(* Title: HOL/Hahn_Banach/Hahn_Banach.thy Author: Gertrud Bauer, TU Munich *) section \The Hahn-Banach Theorem\ theory Hahn_Banach imports Hahn_Banach_Lemmas begin text \ We present the proof of two different versions of the Hahn-Banach Theorem, closely following @{cite \\S36\ "Heuser:1986"}. \ subsection \The Hahn-Banach Theorem for vector spaces\ paragraph \Hahn-Banach Theorem.\ text \ Let \F\ be a subspace of a real vector space \E\, let \p\ be a semi-norm on \E\, and \f\ be a linear form defined on \F\ such that \f\ is bounded by \p\, i.e. \\x \ F. f x \ p x\. Then \f\ can be extended to a linear form \h\ on \E\ such that \h\ is norm-preserving, i.e. \h\ is also bounded by \p\. \ paragraph \Proof Sketch.\ text \ \<^enum> Define \M\ as the set of norm-preserving extensions of \f\ to subspaces of \E\. The linear forms in \M\ are ordered by domain extension. \<^enum> We show that every non-empty chain in \M\ has an upper bound in \M\. \<^enum> With Zorn's Lemma we conclude that there is a maximal function \g\ in \M\. \<^enum> The domain \H\ of \g\ is the whole space \E\, as shown by classical contradiction: \<^item> Assuming \g\ is not defined on whole \E\, it can still be extended in a norm-preserving way to a super-space \H'\ of \H\. \<^item> Thus \g\ can not be maximal. Contradiction! \ theorem Hahn_Banach: assumes E: "vectorspace E" and "subspace F E" and "seminorm E p" and "linearform F f" assumes fp: "\x \ F. f x \ p x" shows "\h. linearform E h \ (\x \ F. h x = f x) \ (\x \ E. h x \ p x)" \ \Let \E\ be a vector space, \F\ a subspace of \E\, \p\ a seminorm on \E\,\ \ \and \f\ a linear form on \F\ such that \f\ is bounded by \p\,\ \ \then \f\ can be extended to a linear form \h\ on \E\ in a norm-preserving way. \<^smallskip>\ proof - interpret vectorspace E by fact interpret subspace F E by fact interpret seminorm E p by fact interpret linearform F f by fact define M where "M = norm_pres_extensions E p F f" then have M: "M = \" by (simp only:) from E have F: "vectorspace F" .. note FE = \F \ E\ { fix c assume cM: "c \ chains M" and ex: "\x. x \ c" have "\c \ M" \ \Show that every non-empty chain \c\ of \M\ has an upper bound in \M\:\ \ \\\c\ is greater than any element of the chain \c\, so it suffices to show \\c \ M\.\ unfolding M_def proof (rule norm_pres_extensionI) let ?H = "domain (\c)" let ?h = "funct (\c)" have a: "graph ?H ?h = \c" proof (rule graph_domain_funct) fix x y z assume "(x, y) \ \c" and "(x, z) \ \c" with M_def cM show "z = y" by (rule sup_definite) qed moreover from M cM a have "linearform ?H ?h" by (rule sup_lf) moreover from a M cM ex FE E have "?H \ E" by (rule sup_subE) moreover from a M cM ex FE have "F \ ?H" by (rule sup_supF) moreover from a M cM ex have "graph F f \ graph ?H ?h" by (rule sup_ext) moreover from a M cM have "\x \ ?H. ?h x \ p x" by (rule sup_norm_pres) ultimately show "\H h. \c = graph H h \ linearform H h \ H \ E \ F \ H \ graph F f \ graph H h \ (\x \ H. h x \ p x)" by blast qed } then have "\g \ M. \x \ M. g \ x \ x = g" \ \With Zorn's Lemma we can conclude that there is a maximal element in \M\. \<^smallskip>\ proof (rule Zorn's_Lemma) \ \We show that \M\ is non-empty:\ show "graph F f \ M" unfolding M_def proof (rule norm_pres_extensionI2) show "linearform F f" by fact show "F \ E" by fact from F show "F \ F" by (rule vectorspace.subspace_refl) show "graph F f \ graph F f" .. show "\x\F. f x \ p x" by fact qed qed then obtain g where gM: "g \ M" and gx: "\x \ M. g \ x \ g = x" by blast from gM obtain H h where g_rep: "g = graph H h" and linearform: "linearform H h" and HE: "H \ E" and FH: "F \ H" and graphs: "graph F f \ graph H h" and hp: "\x \ H. h x \ p x" unfolding M_def .. \ \\g\ is a norm-preserving extension of \f\, in other words:\ \ \\g\ is the graph of some linear form \h\ defined on a subspace \H\ of \E\,\ \ \and \h\ is an extension of \f\ that is again bounded by \p\. \<^smallskip>\ from HE E have H: "vectorspace H" by (rule subspace.vectorspace) have HE_eq: "H = E" \ \We show that \h\ is defined on whole \E\ by classical contradiction. \<^smallskip>\ proof (rule classical) assume neq: "H \ E" \ \Assume \h\ is not defined on whole \E\. Then show that \h\ can be extended\ \ \in a norm-preserving way to a function \h'\ with the graph \g'\. \<^smallskip>\ have "\g' \ M. g \ g' \ g \ g'" proof - from HE have "H \ E" .. with neq obtain x' where x'E: "x' \ E" and "x' \ H" by blast obtain x': "x' \ 0" proof show "x' \ 0" proof assume "x' = 0" with H have "x' \ H" by (simp only: vectorspace.zero) with \x' \ H\ show False by contradiction qed qed define H' where "H' = H + lin x'" \ \Define \H'\ as the direct sum of \H\ and the linear closure of \x'\. \<^smallskip>\ have HH': "H \ H'" proof (unfold H'_def) from x'E have "vectorspace (lin x')" .. with H show "H \ H + lin x'" .. qed obtain xi where xi: "\y \ H. - p (y + x') - h y \ xi \ xi \ p (y + x') - h y" \ \Pick a real number \\\ that fulfills certain inequality; this will\ \ \be used to establish that \h'\ is a norm-preserving extension of \h\. \label{ex-xi-use}\<^smallskip>\ proof - from H have "\xi. \y \ H. - p (y + x') - h y \ xi \ xi \ p (y + x') - h y" proof (rule ex_xi) fix u v assume u: "u \ H" and v: "v \ H" with HE have uE: "u \ E" and vE: "v \ E" by auto from H u v linearform have "h v - h u = h (v - u)" by (simp add: linearform.diff) also from hp and H u v have "\ \ p (v - u)" by (simp only: vectorspace.diff_closed) also from x'E uE vE have "v - u = x' + - x' + v + - u" by (simp add: diff_eq1) also from x'E uE vE have "\ = v + x' + - (u + x')" by (simp add: add_ac) also from x'E uE vE have "\ = (v + x') - (u + x')" by (simp add: diff_eq1) also from x'E uE vE E have "p \ \ p (v + x') + p (u + x')" by (simp add: diff_subadditive) finally have "h v - h u \ p (v + x') + p (u + x')" . then show "- p (u + x') - h u \ p (v + x') - h v" by simp qed then show thesis by (blast intro: that) qed define h' where "h' x = (let (y, a) = SOME (y, a). x = y + a \ x' \ y \ H in h y + a * xi)" for x \ \Define the extension \h'\ of \h\ to \H'\ using \\\. \<^smallskip>\ have "g \ graph H' h' \ g \ graph H' h'" \ \\h'\ is an extension of \h\ \dots \<^smallskip>\ proof show "g \ graph H' h'" proof - have "graph H h \ graph H' h'" proof (rule graph_extI) fix t assume t: "t \ H" from E HE t have "(SOME (y, a). t = y + a \ x' \ y \ H) = (t, 0)" using \x' \ H\ \x' \ E\ \x' \ 0\ by (rule decomp_H'_H) with h'_def show "h t = h' t" by (simp add: Let_def) next from HH' show "H \ H'" .. qed with g_rep show ?thesis by (simp only:) qed show "g \ graph H' h'" proof - have "graph H h \ graph H' h'" proof assume eq: "graph H h = graph H' h'" have "x' \ H'" unfolding H'_def proof from H show "0 \ H" by (rule vectorspace.zero) from x'E show "x' \ lin x'" by (rule x_lin_x) from x'E show "x' = 0 + x'" by simp qed then have "(x', h' x') \ graph H' h'" .. with eq have "(x', h' x') \ graph H h" by (simp only:) then have "x' \ H" .. with \x' \ H\ show False by contradiction qed with g_rep show ?thesis by simp qed qed moreover have "graph H' h' \ M" \ \and \h'\ is norm-preserving. \<^smallskip>\ proof (unfold M_def) show "graph H' h' \ norm_pres_extensions E p F f" proof (rule norm_pres_extensionI2) show "linearform H' h'" using h'_def H'_def HE linearform \x' \ H\ \x' \ E\ \x' \ 0\ E by (rule h'_lf) show "H' \ E" unfolding H'_def proof show "H \ E" by fact show "vectorspace E" by fact from x'E show "lin x' \ E" .. qed from H \F \ H\ HH' show FH': "F \ H'" by (rule vectorspace.subspace_trans) show "graph F f \ graph H' h'" proof (rule graph_extI) fix x assume x: "x \ F" with graphs have "f x = h x" .. also have "\ = h x + 0 * xi" by simp also have "\ = (let (y, a) = (x, 0) in h y + a * xi)" by (simp add: Let_def) also have "(x, 0) = (SOME (y, a). x = y + a \ x' \ y \ H)" using E HE proof (rule decomp_H'_H [symmetric]) from FH x show "x \ H" .. from x' show "x' \ 0" . show "x' \ H" by fact show "x' \ E" by fact qed also have "(let (y, a) = (SOME (y, a). x = y + a \ x' \ y \ H) in h y + a * xi) = h' x" by (simp only: h'_def) finally show "f x = h' x" . next from FH' show "F \ H'" .. qed show "\x \ H'. h' x \ p x" using h'_def H'_def \x' \ H\ \x' \ E\ \x' \ 0\ E HE \seminorm E p\ linearform and hp xi by (rule h'_norm_pres) qed qed ultimately show ?thesis .. qed then have "\ (\x \ M. g \ x \ g = x)" by simp \ \So the graph \g\ of \h\ cannot be maximal. Contradiction! \<^smallskip>\ with gx show "H = E" by contradiction qed from HE_eq and linearform have "linearform E h" by (simp only:) moreover have "\x \ F. h x = f x" proof fix x assume "x \ F" with graphs have "f x = h x" .. then show "h x = f x" .. qed moreover from HE_eq and hp have "\x \ E. h x \ p x" by (simp only:) ultimately show ?thesis by blast qed subsection \Alternative formulation\ text \ The following alternative formulation of the Hahn-Banach Theorem\label{abs-Hahn-Banach} uses the fact that for a real linear form \f\ and a seminorm \p\ the following inequality are equivalent:\footnote{This was shown in lemma @{thm [source] abs_ineq_iff} (see page \pageref{abs-ineq-iff}).} \begin{center} \begin{tabular}{lll} \\x \ H. \h x\ \ p x\ & and & \\x \ H. h x \ p x\ \\ \end{tabular} \end{center} \ theorem abs_Hahn_Banach: assumes E: "vectorspace E" and FE: "subspace F E" and lf: "linearform F f" and sn: "seminorm E p" assumes fp: "\x \ F. \f x\ \ p x" shows "\g. linearform E g \ (\x \ F. g x = f x) \ (\x \ E. \g x\ \ p x)" proof - interpret vectorspace E by fact interpret subspace F E by fact interpret linearform F f by fact interpret seminorm E p by fact have "\g. linearform E g \ (\x \ F. g x = f x) \ (\x \ E. g x \ p x)" using E FE sn lf proof (rule Hahn_Banach) show "\x \ F. f x \ p x" using FE E sn lf and fp by (rule abs_ineq_iff [THEN iffD1]) qed then obtain g where lg: "linearform E g" and *: "\x \ F. g x = f x" and **: "\x \ E. g x \ p x" by blast have "\x \ E. \g x\ \ p x" using _ E sn lg ** proof (rule abs_ineq_iff [THEN iffD2]) show "E \ E" .. qed with lg * show ?thesis by blast qed subsection \The Hahn-Banach Theorem for normed spaces\ text \ Every continuous linear form \f\ on a subspace \F\ of a norm space \E\, can be extended to a continuous linear form \g\ on \E\ such that \\f\ = \g\\. \ theorem norm_Hahn_Banach: fixes V and norm ("\_\") fixes B defines "\V f. B V f \ {0} \ {\f x\ / \x\ | x. x \ 0 \ x \ V}" fixes fn_norm ("\_\\_" [0, 1000] 999) defines "\V f. \f\\V \ \(B V f)" assumes E_norm: "normed_vectorspace E norm" and FE: "subspace F E" and linearform: "linearform F f" and "continuous F f norm" shows "\g. linearform E g \ continuous E g norm \ (\x \ F. g x = f x) \ \g\\E = \f\\F" proof - interpret normed_vectorspace E norm by fact interpret normed_vectorspace_with_fn_norm E norm B fn_norm by (auto simp: B_def fn_norm_def) intro_locales interpret subspace F E by fact interpret linearform F f by fact interpret continuous F f norm by fact have E: "vectorspace E" by intro_locales