Smoothness of finite-dimensional functional calculus












11












$begingroup$


Assume that $f:mathbb Rtomathbb R$ is continuous.
Given a real symmetric matrix $Aintext{Sym}(n)$, we can define $f(A)$ by applying $f$ to its spectrum. More explicitly,
$$ f(A):=sum f(lambda)P_lambda,qquad A=sumlambda P_lambda. $$
Here both sums are finite, and the second one is the decomposition of $A$ as a linear combination of orthogonal projections ($P_lambda$ is the projection onto the eigenspace for the eigenvalue $lambda$, so that $P_lambda P_{lambda'}=0$). Such decomposition exists and is unique by the spectral theorem.



I guess it is well known that $f:text{Sym}(n)totext{Sym}(n)$ is continuous.




Assuming $fin C^infty(mathbb R)$, is the induced map $f:text{Sym}(n)totext{Sym}(n)$ also smooth?




I think I can show that it is (Fréchet) differentiable everywhere, but I am wondering whether it is always $C^1$ or even $C^infty$.










share|cite|improve this question









$endgroup$

















    11












    $begingroup$


    Assume that $f:mathbb Rtomathbb R$ is continuous.
    Given a real symmetric matrix $Aintext{Sym}(n)$, we can define $f(A)$ by applying $f$ to its spectrum. More explicitly,
    $$ f(A):=sum f(lambda)P_lambda,qquad A=sumlambda P_lambda. $$
    Here both sums are finite, and the second one is the decomposition of $A$ as a linear combination of orthogonal projections ($P_lambda$ is the projection onto the eigenspace for the eigenvalue $lambda$, so that $P_lambda P_{lambda'}=0$). Such decomposition exists and is unique by the spectral theorem.



    I guess it is well known that $f:text{Sym}(n)totext{Sym}(n)$ is continuous.




    Assuming $fin C^infty(mathbb R)$, is the induced map $f:text{Sym}(n)totext{Sym}(n)$ also smooth?




    I think I can show that it is (Fréchet) differentiable everywhere, but I am wondering whether it is always $C^1$ or even $C^infty$.










    share|cite|improve this question









    $endgroup$















      11












      11








      11


      5



      $begingroup$


      Assume that $f:mathbb Rtomathbb R$ is continuous.
      Given a real symmetric matrix $Aintext{Sym}(n)$, we can define $f(A)$ by applying $f$ to its spectrum. More explicitly,
      $$ f(A):=sum f(lambda)P_lambda,qquad A=sumlambda P_lambda. $$
      Here both sums are finite, and the second one is the decomposition of $A$ as a linear combination of orthogonal projections ($P_lambda$ is the projection onto the eigenspace for the eigenvalue $lambda$, so that $P_lambda P_{lambda'}=0$). Such decomposition exists and is unique by the spectral theorem.



      I guess it is well known that $f:text{Sym}(n)totext{Sym}(n)$ is continuous.




      Assuming $fin C^infty(mathbb R)$, is the induced map $f:text{Sym}(n)totext{Sym}(n)$ also smooth?




      I think I can show that it is (Fréchet) differentiable everywhere, but I am wondering whether it is always $C^1$ or even $C^infty$.










      share|cite|improve this question









      $endgroup$




      Assume that $f:mathbb Rtomathbb R$ is continuous.
      Given a real symmetric matrix $Aintext{Sym}(n)$, we can define $f(A)$ by applying $f$ to its spectrum. More explicitly,
      $$ f(A):=sum f(lambda)P_lambda,qquad A=sumlambda P_lambda. $$
      Here both sums are finite, and the second one is the decomposition of $A$ as a linear combination of orthogonal projections ($P_lambda$ is the projection onto the eigenspace for the eigenvalue $lambda$, so that $P_lambda P_{lambda'}=0$). Such decomposition exists and is unique by the spectral theorem.



      I guess it is well known that $f:text{Sym}(n)totext{Sym}(n)$ is continuous.




      Assuming $fin C^infty(mathbb R)$, is the induced map $f:text{Sym}(n)totext{Sym}(n)$ also smooth?




