(* Author: Sébastien Gouëzel sebastien.gouezel@univ-rennes1.fr License: BSD *) section ‹Additions to the library› theory Library_Complements imports "HOL-Analysis.Analysis" "HOL-Cardinals.Cardinal_Order_Relation" begin subsection ‹Mono intros› text ‹We have a lot of (large) inequalities to prove. It is very convenient to have a set of introduction rules for this purpose (a lot should be added to it, I have put here all the ones I needed). The typical use case is when one wants to prove some inequality, say $ \exp (x*x) \leq y + \exp(1 + z * z + y)$, assuming $y \geq 0$ and $0 \leq x \leq z$. One would write it has \begin{verbatim} have "0 + \exp(0 + x * x + 0) < = y + \exp(1 + z * z + y)" using `y > = 0` `x < = z` by (intro mono_intros) \end{verbatim} When the left and right hand terms are written in completely analogous ways as above, then the introduction rules (that contain monotonicity of addition, of the exponential, and so on) reduce this to comparison of elementary terms in the formula. This is a very naive strategy, that fails in many situations, but that is very efficient when used correctly. › named_theorems mono_intros "structural introduction rules to prove inequalities" declare le_imp_neg_le [mono_intros] declare add_left_mono [mono_intros] declare add_right_mono [mono_intros] declare add_strict_left_mono [mono_intros] declare add_strict_right_mono [mono_intros] declare add_mono [mono_intros] declare add_less_le_mono [mono_intros] declare diff_right_mono [mono_intros] declare diff_left_mono [mono_intros] declare diff_mono [mono_intros] declare mult_left_mono [mono_intros] declare mult_right_mono [mono_intros] declare mult_mono [mono_intros] declare max.mono [mono_intros] declare min.mono [mono_intros] declare power_mono [mono_intros] declare ln_ge_zero [mono_intros] declare ln_le_minus_one [mono_intros] declare ennreal_minus_mono [mono_intros] declare ennreal_leI [mono_intros] declare e2ennreal_mono [mono_intros] declare enn2ereal_nonneg [mono_intros] declare zero_le [mono_intros] declare top_greatest [mono_intros] declare bot_least [mono_intros] declare dist_triangle [mono_intros] declare dist_triangle2 [mono_intros] declare dist_triangle3 [mono_intros] declare exp_ge_add_one_self [mono_intros] declare exp_gt_one [mono_intros] declare exp_less_mono [mono_intros] declare dist_triangle [mono_intros] declare abs_triangle_ineq [mono_intros] declare abs_triangle_ineq2 [mono_intros] declare abs_triangle_ineq2_sym [mono_intros] declare abs_triangle_ineq3 [mono_intros] declare abs_triangle_ineq4 [mono_intros] declare Liminf_le_Limsup [mono_intros] declare ereal_liminf_add_mono [mono_intros] declare le_of_int_ceiling [mono_intros] declare ereal_minus_mono [mono_intros] declare infdist_triangle [mono_intros] declare divide_right_mono [mono_intros] declare self_le_power [mono_intros] lemma ln_le_cancelI [mono_intros]: assumes "(0::real) < x" "x ≤ y" shows "ln x ≤ ln y" using assms by auto lemma exp_le_cancelI [mono_intros]: assumes "x ≤ (y::real)" shows "exp x ≤ exp y" using assms by simp lemma mult_ge1_mono [mono_intros]: assumes "a ≥ (0::'a::linordered_idom)" "b ≥ 1" shows "a ≤ a * b" "a ≤ b * a" using assms mult_le_cancel_left1 mult_le_cancel_right1 by force+ text ‹A few convexity inequalities we will need later on.› lemma xy_le_uxx_vyy [mono_intros]: assumes "u > 0" "u * v = (1::real)" shows "x * y ≤ u * x^2/2 + v * y^2/2" proof - have "v > 0" using assms by (metis (full_types) dual_order.strict_implies_order le_less_linear mult_nonneg_nonpos not_one_le_zero) then have *: "sqrt u * sqrt v = 1" using assms by (metis real_sqrt_mult real_sqrt_one) have "(sqrt u * x - sqrt v * y)^2 ≥ 0" by auto then have "u * x^2 + v * y^2 - 2 * 1 * x * y ≥ 0" unfolding power2_eq_square *[symmetric] using ‹u > 0› ‹v > 0› by (auto simp add: algebra_simps) then show ?thesis by (auto simp add: algebra_simps divide_simps) qed lemma xy_le_xx_yy [mono_intros]: "x * y ≤ x^2/2 + y^2/2" for x y::real using xy_le_uxx_vyy[of 1 1] by auto lemma ln_squared_bound [mono_intros]: "(ln x)^2 ≤ 2 * x - 2" if "x ≥ 1" for x::real proof - define f where "f = (λx::real. 2 * x - 2 - ln x * ln x)" have *: "DERIV f x :> 2 - 2 * ln x / x" if "x > 0" for x::real unfolding f_def using that by (auto intro!: derivative_eq_intros) have "f 1 ≤ f x" if "x ≥ 1" for x proof (rule DERIV_nonneg_imp_nondecreasing[OF that]) fix t::real assume "t ≥ 1" show "∃y. (f has_real_derivative y) (at t) ∧ 0 ≤ y" apply (rule exI[of _ "2 - 2 * ln t / t"]) using *[of t] ‹t ≥ 1› by (auto simp add: divide_simps ln_bound) qed then show ?thesis unfolding f_def power2_eq_square using that by auto qed text ‹In the next lemma, the assumptions are too strong (negative numbers less than $-1$ also work well to have a square larger than $1$), but in practice one proves inequalities with nonnegative numbers, so this version is really the useful one for \verb+mono_intros+.› lemma mult_ge1_powers [mono_intros]: assumes "a ≥ (1::'a::linordered_idom)" shows "1 ≤ a * a" "1 ≤ a * a * a" "1 ≤ a * a * a * a" using assms by (meson assms dual_order.trans mult_ge1_mono(1) zero_le_one)+ lemmas [mono_intros] = ln_bound lemma mono_cSup: fixes f :: "'a::conditionally_complete_lattice ⇒ 'b::conditionally_complete_lattice" assumes "bdd_above A" "A ≠ {}" "mono f" shows "Sup (f`A) ≤ f (Sup A)" by (metis assms(1) assms(2) assms(3) cSUP_least cSup_upper mono_def) lemma mono_cSup_bij: fixes f :: "'a::conditionally_complete_linorder ⇒ 'b::conditionally_complete_linorder" assumes "bdd_above A" "A ≠ {}" "mono f" "bij f" shows "Sup (f`A) = f(Sup A)" proof - have "Sup ((inv f)`(f`A)) ≤ (inv f) (Sup (f`A))" apply (rule mono_cSup) using mono_inv[OF assms(3) assms(4)] assms(2) bdd_above_image_mono[OF assms(3) assms(1)] by auto then have "f (Sup ((inv f)`(f`A))) ≤ Sup (f`A)" using assms mono_def by (metis (no_types, opaque_lifting) bij_betw_imp_surj_on surj_f_inv_f) moreover have "f (Sup ((inv f)`(f`A))) = f(Sup A)" using assms by (simp add: bij_is_inj) ultimately show ?thesis using mono_cSup[OF assms(1) assms(2) assms(3)] by auto qed subsection ‹More topology› text ‹In situations of interest to us later on, convergence is well controlled only for sequences living in some dense subset of the space (but the limit can be anywhere). This is enough to establish continuity of the function, if the target space is well enough separated. The statement we give below is very general, as we do not assume that the function is continuous inside the original set $S$, it will typically only be continuous at a set $T$ contained in the closure of $S$. In many applications, $T$ will be the closure of $S$, but we are also thinking of the case where one constructs an extension of a function inside a space, to its boundary, and the behaviour at the boundary is better than inside the space. The example we have in mind is the extension of