "uniformity = (INF e\<in>{0<..}. principal {(x, y). dist (x::'a ell2) y < e})"
unfolding dist_ell2_def uniformity_ell2_def by simp
show "open U = (\<forall>x\<in>U. \<forall>\<^sub>F (x', y) in uniformity. (x'::'a ell2) = x \<longrightarrow> y \<in> U)" for U :: "'a ell2 set"
unfolding uniformity_ell2_def open_ell2_def by simp_all
show "(norm a = 0) = (a = 0)"
apply transfer by (fact ell2_norm_0)
show "norm (a + b) \<le> norm a + norm b"
apply transfer by (fact ell2_norm_triangle)
show "norm (r *\<^sub>R (a::'a ell2)) = \<bar>r\<bar> * norm a" for r
and a :: "'a ell2"
apply transfer
by (simp add: ell2_norm_smult(2))
show "norm (r *\<^sub>C a) = cmod r * norm a" for r
apply transfer
by (simp add: ell2_norm_smult(2))
qed
end
lemma norm_point_bound_ell2: "norm (Rep_ell2 x i) \<le> norm x"
apply transfer
by (simp add: ell2_norm_point_bound)
lemma ell2_norm_finite_support:
assumes \<open>finite S\<close> \<open>\<And> i. i \<notin> S \<Longrightarrow> Rep_ell2 x i = 0\<close>
shows \<open>norm x = sqrt ((sum (\<lambda>i. (cmod (Rep_ell2 x i))\<^sup>2)) S)\<close>
proof (insert assms(2), transfer fixing: S)
fix x :: \<open>'a \<Rightarrow> complex\<close>
assume zero: \<open>\<And>i. i \<notin> S \<Longrightarrow> x i = 0\<close>
have \<open>ell2_norm x = sqrt (\<Sum>\<^sub>\<infinity>i. (cmod (x i))\<^sup>2)\<close>
by (auto simp: ell2_norm_def)
also have \<open>\<dots> = sqrt (\<Sum>\<^sub>\<infinity>i\<in>S. (cmod (x i))\<^sup>2)\<close>
apply (subst infsum_cong_neutral[where g=\<open>\<lambda>i. (cmod (x i))\<^sup>2\<close> and S=UNIV and T=S])
using zero by auto
also have \<open>\<dots> = sqrt (\<Sum>i\<in>S. (cmod (x i))\<^sup>2)\<close>
using \<open>finite S\<close> by simp
finally show \<open>ell2_norm x = sqrt (\<Sum>i\<in>S. (cmod (x i))\<^sup>2)\<close>
by -
qed
instantiation ell2 :: (type) complex_inner begin
lift_definition cinner_ell2 :: "'a ell2 \<Rightarrow> 'a ell2 \<Rightarrow> complex" is
"\<lambda>x y. infsum (\<lambda>i. (cnj (x i) * y i)) UNIV" .
declare cinner_ell2_def[code del]
instance
proof standard
fix x y z :: "'a ell2" fix c :: complex
show "cinner x y = cnj (cinner y x)"
proof transfer
fix x y :: "'a\<Rightarrow>complex" assume "has_ell2_norm x" and "has_ell2_norm y"
have "(\<Sum>\<^sub>\<infinity>i. cnj (x i) * y i) = (\<Sum>\<^sub>\<infinity>i. cnj (cnj (y i) * x i))"
by (metis complex_cnj_cnj complex_cnj_mult mult.commute)
also have "\<dots> = cnj (\<Sum>\<^sub>\<infinity>i. cnj (y i) * x i)"
by (metis infsum_cnj)
finally show "(\<Sum>\<^sub>\<infinity>i. cnj (x i) * y i) = cnj (\<Sum>\<^sub>\<infinity>i. cnj (y i) * x i)" .