      I think I can show that it is (Fréchet) differentiable everywhere, but I am wondering whether it is always $C^1$ or even $C^infty$.







      fa.functional-analysis real-analysis sp.spectral-theory






      share|cite|improve this question













      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked 2 days ago









      MizarMizar

      1,6231024




      1,6231024






















          2 Answers
          2






          active

          oldest

          votes


















          9












          $begingroup$

          Yes. The can be derived from the resolvent formalism.



          I'll just do the $C^1$ case and leave higher derivatives as an exercise - ask if it's not clear how to generalize. I am basically using formula (2.7) of "On differentiability of symmetric matrix valued functions", Alexander Shapiro, http://www.optimization-online.org/DB_HTML/2002/07/499.html. (I think there's a typo in the middle case of the display preceeding (2.7): $f(mu_j)/(mu_j-mu_k)$ should be $(f(mu_j)-f(mu_k))/(mu_j-mu_k).$) Shapiro's paper references "(cf., [4])", where [4] is the 600-page textbook "Perturbation Theory for Linear Operators" by T. Kato, but I don't know if that is helpful for this specific question.



          I will call the induced map $f^*$ to distinguish it from $f.$ I'll also call the dimension $p$ instead of $n.$



          It suffices to show $f^*$ is $C^1$ for matrices with eigenvalues in a given bounded interval $J.$ Approximate $f$ by polynomials $f_n$ such that $sup_{xin J}|f(x)-f_n(x)|to 0$ and $sup_{xin J}|f'(x)-f_n'(x)|to 0.$ Since $f_n$ is analytic, $f^*_n$ can be evaluated using resolvents:



          $$f_n^*(X) = frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1} dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $Hinmathrm{Sym}(p),$



          begin{align*}
          f_n^*(X+H)
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X-H)^{-1} dz\
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1}+f_n(z)(z I_p - X)^{-1}H(z I_p - X)^{-1} +dots dz\
          &= frac{1}{2pi i}int_C f_n(z)sum_{lambda}(z-lambda)^{-1}P_lambda +f_n(z)sum_{lambda_1,lambda_2}(z-lambda_1)^{-1}(z-lambda_2)^{-1}P_{lambda_1}HP_{lambda_2}+dots dz\
          &= f_n^*(X)+sum_{lambda_1,lambda_2} P_{lambda_1} H P_{lambda_2}int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          end{align*}



          The second equality uses the Taylor expansion $$(A-H)^{-1}=A^{-1}+A^{-1}HA^{-1}+dots$$ with $A=z I_p-X.$
          The third equality uses $(zI_p - X)^{-1}=sum_lambda (z-lambda)^{-1} P_lambda.$ The fourth equality uses $int_C f_n(z)(z-lambda)^{-1}(z-mu)^{-1}dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          This gives a bound



          $$|Df^*_n(X)H| leq c_p|H|cdot sup_{xin J}|f'_n(x)-f_n'(x)|$$



          for some constant $c_p>0,$ where $|cdot|$ is any matrix norm. This shows that $f^*$ can be approximated arbitrarily well in the $C^1$ norm, which means it's $C^1.$






          share|cite|improve this answer









          $endgroup$









          • 1




            $begingroup$
            Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
            $endgroup$
            – Mizar
            2 days ago










          • $begingroup$
            Higher derivative estimates follow from the formula $sum_{j=0}^kfrac{f(lambda_j)}{prod_{ellneq j}(lambda_j-lambda_ell)}=frac{1}{k!|Delta_k|}int_{Delta_k}f^{(k)}(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex ${t_jge 0,sum t_j=1}$ (assuming wlog the $lambda_j$'s are distinct).
            $endgroup$
            – Mizar
            yesterday










          • $begingroup$
            The formula, in turn, is easy to prove by induction: we can subtract $f(lambda_0)$ from each numerator in the left-hand side (thanks to this: math.stackexchange.com/questions/104262/…) and obtain $LHS=sum_{j=1}^kint_0^1frac{f'(t_0lambda_0+(1-t_0)lambda_j)}{prod_{ellneq j,ell>0}(lambda_j-lambda_ell)}$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^{(k-1)}(z)=(1-t_0)^{k-1}f^{(k)}(t_0lambda_0+(1-t_0)z)$.
            $endgroup$
            – Mizar
            yesterday



















          0












          $begingroup$

          Yes. To show that f(A) is n-times differentiable at A=B, simply interpolate f by a polynomial P so that P and its derivatives up to order n agree with f on the spectrum of B. Clearly P(A) is n-times differentiable, and it isn't too much work to show that f and P have the same nth derivative.






          share|cite|improve this answer








          New contributor




          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.