a quasi-isometry to the boundary of a Gromov hyperbolic space. In the following criterion, we assume that if $u_n$ inside $S$ converges to a point at the boundary $T$, then $f(u_n)$ converges (where $f$ is some function inside). Then, we can extend the function $f$ at the boundary, by picking the limit value of $f(u_n)$ for some sequence converging to $u_n$. Then the lemma asserts that $f$ is continuous at every point $b$ on the boundary. The proof is done in two steps: \begin{enumerate} \item First, if $v_n$ is another inside sequence tending to the same point $b$ on the boundary, then $f(v_n)$ converges to the same value as $f(u_n)$: this is proved by considering the sequence $w$ equal to $u$ at even times and to $v$ at odd times, and saying that $f(w_n)$ converges. Its limit is equal to the limit of $f(u_n)$ and of $f(v_n)$, so they have to coincide. \item Now, consider a general sequence $v$ (in the space or the boundary) converging to $b$. We want to show that $f(v_n)$ tends to $f(b)$. If $v_n$ is inside $S$, we have already done it in the first step. If it is on the boundary, on the other hand, we can approximate it by an inside point $w_n$ for which $f(w_n)$ is very close to $f(v_n)$. Then $w_n$ is an inside sequence converging to $b$, hence $f(w_n)$ converges to $f(b)$ by the first step, and then $f(v_n)$ also converges to $f(b)$. The precise argument is more conveniently written by contradiction. It requires good separation properties of the target space. \end{enumerate}› text ‹First, we introduce the material to interpolate between two sequences, one at even times and the other one at odd times.› definition even_odd_interpolate::"(nat ⇒ 'a) ⇒ (nat ⇒ 'a) ⇒ (nat ⇒ 'a)" where "even_odd_interpolate u v n = (if even n then u (n div 2) else v (n div 2))" lemma even_odd_interpolate_compose: "even_odd_interpolate (f o u) (f o v) = f o (even_odd_interpolate u v)" unfolding even_odd_interpolate_def comp_def by auto lemma even_odd_interpolate_filterlim: "filterlim u F sequentially ∧ filterlim v F sequentially ⟷ filterlim (even_odd_interpolate u v) F sequentially" proof (auto) assume H: "filterlim (even_odd_interpolate u v) F sequentially" define r::"nat ⇒ nat" where "r = (λn. 2 * n)" have "strict_mono r" unfolding r_def strict_mono_def by auto then have "filterlim r sequentially sequentially" by (simp add: filterlim_subseq) have "filterlim (λn. (even_odd_interpolate u v) (r n)) F sequentially" by (rule filterlim_compose[OF H filterlim_subseq[OF ‹strict_mono r›]]) moreover have "even_odd_interpolate u v (r n) = u n" for n unfolding r_def even_odd_interpolate_def by auto ultimately show "filterlim u F sequentially" by auto define r::"nat ⇒ nat" where "r = (λn. 2 * n + 1)" have "strict_mono r" unfolding r_def strict_mono_def by auto then have "filterlim r sequentially sequentially" by (simp add: filterlim_subseq) have "filterlim (λn. (even_odd_interpolate u v) (r n)) F sequentially" by (rule filterlim_compose[OF H filterlim_subseq[OF ‹strict_mono r›]]) moreover have "even_odd_interpolate u v (r n) = v n" for n unfolding r_def even_odd_interpolate_def by auto ultimately show "filterlim v F sequentially" by auto next assume H: "filterlim u F sequentially" "filterlim v F sequentially" show "filterlim (even_odd_interpolate u v) F sequentially" unfolding filterlim_iff eventually_sequentially proof (auto) fix P assume *: "eventually P F" obtain N1 where N1: "⋀n. n ≥ N1 ⟹ P (u n)" using H(1) unfolding filterlim_iff eventually_sequentially using * by auto obtain N2 where N2: "⋀n. n ≥ N2 ⟹ P (v n)" using H(2) unfolding filterlim_iff eventually_sequentially using * by auto have "P (even_odd_interpolate u v n)" if "n ≥ 2 * N1 + 2 * N2" for n proof (cases "even n") case True have "n div 2 ≥ N1" using that by auto then show ?thesis unfolding even_odd_interpolate_def using True N1 by auto next case False have "n div 2 ≥ N2" using that by auto then show ?thesis unfolding even_odd_interpolate_def using False N2 by auto qed then show "∃N. ∀n ≥ N. P (even_odd_interpolate u v n)" by auto qed qed text ‹Then, we prove the continuity criterion for extensions of functions to the boundary $T$ of a set $S$. The first assumption is that $f(u_n)$ converges when $f$ converges to the boundary, and the second one that the extension of $f$ to the boundary has been defined using the limit along some sequence tending to the point under consideration. The following criterion is the most general one, but this is not the version that is most commonly applied so we use a prime in its name.› lemma continuous_at_extension_sequentially': fixes f :: "'a::{first_countable_topology, t2_space} ⇒ 'b::t3_space" assumes "b ∈ T" "⋀u b. (∀n. u n ∈ S) ⟹ b ∈ T ⟹ u ⇢ b ⟹ convergent (λn. f (u n))" "⋀b. b ∈ T ⟹ ∃u. (∀n. u n ∈ S) ∧ u ⇢ b ∧ ((λn. f (u n)) ⇢ f b)" shows "continuous (at b within (S ∪ T)) f" proof - have first_step: "(λn. f (u n)) ⇢ f c" if "⋀n. u n ∈ S" "u ⇢ c" "c ∈ T" for u c proof - obtain v where v: "⋀n. v n ∈ S" "v ⇢ c" "(λn. f (v n)) ⇢ f c" using assms(3)[OF ‹c ∈ T›] by blast then have A: "even_odd_interpolate u v ⇢ c" unfolding even_odd_interpolate_filterlim[symmetric] using ‹u ⇢ c› by auto moreover have B: "∀n. even_odd_interpolate u v n ∈ S" using ‹⋀n. u n ∈ S› ‹⋀n. v n ∈ S› unfolding even_odd_interpolate_def by auto have "convergent (λn. f (even_odd_interpolate u v n))" by (rule assms(2)[OF B ‹c ∈ T› A]) then obtain m where "(λn. f (even_odd_interpolate u v n)) ⇢ m" unfolding convergent_def by auto then have "even_odd_interpolate (f o u) (f o v) ⇢ m" unfolding even_odd_interpolate_compose unfolding comp_def by auto then have "(f o u) ⇢ m" "(f o v) ⇢ m" unfolding even_odd_interpolate_filterlim[symmetric] by auto then have "m = f c" using v(3) unfolding comp_def using LIMSEQ_unique by auto then show ?thesis using ‹(f o u) ⇢ m› unfolding comp_def by auto qed show "continuous (at b within (S ∪ T)) f" proof (rule ccontr) assume "¬ ?thesis" then obtain U where U: "open U" "f b ∈ U" "¬(∀⇩_{F}x in at b within S ∪ T. f x ∈ U)" unfolding continuous_within tendsto_def[where l = "f b"] using sequentially_imp_eventually_nhds_within by auto have "∃V W. open V ∧ open W ∧ f b ∈ V ∧ (UNIV - U) ⊆ W ∧ V ∩ W = {}" apply (rule t3_space) using U by auto then obtain V W where VW: "open V" "open W" "f b ∈ V" "UNIV - U ⊆ W" "V ∩ W = {}" by auto obtain A :: "nat ⇒ 'a set" where *: "⋀i. open (A i)" "⋀i. b ∈ A i" "⋀F. ∀n. F n ∈ A n ⟹ F ⇢ b" by (rule first_countable_topology_class.countable_basis) blast with * U(3) have "∃F. ∀n. F n ∈ S ∪ T ∧ F n ∈ A n ∧ ¬ (f(F n) ∈ U)" unfolding at_within_def eventually_inf_principal eventually_nhds by (intro choice) (meson DiffE) then obtain F where F: "⋀n. F n ∈ S ∪ T" "⋀n. F n ∈ A n" "⋀n. f(F n) ∉ U" by auto have "∃y. y ∈ S ∧ y ∈ A n ∧ f y ∈ W" for n proof (cases "F n ∈ S") case True show ?thesis apply (rule exI[of _ "F n"]) using F VW