qed
show "cinner (x + y) z = cinner x z + cinner y z"
proof transfer
fix x y z :: "'a \<Rightarrow> complex"
assume "has_ell2_norm x"
hence cnj_x: "(\<lambda>i. cnj (x i) * cnj (x i)) abs_summable_on UNIV"
by (simp del: complex_cnj_mult add: norm_mult[symmetric] complex_cnj_mult[symmetric] has_ell2_norm_def power2_eq_square)
assume "has_ell2_norm y"
hence cnj_y: "(\<lambda>i. cnj (y i) * cnj (y i)) abs_summable_on UNIV"
by (simp del: complex_cnj_mult add: norm_mult[symmetric] complex_cnj_mult[symmetric] has_ell2_norm_def power2_eq_square)
assume "has_ell2_norm z"
hence z: "(\<lambda>i. z i * z i) abs_summable_on UNIV"
by (simp add: norm_mult[symmetric] has_ell2_norm_def power2_eq_square)
have cnj_x_z:"(\<lambda>i. cnj (x i) * z i) abs_summable_on UNIV"
using cnj_x z by (rule abs_summable_product)
have cnj_y_z:"(\<lambda>i. cnj (y i) * z i) abs_summable_on UNIV"
using cnj_y z by (rule abs_summable_product)
show "(\<Sum>\<^sub>\<infinity>i. cnj (x i + y i) * z i) = (\<Sum>\<^sub>\<infinity>i. cnj (x i) * z i) + (\<Sum>\<^sub>\<infinity>i. cnj (y i) * z i)"
apply (subst infsum_add [symmetric])
using cnj_x_z cnj_y_z
by (auto simp add: summable_on_iff_abs_summable_on_complex distrib_left mult.commute)
qed
show "cinner (c *\<^sub>C x) y = cnj c * cinner x y"
proof transfer
fix x y :: "'a \<Rightarrow> complex" and c :: complex
assume "has_ell2_norm x"
hence cnj_x: "(\<lambda>i. cnj (x i) * cnj (x i)) abs_summable_on UNIV"
by (simp del: complex_cnj_mult add: norm_mult[symmetric] complex_cnj_mult[symmetric] has_ell2_norm_def power2_eq_square)
assume "has_ell2_norm y"
hence y: "(\<lambda>i. y i * y i) abs_summable_on UNIV"
by (simp add: norm_mult[symmetric] has_ell2_norm_def power2_eq_square)
have cnj_x_y:"(\<lambda>i. cnj (x i) * y i) abs_summable_on UNIV"
using cnj_x y by (rule abs_summable_product)
thus "(\<Sum>\<^sub>\<infinity>i. cnj (c * x i) * y i) = cnj c * (\<Sum>\<^sub>\<infinity>i. cnj (x i) * y i)"
by (auto simp flip: infsum_cmult_right simp add: abs_summable_summable mult.commute vector_space_over_itself.scale_left_commute)
qed
show "0 \<le> cinner x x"
proof transfer
fix x :: "'a \<Rightarrow> complex"
assume "has_ell2_norm x"
hence "(\<lambda>i. cmod (cnj (x i) * x i)) abs_summable_on UNIV"
by (simp add: norm_mult has_ell2_norm_def power2_eq_square)
hence "(\<lambda>i. cnj (x i) * x i) abs_summable_on UNIV"
by auto
hence sum: "(\<lambda>i. cnj (x i) * x i) abs_summable_on UNIV"
unfolding has_ell2_norm_def power2_eq_square.
have "0 = (\<Sum>\<^sub>\<infinity>i::'a. 0)" by auto
also have "\<dots> \<le> (\<Sum>\<^sub>\<infinity>i. cnj (x i) * x i)"
apply (rule infsum_mono_complex)
by (auto simp add: abs_summable_summable sum)
finally show "0 \<le> (\<Sum>\<^sub>\<infinity>i. cnj (x i) * x i)" by assumption
qed
show "(cinner x x = 0) = (x = 0)"
proof (transfer, auto)
fix x :: "'a \<Rightarrow> complex"
assume "has_ell2_norm x"
hence "(\<lambda>i::'a. cmod (cnj (x i) * x i)) abs_summable_on UNIV"
by (smt (verit, del_insts) complex_mod_mult_cnj has_ell2_norm_def mult.commute norm_ge_zero norm_power real_norm_def summable_on_cong)
hence cmod_x2: "(\<lambda>i. cnj (x i) * x i) abs_summable_on UNIV"
unfolding has_ell2_norm_def power2_eq_square
by simp
assume eq0: "(\<Sum>\<^sub>\<infinity>i. cnj (x i) * x i) = 0"
show "x = (\<lambda>_. 0)"
proof (rule ccontr)
assume "x \<noteq> (\<lambda>_. 0)"
then obtain i where "x i \<noteq> 0" by auto
hence "0 < cnj (x i) * x i"
by (metis le_less cnj_x_x_geq0 complex_cnj_zero_iff vector_space_over_itself.scale_eq_0_iff)
also have "\<dots> = (\<Sum>\<^sub>\<infinity>i\<in>{i}. cnj (x i) * x i)" by auto
also have "\<dots> \<le> (\<Sum>\<^sub>\<infinity>i. cnj (x i) * x i)"