          $endgroup$













          • $begingroup$
            Yeah, I thought about this strategy, but it's not so clear why this gives $C^n$ regularity rather than just a Taylor approximation of degree $n$ at each $A$. (If one manages to infer such an approximation exists with coefficients depending continuously on $A$, then one could invoke this result: mathoverflow.net/questions/88501/converse-of-taylors-theorem)
            $endgroup$
            – Mizar
            yesterday














          Your Answer





          StackExchange.ifUsing("editor", function () {
          return StackExchange.using("mathjaxEditing", function () {
          StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
          StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
          });
          });
          }, "mathjax-editing");

          StackExchange.ready(function() {
          var channelOptions = {
          tags: "".split(" "),
          id: "504"
          };
          initTagRenderer("".split(" "), "".split(" "), channelOptions);

          StackExchange.using("externalEditor", function() {
          // Have to fire editor after snippets, if snippets enabled
          if (StackExchange.settings.snippets.snippetsEnabled) {
          StackExchange.using("snippets", function() {
          createEditor();
          });
          }
          else {
          createEditor();
          }
          });

          function createEditor() {
          StackExchange.prepareEditor({
          heartbeatType: 'answer',
          autoActivateHeartbeat: false,
          convertImagesToLinks: true,
          noModals: true,
          showLowRepImageUploadWarning: true,
          reputationToPostImages: 10,
          bindNavPrevention: true,
          postfix: "",
          imageUploader: {
          brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
          contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
          allowUrls: true
          },
          noCode: true, onDemand: true,
          discardSelector: ".discard-answer"
          ,immediatelyShowMarkdownHelp:true
          });


          }
          });














          draft saved

          draft discarded


















          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmathoverflow.net%2fquestions%2f327330%2fsmoothness-of-finite-dimensional-functional-calculus%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown

























          2 Answers
          2






          active

          oldest

          votes








          2 Answers
          2






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          9












          $begingroup$

          Yes. The can be derived from the resolvent formalism.



          I'll just do the $C^1$ case and leave higher derivatives as an exercise - ask if it's not clear how to generalize. I am basically using formula (2.7) of "On differentiability of symmetric matrix valued functions", Alexander Shapiro, http://www.optimization-online.org/DB_HTML/2002/07/499.html. (I think there's a typo in the middle case of the display preceeding (2.7): $f(mu_j)/(mu_j-mu_k)$ should be $(f(mu_j)-f(mu_k))/(mu_j-mu_k).$) Shapiro's paper references "(cf., [4])", where [4] is the 600-page textbook "Perturbation Theory for Linear Operators" by T. Kato, but I don't know if that is helpful for this specific question.



          I will call the induced map $f^*$ to distinguish it from $f.$ I'll also call the dimension $p$ instead of $n.$



          It suffices to show $f^*$ is $C^1$ for matrices with eigenvalues in a given bounded interval $J.$ Approximate $f$ by polynomials $f_n$ such that $sup_{xin J}|f(x)-f_n(x)|to 0$ and $sup_{xin J}|f'(x)-f_n'(x)|to 0.$ Since $f_n$ is analytic, $f^*_n$ can be evaluated using resolvents:



          $$f_n^*(X) = frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1} dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $Hinmathrm{Sym}(p),$



          begin{align*}
          f_n^*(X+H)
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X-H)^{-1} dz\
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1}+f_n(z)(z I_p - X)^{-1}H(z I_p - X)^{-1} +dots dz\
          &= frac{1}{2pi i}int_C f_n(z)sum_{lambda}(z-lambda)^{-1}P_lambda +f_n(z)sum_{lambda_1,lambda_2}(z-lambda_1)^{-1}(z-lambda_2)^{-1}P_{lambda_1}HP_{lambda_2}+dots dz\
          &= f_n^*(X)+sum_{lambda_1,lambda_2} P_{lambda_1} H P_{lambda_2}int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          end{align*}