have F: "vectorspace F" by rule intro_locales have F_norm: "normed_vectorspace F norm" using FE E_norm by (rule subspace_normed_vs) have ge_zero: "0 \ \f\\F" by (rule normed_vectorspace_with_fn_norm.fn_norm_ge_zero [OF normed_vectorspace_with_fn_norm.intro, OF F_norm \continuous F f norm\ , folded B_def fn_norm_def]) txt \We define a function \p\ on \E\ as follows: \p x = \f\ \ \x\\\ define p where "p x = \f\\F * \x\" for x txt \\p\ is a seminorm on \E\:\ have q: "seminorm E p" proof fix x y a assume x: "x \ E" and y: "y \ E" txt \\p\ is positive definite:\ have "0 \ \f\\F" by (rule ge_zero) moreover from x have "0 \ \x\" .. ultimately show "0 \ p x" by (simp add: p_def zero_le_mult_iff) txt \\p\ is absolutely homogeneous:\ show "p (a \ x) = \a\ * p x" proof - have "p (a \ x) = \f\\F * \a \ x\" by (simp only: p_def) also from x have "\a \ x\ = \a\ * \x\" by (rule abs_homogenous) also have "\f\\F * (\a\ * \x\) = \a\ * (\f\\F * \x\)" by simp also have "\ = \a\ * p x" by (simp only: p_def) finally show ?thesis . qed txt \Furthermore, \p\ is subadditive:\ show "p (x + y) \ p x + p y" proof - have "p (x + y) = \f\\F * \x + y\" by (simp only: p_def) also have a: "0 \ \f\\F" by (rule ge_zero) from x y have "\x + y\ \ \x\ + \y\" .. with a have " \f\\F * \x + y\ \ \f\\F * (\x\ + \y\)" by (simp add: mult_left_mono) also have "\ = \f\\F * \x\ + \f\\F * \y\" by (simp only: distrib_left) also have "\ = p x + p y" by (simp only: p_def) finally show ?thesis . qed qed txt \\f\ is bounded by \p\.\ have "\x \ F. \f x\ \ p x" proof fix x assume "x \ F" with \continuous F f norm\ and linearform show "\f x\ \ p x" unfolding p_def by (rule normed_vectorspace_with_fn_norm.fn_norm_le_cong [OF normed_vectorspace_with_fn_norm.intro, OF F_norm, folded B_def fn_norm_def]) qed txt \Using the fact that \p\ is a seminorm and \f\ is bounded by \p\ we can apply the Hahn-Banach Theorem for real vector spaces. So \f\ can be extended in a norm-preserving way to some function \g\ on the whole vector space \E\.\ with E FE linearform q obtain g where linearformE: "linearform E g" and a: "\x \ F. g x = f x" and b: "\x \ E. \g x\ \ p x" by (rule abs_Hahn_Banach [elim_format]) iprover txt \We furthermore have to show that \g\ is also continuous:\ have g_cont: "continuous E g norm" using linearformE proof fix x assume "x \ E" with b show "\g x\ \ \f\\F * \x\" by (simp only: p_def) qed txt \To complete the proof, we show that \\g\ = \f\\.\ have "\g\\E = \f\\F" proof (rule order_antisym) txt \ First we show \\g\ \ \f\\. The function norm \\g\\ is defined as the smallest \c \ \\ such that \begin{center} \begin{tabular}{l} \\x \ E. \g x\ \ c \ \x\\ \end{tabular} \end{center} \<^noindent> Furthermore holds \begin{center} \begin{tabular}{l} \\x \ E. \g x\ \ \f\ \ \x\\ \end{tabular} \end{center} \ from g_cont _ ge_zero show "\g\\E \ \f\\F" proof fix x assume "x \ E" with b show "\g x\ \ \f\\F * \x\" by (simp only: p_def) qed txt \The other direction is achieved by a similar argument.\ show "\f\\F \ \g\\E" proof (rule normed_vectorspace_with_fn_norm.fn_norm_least [OF normed_vectorspace_with_fn_norm.intro, OF F_norm, folded B_def fn_norm_def]) fix x assume x: "x \ F" show "\f x\ \ \g\\E * \x\" proof - from a x have "g x = f x" .. then have "\f x\ = \g x\" by (simp only:) also from g_cont have "\ \ \g\\E * \x\" proof (rule fn_norm_le_cong [OF _ linearformE, folded B_def fn_norm_def]) from FE x show "x \ E" .. qed finally show ?thesis . qed next show "0 \ \g\\E" using g_cont by (rule fn_norm_ge_zero [of g, folded B_def fn_norm_def]) show "continuous F f norm" by fact qed qed with linearformE a g_cont show ?thesis by blast qed end