apply (rule infsum_mono_neutral_complex)
by (auto simp add: abs_summable_summable cmod_x2)
also from eq0 have "\<dots> = 0" by assumption
finally show False by simp
qed
qed
show "norm x = sqrt (cmod (cinner x x))"
proof transfer
fix x :: "'a \<Rightarrow> complex"
assume x: "has_ell2_norm x"
have "(\<lambda>i::'a. cmod (x i) * cmod (x i)) abs_summable_on UNIV \<Longrightarrow>
(\<lambda>i::'a. cmod (cnj (x i) * x i)) abs_summable_on UNIV"
by (simp add: norm_mult has_ell2_norm_def power2_eq_square)
hence sum: "(\<lambda>i. cnj (x i) * x i) abs_summable_on UNIV"
by (metis (no_types, lifting) complex_mod_mult_cnj has_ell2_norm_def mult.commute norm_power summable_on_cong x)
from x have "ell2_norm x = sqrt (\<Sum>\<^sub>\<infinity>i. (cmod (x i))\<^sup>2)"
unfolding ell2_norm_def by simp
also have "\<dots> = sqrt (\<Sum>\<^sub>\<infinity>i. cmod (cnj (x i) * x i))"
unfolding norm_complex_def power2_eq_square by auto
also have "\<dots> = sqrt (cmod (\<Sum>\<^sub>\<infinity>i. cnj (x i) * x i))"
by (auto simp: infsum_cmod abs_summable_summable sum)
finally show "ell2_norm x = sqrt (cmod (\<Sum>\<^sub>\<infinity>i. cnj (x i) * x i))" by assumption
qed
qed
end
instance ell2 :: (type) chilbert_space
proof
fix X :: \<open>nat \<Rightarrow> 'a ell2\<close>
define x where \<open>x n a = Rep_ell2 (X n) a\<close> for n a
have [simp]: \<open>has_ell2_norm (x n)\<close> for n
using Rep_ell2 x_def[abs_def] by simp
assume \<open>Cauchy X\<close>
moreover have "dist (x n a) (x m a) \<le> dist (X n) (X m)" for n m a
by (metis Rep_ell2 x_def dist_norm ell2_norm_point_bound mem_Collect_eq minus_ell2.rep_eq norm_ell2.rep_eq)
ultimately have \<open>Cauchy (\<lambda>n. x n a)\<close> for a
by (meson Cauchy_def le_less_trans)
then obtain l where x_lim: \<open>(\<lambda>n. x n a) \<longlonglongrightarrow> l a\<close> for a
apply atomize_elim apply (rule choice)
by (simp add: convergent_eq_Cauchy)
define L where \<open>L = Abs_ell2 l\<close>
define normF where \<open>normF F x = L2_set (cmod \<circ> x) F\<close> for F :: \<open>'a set\<close> and x
have normF_triangle: \<open>normF F (\<lambda>a. x a + y a) \<le> normF F x + normF F y\<close> if \<open>finite F\<close> for F x y
proof -
have \<open>normF F (\<lambda>a. x a + y a) = L2_set (\<lambda>a. cmod (x a + y a)) F\<close>
by (metis (mono_tags, lifting) L2_set_cong comp_apply normF_def)
also have \<open>\<dots> \<le> L2_set (\<lambda>a. cmod (x a) + cmod (y a)) F\<close>
by (meson L2_set_mono norm_ge_zero norm_triangle_ineq)
also have \<open>\<dots> \<le> L2_set (\<lambda>a. cmod (x a)) F + L2_set (\<lambda>a. cmod (y a)) F\<close>
by (simp add: L2_set_triangle_ineq)
also have \<open>\<dots> \<le> normF F x + normF F y\<close>
by (smt (verit, best) L2_set_cong normF_def comp_apply)
finally show ?thesis
by -
qed
have normF_negate: \<open>normF F (\<lambda>a. - x a) = normF F x\<close> if \<open>finite F\<close> for F x
unfolding normF_def o_def by simp
have normF_ell2norm: \<open>normF F x \<le> ell2_norm x\<close> if \<open>finite F\<close> and \<open>has_ell2_norm x\<close> for F x
apply (auto intro!: cSUP_upper2[where x=F] simp: that normF_def ell2_norm_L2_set)
by (meson has_ell2_norm_L2_set that(2))
note Lim_bounded2[rotated, rule_format, trans]
from \<open>Cauchy X\<close>
obtain I where cauchyX: \<open>norm (X n - X m) \<le> \<epsilon>\<close> if \<open>\<epsilon>>0\<close> \<open>n\<ge>I \<epsilon>\<close> \<open>m\<ge>I \<epsilon>\<close> for \<epsilon> n m
by (metis Cauchy_def dist_norm less_eq_real_def)