          The second equality uses the Taylor expansion $$(A-H)^{-1}=A^{-1}+A^{-1}HA^{-1}+dots$$ with $A=z I_p-X.$
          The third equality uses $(zI_p - X)^{-1}=sum_lambda (z-lambda)^{-1} P_lambda.$ The fourth equality uses $int_C f_n(z)(z-lambda)^{-1}(z-mu)^{-1}dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          This gives a bound



          $$|Df^*_n(X)H| leq c_p|H|cdot sup_{xin J}|f'_n(x)-f_n'(x)|$$



          for some constant $c_p>0,$ where $|cdot|$ is any matrix norm. This shows that $f^*$ can be approximated arbitrarily well in the $C^1$ norm, which means it's $C^1.$






          share|cite|improve this answer









          $endgroup$









          • 1




            $begingroup$
            Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
            $endgroup$
            – Mizar
            2 days ago










          • $begingroup$
            Higher derivative estimates follow from the formula $sum_{j=0}^kfrac{f(lambda_j)}{prod_{ellneq j}(lambda_j-lambda_ell)}=frac{1}{k!|Delta_k|}int_{Delta_k}f^{(k)}(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex ${t_jge 0,sum t_j=1}$ (assuming wlog the $lambda_j$'s are distinct).
            $endgroup$
            – Mizar
            yesterday










          • $begingroup$
            The formula, in turn, is easy to prove by induction: we can subtract $f(lambda_0)$ from each numerator in the left-hand side (thanks to this: math.stackexchange.com/questions/104262/…) and obtain $LHS=sum_{j=1}^kint_0^1frac{f'(t_0lambda_0+(1-t_0)lambda_j)}{prod_{ellneq j,ell>0}(lambda_j-lambda_ell)}$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^{(k-1)}(z)=(1-t_0)^{k-1}f^{(k)}(t_0lambda_0+(1-t_0)z)$.
            $endgroup$
            – Mizar
            yesterday
















          9












          $begingroup$

          Yes. The can be derived from the resolvent formalism.



          I'll just do the $C^1$ case and leave higher derivatives as an exercise - ask if it's not clear how to generalize. I am basically using formula (2.7) of "On differentiability of symmetric matrix valued functions", Alexander Shapiro, http://www.optimization-online.org/DB_HTML/2002/07/499.html. (I think there's a typo in the middle case of the display preceeding (2.7): $f(mu_j)/(mu_j-mu_k)$ should be $(f(mu_j)-f(mu_k))/(mu_j-mu_k).$) Shapiro's paper references "(cf., [4])", where [4] is the 600-page textbook "Perturbation Theory for Linear Operators" by T. Kato, but I don't know if that is helpful for this specific question.



          I will call the induced map $f^*$ to distinguish it from $f.$ I'll also call the dimension $p$ instead of $n.$



          It suffices to show $f^*$ is $C^1$ for matrices with eigenvalues in a given bounded interval $J.$ Approximate $f$ by polynomials $f_n$ such that $sup_{xin J}|f(x)-f_n(x)|to 0$ and $sup_{xin J}|f'(x)-f_n'(x)|to 0.$ Since $f_n$ is analytic, $f^*_n$ can be evaluated using resolvents:



          $$f_n^*(X) = frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1} dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $Hinmathrm{Sym}(p),$



          begin{align*}
          f_n^*(X+H)
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X-H)^{-1} dz\
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1}+f_n(z)(z I_p - X)^{-1}H(z I_p - X)^{-1} +dots dz\
          &= frac{1}{2pi i}int_C f_n(z)sum_{lambda}(z-lambda)^{-1}P_lambda +f_n(z)sum_{lambda_1,lambda_2}(z-lambda_1)^{-1}(z-lambda_2)^{-1}P_{lambda_1}HP_{lambda_2}+dots dz\
          &= f_n^*(X)+sum_{lambda_1,lambda_2} P_{lambda_1} H P_{lambda_2}int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          end{align*}