True by auto next case False then have "F n ∈ T" using ‹F n ∈ S ∪ T› by auto obtain u where u: "⋀p. u p ∈ S" "u ⇢ F n" "(λp. f (u p)) ⇢ f(F n)" using assms(3)[OF ‹F n ∈ T›] by auto moreover have "f(F n) ∈ W" using F VW by auto ultimately have "eventually (λp. f (u p) ∈ W) sequentially" using ‹open W› by (simp add: tendsto_def) moreover have "eventually (λp. u p ∈ A n) sequentially" using ‹F n ∈ A n› u ‹open (A n)› by (simp add: tendsto_def) ultimately have "∃p. f(u p) ∈ W ∧ u p ∈ A n" using eventually_False_sequentially eventually_elim2 by blast then show ?thesis using u(1) by auto qed then have "∃u. ∀n. u n ∈ S ∧ u n ∈ A n ∧ f (u n) ∈ W" by (auto intro: choice) then obtain u where u: "⋀n. u n ∈ S" "⋀n. u n ∈ A n" "⋀n. f (u n) ∈ W" by blast then have "u ⇢ b" using *(3) by auto then have "(λn. f (u n)) ⇢ f b" using first_step assms u by auto then have "eventually (λn. f (u n) ∈ V) sequentially" using VW by (simp add: tendsto_def) then have "∃n. f (u n) ∈ V" using eventually_False_sequentially eventually_elim2 by blast then show False using u(3) ‹V ∩ W = {}› by auto qed qed text ‹We can specialize the previous statement to the common case where one already knows the sequential continuity of $f$ along sequences in $S$ converging to a point in $T$. This will be the case in most --but not all-- applications. This is a straightforward application of the above criterion.› proposition continuous_at_extension_sequentially: fixes f :: "'a::{first_countable_topology, t2_space} ⇒ 'b::t3_space" assumes "a ∈ T" "T ⊆ closure S" "⋀u b. (∀n. u n ∈ S) ⟹ b ∈ T ⟹ u ⇢ b ⟹ (λn. f (u n)) ⇢ f b" shows "continuous (at a within (S ∪ T)) f" apply (rule continuous_at_extension_sequentially'[OF ‹a ∈ T›]) using assms(3) convergent_def apply blast by (metis assms(2) assms(3) closure_sequential subset_iff) text ‹We also give global versions. We can only express the continuity on $T$, so this is slightly weaker than the previous statements since we are not saying anything on inside sequences tending to $T$ -- but in cases where $T$ contains $S$ these statements contain all the information.› lemma continuous_on_extension_sequentially': fixes f :: "'a::{first_countable_topology, t2_space} ⇒ 'b::t3_space" assumes "⋀u b. (∀n. u n ∈ S) ⟹ b ∈ T ⟹ u ⇢ b ⟹ convergent (λn. f (u n))" "⋀b. b ∈ T ⟹ ∃u. (∀n. u n ∈ S) ∧ u ⇢ b ∧ ((λn. f (u n)) ⇢ f b)" shows "continuous_on T f" unfolding continuous_on_eq_continuous_within apply (auto intro!: continuous_within_subset[of _ "S ∪ T" f T]) by (intro continuous_at_extension_sequentially'[OF _ assms], auto) lemma continuous_on_extension_sequentially: fixes f :: "'a::{first_countable_topology, t2_space} ⇒ 'b::t3_space" assumes "T ⊆ closure S" "⋀u b. (∀n. u n ∈ S) ⟹ b ∈ T ⟹ u ⇢ b ⟹ (λn. f (u n)) ⇢ f b" shows "continuous_on T f" unfolding continuous_on_eq_continuous_within apply (auto intro!: continuous_within_subset[of _ "S ∪ T" f T]) by (intro continuous_at_extension_sequentially[OF _ assms], auto) subsubsection ‹Homeomorphisms› text ‹A variant around the notion of homeomorphism, which is only expressed in terms of the function and not of its inverse.› definition homeomorphism_on::"'a set ⇒ ('a::topological_space ⇒ 'b::topological_space) ⇒ bool" where "homeomorphism_on S f = (∃g. homeomorphism S (f`S) f g)" lemma homeomorphism_on_continuous: assumes "homeomorphism_on S f" shows "continuous_on S f" using assms unfolding homeomorphism_on_def homeomorphism_def by auto lemma homeomorphism_on_bij: assumes "homeomorphism_on S f" shows "bij_betw f S (f`S)" using assms unfolding homeomorphism_on_def homeomorphism_def by auto (metis inj_on_def inj_on_imp_bij_betw) lemma homeomorphism_on_homeomorphic: assumes "homeomorphism_on S f" shows "S homeomorphic (f`S)" using assms unfolding homeomorphism_on_def homeomorphic_def by auto lemma homeomorphism_on_compact: fixes f::"'a::topological_space ⇒ 'b::t2_space" assumes "continuous_on S f" "compact S" "inj_on f S" shows "homeomorphism_on S f" unfolding homeomorphism_on_def using homeomorphism_compact[OF assms(2) assms(1) _ assms(3)] by auto lemma homeomorphism_on_subset: assumes "homeomorphism_on S f" "T ⊆ S" shows "homeomorphism_on T f" using assms homeomorphism_of_subsets unfolding homeomorphism_on_def by blast lemma homeomorphism_on_empty [simp]: "homeomorphism_on {} f" unfolding homeomorphism_on_def using homeomorphism_empty[of f] by auto lemma homeomorphism_on_cong: assumes "homeomorphism_on X f" "X' = X" "⋀x. x ∈ X ⟹ f' x = f x" shows "homeomorphism_on X' f'" proof - obtain g where g:"homeomorphism X (f`X) f g" using assms unfolding homeomorphism_on_def by auto have "homeomorphism X' (f'`X') f' g" apply (rule homeomorphism_cong[OF g]) using assms by (auto simp add: rev_image_eqI) then show ?thesis unfolding homeomorphism_on_def by auto qed lemma homeomorphism_on_inverse: fixes f::"'a::topological_space ⇒ 'b::topological_space" assumes "homeomorphism_on X f" shows "homeomorphism_on (f`X) (inv_into X f)" proof - obtain g where g: "homeomorphism X (f`X) f g" using assms unfolding homeomorphism_on_def by auto then have "g`f`X = X" by (simp add: homeomorphism_def) then have "homeomorphism_on (f`X) g" unfolding homeomorphism_on_def using homeomorphism_symD[OF g] by auto moreover have "g x = inv_into X f x" if "x ∈ f`X" for x using g that unfolding homeomorphism_def by (auto, metis f_inv_into_f inv_into_into that) ultimately show ?thesis using homeomorphism_on_cong by force qed text ‹Characterization of homeomorphisms in terms of sequences: a map is a homeomorphism if and only if it respects convergent sequences.› lemma homeomorphism_on_compose: assumes "homeomorphism_on S f" "x ∈ S" "eventually (λn. u n ∈ S) F" shows "(u ⤏ x) F ⟷ ((λn. f (u n)) ⤏ f x) F" proof assume "(u ⤏ x) F" then show "((λn. f (u n)) ⤏ f x) F" using continuous_on_tendsto_compose[OF homeomorphism_on_continuous[OF assms(1)] _ assms(2) assms(3)] by simp next assume *: "((λn. f (u n)) ⤏ f x) F" have I: "inv_into S f (f y) = y" if "y ∈ S" for y using homeomorphism_on_bij[OF assms(1)] by (meson bij_betw_inv_into_left that) then have A: "eventually (λn. u n = inv_into S f (f (u n))) F" using assms eventually_mono by force have "((λn. (inv_into S f) (f (u n))) ⤏ (inv_into S f) (f x)) F" apply (rule continuous_on_tendsto_compose[OF homeomorphism_on_continuous[OF homeomorphism_on_inverse[OF assms(1)]] *]) using assms eventually_mono by (auto) fastforce then show "(u ⤏ x) F" unfolding tendsto_cong[OF A] I[OF ‹x ∈ S›] by simp qed lemma homeomorphism_on_sequentially: fixes f::"'a::{first_countable_topology, t2_space} ⇒ 'b::{first_countable_topology, t2_space}" assumes "⋀x u. x ∈ S ⟹ (∀n. u n ∈ S) ⟹ u ⇢ x ⟷ (λn. f (u n)) ⇢ f x" shows "homeomorphism_on S f" proof - have "x = y" if "f x = f y" "x ∈ S" "y ∈ S" for x y proof - have "(λn. f x) ⇢ f y" using that by auto then have "(λn. x) ⇢ y" using assms(1) that by auto then show "x = y" using LIMSEQ_unique by auto qed then have "inj_on f S" by (simp add: inj_on_def) have Cf: "continuous_on S f" apply (rule continuous_on_sequentiallyI) using assms by auto define g where "g = inv_into S f" have Cg: "continuous_on (f`S) g" proof (rule continuous_on_sequentiallyI) fix v b assume H: "∀n. v n ∈ f ` S" "b ∈ f ` S" "v ⇢ b" define u where "u = (λn. g (v n))" define a where "a = g b" have "u n ∈ S" "f (u n) = v n" for n unfolding u_def g_def using H(1) by (auto simp add: inv_into_into f_inv_into_f) have "a ∈ S" "f a = b" unfolding a_def g_def using H(2) by (auto simp add: inv_into_into f_inv_into_f) show "(λn. g(v n)) ⇢ g b" unfolding u_def[symmetric] a_def[symmetric] apply (rule iffD2[OF assms]) using ‹⋀n. u n ∈ S› ‹a ∈ S› ‹v ⇢ b› unfolding ‹⋀n. f (u n) = v n› ‹f a = b› by auto qed have "homeomorphism S (f`S) f g" apply (rule homeomorphismI[OF Cf Cg]) unfolding g_def using ‹inj_on f S› by auto then show ?thesis unfolding homeomorphism_on_def by auto qed lemma homeomorphism_on_UNIV_sequentially: fixes f::"'a::{first_countable_topology, t2_space} ⇒ 'b::{first_countable_topology, t2_space}" assumes "⋀x u. u ⇢ x ⟷ (λn. f (u n)) ⇢ f x" shows "homeomorphism_on UNIV f" using assms by (auto intro!: homeomorphism_on_sequentially) text ‹Now, we give similar characterizations in terms of sequences living in a dense subset. As in the sequential continuity criteria above, we first give a very general criterion, where the map does not have to be continuous on the approximating set $S$, only on the limit set $T$, without any a priori identification of the limit. Then, we specialize this statement to a less general but often more usable version.› lemma homeomorphism_on_extension_sequentially_precise: fixes f::"'a::{first_countable_topology, t3_space} ⇒ 'b::{first_countable_topology, t3_space}" assumes "⋀u b. (∀n. u n ∈ S) ⟹ b ∈ T ⟹ u ⇢ b ⟹ convergent (λn. f (u n))" "⋀u c. (∀n. u n ∈ S) ⟹ c ∈ f`T ⟹ (λn. f (u n)) ⇢ c ⟹ convergent u" "⋀b. b ∈ T ⟹ ∃u. (∀n. u n ∈ S) ∧ u ⇢ b ∧ ((λn. f (u n)) ⇢ f b)" "⋀n. u n ∈ S ∪ T" "l ∈ T" shows "u ⇢ l ⟷ (λn. f (u n)) ⇢ f l" proof assume H: "u ⇢ l" have "continuous (at l within (S ∪ T)) f" apply (rule continuous_at_extension_sequentially'[OF ‹l ∈ T›]) using assms(1) assms(3) by auto then show "(λn. f (u n)) ⇢ f l" apply (rule continuous_within_tendsto_compose) using H assms(4) by auto next text ‹For the reverse implication, we would like to use the continuity criterion \verb+ continuous_at_extension_sequentially'+ applied to the inverse of $f$. Unfortunately, this inverse is only well defined on $T$, while our sequence takes values in $S \cup T$. So, instead, we redo by hand the proof of the continuity criterion, but in the opposite direction.› assume H: "(λn. f (u n)) ⇢ f l" show "u ⇢ l" proof (rule ccontr) assume "¬ ?thesis" then obtain U where U: "open U" "l ∈ U" "¬(∀⇩_{F}n in sequentially. u n ∈ U)" unfolding continuous_within tendsto_def[where l = l] using sequentially_imp_eventually_nhds_within by auto obtain A :: "nat ⇒ 'b set" where *: "⋀i. open (A i)" "⋀i. f l ∈ A i" "⋀F. ∀n. F n ∈ A n ⟹ F ⇢ f l" by (rule first_countable_topology_class.countable_basis) blast have B: "eventually (λn. f (u n) ∈ A i) sequentially" for i using ‹open (A i)› ‹f l ∈ A i› H topological_tendstoD by fastforce have M: "∃r. r ≥ N ∧ (u r ∉ U) ∧ f (u r) ∈ A i" for N i using U(3) B[of i] unfolding eventually_sequentially by (meson dual_order.trans le_cases) have "∃r. ∀n. (u (r n) ∉ U ∧ f (u (r n)) ∈ A n) ∧ r (Suc n) ≥ r n + 1" apply (rule dependent_nat_choice) using M by auto then obtain r where r: "⋀n. u (r n) ∉ U" "⋀n. f (u (r n)) ∈ A n" "⋀n. r (Suc n) ≥ r n + 1" by auto then have "strict_mono r" by (metis Suc_eq_plus1 Suc_le_lessD strict_monoI_Suc) have "∃V W. open V ∧ open W ∧ l ∈ V ∧ (UNIV - U) ⊆ W ∧ V ∩ W = {}" apply (rule t3_space) using U by auto then obtain V W where VW: "open V" "open W" "l ∈ V" "UNIV - U ⊆ W" "V ∩ W = {}" by auto have "∃z. z ∈ S ∧ f z ∈ A n ∧ z ∈ W" for n proof - define z where "z = u (r n)" have "f z ∈ A n" unfolding z_def using r(2) by auto have "z ∈ S ∪ T" "z ∉ U" unfolding z_def using r(1) assms(4) by auto then have "z ∈ W" using VW by auto show ?thesis proof (cases "z ∈ T") case True obtain u::"nat ⇒ 'a" where u: "⋀p. u p ∈ S" "u ⇢ z" "(λp. f (u p)) ⇢ f z" using assms(3)[OF ‹z ∈ T›] by auto then have "eventually (λp. f (u p) ∈ A n) sequentially" using ‹open (A n)› ‹f z ∈ A n› unfolding tendsto_def by simp moreover have "eventually (λp. u p ∈ W) sequentially" using ‹open W› ‹z ∈ W› u unfolding tendsto_def by simp ultimately have "∃p. u p ∈ W ∧ f (u p) ∈ A n" using eventually_False_sequentially eventually_elim2 by blast then show ?thesis using u(1) by auto next case False then have "z ∈ S" using ‹z ∈ S ∪ T› by auto then show ?thesis using ‹f z ∈ A n› ‹z ∈ W› by auto qed qed then have "∃v. ∀n. v n ∈ S ∧ f (v n) ∈ A n ∧ v n ∈ W" by (auto intro: choice) then obtain v where v: "⋀n. v n ∈ S" "⋀n. f (v n) ∈ A n" "⋀n. v n ∈ W" by blast then have I: "(λn. f (v n)) ⇢ f l" using *(3) by auto obtain w where w: "⋀n. w n ∈ S" "w ⇢ l" "((λn. f (w n)) ⇢ f l)" using assms(3)[OF ‹l ∈ T›] by auto have "even_odd_interpolate (f o v) (f o w) ⇢ f l" unfolding even_odd_interpolate_filterlim[symmetric] comp_def using v w I by auto then have *: "(λn. f (even_odd_interpolate v w n)) ⇢ f l" unfolding even_odd_interpolate_compose unfolding comp_def by auto have "convergent (even_odd_interpolate v w)" apply (rule assms(2)[OF _ _ *]) unfolding even_odd_interpolate_def using v(1) w(1) ‹l ∈ T› by auto then obtain z where "even_odd_interpolate v w ⇢ z" unfolding convergent_def by auto then have *: "v ⇢ z" "w ⇢ z" unfolding even_odd_interpolate_filterlim[symmetric] by auto then have "z = l" using v(2) w(2) LIMSEQ_unique by auto then have "v ⇢ l" using * by simp then have "eventually (λn. v n ∈ V) sequentially" using VW by (simp add: tendsto_def) then have "∃n. v n ∈ V" using eventually_False_sequentially eventually_elim2 by blast then show False using v(3) ‹V ∩ W = {}› by auto qed qed lemma homeomorphism_on_extension_sequentially': fixes f::"'a::{first_countable_topology, t3_space} ⇒ 'b::{first_countable_topology, t3_space}" assumes "⋀u b. (∀n. u n ∈ S) ⟹ b ∈ T ⟹ u ⇢ b ⟹ convergent (λn. f (u n))" "⋀u c. (∀n. u n ∈ S) ⟹ c ∈ f`T ⟹ (λn. f (u n)) ⇢ c ⟹ convergent u" "⋀b. b ∈ T ⟹ ∃u. (∀n. u n ∈ S) ∧ u ⇢ b ∧ ((λn. f (u n)) ⇢ f b)" shows "homeomorphism_on T f" apply (rule homeomorphism_on_sequentially, rule homeomorphism_on_extension_sequentially_precise[of S T]) using assms by auto proposition homeomorphism_on_extension_sequentially: fixes f::"'a::{first_countable_topology, t3_space} ⇒ 'b::{first_countable_topology, t3_space}" assumes "⋀u b. (∀n. u n ∈ S) ⟹ u ⇢ b ⟷ (λn. f (u n)) ⇢ f b" "T ⊆ closure S" shows "homeomorphism_on T f" apply (rule homeomorphism_on_extension_sequentially'[of S]) using assms(1) convergent_def apply fastforce using assms(1) convergent_def apply blast by (metis assms(1) assms(2) closure_sequential subsetCE) lemma homeomorphism_on_UNIV_extension_sequentially: fixes f::"'a::{first_countable_topology, t3_space} ⇒ 'b::{first_countable_topology, t3_space}" assumes "⋀u b. (∀n. u n ∈ S) ⟹ u ⇢ b ⟷ (λn. f (u n)) ⇢ f b" "closure S = UNIV" shows "homeomorphism_on UNIV f" apply (rule homeomorphism_on_extension_sequentially[of S]) using assms by auto subsubsection ‹Proper spaces› text ‹Proper spaces, i.e., spaces in which every closed ball is compact -- or, equivalently, any closed bounded set is compact.