have normF_xx: \<open>normF F (\<lambda>a. x n a - x m a) \<le> \<epsilon>\<close> if \<open>finite F\<close> \<open>\<epsilon>>0\<close> \<open>n\<ge>I \<epsilon>\<close> \<open>m\<ge>I \<epsilon>\<close> for \<epsilon> n m F
apply (subst asm_rl[of \<open>(\<lambda>a. x n a - x m a) = Rep_ell2 (X n - X m)\<close>])
apply (simp add: x_def minus_ell2.rep_eq)
using that cauchyX by (metis Rep_ell2 mem_Collect_eq normF_ell2norm norm_ell2.rep_eq order_trans)
have normF_xl_lim: \<open>(\<lambda>m. normF F (\<lambda>a. x m a - l a)) \<longlonglongrightarrow> 0\<close> if \<open>finite F\<close> for F
proof -
have \<open>(\<lambda>xa. cmod (x xa m - l m)) \<longlonglongrightarrow> 0\<close> for m
using x_lim by (simp add: LIM_zero_iff tendsto_norm_zero)
then have \<open>(\<lambda>m. \<Sum>i\<in>F. ((cmod \<circ> (\<lambda>a. x m a - l a)) i)\<^sup>2) \<longlonglongrightarrow> 0\<close>
by (auto intro: tendsto_null_sum)
then show ?thesis
unfolding normF_def L2_set_def
using tendsto_real_sqrt by force
qed
have normF_xl: \<open>normF F (\<lambda>a. x n a - l a) \<le> \<epsilon>\<close>
if \<open>n \<ge> I \<epsilon>\<close> and \<open>\<epsilon> > 0\<close> and \<open>finite F\<close> for n \<epsilon> F
proof -
have \<open>normF F (\<lambda>a. x n a - l a) - \<epsilon> \<le> normF F (\<lambda>a. x n a - x m a) + normF F (\<lambda>a. x m a - l a) - \<epsilon>\<close> for m
using normF_triangle[OF \<open>finite F\<close>, where x=\<open>(\<lambda>a. x n a - x m a)\<close> and y=\<open>(\<lambda>a. x m a - l a)\<close>]
by auto
also have \<open>\<dots> m \<le> normF F (\<lambda>a. x m a - l a)\<close> if \<open>m \<ge> I \<epsilon>\<close> for m
using normF_xx[OF \<open>finite F\<close> \<open>\<epsilon>>0\<close> \<open>n \<ge> I \<epsilon>\<close> \<open>m \<ge> I \<epsilon>\<close>]
by auto
also have \<open>(\<lambda>m. \<dots> m) \<longlonglongrightarrow> 0\<close>
using \<open>finite F\<close> by (rule normF_xl_lim)
finally show ?thesis
by auto
qed
have \<open>normF F l \<le> 1 + normF F (x (I 1))\<close> if [simp]: \<open>finite F\<close> for F
using normF_xl[where F=F and \<epsilon>=1 and n=\<open>I 1\<close>]
using normF_triangle[where F=F and x=\<open>x (I 1)\<close> and y=\<open>\<lambda>a. l a - x (I 1) a\<close>]
using normF_negate[where F=F and x=\<open>(\<lambda>a. x (I 1) a - l a)\<close>]
by auto
also have \<open>\<dots> F \<le> 1 + ell2_norm (x (I 1))\<close> if \<open>finite F\<close> for F
using normF_ell2norm that by simp
finally have [simp]: \<open>has_ell2_norm l\<close>
unfolding has_ell2_norm_L2_set
by (auto intro!: bdd_aboveI simp flip: normF_def)
then have \<open>l = Rep_ell2 L\<close>
by (simp add: Abs_ell2_inverse L_def)
have [simp]: \<open>has_ell2_norm (\<lambda>a. x n a - l a)\<close> for n
apply (subst diff_conv_add_uminus)
apply (rule ell2_norm_triangle)
by (auto intro!: ell2_norm_uminus)
from normF_xl have ell2norm_xl: \<open>ell2_norm (\<lambda>a. x n a - l a) \<le> \<epsilon>\<close>
if \<open>n \<ge> I \<epsilon>\<close> and \<open>\<epsilon> > 0\<close> for n \<epsilon>
apply (subst ell2_norm_L2_set)
using that by (auto intro!: cSUP_least simp: normF_def)
have \<open>norm (X n - L) \<le> \<epsilon>\<close> if \<open>n \<ge> I \<epsilon>\<close> and \<open>\<epsilon> > 0\<close> for n \<epsilon>
using ell2norm_xl[OF that]
by (simp add: x_def norm_ell2.rep_eq \<open>l = Rep_ell2 L\<close> minus_ell2.rep_eq)
then have \<open>X \<longlonglongrightarrow> L\<close>
unfolding tendsto_iff
apply (auto simp: dist_norm eventually_sequentially)
by (meson field_lbound_gt_zero le_less_trans)
then show \<open>convergent X\<close>
by (rule convergentI)
qed
instantiation ell2 :: (CARD_1) complex_algebra_1
begin
lift_definition one_ell2 :: "'a ell2" is "\<lambda>_. 1" by simp