          The second equality uses the Taylor expansion $$(A-H)^{-1}=A^{-1}+A^{-1}HA^{-1}+dots$$ with $A=z I_p-X.$
          The third equality uses $(zI_p - X)^{-1}=sum_lambda (z-lambda)^{-1} P_lambda.$ The fourth equality uses $int_C f_n(z)(z-lambda)^{-1}(z-mu)^{-1}dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          This gives a bound



          $$|Df^*_n(X)H| leq c_p|H|cdot sup_{xin J}|f'_n(x)-f_n'(x)|$$



          for some constant $c_p>0,$ where $|cdot|$ is any matrix norm. This shows that $f^*$ can be approximated arbitrarily well in the $C^1$ norm, which means it's $C^1.$






          share|cite|improve this answer









          $endgroup$









          • 1




            $begingroup$
            Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
            $endgroup$
            – Mizar
            2 days ago










          • $begingroup$
            Higher derivative estimates follow from the formula $sum_{j=0}^kfrac{f(lambda_j)}{prod_{ellneq j}(lambda_j-lambda_ell)}=frac{1}{k!|Delta_k|}int_{Delta_k}f^{(k)}(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex ${t_jge 0,sum t_j=1}$ (assuming wlog the $lambda_j$'s are distinct).
            $endgroup$
            – Mizar
            yesterday










          • $begingroup$
            The formula, in turn, is easy to prove by induction: we can subtract $f(lambda_0)$ from each numerator in the left-hand side (thanks to this: math.stackexchange.com/questions/104262/…) and obtain $LHS=sum_{j=1}^kint_0^1frac{f'(t_0lambda_0+(1-t_0)lambda_j)}{prod_{ellneq j,ell>0}(lambda_j-lambda_ell)}$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^{(k-1)}(z)=(1-t_0)^{k-1}f^{(k)}(t_0lambda_0+(1-t_0)z)$.
            $endgroup$
            – Mizar
            yesterday














          9












          9








          9





          $begingroup$

          Yes. The can be derived from the resolvent formalism.



          I'll just do the $C^1$ case and leave higher derivatives as an exercise - ask if it's not clear how to generalize. I am basically using formula (2.7) of "On differentiability of symmetric matrix valued functions", Alexander Shapiro, http://www.optimization-online.org/DB_HTML/2002/07/499.html. (I think there's a typo in the middle case of the display preceeding (2.7): $f(mu_j)/(mu_j-mu_k)$ should be $(f(mu_j)-f(mu_k))/(mu_j-mu_k).$) Shapiro's paper references "(cf., [4])", where [4] is the 600-page textbook "Perturbation Theory for Linear Operators" by T. Kato, but I don't know if that is helpful for this specific question.



          I will call the induced map $f^*$ to distinguish it from $f.$ I'll also call the dimension $p$ instead of $n.$



          It suffices to show $f^*$ is $C^1$ for matrices with eigenvalues in a given bounded interval $J.$ Approximate $f$ by polynomials $f_n$ such that $sup_{xin J}|f(x)-f_n(x)|to 0$ and $sup_{xin J}|f'(x)-f_n'(x)|to 0.$ Since $f_n$ is analytic, $f^*_n$ can be evaluated using resolvents:



          $$f_n^*(X) = frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1} dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $Hinmathrm{Sym}(p),$



          begin{align*}
          f_n^*(X+H)
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X-H)^{-1} dz\
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1}+f_n(z)(z I_p - X)^{-1}H(z I_p - X)^{-1} +dots dz\
          &= frac{1}{2pi i}int_C f_n(z)sum_{lambda}(z-lambda)^{-1}P_lambda +f_n(z)sum_{lambda_1,lambda_2}(z-lambda_1)^{-1}(z-lambda_2)^{-1}P_{lambda_1}HP_{lambda_2}+dots dz\
          &= f_n^*(X)+sum_{lambda_1,lambda_2} P_{lambda_1} H P_{lambda_2}int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          end{align*}



          The second equality uses the Taylor expansion $$(A-H)^{-1}=A^{-1}+A^{-1}HA^{-1}+dots$$ with $A=z I_p-X.$
          The third equality uses $(zI_p - X)^{-1}=sum_lambda (z-lambda)^{-1} P_lambda.$ The fourth equality uses $int_C f_n(z)(z-lambda)^{-1}(z-mu)^{-1}dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          This gives a bound



          $$|Df^*_n(X)H| leq c_p|H|cdot sup_{xin J}|f'_n(x)-f_n'(x)|$$



          for some constant $c_p>0,$ where $|cdot|$ is any matrix norm. This shows that $f^*$ can be approximated arbitrarily well in the $C^1$ norm, which means it's $C^1.$






          share|cite|improve this answer









          $endgroup$



          Yes. The can be derived from the resolvent formalism.