› definition proper::"('a::metric_space) set ⇒ bool" where "proper S ≡ (∀ x r. compact (cball x r ∩ S))" lemma properI: assumes "⋀x r. compact (cball x r ∩ S)" shows "proper S" using assms unfolding proper_def by auto lemma proper_compact_cball: assumes "proper (UNIV::'a::metric_space set)" shows "compact (cball (x::'a) r)" using assms unfolding proper_def by auto lemma proper_compact_bounded_closed: assumes "proper (UNIV::'a::metric_space set)" "closed (S::'a set)" "bounded S" shows "compact S" proof - obtain x r where "S ⊆ cball x r" using ‹bounded S› bounded_subset_cball by blast then have *: "S = S ∩ cball x r" by auto show ?thesis apply (subst *, rule closed_Int_compact) using assms unfolding proper_def by auto qed lemma proper_real [simp]: "proper (UNIV::real set)" unfolding proper_def by auto lemma complete_of_proper: assumes "proper S" shows "complete S" proof - have "∃l∈S. u ⇢ l" if "Cauchy u" "⋀n. u n ∈ S" for u proof - have "bounded (range u)" using ‹Cauchy u› cauchy_imp_bounded by auto then obtain x r where *: "⋀n. dist x (u n) ≤ r" unfolding bounded_def by auto then have "u n ∈ (cball x r) ∩ S" for n using ‹u n ∈ S› by auto moreover have "complete ((cball x r) ∩ S)" apply (rule compact_imp_complete) using assms unfolding proper_def by auto ultimately show ?thesis unfolding complete_def using ‹Cauchy u› by auto qed then show ?thesis unfolding complete_def by auto qed lemma proper_of_compact: assumes "compact S" shows "proper S" using assms by (auto intro: properI) lemma proper_Un: assumes "proper A" "proper B" shows "proper (A ∪ B)" using assms unfolding proper_def by (auto simp add: compact_Un inf_sup_distrib1) subsubsection ‹Miscellaneous topology› text ‹When manipulating the triangle inequality, it is very frequent to deal with 4 points (and automation has trouble doing it automatically). Even sometimes with 5 points...› lemma dist_triangle4 [mono_intros]: "dist x t ≤ dist x y + dist y z + dist z t" using dist_triangle[of x z y] dist_triangle[of x t z] by auto lemma dist_triangle5 [mono_intros]: "dist x u ≤ dist x y + dist y z + dist z t + dist t u" using dist_triangle4[of x u y z] dist_triangle[of z u t] by auto text ‹A thickening of a compact set is closed.› lemma compact_has_closed_thickening: assumes "compact C" "continuous_on C f" shows "closed (⋃x∈C. cball x (f x))" proof (auto simp add: closed_sequential_limits) fix u l assume *: "∀n::nat. ∃x∈C. dist x (u n) ≤ f x" "u ⇢ l" have "∃x::nat⇒'a. ∀n. x n ∈ C ∧ dist (x n) (u n) ≤ f (x n)" apply (rule choice) using * by auto then obtain x::"nat ⇒ 'a" where x: "⋀n. x n ∈ C" "⋀n. dist (x n) (u n) ≤ f (x n)" by blast obtain r c where "strict_mono r" "c ∈ C" "(x o r) ⇢ c" using x(1) ‹compact C› by (meson compact_eq_seq_compact_metric seq_compact_def) then have "c ∈ C" using x(1) ‹compact C› by auto have lim: "(λn. f (x (r n)) - dist (x (r n)) (u (r n))) ⇢ f c - dist c l" apply (intro tendsto_intros, rule continuous_on_tendsto_compose[of C f]) using *(2) x(1) ‹(x o r) ⇢ c› ‹continuous_on C f› ‹c ∈ C› ‹strict_mono r› LIMSEQ_subseq_LIMSEQ unfolding comp_def by auto have "f c - dist c l ≥ 0" apply (rule LIMSEQ_le_const[OF lim]) using x(2) by auto then show "∃x∈C. dist x l ≤ f x" using ‹c ∈ C› by auto qed text ‹congruence rule for continuity. The assumption that $f y = g y$ is necessary since \verb+at x+ is the pointed neighborhood at $x$.› lemma continuous_within_cong: assumes "continuous (at y within S) f" "eventually (λx. f x = g x) (at y within S)" "f y = g y" shows "continuous (at y within S) g" using assms continuous_within filterlim_cong by fastforce text ‹A function which tends to infinity at infinity, on a proper set, realizes its infimum› lemma continuous_attains_inf_proper: fixes f :: "'a::metric_space ⇒ 'b::linorder_topology" assumes "proper s" "a ∈ s" "continuous_on s f" "⋀z. z ∈ s - cball a r ⟹ f z ≥ f a" shows "∃x∈s. ∀y∈s. f x ≤ f y" proof (cases "r ≥ 0") case True have "∃x∈cball a r ∩ s. ∀y ∈ cball a r ∩ s. f x ≤ f y" apply (rule continuous_attains_inf) using assms True unfolding proper_def apply (auto simp add: continuous_on_subset) using centre_in_cball by blast then obtain x where x: "x ∈ cball a r ∩ s" "⋀y. y ∈ cball a r ∩ s ⟹ f x ≤ f y" by auto have "f x ≤ f y" if "y ∈ s" for y proof (cases "y ∈ cball a r") case True then show ?thesis using x(2) that by auto next case False have "f x ≤ f a" apply (rule x(2)) using assms True by auto then show ?thesis using assms(4)[of y] that False by auto qed then show ?thesis using x(1) by auto next case False show ?thesis apply (rule bexI[of _ a]) using assms False by auto qed subsubsection ‹Measure of balls› text ‹The image of a ball by an affine map is still a ball, with explicit center and radius. (Now unused)› lemma affine_image_ball [simp]: "(λy. R *⇩_{R}y + x) ` cball 0 1 = cball (x::('a::real_normed_vector)) ¦R¦" proof have "dist x (R *⇩_{R}y + x) ≤ ¦R¦" if "dist 0 y ≤ 1" for y proof - have "dist x (R *⇩_{R}y + x) = norm ((R *⇩_{R}y + x) - x)" by (simp add: dist_norm) also have "... = ¦R¦ * norm y" by auto finally show ?thesis using that by (simp add: mult_left_le) qed then show "(λy. R *⇩_{R}y + x) ` cball 0 1 ⊆ cball x ¦R¦" by auto show "cball x ¦R¦ ⊆ (λy. R *⇩_{R}y + x) ` cball 0 1" proof (cases "¦R¦ = 0") case True then have "cball x ¦R¦ = {x}" by auto moreover have "x = R *⇩_{R}0 + x ∧ 0 ∈ cball 0 1" by auto ultimately show ?thesis by auto next case False have "z ∈ (λy. R *⇩_{R}y + x) ` cball 0 1" if "z ∈ cball x ¦R¦" for z proof - define y where "y = (z - x) /⇩_{R}R" have "R *⇩_{R}y + x = z" unfolding y_def using False by auto moreover have "y ∈ cball 0 1" using ‹z ∈ cball x ¦R¦› False unfolding y_def by (auto simp add: dist_norm[symmetric] divide_simps dist_commute) ultimately show ?thesis by auto qed then show ?thesis by auto qed qed text ‹From the rescaling properties of Lebesgue measure in a euclidean space, it follows that the measure of any ball can be expressed in terms of the measure of the unit ball.