lift_definition times_ell2 :: "'a ell2 \<Rightarrow> 'a ell2 \<Rightarrow> 'a ell2" is "\<lambda>a b x. a x * b x"
by simp
instance
proof
fix a b c :: "'a ell2" and r :: complex
show "a * b * c = a * (b * c)"
by (transfer, auto)
show "(a + b) * c = a * c + b * c"
apply (transfer, rule ext)
by (simp add: distrib_left mult.commute)
show "a * (b + c) = a * b + a * c"
apply transfer
by (simp add: ring_class.ring_distribs(1))
show "r *\<^sub>C a * b = r *\<^sub>C (a * b)"
by (transfer, auto)
show "(a::'a ell2) * r *\<^sub>C b = r *\<^sub>C (a * b)"
by (transfer, auto)
show "1 * a = a"
by (transfer, rule ext, auto)
show "a * 1 = a"
by (transfer, rule ext, auto)
show "(0::'a ell2) \<noteq> 1"
apply transfer
by (meson zero_neq_one)
qed
end
instantiation ell2 :: (CARD_1) field begin
lift_definition divide_ell2 :: "'a ell2 \<Rightarrow> 'a ell2 \<Rightarrow> 'a ell2" is "\<lambda>a b x. a x / b x"
by simp
lift_definition inverse_ell2 :: "'a ell2 \<Rightarrow> 'a ell2" is "\<lambda>a x. inverse (a x)"
by simp
instance
proof (intro_classes; transfer)
fix a :: "'a \<Rightarrow> complex"
assume "a \<noteq> (\<lambda>_. 0)"
then obtain y where ay: "a y \<noteq> 0"
by auto
show "(\<lambda>x. inverse (a x) * a x) = (\<lambda>_. 1)"
proof (rule ext)
fix x
have "x = y"
by auto
with ay have "a x \<noteq> 0"
by metis
then show "inverse (a x) * a x = 1"
by auto
qed
qed (auto simp add: divide_complex_def mult.commute ring_class.ring_distribs)
end
subsection \<open>Orthogonality\<close>
lemma ell2_pointwise_ortho:
assumes \<open>\<And> i. Rep_ell2 x i = 0 \<or> Rep_ell2 y i = 0\<close>
shows \<open>is_orthogonal x y\<close>
using assms apply transfer
by (simp add: infsum_0)
subsection \<open>Truncated vectors\<close>
lift_definition trunc_ell2:: \<open>'a set \<Rightarrow> 'a ell2 \<Rightarrow> 'a ell2\<close>
is \<open>\<lambda> S x. (\<lambda> i. (if i \<in> S then x i else 0))\<close>
proof (rename_tac S x)
fix x :: \<open>'a \<Rightarrow> complex\<close> and S :: \<open>'a set\<close>
assume \<open>has_ell2_norm x\<close>
then have \<open>(\<lambda>i. (x i)\<^sup>2) abs_summable_on UNIV\<close>
unfolding has_ell2_norm_def by -
then have \<open>(\<lambda>i. (x i)\<^sup>2) abs_summable_on S\<close>
using summable_on_subset_banach by blast
then have \<open>(\<lambda>xa. (if xa \<in> S then x xa else 0)\<^sup>2) abs_summable_on UNIV\<close>
apply (rule summable_on_cong_neutral[THEN iffD1, rotated -1])
by auto
then show \<open>has_ell2_norm (\<lambda>i. if i \<in> S then x i else 0)\<close>
unfolding has_ell2_norm_def by -
qed
lemma trunc_ell2_empty[simp]: \<open>trunc_ell2 {} x = 0\<close>
apply transfer by simp
lemma norm_id_minus_trunc_ell2:
\<open>(norm (x - trunc_ell2 S x))^2 = (norm x)^2 - (norm (trunc_ell2 S x))^2\<close>
proof-
have \<open>Rep_ell2 (trunc_ell2 S x) i = 0 \<or> Rep_ell2 (x - trunc_ell2 S x) i = 0\<close> for i
apply transfer
by auto
hence \<open>\<langle> (trunc_ell2 S x), (x - trunc_ell2 S x) \<rangle> = 0\<close>
using ell2_pointwise_ortho by blast
hence \<open>(norm x)^2 = (norm (trunc_ell2 S x))^2 + (norm (x - trunc_ell2 S x))^2\<close>
using pythagorean_theorem by fastforce
thus ?thesis by simp
qed
lemma norm_trunc_ell2_finite:
\<open>finite S \<Longrightarrow> (norm (trunc_ell2 S x)) = sqrt ((sum (\<lambda>i. (cmod (Rep_ell2 x i))\<^sup>2)) S)\<close>
proof-
assume \<open>finite S\<close>
moreover have \<open>\<And> i. i \<notin> S \<Longrightarrow> Rep_ell2 ((trunc_ell2 S x)) i = 0\<close>
by (simp add: trunc_ell2.rep_eq)
ultimately have \<open>(norm (trunc_ell2 S x)) = sqrt ((sum (\<lambda>i. (cmod (Rep_ell2 ((trunc_ell2 S x)) i))\<^sup>2)) S)\<close>
using ell2_norm_finite_support
