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Quellcode-Bibliothek
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Datei:
strategy.vdmrt
Sprache: Isabelle
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(* Title: HOL/Analysis/Derivative.thy
Author: John Harrison
Author: Robert Himmelmann, TU Muenchen (translation from HOL Light); tidied by LCP
*)
section \<open>Derivative\<close>
theory Derivative
imports
Bounded_Linear_Function
Line_Segment
Convex_Euclidean_Space
begin
declare bounded_linear_inner_left [intro]
declare has_derivative_bounded_linear[dest]
subsection \<open>Derivatives\<close>
lemma has_derivative_add_const:
"(f has_derivative f') net \ ((\x. f x + c) has_derivative f') net"
by (intro derivative_eq_intros) auto
subsection\<^marker>\<open>tag unimportant\<close> \<open>Derivative with composed bilinear function\<close>
text \<open>More explicit epsilon-delta forms.\<close>
proposition has_derivative_within':
"(f has_derivative f')(at x within s) \
bounded_linear f' \
(\<forall>e>0. \<exists>d>0. \<forall>x'\<in>s. 0 < norm (x' - x) \<and> norm (x' - x) < d \<longrightarrow>
norm (f x' - f x - f'(x' - x)) / norm (x' - x) < e)"
unfolding has_derivative_within Lim_within dist_norm
by (simp add: diff_diff_eq)
lemma has_derivative_at':
"(f has_derivative f') (at x)
\<longleftrightarrow> bounded_linear f' \<and>
(\<forall>e>0. \<exists>d>0. \<forall>x'. 0 < norm (x' - x) \<and> norm (x' - x) < d \<longrightarrow>
norm (f x' - f x - f'(x' - x)) / norm (x' - x) < e)"
using has_derivative_within' [of f f' x UNIV] by simp
lemma has_derivative_componentwise_within:
"(f has_derivative f') (at a within S) \
(\<forall>i \<in> Basis. ((\<lambda>x. f x \<bullet> i) has_derivative (\<lambda>x. f' x \<bullet> i)) (at a within S))"
apply (simp add: has_derivative_within)
apply (subst tendsto_componentwise_iff)
apply (simp add: bounded_linear_componentwise_iff [symmetric] ball_conj_distrib)
apply (simp add: algebra_simps)
done
lemma has_derivative_at_withinI:
"(f has_derivative f') (at x) \ (f has_derivative f') (at x within s)"
unfolding has_derivative_within' has_derivative_at'
by blast
lemma has_derivative_right:
fixes f :: "real \ real"
and y :: "real"
shows "(f has_derivative ((*) y)) (at x within ({x <..} \ I)) \
((\<lambda>t. (f x - f t) / (x - t)) \<longlongrightarrow> y) (at x within ({x <..} \<inter> I))"
proof -
have "((\t. (f t - (f x + y * (t - x))) / \t - x\) \ 0) (at x within ({x<..} \ I)) \
((\<lambda>t. (f t - f x) / (t - x) - y) \<longlongrightarrow> 0) (at x within ({x<..} \<inter> I))"
by (intro Lim_cong_within) (auto simp add: diff_divide_distrib add_divide_distrib)
also have "\ \ ((\t. (f t - f x) / (t - x)) \ y) (at x within ({x<..} \ I))"
by (simp add: Lim_null[symmetric])
also have "\ \ ((\t. (f x - f t) / (x - t)) \ y) (at x within ({x<..} \ I))"
by (intro Lim_cong_within) (simp_all add: field_simps)
finally show ?thesis
by (simp add: bounded_linear_mult_right has_derivative_within)
qed
subsubsection \<open>Caratheodory characterization\<close>
lemma DERIV_caratheodory_within:
"(f has_field_derivative l) (at x within S) \
(\<exists>g. (\<forall>z. f z - f x = g z * (z - x)) \<and> continuous (at x within S) g \<and> g x = l)"
(is "?lhs = ?rhs")
proof
assume ?lhs
show ?rhs
proof (intro exI conjI)
let ?g = "(%z. if z = x then l else (f z - f x) / (z-x))"
show "\z. f z - f x = ?g z * (z-x)" by simp
show "continuous (at x within S) ?g" using \<open>?lhs\<close>
by (auto simp add: continuous_within has_field_derivative_iff cong: Lim_cong_within)
show "?g x = l" by simp
qed
next
assume ?rhs
then obtain g where
"(\z. f z - f x = g z * (z-x))" and "continuous (at x within S) g" and "g x = l" by blast
thus ?lhs
by (auto simp add: continuous_within has_field_derivative_iff cong: Lim_cong_within)
qed
subsection \<open>Differentiability\<close>
definition\<^marker>\<open>tag important\<close>
differentiable_on :: "('a::real_normed_vector \ 'b::real_normed_vector) \ 'a set \ bool"
(infix "differentiable'_on" 50)
where "f differentiable_on s \ (\x\s. f differentiable (at x within s))"
lemma differentiableI: "(f has_derivative f') net \ f differentiable net"
unfolding differentiable_def
by auto
lemma differentiable_onD: "\f differentiable_on S; x \ S\ \ f differentiable (at x within S)"
using differentiable_on_def by blast
lemma differentiable_at_withinI: "f differentiable (at x) \ f differentiable (at x within s)"
unfolding differentiable_def
using has_derivative_at_withinI
by blast
lemma differentiable_at_imp_differentiable_on:
"(\x. x \ s \ f differentiable at x) \ f differentiable_on s"
by (metis differentiable_at_withinI differentiable_on_def)
corollary\<^marker>\<open>tag unimportant\<close> differentiable_iff_scaleR:
fixes f :: "real \ 'a::real_normed_vector"
shows "f differentiable F \ (\d. (f has_derivative (\x. x *\<^sub>R d)) F)"
by (auto simp: differentiable_def dest: has_derivative_linear linear_imp_scaleR)
lemma differentiable_on_eq_differentiable_at:
"open s \ f differentiable_on s \ (\x\s. f differentiable at x)"
unfolding differentiable_on_def
by (metis at_within_interior interior_open)
lemma differentiable_transform_within:
assumes "f differentiable (at x within s)"
and "0 < d"
and "x \ s"
and "\x'. \x'\s; dist x' x < d\ \ f x' = g x'"
shows "g differentiable (at x within s)"
using assms has_derivative_transform_within unfolding differentiable_def
by blast
lemma differentiable_on_ident [simp, derivative_intros]: "(\x. x) differentiable_on S"
by (simp add: differentiable_at_imp_differentiable_on)
lemma differentiable_on_id [simp, derivative_intros]: "id differentiable_on S"
by (simp add: id_def)
lemma differentiable_on_const [simp, derivative_intros]: "(\z. c) differentiable_on S"
by (simp add: differentiable_on_def)
lemma differentiable_on_mult [simp, derivative_intros]:
fixes f :: "'M::real_normed_vector \ 'a::real_normed_algebra"
shows "\f differentiable_on S; g differentiable_on S\ \ (\z. f z * g z) differentiable_on S"
unfolding differentiable_on_def differentiable_def
using differentiable_def differentiable_mult by blast
lemma differentiable_on_compose:
"\g differentiable_on S; f differentiable_on (g ` S)\ \ (\x. f (g x)) differentiable_on S"
by (simp add: differentiable_in_compose differentiable_on_def)
lemma bounded_linear_imp_differentiable_on: "bounded_linear f \ f differentiable_on S"
by (simp add: differentiable_on_def bounded_linear_imp_differentiable)
lemma linear_imp_differentiable_on:
fixes f :: "'a::euclidean_space \ 'b::real_normed_vector"
shows "linear f \ f differentiable_on S"
by (simp add: differentiable_on_def linear_imp_differentiable)
lemma differentiable_on_minus [simp, derivative_intros]:
"f differentiable_on S \ (\z. -(f z)) differentiable_on S"
by (simp add: differentiable_on_def)
lemma differentiable_on_add [simp, derivative_intros]:
"\f differentiable_on S; g differentiable_on S\ \ (\z. f z + g z) differentiable_on S"
by (simp add: differentiable_on_def)
lemma differentiable_on_diff [simp, derivative_intros]:
"\f differentiable_on S; g differentiable_on S\ \ (\z. f z - g z) differentiable_on S"
by (simp add: differentiable_on_def)
lemma differentiable_on_inverse [simp, derivative_intros]:
fixes f :: "'a :: real_normed_vector \ 'b :: real_normed_field"
shows "f differentiable_on S \ (\x. x \ S \ f x \ 0) \ (\x. inverse (f x)) differentiable_on S"
by (simp add: differentiable_on_def)
lemma differentiable_on_scaleR [derivative_intros, simp]:
"\f differentiable_on S; g differentiable_on S\ \ (\x. f x *\<^sub>R g x) differentiable_on S"
unfolding differentiable_on_def
by (blast intro: differentiable_scaleR)
lemma has_derivative_sqnorm_at [derivative_intros, simp]:
"((\x. (norm x)\<^sup>2) has_derivative (\x. 2 *\<^sub>R (a \ x))) (at a)"
using bounded_bilinear.FDERIV [of "(\)" id id a _ id id]
by (auto simp: inner_commute dot_square_norm bounded_bilinear_inner)
lemma differentiable_sqnorm_at [derivative_intros, simp]:
fixes a :: "'a :: {real_normed_vector,real_inner}"
shows "(\x. (norm x)\<^sup>2) differentiable (at a)"
by (force simp add: differentiable_def intro: has_derivative_sqnorm_at)
lemma differentiable_on_sqnorm [derivative_intros, simp]:
fixes S :: "'a :: {real_normed_vector,real_inner} set"
shows "(\x. (norm x)\<^sup>2) differentiable_on S"
by (simp add: differentiable_at_imp_differentiable_on)
lemma differentiable_norm_at [derivative_intros, simp]:
fixes a :: "'a :: {real_normed_vector,real_inner}"
shows "a \ 0 \ norm differentiable (at a)"
using differentiableI has_derivative_norm by blast
lemma differentiable_on_norm [derivative_intros, simp]:
fixes S :: "'a :: {real_normed_vector,real_inner} set"
shows "0 \ S \ norm differentiable_on S"
by (metis differentiable_at_imp_differentiable_on differentiable_norm_at)
subsection \<open>Frechet derivative and Jacobian matrix\<close>
definition "frechet_derivative f net = (SOME f'. (f has_derivative f') net)"
proposition frechet_derivative_works:
"f differentiable net \ (f has_derivative (frechet_derivative f net)) net"
unfolding frechet_derivative_def differentiable_def
unfolding some_eq_ex[of "\ f' . (f has_derivative f') net"] ..