› lemma lebesgue_measure_ball: assumes "R ≥ 0" shows "measure lborel (cball (x::('a::euclidean_space)) R) = R^(DIM('a)) * measure lborel (cball (0::'a) 1)" "emeasure lborel (cball (x::('a::euclidean_space)) R) = R^(DIM('a)) * emeasure lborel (cball (0::'a) 1)" apply (simp add: assms content_cball) by (simp add: assms emeasure_cball ennreal_mult' ennreal_power mult.commute) text ‹We show that the unit ball has positive measure -- this is obvious, but useful. We could show it by arguing that it contains a box, whose measure can be computed, but instead we say that if the measure vanished then the measure of any ball would also vanish, contradicting the fact that the space has infinite measure. This avoids all computations.› lemma lebesgue_measure_ball_pos: "emeasure lborel (cball (0::'a::euclidean_space) 1) > 0" "measure lborel (cball (0::'a::euclidean_space) 1) > 0" proof - show "emeasure lborel (cball (0::'a::euclidean_space) 1) > 0" proof (rule ccontr) assume "¬(emeasure lborel (cball (0::'a::euclidean_space) 1) > 0)" then have "emeasure lborel (cball (0::'a) 1) = 0" by auto then have "emeasure lborel (cball (0::'a) n) = 0" for n::nat using lebesgue_measure_ball(2)[of "real n" 0] by (metis mult_zero_right of_nat_0_le_iff) then have "emeasure lborel (⋃n. cball (0::'a) (real n)) = 0" by (metis (mono_tags, lifting) borel_closed closed_cball emeasure_UN_eq_0 imageE sets_lborel subsetI) moreover have "(⋃n. cball (0::'a) (real n)) = UNIV" by (auto simp add: real_arch_simple) ultimately show False by simp qed moreover have "emeasure lborel (cball (0::'a::euclidean_space) 1) < ∞" by (rule emeasure_bounded_finite, auto) ultimately show "measure lborel (cball (0::'a::euclidean_space) 1) > 0" by (metis borel_closed closed_cball ennreal_0 has_integral_iff_emeasure_lborel has_integral_measure_lborel less_irrefl order_refl zero_less_measure_iff) qed subsubsection ‹infdist and closest point projection› text ‹The distance to a union of two sets is the minimum of the distance to the two sets.› lemma infdist_union_min [mono_intros]: assumes "A ≠ {}" "B ≠ {}" shows "infdist x (A ∪ B) = min (infdist x A) (infdist x B)" using assms by (simp add: infdist_def cINF_union inf_real_def) text ‹The distance to a set is non-increasing with the set.› lemma infdist_mono [mono_intros]: assumes "A ⊆ B" "A ≠ {}" shows "infdist x B ≤ infdist x A" by (simp add: assms infdist_eq_setdist setdist_subset_right) text ‹If a set is proper, then the infimum of the distances to this set is attained.› lemma infdist_proper_attained: assumes "proper C" "C ≠ {}" shows "∃c∈C. infdist x C = dist x c" proof - obtain a where "a ∈ C" using assms by auto have *: "dist x a ≤ dist x z" if "dist a z ≥ 2 * dist a x" for z proof - have "2 * dist a x ≤ dist a z" using that by simp also have "... ≤ dist a x + dist x z" by (intro mono_intros) finally show ?thesis by (simp add: dist_commute) qed have "∃c∈C. ∀d∈C. dist x c ≤ dist x d" apply (rule continuous_attains_inf_proper[OF assms(1) ‹a ∈ C›, of _ "2 * dist a x"]) using * by (auto intro: continuous_intros) then show ?thesis unfolding infdist_def using ‹C ≠ {}› by (metis antisym bdd_below_image_dist cINF_lower le_cINF_iff) qed lemma infdist_almost_attained: assumes "infdist x X < a" "X ≠ {}" shows "∃y∈X. dist x y < a" using assms using cInf_less_iff[of "(dist x)`X"] unfolding infdist_def by auto lemma infdist_triangle_abs [mono_intros]: "¦infdist x A - infdist y A¦ ≤ dist x y" by (metis (full_types) abs_diff_le_iff diff_le_eq dist_commute infdist_triangle) text ‹The next lemma is missing in the library, contrary to its cousin \verb+continuous_infdist+.› text ‹The infimum of the distance to a singleton set is simply the distance to the unique member of the set.› text ‹The closest point projection of $x$ on $A$. It is not unique, so we choose one point realizing the minimal distance. And if there is no such point, then we use $x$, to make some statements true without any assumption.› definition proj_set::"'a::metric_space ⇒ 'a set ⇒ 'a set" where "proj_set x A = {y ∈ A. dist x y = infdist x A}" definition distproj::"'a::metric_space ⇒ 'a set ⇒ 'a" where "distproj x A = (if proj_set x A ≠ {} then SOME y. y ∈ proj_set x A else x)" lemma proj_setD: assumes "y ∈ proj_set x A" shows "y ∈ A" "dist x y = infdist x A" using assms unfolding proj_set_def by auto lemma proj_setI: assumes "y ∈ A" "dist x y ≤ infdist x A" shows "y ∈ proj_set x A" using assms infdist_le[OF ‹y ∈ A›, of x] unfolding proj_set_def by auto lemma proj_setI': assumes "y ∈ A" "⋀z. z ∈ A ⟹ dist x y ≤ dist x z" shows "y ∈ proj_set x A" proof (rule proj_setI[OF ‹y ∈ A›]) show "dist x y ≤ infdist x A" apply (subst infdist_notempty) using assms by (auto intro!: cInf_greatest) qed lemma distproj_in_proj_set: assumes "proj_set x A ≠ {}" shows "distproj x A ∈ proj_set x A" "distproj x A ∈ A" "dist x (distproj x A) = infdist x A" proof - show "distproj x A ∈ proj_set x A" using assms unfolding distproj_def using some_in_eq by auto then show "distproj x A ∈ A" "dist x (distproj x A) = infdist x A" unfolding proj_set_def by auto qed lemma proj_set_nonempty_of_proper: assumes "proper A" "A ≠ {}" shows "proj_set x A ≠ {}" proof - have "∃y. y ∈ A ∧ dist x y = infdist x A" using infdist_proper_attained[OF assms, of x] by auto then show "proj_set x A ≠ {}" unfolding proj_set_def by auto qed lemma distproj_self [simp]: assumes "x ∈ A" shows "proj_set x A = {x}" "distproj x A = x" proof - show "proj_set x A = {x}" unfolding proj_set_def using assms by auto then show "distproj x A = x" unfolding distproj_def by auto qed lemma distproj_closure [simp]: assumes "x ∈ closure A" shows "distproj x A = x" proof (cases "proj_set x A ≠ {}") case True show ?thesis using distproj_in_proj_set(3)[OF True] assms by (metis closure_empty dist_eq_0_iff distproj_self(2) in_closure_iff_infdist_zero) next case False then show ?thesis unfolding distproj_def by auto qed lemma distproj_le: assumes "y ∈ A" shows "dist x (distproj x A) ≤ dist x y" proof (cases "proj_set x A ≠ {}") case True show ?thesis using distproj_in_proj_set(3)[OF True] infdist_le[OF assms] by auto next case False then show ?thesis unfolding distproj_def by auto qed lemma proj_set_dist_le: assumes "y ∈ A" "p ∈ proj_set x A" shows "dist x p ≤ dist x y" using assms infdist_le unfolding proj_set_def by auto subsection ‹Material on ereal and ennreal› text ‹We add the simp rules that we needed to make all computations become more or less automatic.› lemma ereal_of_real_of_ereal_iff [simp]: "ereal(real_of_ereal x) = x ⟷ x ≠ ∞ ∧ x ≠ - ∞" "x = ereal(real_of_ereal x) ⟷ x ≠ ∞ ∧ x ≠ - ∞" by (metis MInfty_neq_ereal(1) PInfty_neq_ereal(2) real_of_ereal.elims)+ declare ereal_inverse_eq_0 [simp] declare ereal_0_gt_inverse [simp] declare ereal_inverse_le_0_iff [simp] declare ereal_divide_eq_0_iff [simp] declare ereal_mult_le_0_iff [simp] declare ereal_zero_le_0_iff [simp] declare ereal_mult_less_0_iff [simp] declare ereal_zero_less_0_iff [simp] declare ereal_uminus_eq_reorder [simp] declare ereal_minus_le_iff [simp] lemma ereal_inverse_noteq_minus_infinity [simp]: "1/(x::ereal) ≠ -∞" by (simp add: divide_ereal_def) lemma ereal_inverse_positive_iff_nonneg_not_infinity [simp]: "0 < 1/(x::ereal) ⟷ (x ≥ 0 ∧ x ≠ ∞)" by (cases x, auto simp add: one_ereal_def) lemma ereal_inverse_negative_iff_nonpos_not_infinity' [simp]: "0 > inverse (x::ereal) ⟷ (x < 0 ∧ x ≠ -∞)" by (cases x, auto simp add: one_ereal_def) lemma ereal_divide_pos_iff [simp]: "0 < x/(y::ereal) ⟷ (y ≠ ∞ ∧ y ≠ -∞) ∧ ((x > 0 ∧ y > 0) ∨ (x < 0 ∧ y < 0) ∨ (y = 0 ∧ x > 0))" unfolding divide_ereal_def by auto lemma ereal_divide_neg_iff [simp]: "0 > x/(y::ereal) ⟷ (y ≠ ∞ ∧ y ≠ -∞) ∧ ((x > 0 ∧ y < 0) ∨ (x < 0 ∧ y > 0) ∨ (y = 0 ∧ x < 0))" unfolding divide_ereal_def by auto text ‹More additions to \verb+mono_intros+.› lemma ereal_leq_imp_neg_leq [mono_intros]: fixes x y::ereal assumes "x ≤ y" shows "-y ≤ -x" using assms by auto lemma ereal_le_imp_neg_le [mono_intros]: fixes x y::ereal assumes "x < y" shows "-y < -x" using assms by auto declare ereal_mult_left_mono [mono_intros] declare ereal_mult_right_mono [mono_intros] declare ereal_mult_strict_right_mono [mono_intros] declare ereal_mult_strict_left_mono [mono_intros] text ‹Monotonicity of basic inclusions.› lemma ennreal_mono': "mono ennreal" by (simp add: ennreal_leI monoI) lemma enn2ereal_mono': "mono enn2ereal" by (simp add: less_eq_ennreal.rep_eq mono_def) lemma e2ennreal_mono': "mono e2ennreal" by (simp add: e2ennreal_mono mono_def) lemma enn2ereal_mono [mono_intros]: assumes "x ≤ y" shows "enn2ereal x ≤ enn2ereal y" using assms less_eq_ennreal.rep_eq by auto lemma ereal_mono: "mono ereal" unfolding mono_def by auto lemma ereal_strict_mono: "strict_mono ereal" unfolding strict_mono_def by auto lemma ereal_mono2 [mono_intros]: assumes "x ≤ y" shows "ereal x ≤ ereal y" by (simp add: assms) lemma ereal_strict_mono2 [mono_intros]: assumes "x < y" shows "ereal x < ereal y" using assms by auto lemma enn2ereal_a_minus_b_plus_b [mono_intros]: "enn2ereal a ≤ enn2ereal (a - b) + enn2ereal b" by (metis diff_add_self_ennreal less_eq_ennreal.rep_eq linear plus_ennreal.rep_eq) text ‹The next lemma follows from the same assertion in ereals.› lemma enn2ereal_strict_mono [mono_intros]: assumes "x < y" shows "enn2ereal x < enn2ereal y" using assms less_ennreal.rep_eq by auto declare ennreal_mult_strict_left_mono [mono_intros] declare ennreal_mult_strict_right_mono [mono_intros] lemma ennreal_ge_0 [mono_intros]: assumes "0 < x" shows "0 < ennreal x" by (simp add: assms) text ‹The next lemma is true and useful in ereal. Note that variants such as $a + b \leq c + d$ implies $a-d \leq c -b$ are not true -- take $a = c = \infty$ and $b = d = 0$...› lemma ereal_minus_le_minus_plus [mono_intros]: fixes a b c::ereal assumes "a ≤ b + c" shows "-b ≤ -a + c" using assms apply (cases a, cases b, cases c, auto) using ereal_infty_less_eq2(2) ereal_plus_1(4) by fastforce lemma tendsto_ennreal_0 [tendsto_intros]: assumes "(u ⤏ 0) F" shows "((λn. ennreal(u n)) ⤏ 0) F" unfolding ennreal_0[symmetric] by (intro tendsto_intros assms) lemma tendsto_ennreal_1 [tendsto_intros]: assumes "(u ⤏ 1) F" shows "((λn. ennreal(u n)) ⤏ 1) F" unfolding ennreal_1[symmetric] by (intro tendsto_intros assms) subsection ‹Miscellaneous› lemma lim_ceiling_over_n [tendsto_intros]: assumes "(λn. u n/n) ⇢ l" shows "(λn. ceiling(u n)/n) ⇢ l" proof (rule tendsto_sandwich[of "λn. u n/n" _ _ "λn. u n/n + 1/n"]) show "∀⇩_{F}n in sequentially. u n / real n ≤ real_of_int ⌈u n⌉ / real n" unfolding eventually_sequentially by (rule exI[of _ 1], auto simp add: divide_simps) show "∀⇩_{F}n in sequentially. real_of_int ⌈u n⌉ / real n ≤ u n / real n + 1 / real n" unfolding eventually_sequentially by (rule exI[of _ 1], auto simp add: divide_simps) have "(λn. u n / real n + 1 / real n) ⇢ l + 0" by (intro tendsto_intros assms) then show "(λn. u n / real n + 1 / real n) ⇢ l" by auto qed (simp add: assms) subsubsection ‹Liminfs and Limsups› text ‹More facts on liminfs and limsups› lemma Limsup_obtain': fixes u::"'a ⇒ 'b::complete_linorder" assumes "Limsup F u > c" "eventually P F" shows "∃n. P n ∧ u n > c" proof - have *: "(INF P∈{P. eventually P F}. SUP x∈{x. P x}. u x) > c" using assms by (simp add: Limsup_def) have **: "c < (SUP x∈{x. P x}. u x)" using less_INF_D[OF *, of P] assms by auto then show ?thesis by (simp add: less_SUP_iff) qed lemma limsup_obtain: fixes u::"nat ⇒ 'a :: complete_linorder" assumes "limsup u > c" shows "∃n ≥ N. u n > c" using Limsup_obtain'[OF assms, of "λn. n ≥ N"] unfolding eventually_sequentially by auto lemma Liminf_obtain': fixes u::"'a ⇒ 'b::complete_linorder" assumes "Liminf F u < c" "eventually P F" shows "∃n. P n ∧ u n < c" proof - have *: "(SUP P∈{P. eventually P F}. INF x∈{x. P x}. u x) < c" using assms by (simp add: Liminf_def) have **: "(INF x∈{x. P x}. u x) < c" using SUP_lessD[OF *, of P] assms by auto then show ?thesis by (simp add: INF_less_iff) qed lemma liminf_obtain: fixes u::"nat ⇒ 'a :: complete_linorder" assumes "liminf u < c" shows "∃n ≥ N. u n < c" using Liminf_obtain'[OF assms, of "λn. n ≥ N"] unfolding eventually_sequentially by auto text ‹The Liminf of a minimum is the minimum of the Liminfs.› lemma Liminf_min_eq_min_Liminf: fixes u v::"nat ⇒ 'a::complete_linorder" shows "Liminf F (λn. min (u n) (v n)) = min (Liminf F u) (Liminf F v)" proof (rule order_antisym) show "Liminf F (λn. min (u n) (v n)) ≤ min (Liminf F u) (Liminf F v)" by (auto simp add: Liminf_mono) have "Liminf F (λn. min (u n) (v n)) > w" if H: "min (Liminf F u) (Liminf F v) > w" for w proof (cases "{w<..<min (Liminf F u) (Liminf F v)} = {}") case True have "eventually (λn. u n > w) F" "eventually (λn. v n > w) F" using H le_Liminf_iff by fastforce+ then have "eventually (λn. min (u n) (v n) > w) F" apply auto using eventually_elim2 by fastforce moreover have "z > w ⟹ z ≥ min (Liminf F u) (Liminf F v)" for z using H True not_le_imp_less by fastforce ultimately have "eventually (λn. min (u n) (v n) ≥ min (Liminf F u) (Liminf F v)) F" by (simp add: eventually_mono) then have "min (Liminf F u) (Liminf F v) ≤ Liminf F (λn. min (u n) (v n))" by (metis Liminf_bounded) then show ?thesis using H less_le_trans by blast next case False then obtain z where "z ∈ {w<..<min (Liminf F u) (Liminf F v)}" by blast then have H: "w < z" "z < min (Liminf F u) (Liminf F v)" by auto then have "eventually (λn. u n > z) F" "eventually (λn. v n > z) F" using le_Liminf_iff by fastforce+ then have "eventually (λn. min (u n) (v n) > z) F" apply auto using eventually_elim2 by fastforce then have "Liminf F (λn. min (u n) (v n)) ≥ z" by (simp add: Liminf_bounded eventually_mono less_imp_le) then show ?thesis using H(1) by auto qed then show "min (Liminf F u) (Liminf F v) ≤ Liminf F (λn. min (u n) (v n))" using not_le_imp_less by blast qed text ‹The Limsup of a maximum is the maximum of the Limsups.› lemma Limsup_max_eq_max_Limsup: fixes u::"'a ⇒ 'b::complete_linorder" shows "Limsup F (λn. max (u n) (v n)) = max (Limsup F u) (Limsup F v)" proof (rule order_antisym) show "max (Limsup F u) (Limsup F v) ≤ Limsup F (λn. max (u n) (v n))" by (auto intro: Limsup_mono) have "Limsup F (λn. max (u n) (v n)) < e" if "max (Limsup F u) (Limsup F v) < e" for e proof (cases "∃t. max (Limsup F u) (Limsup F v) < t ∧ t < e") case True then obtain t where t: "t < e" "max (Limsup F u) (Limsup F v) < t" by auto then have "Limsup F u < t" "Limsup F v < t" using that max_def by auto then have *: "eventually (λn. u n < t) F" "eventually (λn. v n < t) F" by (auto simp: Limsup_lessD) have "eventually (λn. max (u n) (v n) < t) F" using eventually_mono[OF eventually_conj[OF *]] by auto then have "Limsup F (λn. max (u n) (v n)) ≤ t" by (meson Limsup_obtain' not_le_imp_less order.asym) then show ?thesis using t by auto next case False have "Limsup F u < e" "Limsup F v < e" using that max_def by auto then have *: "eventually (λn. u n < e) F" "eventually (λn. v n < e) F" by (auto simp: Limsup_lessD) have "eventually (λn. max (u n) (v n) ≤ max (Limsup F u) (Limsup F v)) F" apply (rule eventually_mono[OF eventually_conj[OF *]]) using False not_le_imp_less by force then have "Limsup F (λn. max (u n) (v n)) ≤ max (Limsup F u) (Limsup F v)" by (meson Limsup_obtain' leD leI) then show ?thesis using that le_less_trans by blast qed then show "Limsup F (λn. max (u n) (v n)) ≤ max (Limsup F u) (Limsup F v)" using not_le_imp_less by blast qed subsubsection ‹Bounding the cardinality of a finite set› text ‹A variation with real bounds.› lemma finite_finite_subset_caract': fixes C::real assumes "⋀G. G ⊆ F ⟹ finite G ⟹ card G ≤ C" shows "finite F ∧ card F ≤ C" by (meson assms finite_if_finite_subsets_card_bdd le_nat_floor order_refl) text ‹To show that a set has cardinality at most one, it suffices to show that any two of its elements coincide.› lemma finite_at_most_singleton: assumes "⋀x y. x ∈ F ⟹ y ∈ F ⟹ x = y" shows "finite F ∧ card F ≤ 1" proof (cases "F = {}") case True then show ?thesis by auto next case False then obtain x where "x ∈ F" by auto then have "F = {x}" using assms by auto then show ?thesis by auto qed text ‹Bounded sets of integers are finite.› lemma finite_real_int_interval [simp]: "finite (range real_of_int ∩ {a..b})" proof - have "range real_of_int ∩ {a..b} ⊆ real_of_int`{floor a..ceiling b}" by (auto, metis atLeastAtMost_iff ceiling_mono ceiling_of_int floor_mono floor_of_int image_eqI) then show ?thesis using finite_subset by blast qed text ‹Well separated sets of real numbers are finite, with controlled cardinality.› lemma separated_in_real_card_bound: assumes "T ⊆ {a..(b::real)}" "d > 0" "⋀x y. x ∈ T ⟹ y ∈ T ⟹ y > x ⟹ y ≥ x + d" shows "finite T" "card T ≤ nat (floor ((b-a)/d) + 1)" proof - define f where "f = (λx. floor ((x-a) / d))" have "f`{a..b} ⊆ {0..floor ((b-a)/d)}" unfolding f_def using ‹d > 0› by (auto simp add: floor_mono frac_le) then have *: "f`T ⊆ {0..floor ((b-a)/d)}" using ‹T ⊆ {a..b}› by auto then have "finite (f`T)" by (rule finite_subset, auto) have "card (f`T) ≤ card {0..floor ((b-a)/d)}" apply (rule card_mono) using * by auto then have card_le: "card (f`T) ≤ nat (floor ((b-a)/d) + 1)" using card_atLeastAtMost_int by auto have *: "f x ≠ f y" if "y ≥ x + d" for x y proof - have "(y-a)/d ≥ (x-a)/d + 1" using ‹d > 0› that by (auto simp add: divide_simps) then show ?thesis unfolding f_def by linarith qed have "inj_on f T" unfolding inj_on_def using * assms(3) by (auto, metis not_less_iff_gr_or_eq) show "finite T" using ‹finite (f`T)› ‹inj_on f T› finite_image_iff by blast have "card T = card (f`T)" using ‹inj_on f T› by (simp add: card_image) then show "card T ≤ nat (floor ((b-a)/d) + 1)" using card_le by auto qed subsection ‹Manipulating finite ordered sets› text ‹We will need below to construct finite sets of real numbers with good properties expressed in terms of consecutive elements of the set. We introduce tools to manipulate such sets, expressing in particular the next and the previous element of the set and controlling how they evolve when one inserts a new element in the set. It works in fact in any linorder, and could also prove useful to construct sets of integer numbers. Manipulating the next and previous elements work well, except at the top (respectively bottom). In our constructions, these will be fixed and called $b$ and $a$.› text ‹Notations for the next and the previous elements.› definition next_in::"'a set ⇒ 'a ⇒ ('a::linorder)" where "next_in A u = Min (A ∩ {u<..})" definition prev_in::"'a set ⇒ 'a ⇒ ('a::linorder)" where "prev_in A u = Max (A ∩ {..<u})" context fixes A::"('a::linorder) set" and a b::'a assumes A: "finite A" "A ⊆ {a..b}" "a ∈ A" "b ∈ A" "a < b" begin text ‹Basic properties of the next element, when one starts from an element different from top.› lemma next_in_basics: assumes "u ∈ {a..<b}" shows "next_in A u ∈ A" "next_in A u > u" "A ∩ {u<..<next_in A u} = {}" proof - have next_in_A: "next_in A u ∈ A ∩ {u<..}" unfolding next_in_def apply (rule Min_in) using assms ‹finite A› ‹b ∈ A› by auto then show "next_in A u ∈ A" "next_in A u > u" by auto show "A ∩ {u<..<next_in A u} = {}" unfolding next_in_def using A by (auto simp add: leD) qed lemma next_inI: assumes "u ∈ {a..<b}" "v ∈ A" "v > u" "{u<..<v} ∩ A = {}" shows "next_in A u = v" using assms next_in_basics[OF ‹u ∈ {a..<b}›] by fastforce text ‹Basic properties of the previous element, when one starts from an element different from bottom.› lemma prev_in_basics: assumes "u ∈ {a<..b}" shows "prev_in A u ∈ A" "prev_in A u < u" "A ∩ {prev_in A u<..<u} = {}" proof - have prev_in_A: "prev_in A u ∈ A ∩ {..<u}" unfolding prev_in_def apply (rule Max_in) using assms ‹finite A› ‹a ∈ A› by auto then show "prev_in A u ∈ A" "prev_in A u < u" by auto show "A ∩ {prev_in A u<..<u} = {}" unfolding prev_in_def using A by (auto simp add: leD) qed lemma prev_inI: assumes "u ∈ {a<..b}" "v ∈ A" "v < u" "{v<..<u} ∩ A = {}" shows "prev_in A u = v" using assms prev_in_basics[OF ‹u ∈ {a<..b}›] by (meson disjoint_iff_not_equal greaterThanLessThan_iff less_linear) text ‹The interval $[a,b]$ is covered by the intervals between the consecutive elements of $A$.› lemma intervals_decomposition: "(⋃ U ∈ {{u..next_in A u} | u. u ∈ A - {b}}. U) = {a..b}" proof show "(⋃U∈{{u..next_in A u} |u. u ∈ A - {b}}. U) ⊆ {a..b}" using ‹A ⊆ {a..b}› next_in_basics(1) apply auto apply fastforce by (metis ‹A ⊆ {a..b}› atLeastAtMost_iff eq_iff le_less_trans less_eq_real_def not_less subset_eq subset_iff_psubset_eq) have "x ∈ (⋃U∈{{u..next_in A u} |u. u ∈ A - {b}}. U)" if "x ∈ {a..b}" for x proof - consider "x = b" | "x ∈ A - {b}" | "x ∉ A" by blast then show ?thesis proof(cases) case 1 define u where "u = prev_in A b" have "b ∈ {a<..b}" using ‹a < b› by simp have "u ∈ A - {b}" unfolding u_def using prev_in_basics[OF ‹b ∈ {a<..b}›] by simp then have "u ∈ {a..<b}" using ‹A ⊆ {a..b}› ‹a