by blast
moreover have \<open>\<And> i. i \<in> S \<Longrightarrow> Rep_ell2 ((trunc_ell2 S x)) i = Rep_ell2 x i\<close>
by (simp add: trunc_ell2.rep_eq)
ultimately show ?thesis by simp
qed
lemma trunc_ell2_lim_at_UNIV:
\<open>((\<lambda>S. trunc_ell2 S \<psi>) \<longlongrightarrow> \<psi>) (finite_subsets_at_top UNIV)\<close>
proof -
define f where \<open>f i = (cmod (Rep_ell2 \<psi> i))\<^sup>2\<close> for i
have has: \<open>has_ell2_norm (Rep_ell2 \<psi>)\<close>
using Rep_ell2 by blast
then have summable: "f abs_summable_on UNIV"
by (smt (verit, del_insts) f_def has_ell2_norm_def norm_ge_zero norm_power real_norm_def summable_on_cong)
have \<open>norm \<psi> = (ell2_norm (Rep_ell2 \<psi>))\<close>
apply transfer by simp
also have \<open>\<dots> = sqrt (infsum f UNIV)\<close>
by (simp add: ell2_norm_def f_def[symmetric])
finally have norm\<psi>: \<open>norm \<psi> = sqrt (infsum f UNIV)\<close>
by -
have norm_trunc: \<open>norm (trunc_ell2 S \<psi>) = sqrt (sum f S)\<close> if \<open>finite S\<close> for S
using f_def that norm_trunc_ell2_finite by fastforce
have \<open>(sum f \<longlongrightarrow> infsum f UNIV) (finite_subsets_at_top UNIV)\<close>
using f_def[abs_def] infsum_tendsto local.summable by fastforce
then have \<open>((\<lambda>S. sqrt (sum f S)) \<longlongrightarrow> sqrt (infsum f UNIV)) (finite_subsets_at_top UNIV)\<close>
using tendsto_real_sqrt by blast
then have \<open>((\<lambda>S. norm (trunc_ell2 S \<psi>)) \<longlongrightarrow> norm \<psi>) (finite_subsets_at_top UNIV)\<close>
apply (subst tendsto_cong[where g=\<open>\<lambda>S. sqrt (sum f S)\<close>])
by (auto simp add: eventually_finite_subsets_at_top_weakI norm_trunc norm\<psi>)
then have \<open>((\<lambda>S. (norm (trunc_ell2 S \<psi>))\<^sup>2) \<longlongrightarrow> (norm \<psi>)\<^sup>2) (finite_subsets_at_top UNIV)\<close>
by (simp add: tendsto_power)
then have \<open>((\<lambda>S. (norm \<psi>)\<^sup>2 - (norm (trunc_ell2 S \<psi>))\<^sup>2) \<longlongrightarrow> 0) (finite_subsets_at_top UNIV)\<close>
apply (rule tendsto_diff[where a=\<open>(norm \<psi>)^2\<close> and b=\<open>(norm \<psi>)^2\<close>, simplified, rotated])
by auto
then have \<open>((\<lambda>S. (norm (\<psi> - trunc_ell2 S \<psi>))\<^sup>2) \<longlongrightarrow> 0) (finite_subsets_at_top UNIV)\<close>
unfolding norm_id_minus_trunc_ell2 by simp
then have \<open>((\<lambda>S. norm (\<psi> - trunc_ell2 S \<psi>)) \<longlongrightarrow> 0) (finite_subsets_at_top UNIV)\<close>
by auto
then have \<open>((\<lambda>S. \<psi> - trunc_ell2 S \<psi>) \<longlongrightarrow> 0) (finite_subsets_at_top UNIV)\<close>
by (rule tendsto_norm_zero_cancel)
then show ?thesis
apply (rule Lim_transform2[where f=\<open>\<lambda>_. \<psi>\<close>, rotated])
by simp
qed
subsection \<open>Kets and bras\<close>
lift_definition ket :: "'a \<Rightarrow> 'a ell2" is "\<lambda>x y. if x=y then 1 else 0"
by (rule has_ell2_norm_ket)
abbreviation bra :: "'a \<Rightarrow> (_,complex) cblinfun" where "bra i \<equiv> vector_to_cblinfun (ket i)*" for i
instance ell2 :: (type) not_singleton
proof standard
have "ket undefined \<noteq> (0::'a ell2)"
proof transfer
show "(\<lambda>y. if (undefined::'a) = y then 1::complex else 0) \<noteq> (\<lambda>_. 0)"
by (meson one_neq_zero)
qed
thus \<open>\<exists>x y::'a ell2. x \<noteq> y\<close>
by blast
qed
lemma cinner_ket_left: \<open>\<langle>ket i, \<psi>\<rangle> = Rep_ell2 \<psi> i\<close>
apply (transfer fixing: i)
apply (subst infsum_cong_neutral[where T=\<open>{i}\<close>])
by auto
lemma cinner_ket_right: \<open>\<langle>\<psi>, ket i\<rangle> = cnj (Rep_ell2 \<psi> i)\<close>
apply (transfer fixing: i)