          I'll just do the $C^1$ case and leave higher derivatives as an exercise - ask if it's not clear how to generalize. I am basically using formula (2.7) of "On differentiability of symmetric matrix valued functions", Alexander Shapiro, http://www.optimization-online.org/DB_HTML/2002/07/499.html. (I think there's a typo in the middle case of the display preceeding (2.7): $f(mu_j)/(mu_j-mu_k)$ should be $(f(mu_j)-f(mu_k))/(mu_j-mu_k).$) Shapiro's paper references "(cf., [4])", where [4] is the 600-page textbook "Perturbation Theory for Linear Operators" by T. Kato, but I don't know if that is helpful for this specific question.



          I will call the induced map $f^*$ to distinguish it from $f.$ I'll also call the dimension $p$ instead of $n.$



          It suffices to show $f^*$ is $C^1$ for matrices with eigenvalues in a given bounded interval $J.$ Approximate $f$ by polynomials $f_n$ such that $sup_{xin J}|f(x)-f_n(x)|to 0$ and $sup_{xin J}|f'(x)-f_n'(x)|to 0.$ Since $f_n$ is analytic, $f^*_n$ can be evaluated using resolvents:



          $$f_n^*(X) = frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1} dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $Hinmathrm{Sym}(p),$



          begin{align*}
          f_n^*(X+H)
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X-H)^{-1} dz\
          &= frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1}+f_n(z)(z I_p - X)^{-1}H(z I_p - X)^{-1} +dots dz\
          &= frac{1}{2pi i}int_C f_n(z)sum_{lambda}(z-lambda)^{-1}P_lambda +f_n(z)sum_{lambda_1,lambda_2}(z-lambda_1)^{-1}(z-lambda_2)^{-1}P_{lambda_1}HP_{lambda_2}+dots dz\
          &= f_n^*(X)+sum_{lambda_1,lambda_2} P_{lambda_1} H P_{lambda_2}int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          end{align*}



          The second equality uses the Taylor expansion $$(A-H)^{-1}=A^{-1}+A^{-1}HA^{-1}+dots$$ with $A=z I_p-X.$
          The third equality uses $(zI_p - X)^{-1}=sum_lambda (z-lambda)^{-1} P_lambda.$ The fourth equality uses $int_C f_n(z)(z-lambda)^{-1}(z-mu)^{-1}dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          This gives a bound



          $$|Df^*_n(X)H| leq c_p|H|cdot sup_{xin J}|f'_n(x)-f_n'(x)|$$



          for some constant $c_p>0,$ where $|cdot|$ is any matrix norm. This shows that $f^*$ can be approximated arbitrarily well in the $C^1$ norm, which means it's $C^1.$







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered 2 days ago









          DapDap

          94826




          94826








          • 1




            $begingroup$
            Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
            $endgroup$
            – Mizar
            2 days ago










          • $begingroup$
            Higher derivative estimates follow from the formula $sum_{j=0}^kfrac{f(lambda_j)}{prod_{ellneq j}(lambda_j-lambda_ell)}=frac{1}{k!|Delta_k|}int_{Delta_k}f^{(k)}(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex ${t_jge 0,sum t_j=1}$ (assuming wlog the $lambda_j$'s are distinct).
            $endgroup$
            – Mizar
            yesterday










          • $begingroup$
            The formula, in turn, is easy to prove by induction: we can subtract $f(lambda_0)$ from each numerator in the left-hand side (thanks to this: math.stackexchange.com/questions/104262/…) and obtain $LHS=sum_{j=1}^kint_0^1frac{f'(t_0lambda_0+(1-t_0)lambda_j)}{prod_{ellneq j,ell>0}(lambda_j-lambda_ell)}$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^{(k-1)}(z)=(1-t_0)^{k-1}f^{(k)}(t_0lambda_0+(1-t_0)z)$.
            $endgroup$
            – Mizar
            yesterday