lemma linear_frechet_derivative: "f differentiable net \ linear (frechet_derivative f net)"
unfolding frechet_derivative_works has_derivative_def
by (auto intro: bounded_linear.linear)
lemma frechet_derivative_const [simp]: "frechet_derivative (\x. c) (at a) = (\x. 0)"
using differentiable_const frechet_derivative_works has_derivative_const has_derivative_unique by blast
lemma frechet_derivative_id [simp]: "frechet_derivative id (at a) = id"
using differentiable_def frechet_derivative_works has_derivative_id has_derivative_unique by blast
lemma frechet_derivative_ident [simp]: "frechet_derivative (\x. x) (at a) = (\x. x)"
by (metis eq_id_iff frechet_derivative_id)
subsection \<open>Differentiability implies continuity\<close>
proposition differentiable_imp_continuous_within:
"f differentiable (at x within s) \ continuous (at x within s) f"
by (auto simp: differentiable_def intro: has_derivative_continuous)
lemma differentiable_imp_continuous_on:
"f differentiable_on s \ continuous_on s f"
unfolding differentiable_on_def continuous_on_eq_continuous_within
using differentiable_imp_continuous_within by blast
lemma differentiable_on_subset:
"f differentiable_on t \ s \ t \ f differentiable_on s"
unfolding differentiable_on_def
using differentiable_within_subset
by blast
lemma differentiable_on_empty: "f differentiable_on {}"
unfolding differentiable_on_def
by auto
lemma has_derivative_continuous_on:
"(\x. x \ s \ (f has_derivative f' x) (at x within s)) \ continuous_on s f"
by (auto intro!: differentiable_imp_continuous_on differentiableI simp: differentiable_on_def)
text \<open>Results about neighborhoods filter.\<close>
lemma eventually_nhds_metric_le:
"eventually P (nhds a) = (\d>0. \x. dist x a \ d \ P x)"
unfolding eventually_nhds_metric by (safe, rule_tac x="d / 2" in exI, auto)
lemma le_nhds: "F \ nhds a \ (\S. open S \ a \ S \ eventually (\x. x \ S) F)"
unfolding le_filter_def eventually_nhds by (fast elim: eventually_mono)
lemma le_nhds_metric: "F \ nhds a \ (\e>0. eventually (\x. dist x a < e) F)"
unfolding le_filter_def eventually_nhds_metric by (fast elim: eventually_mono)
lemma le_nhds_metric_le: "F \ nhds a \ (\e>0. eventually (\x. dist x a \ e) F)"
unfolding le_filter_def eventually_nhds_metric_le by (fast elim: eventually_mono)
text \<open>Several results are easier using a "multiplied-out" variant.
(I got this idea from Dieudonne's proof of the chain rule).\
lemma has_derivative_within_alt:
"(f has_derivative f') (at x within s) \ bounded_linear f' \
(\<forall>e>0. \<exists>d>0. \<forall>y\<in>s. norm(y - x) < d \<longrightarrow> norm (f y - f x - f' (y - x)) \<le> e * norm (y - x))"
unfolding has_derivative_within filterlim_def le_nhds_metric_le eventually_filtermap
eventually_at dist_norm diff_diff_eq
by (force simp add: linear_0 bounded_linear.linear pos_divide_le_eq)
lemma has_derivative_within_alt2:
"(f has_derivative f') (at x within s) \ bounded_linear f' \
(\<forall>e>0. eventually (\<lambda>y. norm (f y - f x - f' (y - x)) \<le> e * norm (y - x)) (at x within s))"
unfolding has_derivative_within filterlim_def le_nhds_metric_le eventually_filtermap
eventually_at dist_norm diff_diff_eq
by (force simp add: linear_0 bounded_linear.linear pos_divide_le_eq)
lemma has_derivative_at_alt:
"(f has_derivative f') (at x) \
bounded_linear f' \
(\<forall>e>0. \<exists>d>0. \<forall>y. norm(y - x) < d \<longrightarrow> norm (f y - f x - f'(y - x)) \<le> e * norm (y - x))"
using has_derivative_within_alt[where s=UNIV]
by simp
subsection \<open>The chain rule\<close>
proposition diff_chain_within[derivative_intros]:
assumes "(f has_derivative f') (at x within s)"
and "(g has_derivative g') (at (f x) within (f ` s))"
shows "((g \ f) has_derivative (g' \ f'))(at x within s)"
using has_derivative_in_compose[OF assms]
by (simp add: comp_def)
lemma diff_chain_at[derivative_intros]:
"(f has_derivative f') (at x) \
(g has_derivative g') (at (f x)) \ ((g \ f) has_derivative (g' \ f')) (at x)"
using has_derivative_compose[of f f' x UNIV g g']
by (simp add: comp_def)
lemma has_vector_derivative_within_open:
"a \ S \ open S \
(f has_vector_derivative f') (at a within S) \ (f has_vector_derivative f') (at a)"
by (simp only: at_within_interior interior_open)
lemma field_vector_diff_chain_within:
assumes Df: "(f has_vector_derivative f') (at x within S)"
and Dg: "(g has_field_derivative g') (at (f x) within f ` S)"
shows "((g \ f) has_vector_derivative (f' * g')) (at x within S)"
using diff_chain_within[OF Df[unfolded has_vector_derivative_def]
Dg [unfolded has_field_derivative_def]]
by (auto simp: o_def mult.commute has_vector_derivative_def)
lemma vector_derivative_diff_chain_within:
assumes Df: "(f has_vector_derivative f') (at x within S)"
and Dg: "(g has_derivative g') (at (f x) within f`S)"
shows "((g \ f) has_vector_derivative (g' f')) (at x within S)"
using diff_chain_within[OF Df[unfolded has_vector_derivative_def] Dg]
linear.scaleR[OF has_derivative_linear[OF Dg]]
unfolding has_vector_derivative_def o_def
by (auto simp: o_def mult.commute has_vector_derivative_def)
subsection\<^marker>\<open>tag unimportant\<close> \<open>Composition rules stated just for differentiability\<close>
lemma differentiable_chain_at:
"f differentiable (at x) \
g differentiable (at (f x)) \<Longrightarrow> (g \<circ> f) differentiable (at x)"
unfolding differentiable_def
by (meson diff_chain_at)
lemma differentiable_chain_within:
"f differentiable (at x within S) \
g differentiable (at(f x) within (f ` S)) \<Longrightarrow> (g \<circ> f) differentiable (at x within S)"
unfolding differentiable_def
by (meson diff_chain_within)
subsection \<open>Uniqueness of derivative\<close>
text\<^marker>\<open>tag important\<close> \<open>
The general result is a bit messy because we need approachability of the
limit point from any direction. But OK for nontrivial intervals etc.
\<close>
proposition frechet_derivative_unique_within:
fixes f :: "'a::euclidean_space \ 'b::real_normed_vector"
assumes 1: "(f has_derivative f') (at x within S)"
and 2: "(f has_derivative f'') (at x within S)"
and S: "\i e. \i\Basis; e>0\ \ \d. 0 < \d\ \ \d\ < e \ (x + d *\<^sub>R i) \ S"
shows "f' = f''"
proof -
note as = assms(1,2)[unfolded has_derivative_def]
then interpret f': bounded_linear f' by auto
from as interpret f'': bounded_linear f'' by auto
have "x islimpt S" unfolding islimpt_approachable
proof (intro allI impI)
fix e :: real
assume "e > 0"
obtain d where "0 < \d\" and "\d\ < e" and "x + d *\<^sub>R (SOME i. i \ Basis) \ S"
using assms(3) SOME_Basis \<open>e>0\<close> by blast
then show "\x'\S. x' \ x \ dist x' x < e"
by (rule_tac x="x + d *\<^sub>R (SOME i. i \ Basis)" in bexI) (auto simp: dist_norm SOME_Basis nonzero_Basis) qed
then have *: "netlimit (at x within S) = x"
by (simp add: Lim_ident_at trivial_limit_within)
show ?thesis
proof (rule linear_eq_stdbasis)
show "linear f'" "linear f''"
unfolding linear_conv_bounded_linear using as by auto
next
fix i :: 'a
assume i: "i \ Basis"
define e where "e = norm (f' i - f'' i)"
show "f' i = f'' i"
proof (rule ccontr)
assume "f' i \ f'' i"
then have "e > 0"
unfolding e_def by auto
obtain d where d:
"0 < d"
"(\y. y\S \ 0 < dist y x \ dist y x < d \
dist ((f y - f x - f' (y - x)) /\<^sub>R norm (y - x) -
(f y - f x - f'' (y - x)) /\<^sub>R norm (y - x)) (0 - 0) < e)"
using tendsto_diff [OF as(1,2)[THEN conjunct2]]
unfolding * Lim_within
using \<open>e>0\<close> by blast
obtain c where c: "0 < \c\" "\c\ < d \ x + c *\<^sub>R i \ S"
using assms(3) i d(1) by blast
have *: "norm (- ((1 / \c\) *\<^sub>R f' (c *\<^sub>R i)) + (1 / \c\) *\<^sub>R f'' (c *\<^sub>R i)) =
norm ((1 / \<bar>c\<bar>) *\<^sub>R (- (f' (c *\<^sub>R i)) + f'' (c *\<^sub>R i)))"
unfolding scaleR_right_distrib by auto
also have "\ = norm ((1 / \c\) *\<^sub>R (c *\<^sub>R (- (f' i) + f'' i)))"
unfolding f'.scaleR f''.scaleR
unfolding scaleR_right_distrib scaleR_minus_right
by auto
also have "\ = e"
unfolding e_def
using c(1)
using norm_minus_cancel[of "f' i - f'' i"]
by auto
finally show False
using c
using d(2)[of "x + c *\<^sub>R i"]
unfolding dist_norm
unfolding f'.scaleR f''.scaleR f'.add f''.add f'.diff f''.diff
scaleR_scaleR scaleR_right_diff_distrib scaleR_right_distrib
using i
by (auto simp: inverse_eq_divide)
qed
qed
qed
proposition frechet_derivative_unique_within_closed_interval:
fixes f::"'a::euclidean_space \ 'b::real_normed_vector"
assumes ab: "\i. i\Basis \ a\i < b\i"
and x: "x \ cbox a b"
and "(f has_derivative f' ) (at x within cbox a b)"
and "(f has_derivative f'') (at x within cbox a b)"
shows "f' = f''"
proof (rule frechet_derivative_unique_within)
fix e :: real
fix i :: 'a
assume "e > 0" and i: "i \ Basis"
then show "\d. 0 < \d\ \ \d\ < e \ x + d *\<^sub>R i \ cbox a b"
proof (cases "x\i = a\i")
case True
with ab[of i] \<open>e>0\<close> x i show ?thesis
by (rule_tac x="(min (b\i - a\i) e) / 2" in exI)
(auto simp add: mem_box field_simps inner_simps inner_Basis)
next
case False
moreover have "a \ i < x \ i"
using False i mem_box(2) x by force
moreover {
have "a \ i * 2 + min (x \ i - a \ i) e \ a\i *2 + x\i - a\i"
by auto
also have "\ = a\i + x\i"
by auto
also have "\ \ 2 * (x\i)"
using \<open>a \<bullet> i < x \<bullet> i\<close> by auto
finally have "a \ i * 2 + min (x \ i - a \ i) e \ x \ i * 2"
by auto
}
moreover have "min (x \ i - a \ i) e \ 0"
by (simp add: \<open>0 < e\<close> \<open>a \<bullet> i < x \<bullet> i\<close> less_eq_real_def)
then have "x \ i * 2 \ b \ i * 2 + min (x \ i - a \ i) e"
using i mem_box(2) x by force
ultimately show ?thesis
using ab[of i] \<open>e>0\<close> x i
by (rule_tac x="- (min (x\i - a\i) e) / 2" in exI)
(auto simp add: mem_box field_simps inner_simps inner_Basis)
qed
qed (use assms in auto)
lemma frechet_derivative_unique_within_open_interval:
fixes f::"'a::euclidean_space \ 'b::real_normed_vector"
assumes x: "x \ box a b"
and f: "(f has_derivative f' ) (at x within box a b)" "(f has_derivative f'') (at x within box a b)"
shows "f' = f''"
proof -
have "at x within box a b = at x"
by (metis x at_within_interior interior_open open_box)
with f show "f' = f''"
by (simp add: has_derivative_unique)
qed
lemma frechet_derivative_at:
"(f has_derivative f') (at x) \ f' = frechet_derivative f (at x)"
using differentiable_def frechet_derivative_works has_derivative_unique by blast
lemma frechet_derivative_compose:
"frechet_derivative (f o g) (at x) = frechet_derivative (f) (at (g x)) o frechet_derivative g (at x)"
if "g differentiable at x" "f differentiable at (g x)"
by (metis diff_chain_at frechet_derivative_at frechet_derivative_works that)
lemma frechet_derivative_within_cbox:
fixes f :: "'a::euclidean_space \ 'b::real_normed_vector"
assumes "\i. i\Basis \ a\i < b\i"
and "x \ cbox a b"
and "(f has_derivative f') (at x within cbox a b)"
shows "frechet_derivative f (at x within cbox a b) = f'"
using assms
by (metis Derivative.differentiableI frechet_derivative_unique_within_closed_interval frechet_derivative_works)
lemma frechet_derivative_transform_within_open:
"frechet_derivative f (at x) = frechet_derivative g (at x)"
if "f differentiable at x" "open X" "x \ X" "\x. x \ X \ f x = g x"
by (meson frechet_derivative_at frechet_derivative_works has_derivative_transform_within_open that)
subsection \<open>Derivatives of local minima and maxima are zero\<close>
lemma has_derivative_local_min:
fixes f :: "'a::real_normed_vector \ real"
assumes deriv: "(f has_derivative f') (at x)"
assumes min: "eventually (\y. f x \ f y) (at x)"
shows "f' = (\h. 0)"
proof
fix h :: 'a
interpret f': bounded_linear f'
using deriv by (rule has_derivative_bounded_linear)
show "f' h = 0"
proof (cases "h = 0")
case False
from min obtain d where d1: "0 < d" and d2: "\y\ball x d. f x \ f y"
unfolding eventually_at by (force simp: dist_commute)
have "FDERIV (\r. x + r *\<^sub>R h) 0 :> (\r. r *\<^sub>R h)"
by (intro derivative_eq_intros) auto
then have "FDERIV (\r. f (x + r *\<^sub>R h)) 0 :> (\k. f' (k *\<^sub>R h))"
by (rule has_derivative_compose, simp add: deriv)
then have "DERIV (\r. f (x + r *\<^sub>R h)) 0 :> f' h"
unfolding has_field_derivative_def by (simp add: f'.scaleR mult_commute_abs)
moreover have "0 < d / norm h" using d1 and \<open>h \<noteq> 0\<close> by simp
moreover have "\y. \0 - y\ < d / norm h \ f (x + 0 *\<^sub>R h) \ f (x + y *\<^sub>R h)"
using \<open>h \<noteq> 0\<close> by (auto simp add: d2 dist_norm pos_less_divide_eq)
ultimately show "f' h = 0"
by (rule DERIV_local_min)
qed simp
qed
lemma has_derivative_local_max:
fixes f :: "'a::real_normed_vector \ real"
assumes "(f has_derivative f') (at x)"
assumes "eventually (\y. f y \ f x) (at x)"
shows "f' = (\h. 0)"
using has_derivative_local_min [of "\x. - f x" "\h. - f' h" "x"]
using assms unfolding fun_eq_iff by simp
lemma differential_zero_maxmin:
fixes f::"'a::real_normed_vector \ real"
assumes "x \ S"
and "open S"
and deriv: "(f has_derivative f') (at x)"
and mono: "(\y\S. f y \ f x) \ (\y\S. f x \ f y)"
shows "f' = (\v. 0)"
using mono
proof
assume "\y\S. f y \ f x"
with \<open>x \<in> S\<close> and \<open>open S\<close> have "eventually (\<lambda>y. f y \<le> f x) (at x)"
unfolding eventually_at_topological by auto
with deriv show ?thesis
by (rule has_derivative_local_max)
next
assume "\y\S. f x \ f y"
with \<open>x \<in> S\<close> and \<open>open S\<close> have "eventually (\<lambda>y. f x \<le> f y) (at x)"
unfolding eventually_at_topological by auto
with deriv show ?thesis
by (rule has_derivative_local_min)
qed
lemma differential_zero_maxmin_component:
fixes f :: "'a::euclidean_space \ 'b::euclidean_space"
assumes k: "k \ Basis"
and ball: "0 < e" "(\y \ ball x e. (f y)\k \ (f x)\k) \ (\y\ball x e. (f x)\k \ (f y)\k)"
and diff: "f differentiable (at x)"
shows "(\j\Basis. (frechet_derivative f (at x) j \ k) *\<^sub>R j) = (0::'a)" (is "?D k = 0")
proof -
let ?f' = "frechet_derivative f (at x)"
have "x \ ball x e" using \0 < e\ by simp
moreover have "open (ball x e)" by simp
moreover have "((\x. f x \ k) has_derivative (\h. ?f' h \ k)) (at x)"
using bounded_linear_inner_left diff[unfolded frechet_derivative_works]
by (rule bounded_linear.has_derivative)
ultimately have "(\h. frechet_derivative f (at x) h \ k) = (\v. 0)"
using ball(2) by (rule differential_zero_maxmin)
then show ?thesis
unfolding fun_eq_iff by simp
qed
subsection \<open>One-dimensional mean value theorem\<close>
lemma mvt_simple:
fixes f :: "real \ real"
assumes "a < b"
and derf: "\x. \a \ x; x \ b\ \ (f has_derivative f' x) (at x within {a..b})"
shows "\x\{a<..
proof (rule mvt)
have "f differentiable_on {a..b}"
using derf unfolding differentiable_on_def differentiable_def by force
then show "continuous_on {a..b} f"
by (rule differentiable_imp_continuous_on)
show "(f has_derivative f' x) (at x)" if "a < x" "x < b" for x
by (metis at_within_Icc_at derf leI order.asym that)
qed (use assms in auto)
lemma mvt_very_simple:
fixes f :: "real \ real"
assumes "a \ b"
and derf: "\x. \a \ x; x \ b\ \ (f has_derivative f' x) (at x within {a..b})"
shows "\x\{a..b}. f b - f a = f' x (b - a)"
proof (cases "a = b")
interpret bounded_linear "f' b"
using assms(2) assms(1) by auto
case True
then show ?thesis
by force
next
case False
then show ?thesis
using mvt_simple[OF _ derf]
by (metis \<open>a \<le> b\<close> atLeastAtMost_iff dual_order.order_iff_strict greaterThanLessThan_iff)
qed
text \<open>A nice generalization (see Havin's proof of 5.19 from Rudin's book).\<close>
lemma mvt_general:
fixes f :: "real \ 'a::real_inner"
assumes "a < b"
and contf: "continuous_on {a..b} f"
and derf: "\x. \a < x; x < b\ \ (f has_derivative f' x) (at x)"
shows "\x\{a<.. norm (f' x (b - a))"
proof -
have "\x\{a<.. f b - (f b - f a) \ f a = (f b - f a) \ f' x (b - a)"
apply (rule mvt [OF \<open>a < b\<close>, where f = "\<lambda>x. (f b - f a) \<bullet> f x"])
apply (intro continuous_intros contf)
using derf apply (auto intro: has_derivative_inner_right)
done
then obtain x where x: "x \ {a<..
"(f b - f a) \ f b - (f b - f a) \ f a = (f b - f a) \ f' x (b - a)" ..
show ?thesis
proof (cases "f a = f b")
case False
have "norm (f b - f a) * norm (f b - f a) = (norm (f b - f a))\<^sup>2"
by (simp add: power2_eq_square)
also have "\ = (f b - f a) \ (f b - f a)"
unfolding power2_norm_eq_inner ..
also have "\ = (f b - f a) \ f' x (b - a)"
using x(2) by (simp only: inner_diff_right)
also have "\ \ norm (f b - f a) * norm (f' x (b - a))"
by (rule norm_cauchy_schwarz)
finally show ?thesis
using False x(1)
by (auto simp add: mult_left_cancel)
next
case True
then show ?thesis
using \<open>a < b\<close> by (rule_tac x="(a + b) /2" in bexI) auto
qed
qed
subsection \<open>More general bound theorems\<close>
proposition differentiable_bound_general:
fixes f :: "real \ 'a::real_normed_vector"
assumes "a < b"
and f_cont: "continuous_on {a..b} f"
and phi_cont: "continuous_on {a..b} \"
and f': "\x. a < x \ x < b \ (f has_vector_derivative f' x) (at x)"
and phi': "\x. a < x \ x < b \ (\ has_vector_derivative \' x) (at x)"
and bnd: "\x. a < x \ x < b \ norm (f' x) \ \' x"
shows "norm (f b - f a) \ \ b - \ a"
proof -
{
fix x assume x: "a < x" "x < b"
have "0 \ norm (f' x)" by simp
also have "\ \ \' x" using x by (auto intro!: bnd)
finally have "0 \ \' x" .
} note phi'_nonneg = this
note f_tendsto = assms(2)[simplified continuous_on_def, rule_format]
note phi_tendsto = assms(3)[simplified continuous_on_def, rule_format]
{
fix e::real assume "e > 0"
define e2 where "e2 = e / 2"
with \<open>e > 0\<close> have "e2 > 0" by simp
let ?le = "\x1. norm (f x1 - f a) \ \ x1 - \ a + e * (x1 - a) + e"
define A where "A = {x2. a \ x2 \ x2 \ b \ (\x1\{a ..< x2}. ?le x1)}"
have A_subset: "A \ {a..b}" by (auto simp: A_def)
{
fix x2
assume a: "a \ x2" "x2 \ b" and le: "\x1\{a..
have "?le x2" using \<open>e > 0\<close>
proof cases
assume "x2 \ a" with a have "a < x2" by simp
have "at x2 within {a <.. bot"
using \<open>a < x2\<close>
by (auto simp: trivial_limit_within islimpt_in_closure)
moreover
have "((\x1. (\ x1 - \ a) + e * (x1 - a) + e) \ (\ x2 - \ a) + e * (x2 - a) + e) (at x2 within {a <..
"((\x1. norm (f x1 - f a)) \ norm (f x2 - f a)) (at x2 within {a <..
using a
by (auto intro!: tendsto_eq_intros f_tendsto phi_tendsto
intro: tendsto_within_subset[where S="{a..b}"])
moreover
have "eventually (\x. x > a) (at x2 within {a <..
by (auto simp: eventually_at_filter)
hence "eventually ?le (at x2 within {a <..
unfolding eventually_at_filter
by eventually_elim (insert le, auto)
ultimately
show ?thesis
by (rule tendsto_le)
qed simp
} note le_cont = this
have "a \ A"
using assms by (auto simp: A_def)
hence [simp]: "A \ {}" by auto
have A_ivl: "\x1 x2. x2 \ A \ x1 \ {a ..x2} \ x1 \ A"
by (simp add: A_def)
have [simp]: "bdd_above A" by (auto simp: A_def)
define y where "y = Sup A"
have "y \ b"
unfolding y_def
by (simp add: cSup_le_iff) (simp add: A_def)
have leI: "\x x1. a \ x1 \ x \ A \ x1 < x \ ?le x1"
by (auto simp: A_def intro!: le_cont)
have y_all_le: "\x1\{a..
by (auto simp: y_def less_cSup_iff leI)
have "a \ y"
by (metis \<open>a \<in> A\<close> \<open>bdd_above A\<close> cSup_upper y_def)
have "y \ A"
using y_all_le \<open>a \<le> y\<close> \<open>y \<le> b\<close>
by (auto simp: A_def)
hence "A = {a .. y}"
using A_subset by (auto simp: subset_iff y_def cSup_upper intro: A_ivl)
from le_cont[OF \<open>a \<le> y\<close> \<open>y \<le> b\<close> y_all_le] have le_y: "?le y" .
have "y = b"
proof (cases "a = y")
case True
with \<open>a < b\<close> have "y < b" by simp
with \<open>a = y\<close> f_cont phi_cont \<open>e2 > 0\<close>
have 1: "\\<^sub>F x in at y within {y..b}. dist (f x) (f y) < e2"
and 2: "\\<^sub>F x in at y within {y..b}. dist (\ x) (\ y) < e2"
by (auto simp: continuous_on_def tendsto_iff)
have 3: "eventually (\x. y < x) (at y within {y..b})"
by (auto simp: eventually_at_filter)
have 4: "eventually (\x::real. x < b) (at y within {y..b})"
using _ \<open>y < b\<close>
by (rule order_tendstoD) (auto intro!: tendsto_eq_intros)
from 1 2 3 4
have eventually_le: "eventually (\x. ?le x) (at y within {y .. b})"
proof eventually_elim
case (elim x1)
have "norm (f x1 - f a) = norm (f x1 - f y)"
by (simp add: \<open>a = y\<close>)
also have "norm (f x1 - f y) \ e2"
using elim \<open>a = y\<close> by (auto simp : dist_norm intro!: less_imp_le)
also have "\ \ e2 + (\ x1 - \ a + e2 + e * (x1 - a))"
using \<open>0 < e\<close> elim
by (intro add_increasing2[OF add_nonneg_nonneg order.refl])
(auto simp: \<open>a = y\<close> dist_norm intro!: mult_nonneg_nonneg)
also have "\ = \ x1 - \ a + e * (x1 - a) + e"
by (simp add: e2_def)
finally show "?le x1" .
qed
from this[unfolded eventually_at_topological] \<open>?le y\<close>
obtain S where S: "open S" "y \ S" "\x. x\S \ x \ {y..b} \ ?le x"
by metis
from \<open>open S\<close> obtain d where d: "\<And>x. dist x y < d \<Longrightarrow> x \<in> S" "d > 0"
by (force simp: dist_commute open_dist ball_def dest!: bspec[OF _ \<open>y \<in> S\<close>])
define d' where "d' = min b (y + (d/2))"
have "d' \ A"
unfolding A_def
proof safe
show "a \ d'" using \a = y\ \0 < d\ \y < b\ by (simp add: d'_def)
show "d' \ b" by (simp add: d'_def)
fix x1
assume "x1 \ {a..
hence "x1 \ S" "x1 \ {y..b}"
by (auto simp: \<open>a = y\<close> d'_def dist_real_def intro!: d )
thus "?le x1"
by (rule S)
qed
hence "d' \ y"
unfolding y_def
by (rule cSup_upper) simp
then show "y = b" using \<open>d > 0\<close> \<open>y < b\<close>
by (simp add: d'_def)
next
case False
with \<open>a \<le> y\<close> have "a < y" by simp
show "y = b"
proof (rule ccontr)
assume "y \ b"
hence "y < b" using \<open>y \<le> b\<close> by simp
let ?F = "at y within {y..
from f' phi'
have "(f has_vector_derivative f' y) ?F"
and "(\ has_vector_derivative \' y) ?F"
using \<open>a < y\<close> \<open>y < b\<close>
by (auto simp add: at_within_open[of _ "{a<..] has_vector_derivative_def
intro!: has_derivative_subset[where s="{a<.. and t="{y..])
hence "\\<^sub>F x1 in ?F. norm (f x1 - f y - (x1 - y) *\<^sub>R f' y) \ e2 * \x1 - y\"
"\\<^sub>F x1 in ?F. norm (\ x1 - \ y - (x1 - y) *\<^sub>R \' y) \ e2 * \x1 - y\"
using \<open>e2 > 0\<close>
by (auto simp: has_derivative_within_alt2 has_vector_derivative_def)
moreover
have "\\<^sub>F x1 in ?F. y \ x1" "\\<^sub>F x1 in ?F. x1 < b"
by (auto simp: eventually_at_filter)
ultimately
have "\\<^sub>F x1 in ?F. norm (f x1 - f y) \ (\ x1 - \ y) + e * \x1 - y\"
(is "\\<^sub>F x1 in ?F. ?le' x1")
proof eventually_elim
case (elim x1)
from norm_triangle_ineq2[THEN order_trans, OF elim(1)]
have "norm (f x1 - f y) \ norm (f' y) * \x1 - y\ + e2 * \x1 - y\"
by (simp add: ac_simps)
also have "norm (f' y) \ \' y" using bnd \a < y\ \y < b\ by simp
also have "\' y * \x1 - y\ \ \ x1 - \ y + e2 * \x1 - y\"
using elim by (simp add: ac_simps)
finally
have "norm (f x1 - f y) \ \ x1 - \ y + e2 * \x1 - y\ + e2 * \x1 - y\"
by (auto simp: mult_right_mono)
thus ?case by (simp add: e2_def)
qed
moreover have "?le' y" by simp
ultimately obtain S
where S: "open S" "y \ S" "\x. x\S \ x \ {y.. ?le' x"
unfolding eventually_at_topological
by metis
from \<open>open S\<close> obtain d where d: "\<And>x. dist x y < d \<Longrightarrow> x \<in> S" "d > 0"
by (force simp: dist_commute open_dist ball_def dest!: bspec[OF _ \<open>y \<in> S\<close>])
define d' where "d' = min ((y + b)/2) (y + (d/2))"
have "d' \ A"
unfolding A_def
proof safe
show "a \ d'" using \a < y\ \0 < d\ \y < b\ by (simp add: d'_def)
show "d' \ b" using \y < b\ by (simp add: d'_def min_def)
fix x1
assume x1: "x1 \ {a..
show "?le x1"
proof (cases "x1 < y")
case True
then show ?thesis
using \<open>y \<in> A\<close> local.leI x1 by auto
next
case False
hence x1': "x1 \ S" "x1 \ {y..
by (auto simp: d'_def dist_real_def intro!: d)
have "norm (f x1 - f a) \ norm (f x1 - f y) + norm (f y - f a)"
by (rule order_trans[OF _ norm_triangle_ineq]) simp
also note S(3)[OF x1']
also note le_y
finally show "?le x1"
using False by (auto simp: algebra_simps)
qed
qed
hence "d' \ y"
unfolding y_def by (rule cSup_upper) simp
thus False using \<open>d > 0\<close> \<open>y < b\<close>
by (simp add: d'_def min_def split: if_split_asm)
qed
qed
with le_y have "norm (f b - f a) \ \ b - \ a + e * (b - a + 1)"
by (simp add: algebra_simps)
} note * = this
show ?thesis
proof (rule field_le_epsilon)
fix e::real assume "e > 0"
then show "norm (f b - f a) \ \ b - \ a + e"
using *[of "e / (b - a + 1)"] \<open>a < b\<close> by simp
qed
qed
lemma differentiable_bound:
fixes f :: "'a::real_normed_vector \ 'b::real_normed_vector"
assumes "convex S"
and derf: "\x. x\S \ (f has_derivative f' x) (at x within S)"
and B: "\x. x \ S \ onorm (f' x) \ B"
and x: "x \ S"
and y: "y \ S"
shows "norm (f x - f y) \ B * norm (x - y)"
proof -
let ?p = "\u. x + u *\<^sub>R (y - x)"
let ?\<phi> = "\<lambda>h. h * B * norm (x - y)"
have *: "x + u *\<^sub>R (y - x) \ S" if "u \ {0..1}" for u
proof -
have "u *\<^sub>R y = u *\<^sub>R (y - x) + u *\<^sub>R x"
by (simp add: scale_right_diff_distrib)
then show "x + u *\<^sub>R (y - x) \ S"
using that \<open>convex S\<close> x y by (simp add: convex_alt)
(metis pth_b(2) pth_c(1) scaleR_collapse)
qed
have "\z. z \ (\u. x + u *\<^sub>R (y - x)) ` {0..1} \
(f has_derivative f' z) (at z within (\u. x + u *\<^sub>R (y - x)) ` {0..1})"
by (auto intro: * has_derivative_subset [OF derf])
then have "continuous_on (?p ` {0..1}) f"
unfolding continuous_on_eq_continuous_within
by (meson has_derivative_continuous)
with * have 1: "continuous_on {0 .. 1} (f \ ?p)"
by (intro continuous_intros)+
{
fix u::real assume u: "u \{0 <..< 1}"
let ?u = "?p u"
interpret linear "(f' ?u)"
using u by (auto intro!: has_derivative_linear derf *)
have "(f \ ?p has_derivative (f' ?u) \ (\u. 0 + u *\<^sub>R (y - x))) (at u within box 0 1)"
by (intro derivative_intros has_derivative_subset [OF derf]) (use u * in auto)
hence "((f \ ?p) has_vector_derivative f' ?u (y - x)) (at u)"
by (simp add: at_within_open[OF u open_greaterThanLessThan] scaleR has_vector_derivative_def o_def)
} note 2 = this
have 3: "continuous_on {0..1} ?\"
by (rule continuous_intros)+
have 4: "(?\ has_vector_derivative B * norm (x - y)) (at u)" for u
by (auto simp: has_vector_derivative_def intro!: derivative_eq_intros)
{
fix u::real assume u: "u \{0 <..< 1}"
let ?u = "?p u"
interpret bounded_linear "(f' ?u)"
using u by (auto intro!: has_derivative_bounded_linear derf *)
have "norm (f' ?u (y - x)) \ onorm (f' ?u) * norm (y - x)"
by (rule onorm) (rule bounded_linear)
also have "onorm (f' ?u) \ B"
using u by (auto intro!: assms(3)[rule_format] *)
finally have "norm ((f' ?u) (y - x)) \ B * norm (x - y)"
by (simp add: mult_right_mono norm_minus_commute)
} note 5 = this
have "norm (f x - f y) = norm ((f \ (\u. x + u *\<^sub>R (y - x))) 1 - (f \ (\u. x + u *\<^sub>R (y - x))) 0)"
by (auto simp add: norm_minus_commute)
also
from differentiable_bound_general[OF zero_less_one 1, OF 3 2 4 5]
have "norm ((f \ ?p) 1 - (f \ ?p) 0) \ B * norm (x - y)"
by simp
finally show ?thesis .
qed
lemma field_differentiable_bound:
fixes S :: "'a::real_normed_field set"
assumes cvs: "convex S"
and df: "\z. z \ S \ (f has_field_derivative f' z) (at z within S)"
and dn: "\z. z \ S \ norm (f' z) \ B"
and "x \ S" "y \ S"
shows "norm(f x - f y) \ B * norm(x - y)"
apply (rule differentiable_bound [OF cvs])
apply (erule df [unfolded has_field_derivative_def])
apply (rule onorm_le, simp_all add: norm_mult mult_right_mono assms)
done
lemma
differentiable_bound_segment:
fixes f::"'a::real_normed_vector \ 'b::real_normed_vector"
assumes "\t. t \ {0..1} \ x0 + t *\<^sub>R a \ G"
assumes f': "\x. x \ G \ (f has_derivative f' x) (at x within G)"
assumes B: "\x. x \ {0..1} \ onorm (f' (x0 + x *\<^sub>R a)) \ B"
shows "norm (f (x0 + a) - f x0) \ norm a * B"
proof -
let ?G = "(\x. x0 + x *\<^sub>R a) ` {0..1}"
have "?G = (+) x0 ` (\x. x *\<^sub>R a) ` {0..1}" by auto
also have "convex \"
by (intro convex_translation convex_scaled convex_real_interval)
finally have "convex ?G" .
moreover have "?G \ G" "x0 \ ?G" "x0 + a \ ?G" using assms by (auto intro: image_eqI[where x=1])
ultimately show ?thesis
using has_derivative_subset[OF f' \?G \ G\] B
differentiable_bound[of "(\x. x0 + x *\<^sub>R a) ` {0..1}" f f' B "x0 + a" x0]
by (force simp: ac_simps)
qed
lemma differentiable_bound_linearization:
fixes f::"'a::real_normed_vector \ 'b::real_normed_vector"
assumes S: "\t. t \ {0..1} \ a + t *\<^sub>R (b - a) \ S"
assumes f'[derivative_intros]: "\x. x \ S \ (f has_derivative f' x) (at x within S)"
assumes B: "\x. x \ S \ onorm (f' x - f' x0) \ B"
assumes "x0 \ S"
shows "norm (f b - f a - f' x0 (b - a)) \ norm (b - a) * B"
proof -
define g where [abs_def]: "g x = f x - f' x0 x" for x
have g: "\x. x \ S \ (g has_derivative (\i. f' x i - f' x0 i)) (at x within S)"
unfolding g_def using assms
by (auto intro!: derivative_eq_intros
bounded_linear.has_derivative[OF has_derivative_bounded_linear, OF f'])
from B have "\x\{0..1}. onorm (\i. f' (a + x *\<^sub>R (b - a)) i - f' x0 i) \ B"
using assms by (auto simp: fun_diff_def)
with differentiable_bound_segment[OF S g] \<open>x0 \<in> S\<close>
show ?thesis
by (simp add: g_def field_simps linear_diff[OF has_derivative_linear[OF f']])
qed
lemma vector_differentiable_bound_linearization:
fixes f::"real \ 'b::real_normed_vector"
assumes f': "\x. x \ S \ (f has_vector_derivative f' x) (at x within S)"
assumes "closed_segment a b \ S"
assumes B: "\x. x \ S \ norm (f' x - f' x0) \ B"
assumes "x0 \ S"
shows "norm (f b - f a - (b - a) *\<^sub>R f' x0) \ norm (b - a) * B"
using assms
by (intro differentiable_bound_linearization[of a b S f "\x h. h *\<^sub>R f' x" x0 B])
(force simp: closed_segment_real_eq has_vector_derivative_def
scaleR_diff_right[symmetric] mult.commute[of B]
intro!: onorm_le mult_left_mono)+
text \<open>In particular.\<close>
lemma has_derivative_zero_constant:
fixes f :: "'a::real_normed_vector \ 'b::real_normed_vector"
assumes "convex s"
and "\x. x \ s \ (f has_derivative (\h. 0)) (at x within s)"
shows "\c. \x\s. f x = c"
proof -
{ fix x y assume "x \ s" "y \ s"
then have "norm (f x - f y) \ 0 * norm (x - y)"
using assms by (intro differentiable_bound[of s]) (auto simp: onorm_zero)
then have "f x = f y"
by simp }
then show ?thesis
by metis
qed
lemma has_field_derivative_zero_constant:
assumes "convex s" "\x. x \ s \ (f has_field_derivative 0) (at x within s)"
shows "\c. \x\s. f (x) = (c :: 'a :: real_normed_field)"
proof (rule has_derivative_zero_constant)
have A: "(*) 0 = (\_. 0 :: 'a)" by (intro ext) simp
fix x assume "x \ s" thus "(f has_derivative (\h. 0)) (at x within s)"
using assms(2)[of x] by (simp add: has_field_derivative_def A)
qed fact
lemma
has_vector_derivative_zero_constant:
assumes "convex s"
assumes "\x. x \ s \ (f has_vector_derivative 0) (at x within s)"
obtains c where "\x. x \ s \ f x = c"
using has_derivative_zero_constant[of s f] assms
by (auto simp: has_vector_derivative_def)
lemma has_derivative_zero_unique:
fixes f :: "'a::real_normed_vector \ 'b::real_normed_vector"
assumes "convex s"
and "\x. x \ s \ (f has_derivative (\h. 0)) (at x within s)"
and "x \ s" "y \ s"
shows "f x = f y"
using has_derivative_zero_constant[OF assms(1,2)] assms(3-) by force
lemma has_derivative_zero_unique_connected:
fixes f :: "'a::real_normed_vector \ 'b::real_normed_vector"
assumes "open s" "connected s"
assumes f: "\x. x \ s \ (f has_derivative (\x. 0)) (at x)"
assumes "x \ s" "y \ s"
shows "f x = f y"
proof (rule connected_local_const[where f=f, OF \<open>connected s\<close> \<open>x\<in>s\<close> \<open>y\<in>s\<close>])
show "\a\s. eventually (\b. f a = f b) (at a within s)"
proof
fix a assume "a \ s"
with \<open>open s\<close> obtain e where "0 < e" "ball a e \<subseteq> s"
by (rule openE)
then have "\c. \x\ball a e. f x = c"
by (intro has_derivative_zero_constant)
(auto simp: at_within_open[OF _ open_ball] f)
with \<open>0<e\<close> have "\<forall>x\<in>ball a e. f a = f x"
by auto
then show "eventually (\b. f a = f b) (at a within s)"
using \<open>0<e\<close> unfolding eventually_at_topological
by (intro exI[of _ "ball a e"]) auto
qed
qed
subsection \<open>Differentiability of inverse function (most basic form)\<close>
lemma has_derivative_inverse_basic:
fixes f :: "'a::real_normed_vector \ 'b::real_normed_vector"
assumes derf: "(f has_derivative f') (at (g y))"
and ling': "bounded_linear g'"
and "g' \ f' = id"
and contg: "continuous (at y) g"
and "open T"
and "y \ T"
and fg: "\z. z \ T \ f (g z) = z"
shows "(g has_derivative g') (at y)"
proof -
interpret f': bounded_linear f'
using assms unfolding has_derivative_def by auto
interpret g': bounded_linear g'
using assms by auto
obtain C where C: "0 < C" "\x. norm (g' x) \ norm x * C"
using bounded_linear.pos_bounded[OF assms(2)] by blast
have lem1: "\e>0. \d>0. \z.
norm (z - y) < d \<longrightarrow> norm (g z - g y - g'(z - y)) \<le> e * norm (g z - g y)"
proof (intro allI impI)
fix e :: real
assume "e > 0"
with C(1) have *: "e / C > 0" by auto
obtain d0 where "0 < d0" and d0:
"\u. norm (u - g y) < d0 \ norm (f u - f (g y) - f' (u - g y)) \ e / C * norm (u - g y)"
using derf * unfolding has_derivative_at_alt by blast
obtain d1 where "0 < d1" and d1: "\x. \0 < dist x y; dist x y < d1\ \ dist (g x) (g y) < d0"
using contg \<open>0 < d0\<close> unfolding continuous_at Lim_at by blast
obtain d2 where "0 < d2" and d2: "\u. dist u y < d2 \ u \ T"
using \<open>open T\<close> \<open>y \<in> T\<close> unfolding open_dist by blast
obtain d where d: "0 < d" "d < d1" "d < d2"
using field_lbound_gt_zero[OF \<open>0 < d1\<close> \<open>0 < d2\<close>] by blast
show "\d>0. \z. norm (z - y) < d \ norm (g z - g y - g' (z - y)) \ e * norm (g z - g y)"
proof (intro exI allI impI conjI)
fix z
assume as: "norm (z - y) < d"
then have "z \ T"
using d2 d unfolding dist_norm by auto
have "norm (g z - g y - g' (z - y)) \ norm (g' (f (g z) - y - f' (g z - g y)))"
unfolding g'.diff f'.diff
unfolding assms(3)[unfolded o_def id_def, THEN fun_cong] fg[OF \<open>z\<in>T\<close>]
by (simp add: norm_minus_commute)
also have "\ \ norm (f (g z) - y - f' (g z - g y)) * C"
by (rule C(2))
also have "\ \ (e / C) * norm (g z - g y) * C"
proof -
have "norm (g z - g y) < d0"
by (metis as cancel_comm_monoid_add_class.diff_cancel d(2) \<open>0 < d0\<close> d1 diff_gt_0_iff_gt diff_strict_mono dist_norm dist_self zero_less_dist_iff)
then show ?thesis
by (metis C(1) \<open>y \<in> T\<close> d0 fg mult_le_cancel_iff1)
qed
also have "\ \ e * norm (g z - g y)"
using C by (auto simp add: field_simps)
finally show "norm (g z - g y - g' (z - y)) \ e * norm (g z - g y)"
by simp
qed (use d in auto)
qed
have *: "(0::real) < 1 / 2"
by auto
obtain d where "0 < d" and d:
"\z. norm (z - y) < d \ norm (g z - g y - g' (z - y)) \ 1/2 * norm (g z - g y)"
using lem1 * by blast
define B where "B = C * 2"
have "B > 0"
unfolding B_def using C by auto
have lem2: "norm (g z - g y) \ B * norm (z - y)" if z: "norm(z - y) < d" for z
proof -
have "norm (g z - g y) \ norm(g' (z - y)) + norm ((g z - g y) - g'(z - y))"
by (rule norm_triangle_sub)
also have "\ \ norm (g' (z - y)) + 1 / 2 * norm (g z - g y)"
by (rule add_left_mono) (use d z in auto)
also have "\ \ norm (z - y) * C + 1 / 2 * norm (g z - g y)"
by (rule add_right_mono) (use C in auto)
finally show "norm (g z - g y) \ B * norm (z - y)"
unfolding B_def
by (auto simp add: field_simps)
qed
show ?thesis
unfolding has_derivative_at_alt
proof (intro conjI assms allI impI)
fix e :: real
assume "e > 0"
then have *: "e / B > 0" by (metis \<open>B > 0\<close> divide_pos_pos)
obtain d' where "0 < d'" and d':
"\z. norm (z - y) < d' \ norm (g z - g y - g' (z - y)) \ e / B * norm (g z - g y)"
using lem1 * by blast
obtain k where k: "0 < k" "k < d" "k < d'"
using field_lbound_gt_zero[OF \<open>0 < d\<close> \<open>0 < d'\<close>] by blast
show "\d>0. \ya. norm (ya - y) < d \ norm (g ya - g y - g' (ya - y)) \ e * norm (ya - y)"
proof (intro exI allI impI conjI)
fix z
assume as: "norm (z - y) < k"
then have "norm (g z - g y - g' (z - y)) \ e / B * norm(g z - g y)"
using d' k by auto
also have "\ \ e * norm (z - y)"
unfolding times_divide_eq_left pos_divide_le_eq[OF \<open>B>0\<close>]
using lem2[of z] k as \<open>e > 0\<close>
by (auto simp add: field_simps)
finally show "norm (g z - g y - g' (z - y)) \ e * norm (z - y)"
by simp
qed (use k in auto)
qed
qed
text\<^marker>\<open>tag unimportant\<close>\<open>Inverse function theorem for complex derivatives\<close>
lemma has_field_derivative_inverse_basic:
shows "DERIV f (g y) :> f' \
f' \ 0 \
continuous (at y) g \<Longrightarrow>
open t \<Longrightarrow>
y \<in> t \<Longrightarrow>
(\<And>z. z \<in> t \<Longrightarrow> f (g z) = z)
\<Longrightarrow> DERIV g y :> inverse (f')"
unfolding has_field_derivative_def
apply (rule has_derivative_inverse_basic)
apply (auto simp: bounded_linear_mult_right)
done
text \<open>Simply rewrite that based on the domain point x.\<close>
lemma has_derivative_inverse_basic_x:
fixes f :: "'a::real_normed_vector \ 'b::real_normed_vector"
assumes "(f has_derivative f') (at x)"
and "bounded_linear g'"
and "g' \ f' = id"
and "continuous (at (f x)) g"
and "g (f x) = x"
and "open T"
and "f x \ T"
and "\y. y \ T \ f (g y) = y"
shows "(g has_derivative g') (at (f x))"
by (rule has_derivative_inverse_basic) (use assms in auto)
text \<open>This is the version in Dieudonne', assuming continuity of f and g.\<close>
lemma has_derivative_inverse_dieudonne:
fixes f :: "'a::real_normed_vector \ 'b::real_normed_vector"
assumes "open S"
and "open (f ` S)"
and "continuous_on S f"
and "continuous_on (f ` S) g"
and "\x. x \ S \ g (f x) = x"
and "x \ S"
and "(f has_derivative f') (at x)"
and "bounded_linear g'"
and "g' \ f' = id"
shows "(g has_derivative g') (at (f x))"
apply (rule has_derivative_inverse_basic_x[OF assms(7-9) _ _ assms(2)])
using assms(3-6)
unfolding continuous_on_eq_continuous_at[OF assms(1)] continuous_on_eq_continuous_at[OF assms(2)]
apply auto
done
text \<open>Here's the simplest way of not assuming much about g.\<close>
proposition has_derivative_inverse:
fixes f :: "'a::real_normed_vector \ 'b::real_normed_vector"
assumes "compact S"
and "x \ S"
and fx: "f x \ interior (f ` S)"
and "continuous_on S f"
and gf: "\y. y \ S \ g (f y) = y"
and "(f has_derivative f') (at x)"
and "bounded_linear g'"
and "g' \ f' = id"
shows "(g has_derivative g') (at (f x))"
proof -
have *: "\y. y \ interior (f ` S) \ f (g y) = y"
by (metis gf image_iff interior_subset subsetCE)
show ?thesis
apply (rule has_derivative_inverse_basic_x[OF assms(6-8), where T = "interior (f ` S)"])
apply (rule continuous_on_interior[OF _ fx])
apply (rule continuous_on_inv)
apply (simp_all add: assms *)
done
qed
text \<open>Invertible derivative continuous at a point implies local
injectivity. It's only for this we need continuity of the derivative,
except of course if we want the fact that the inverse derivative is
also continuous. So if we know for some other reason that the inverse
function exists, it's OK.\
proposition has_derivative_locally_injective:
fixes f :: "'n::euclidean_space \ 'm::euclidean_space"
assumes "a \ S"
and "open S"
and bling: "bounded_linear g'"
and "g' \ f' a = id"
and derf: "\x. x \ S \ (f has_derivative f' x) (at x)"
and "\e. e > 0 \ \d>0. \x. dist a x < d \ onorm (\v. f' x v - f' a v) < e"
obtains r where "r > 0" "ball a r \ S" "inj_on f (ball a r)"
proof -
interpret bounded_linear g'
using assms by auto
note f'g' = assms(4)[unfolded id_def o_def,THEN cong]
have "g' (f' a (\Basis)) = (\Basis)" "(\Basis) \ (0::'n)"
using f'g' by auto
then have *: "0 < onorm g'"
unfolding onorm_pos_lt[OF assms(3)]
by fastforce
define k where "k = 1 / onorm g' / 2"
have *: "k > 0"
unfolding k_def using * by auto
obtain d1 where d1:
"0 < d1"
"\x. dist a x < d1 \ onorm (\v. f' x v - f' a v) < k"
using assms(6) * by blast
from \<open>open S\<close> obtain d2 where "d2 > 0" "ball a d2 \<subseteq> S"
using \<open>a\<in>S\<close> ..
obtain d2 where d2: "0 < d2" "ball a d2 \ S"
using \<open>0 < d2\<close> \<open>ball a d2 \<subseteq> S\<close> by blast
obtain d where d: "0 < d" "d < d1" "d < d2"
using field_lbound_gt_zero[OF d1(1) d2(1)] by blast
show ?thesis
proof
show "0 < d" by (fact d)
show "ball a d \ S"
using \<open>d < d2\<close> \<open>ball a d2 \<subseteq> S\<close> by auto
show "inj_on f (ball a d)"
unfolding inj_on_def
proof (intro strip)
fix x y
assume as: "x \ ball a d" "y \ ball a d" "f x = f y"
define ph where [abs_def]: "ph w = w - g' (f w - f x)" for w
have ph':"ph = g' \<circ> (\<lambda>w. f' a w - (f w - f x))"
unfolding ph_def o_def by (simp add: diff f'g')
have "norm (ph x - ph y) \ (1 / 2) * norm (x - y)"
proof (rule differentiable_bound[OF convex_ball _ _ as(1-2)])
fix u
assume u: "u \ ball a d"
then have "u \ S"
using d d2 by auto
have *: "(\v. v - g' (f' u v)) = g' \ (\w. f' a w - f' u w)"
unfolding o_def and diff
using f'g' by auto
have blin: "bounded_linear (f' a)"
using \<open>a \<in> S\<close> derf by blast
show "(ph has_derivative (\v. v - g' (f' u v))) (at u within ball a d)"
unfolding ph' * comp_def
by (rule \<open>u \<in> S\<close> derivative_eq_intros has_derivative_at_withinI [OF derf] bounded_linear.has_derivative [OF blin] bounded_linear.has_derivative [OF bling] |simp)+
have **: "bounded_linear (\x. f' u x - f' a x)" "bounded_linear (\x. f' a x - f' u x)"
using \<open>u \<in> S\<close> blin bounded_linear_sub derf by auto
then have "onorm (\v. v - g' (f' u v)) \ onorm g' * onorm (\w. f' a w - f' u w)"
by (simp add: "*" bounded_linear_axioms onorm_compose)
also have "\ \ onorm g' * k"
apply (rule mult_left_mono)
using d1(2)[of u]
using onorm_neg[where f="\x. f' u x - f' a x"] d u onorm_pos_le[OF bling] apply (auto simp: algebra_simps)
done
also have "\ \ 1 / 2"
unfolding k_def by auto
finally show "onorm (\v. v - g' (f' u v)) \ 1 / 2" .
qed
moreover have "norm (ph y - ph x) = norm (y - x)"
by (simp add: as(3) ph_def)
ultimately show "x = y"
unfolding norm_minus_commute by auto
qed
qed
qed
subsection \<open>Uniformly convergent sequence of derivatives\<close>
lemma has_derivative_sequence_lipschitz_lemma:
fixes f :: "nat \ 'a::real_normed_vector \ 'b::real_normed_vector"
assumes "convex S"
and derf: "\n x. x \ S \ ((f n) has_derivative (f' n x)) (at x within S)"
and nle: "\n x h. \n\N; x \ S\ \ norm (f' n x h - g' x h) \ e * norm h"
and "0 \ e"
shows "\m\N. \n\N. \x\S. \y\S. norm ((f m x - f n x) - (f m y - f n y)) \ 2 * e * norm (x - y)"
proof clarify
fix m n x y
assume as: "N \ m" "N \ n" "x \ S" "y \ S"
show "norm ((f m x - f n x) - (f m y - f n y)) \ 2 * e * norm (x - y)"
proof (rule differentiable_bound[where f'="\x h. f' m x h - f' n x h", OF \convex S\ _ _ as(3-4)])
fix x
assume "x \ S"
show "((\a. f m a - f n a) has_derivative (\h. f' m x h - f' n x h)) (at x within S)"
by (rule derivative_intros derf \<open>x\<in>S\<close>)+
show "onorm (\h. f' m x h - f' n x h) \ 2 * e"
proof (rule onorm_bound)
fix h
have "norm (f' m x h - f' n x h) \ norm (f' m x h - g' x h) + norm (f' n x h - g' x h)"
using norm_triangle_ineq[of "f' m x h - g' x h" "- f' n x h + g' x h"]
by (auto simp add: algebra_simps norm_minus_commute)
also have "\ \ e * norm h + e * norm h"
using nle[OF \<open>N \<le> m\<close> \<open>x \<in> S\<close>, of h] nle[OF \<open>N \<le> n\<close> \<open>x \<in> S\<close>, of h]
by (auto simp add: field_simps)
finally show "norm (f' m x h - f' n x h) \ 2 * e * norm h"
by auto
qed (simp add: \<open>0 \<le> e\<close>)
qed
qed
lemma has_derivative_sequence_Lipschitz:
fixes f :: "nat \ 'a::real_normed_vector \ 'b::real_normed_vector"
assumes "convex S"
and "\n x. x \ S \ ((f n) has_derivative (f' n x)) (at x within S)"
and nle: "\e. e > 0 \ \\<^sub>F n in sequentially. \x\S. \h. norm (f' n x h - g' x h) \ e * norm h"
and "e > 0"
shows "\N. \m\N. \n\N. \x\S. \y\S.
norm ((f m x - f n x) - (f m y - f n y)) \<le> e * norm (x - y)"
proof -
have *: "2 * (e/2) = e"
using \<open>e > 0\<close> by auto
obtain N where "\n\N. \x\S. \h. norm (f' n x h - g' x h) \ (e/2) * norm h"
using nle \<open>e > 0\<close>
unfolding eventually_sequentially
by (metis less_divide_eq_numeral1(1) mult_zero_left)
then show "\N. \m\N. \n\N. \x\S. \y\S. norm (f m x - f n x - (f m y - f n y)) \ e * norm (x - y)"
apply (rule_tac x=N in exI)
apply (rule has_derivative_sequence_lipschitz_lemma[where e="e/2", unfolded *])
using assms \<open>e > 0\<close>
apply auto
done
qed
proposition has_derivative_sequence:
fixes f :: "nat \ 'a::real_normed_vector \ 'b::banach"
assumes "convex S"
and derf: "\n x. x \ S \ ((f n) has_derivative (f' n x)) (at x within S)"
and nle: "\e. e > 0 \ \\<^sub>F n in sequentially. \x\S. \h. norm (f' n x h - g' x h) \ e * norm h"
and "x0 \ S"
--> --------------------
--> maximum size reached
--> --------------------
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