apply (subst infsum_cong_neutral[where T=\<open>{i}\<close>])
by auto
lemma cinner_ket_eqI:
assumes \<open>\<And>i. cinner (ket i) \<psi> = cinner (ket i) \<phi>\<close>
shows \<open>\<psi> = \<phi>\<close>
by (metis Rep_ell2_inject assms cinner_ket_left ext)
lemma norm_ket[simp]: "norm (ket i) = 1"
apply transfer by (rule ell2_norm_ket)
lemma cinner_ket_same[simp]:
\<open>\<langle>ket i, ket i\<rangle> = 1\<close>
proof-
have \<open>norm (ket i) = 1\<close>
by simp
hence \<open>sqrt (cmod \<langle>ket i, ket i\<rangle>) = 1\<close>
by (metis norm_eq_sqrt_cinner)
hence \<open>cmod \<langle>ket i, ket i\<rangle> = 1\<close>
using real_sqrt_eq_1_iff by blast
moreover have \<open>\<langle>ket i, ket i\<rangle> = cmod \<langle>ket i, ket i\<rangle>\<close>
proof-
have \<open>\<langle>ket i, ket i\<rangle> \<in> \<real>\<close>
by (simp add: cinner_real)
thus ?thesis
by (metis cinner_ge_zero complex_of_real_cmod)
qed
ultimately show ?thesis by simp
qed
lemma orthogonal_ket[simp]:
\<open>is_orthogonal (ket i) (ket j) \<longleftrightarrow> i \<noteq> j\<close>
by (simp add: cinner_ket_left ket.rep_eq)
lemma cinner_ket: \<open>\<langle>ket i, ket j\<rangle> = (if i=j then 1 else 0)\<close>
by (simp add: cinner_ket_left ket.rep_eq)
lemma ket_injective[simp]: \<open>ket i = ket j \<longleftrightarrow> i = j\<close>
by (metis cinner_ket one_neq_zero)
lemma inj_ket[simp]: \<open>inj ket\<close>
by (simp add: inj_on_def)
lemma trunc_ell2_ket_cspan:
\<open>trunc_ell2 S x \<in> (cspan (range ket))\<close> if \<open>finite S\<close>
proof (use that in induction)
case empty
then show ?case
by (auto intro: complex_vector.span_zero)
next
case (insert a F)
from insert.hyps have \<open>trunc_ell2 (insert a F) x = trunc_ell2 F x + Rep_ell2 x a *\<^sub>C ket a\<close>
apply (transfer fixing: F a)
by auto
with insert.IH
show ?case
by (simp add: complex_vector.span_add_eq complex_vector.span_base complex_vector.span_scale)
qed
lemma closed_cspan_range_ket[simp]:
\<open>closure (cspan (range ket)) = UNIV\<close>
proof (intro set_eqI iffI UNIV_I closure_approachable[THEN iffD2] allI impI)
fix \<psi> :: \<open>'a ell2\<close>
fix e :: real assume \<open>e > 0\<close>
have \<open>((\<lambda>S. trunc_ell2 S \<psi>) \<longlongrightarrow> \<psi>) (finite_subsets_at_top UNIV)\<close>
by (rule trunc_ell2_lim_at_UNIV)
then obtain F where \<open>finite F\<close> and \<open>dist (trunc_ell2 F \<psi>) \<psi> < e\<close>
apply (drule_tac tendstoD[OF _ \<open>e > 0\<close>])
by (auto dest: simp: eventually_finite_subsets_at_top)
moreover have \<open>trunc_ell2 F \<psi> \<in> cspan (range ket)\<close>
using \<open>finite F\<close> trunc_ell2_ket_cspan by blast
ultimately show \<open>\<exists>\<phi>\<in>cspan (range ket). dist \<phi> \<psi> < e\<close>
by auto
qed
lemma ccspan_range_ket[simp]: "ccspan (range ket) = (top::('a ell2 ccsubspace))"
proof-
have \<open>closure (complex_vector.span (range ket)) = (UNIV::'a ell2 set)\<close>
using Complex_L2.closed_cspan_range_ket by blast
thus ?thesis
by (simp add: ccspan.abs_eq top_ccsubspace.abs_eq)
qed
lemma cspan_range_ket_finite[simp]: "cspan (range ket :: 'a::finite ell2 set) = UNIV"
by (metis closed_cspan_range_ket closure_finite_cspan finite_class.finite_UNIV finite_imageI)
instance ell2 :: (finite) cfinite_dim
proof
define basis :: \<open>'a ell2 set\<close> where \<open>basis = range ket\<close>
have \<open>finite basis\<close>
unfolding basis_def by simp
moreover have \<open>cspan basis = UNIV\<close>
by (simp add: basis_def)
ultimately show \<open>\<exists>basis::'a ell2 set. finite basis \<and> cspan basis = UNIV\<close>
by auto
qed
instantiation ell2 :: (enum) onb_enum begin