          • 1




            $begingroup$
            Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
            $endgroup$
            – Mizar
            2 days ago










          • $begingroup$
            Higher derivative estimates follow from the formula $sum_{j=0}^kfrac{f(lambda_j)}{prod_{ellneq j}(lambda_j-lambda_ell)}=frac{1}{k!|Delta_k|}int_{Delta_k}f^{(k)}(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex ${t_jge 0,sum t_j=1}$ (assuming wlog the $lambda_j$'s are distinct).
            $endgroup$
            – Mizar
            yesterday










          • $begingroup$
            The formula, in turn, is easy to prove by induction: we can subtract $f(lambda_0)$ from each numerator in the left-hand side (thanks to this: math.stackexchange.com/questions/104262/…) and obtain $LHS=sum_{j=1}^kint_0^1frac{f'(t_0lambda_0+(1-t_0)lambda_j)}{prod_{ellneq j,ell>0}(lambda_j-lambda_ell)}$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^{(k-1)}(z)=(1-t_0)^{k-1}f^{(k)}(t_0lambda_0+(1-t_0)z)$.
            $endgroup$
            – Mizar
            yesterday








          1




          1




          $begingroup$
          Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
          $endgroup$
          – Mizar
          2 days ago




          $begingroup$
          Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
          $endgroup$
          – Mizar
          2 days ago












          $begingroup$
          Higher derivative estimates follow from the formula $sum_{j=0}^kfrac{f(lambda_j)}{prod_{ellneq j}(lambda_j-lambda_ell)}=frac{1}{k!|Delta_k|}int_{Delta_k}f^{(k)}(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex ${t_jge 0,sum t_j=1}$ (assuming wlog the $lambda_j$'s are distinct).
          $endgroup$
          – Mizar
          yesterday




          $begingroup$
          Higher derivative estimates follow from the formula $sum_{j=0}^kfrac{f(lambda_j)}{prod_{ellneq j}(lambda_j-lambda_ell)}=frac{1}{k!|Delta_k|}int_{Delta_k}f^{(k)}(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex ${t_jge 0,sum t_j=1}$ (assuming wlog the $lambda_j$'s are distinct).
          $endgroup$
          – Mizar
          yesterday












          $begingroup$
          The formula, in turn, is easy to prove by induction: we can subtract $f(lambda_0)$ from each numerator in the left-hand side (thanks to this: math.stackexchange.com/questions/104262/…) and obtain $LHS=sum_{j=1}^kint_0^1frac{f'(t_0lambda_0+(1-t_0)lambda_j)}{prod_{ellneq j,ell>0}(lambda_j-lambda_ell)}$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^{(k-1)}(z)=(1-t_0)^{k-1}f^{(k)}(t_0lambda_0+(1-t_0)z)$.
          $endgroup$
          – Mizar
          yesterday




          $begingroup$
          The formula, in turn, is easy to prove by induction: we can subtract $f(lambda_0)$ from each numerator in the left-hand side (thanks to this: math.stackexchange.com/questions/104262/…) and obtain $LHS=sum_{j=1}^kint_0^1frac{f'(t_0lambda_0+(1-t_0)lambda_j)}{prod_{ellneq j,ell>0}(lambda_j-lambda_ell)}$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^{(k-1)}(z)=(1-t_0)^{k-1}f^{(k)}(t_0lambda_0+(1-t_0)z)$.
          $endgroup$
          – Mizar
          yesterday











          0












          $begingroup$

          Yes. To show that f(A) is n-times differentiable at A=B, simply interpolate f by a polynomial P so that P and its derivatives up to order n agree with f on the spectrum of B. Clearly P(A) is n-times differentiable, and it isn't too much work to show that f and P have the same nth derivative.






          share|cite|improve this answer








          New contributor




          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.






          $endgroup$













          • $begingroup$
            Yeah, I thought about this strategy, but it's not so clear why this gives $C^n$ regularity rather than just a Taylor approximation of degree $n$ at each $A$. (If one manages to infer such an approximation exists with coefficients depending continuously on $A$, then one could invoke this result: mathoverflow.net/questions/88501/converse-of-taylors-theorem)
            $endgroup$
            – Mizar
            yesterday


















          0












          $begingroup$

          Yes. To show that f(A) is n-times differentiable at A=B, simply interpolate f by a polynomial P so that P and its derivatives up to order n agree with f on the spectrum of B. Clearly P(A) is n-times differentiable, and it isn't too much work to show that f and P have the same nth derivative.






          share|cite|improve this answer








          New contributor




          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.






          $endgroup$













          • $begingroup$
            Yeah, I thought about this strategy, but it's not so clear why this gives $C^n$ regularity rather than just a Taylor approximation of degree $n$ at each $A$. (If one manages to infer such an approximation exists with coefficients depending continuously on $A$, then one could invoke this result: mathoverflow.net/questions/88501/converse-of-taylors-theorem)
            $endgroup$
            – Mizar
            yesterday
















          0












          0








          0





          $begingroup$

          Yes. To show that f(A) is n-times differentiable at A=B, simply interpolate f by a polynomial P so that P and its derivatives up to order n agree with f on the spectrum of B. Clearly P(A) is n-times differentiable, and it isn't too much work to show that f and P have the same nth derivative.






          share|cite|improve this answer








          New contributor




          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.






          $endgroup$



          Yes. To show that f(A) is n-times differentiable at A=B, simply interpolate f by a polynomial P so that P and its derivatives up to order n agree with f on the spectrum of B. Clearly P(A) is n-times differentiable, and it isn't too much work to show that f and P have the same nth derivative.







          share|cite|improve this answer








          New contributor




          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.









          share|cite|improve this answer



          share|cite|improve this answer






          New contributor




          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.









          answered yesterday









          B ChinB Chin

          1




          1




          New contributor




          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.





          New contributor





          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.






          B Chin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.












          • $begingroup$
            Yeah, I thought about this strategy, but it's not so clear why this gives $C^n$ regularity rather than just a Taylor approximation of degree $n$ at each $A$. (If one manages to infer such an approximation exists with coefficients depending continuously on $A$, then one could invoke this result: mathoverflow.net/questions/88501/converse-of-taylors-theorem)
            $endgroup$
            – Mizar
            yesterday




















          • $begingroup$
            Yeah, I thought about this strategy, but it's not so clear why this gives $C^n$ regularity rather than just a Taylor approximation of degree $n$ at each $A$. (If one manages to infer such an approximation exists with coefficients depending continuously on $A$, then one could invoke this result: mathoverflow.net/questions/88501/converse-of-taylors-theorem)
            $endgroup$
            – Mizar
            yesterday


















          $begingroup$
          Yeah, I thought about this strategy, but it's not so clear why this gives $C^n$ regularity rather than just a Taylor approximation of degree $n$ at each $A$. (If one manages to infer such an approximation exists with coefficients depending continuously on $A$, then one could invoke this result: mathoverflow.net/questions/88501/converse-of-taylors-theorem)
          $endgroup$
          – Mizar
          yesterday






          $begingroup$
          Yeah, I thought about this strategy, but it's not so clear why this gives $C^n$ regularity rather than just a Taylor approximation of degree $n$ at each $A$. (If one manages to infer such an approximation exists with coefficients depending continuously on $A$, then one could invoke this result: mathoverflow.net/questions/88501/converse-of-taylors-theorem)
          $endgroup$
          – Mizar
          yesterday




















          draft saved

          draft discarded




















































          Thanks for contributing an answer to MathOverflow!


          • Please be sure to answer the question. Provide details and share your research!

          But avoid



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          Use MathJax to format equations. MathJax reference.


          To learn more, see our tips on writing great answers.




          draft saved


          draft discarded














          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmathoverflow.net%2fquestions%2f327330%2fsmoothness-of-finite-dimensional-functional-calculus%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown





















































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown

































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown







          Popular posts from this blog

          What other Star Trek series did the main TNG cast show up in?

          Berlina muro

          Berlina aerponto