definition "canonical_basis_ell2 = map ket Enum.enum"
instance
proof
show "distinct (canonical_basis::'a ell2 list)"
proof-
have \<open>finite (UNIV::'a set)\<close>
by simp
have \<open>distinct (enum_class.enum::'a list)\<close>
using enum_distinct by blast
moreover have \<open>inj_on ket (set enum_class.enum)\<close>
by (meson inj_onI ket_injective)
ultimately show ?thesis
unfolding canonical_basis_ell2_def
using distinct_map
by blast
qed
show "is_ortho_set (set (canonical_basis::'a ell2 list))"
apply (auto simp: canonical_basis_ell2_def enum_UNIV)
by (smt (z3) norm_ket f_inv_into_f is_ortho_set_def orthogonal_ket norm_zero)
show "cindependent (set (canonical_basis::'a ell2 list))"
apply (auto simp: canonical_basis_ell2_def enum_UNIV)
by (smt (verit, best) norm_ket f_inv_into_f is_ortho_set_def is_ortho_set_cindependent orthogonal_ket norm_zero)
show "cspan (set (canonical_basis::'a ell2 list)) = UNIV"
by (auto simp: canonical_basis_ell2_def enum_UNIV)
show "norm (x::'a ell2) = 1"
if "(x::'a ell2) \<in> set canonical_basis"
for x :: "'a ell2"
using that unfolding canonical_basis_ell2_def
by auto
qed
end
lemma canonical_basis_length_ell2[code_unfold, simp]:
"length (canonical_basis ::'a::enum ell2 list) = CARD('a)"
unfolding canonical_basis_ell2_def apply simp
using card_UNIV_length_enum by metis
lemma ket_canonical_basis: "ket x = canonical_basis ! enum_idx x"
proof-
have "x = (enum_class.enum::'a list) ! enum_idx x"
using enum_idx_correct[where i = x] by simp
hence p1: "ket x = ket ((enum_class.enum::'a list) ! enum_idx x)"
by simp
have "enum_idx x < length (enum_class.enum::'a list)"
using enum_idx_bound[where x = x].
hence "(map ket (enum_class.enum::'a list)) ! enum_idx x
= ket ((enum_class.enum::'a list) ! enum_idx x)"
by auto
thus ?thesis
unfolding canonical_basis_ell2_def using p1 by auto
qed
lemma clinear_equal_ket:
fixes f g :: \<open>'a::finite ell2 \<Rightarrow> _\<close>
assumes \<open>clinear f\<close>
assumes \<open>clinear g\<close>
assumes \<open>\<And>i. f (ket i) = g (ket i)\<close>
shows \<open>f = g\<close>
apply (rule ext)
apply (rule complex_vector.linear_eq_on_span[where f=f and g=g and B=\<open>range ket\<close>])
using assms by auto
lemma equal_ket:
fixes A B :: \<open>('a ell2, 'b::complex_normed_vector) cblinfun\<close>
assumes \<open>\<And> x. cblinfun_apply A (ket x) = cblinfun_apply B (ket x)\<close>
shows \<open>A = B\<close>
apply (rule cblinfun_eq_gen_eqI[where G=\<open>range ket\<close>])
using assms by auto
lemma antilinear_equal_ket:
fixes f g :: \<open>'a::finite ell2 \<Rightarrow> _\<close>
assumes \<open>antilinear f\<close>
assumes \<open>antilinear g\<close>
assumes \<open>\<And>i. f (ket i) = g (ket i)\<close>
shows \<open>f = g\<close>
proof -
have [simp]: \<open>clinear (f \<circ> from_conjugate_space)\<close>
apply (rule antilinear_o_antilinear)
using assms by (simp_all add: antilinear_from_conjugate_space)
have [simp]: \<open>clinear (g \<circ> from_conjugate_space)\<close>
apply (rule antilinear_o_antilinear)
using assms by (simp_all add: antilinear_from_conjugate_space)
have [simp]: \<open>cspan (to_conjugate_space ` (range ket :: 'a ell2 set)) = UNIV\<close>
by simp
have "f o from_conjugate_space = g o from_conjugate_space"
apply (rule ext)
apply (rule complex_vector.linear_eq_on_span[where f="f o from_conjugate_space" and g="g o from_conjugate_space" and B=\<open>to_conjugate_space ` range ket\<close>])
apply (simp, simp)
using assms(3) by (auto simp: to_conjugate_space_inverse)
then show "f = g"
by (smt (verit) UNIV_I from_conjugate_space_inverse surj_def surj_fun_eq to_conjugate_space_inject)
qed
lemma cinner_ket_adjointI: