Smoothness of finite-dimensional functional calculus“Converse” of Taylor's theoremHow “generalized eigenvalues” combine into producing the spectral measure?Can be this operator extended to an unbounded self-adjoint operator ? Resonance of Schrödinger operatorFinding the spectrum of the composition of a projection with a multiplication operatorSchrodinger's equation via Spectral TheoremIs there an asymptotic bound for this oscillatory integral?If $H$ is the closure of the set of solenoidal smooth vecor fields in $L^2$ and $P_H$ denote the orthogonal projection onto $H$, then $P_HH_0^1⊆H_0^1$Gaps in the spectrum of Laplace-Beltrami operatorsPerturbation theory compact operatorIf $A$ is a dissipative self-adjoint operator with spectral decomposition $(H_λ)$, then $e^tAx$ tends to the projection of $x$ onto $H_0$ as $t→∞$

Smoothness of finite-dimensional functional calculus


“Converse” of Taylor's theoremHow “generalized eigenvalues” combine into producing the spectral measure?Can be this operator extended to an unbounded self-adjoint operator ? Resonance of Schrödinger operatorFinding the spectrum of the composition of a projection with a multiplication operatorSchrodinger's equation via Spectral TheoremIs there an asymptotic bound for this oscillatory integral?If $H$ is the closure of the set of solenoidal smooth vecor fields in $L^2$ and $P_H$ denote the orthogonal projection onto $H$, then $P_HH_0^1⊆H_0^1$Gaps in the spectrum of Laplace-Beltrami operatorsPerturbation theory compact operatorIf $A$ is a dissipative self-adjoint operator with spectral decomposition $(H_λ)$, then $e^tAx$ tends to the projection of $x$ onto $H_0$ as $t→∞$













7












$begingroup$


Assume that $f:mathbb Rtomathbb R$ is continuous.
Given a real symmetric matrix $AintextSym(n)$, 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 $f:textSym(n)totextSym(n)$ is continuous.




Assuming $fin C^infty(mathbb R)$, is the induced map $f:textSym(n)totextSym(n)$ 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









$endgroup$
















    7












    $begingroup$


    Assume that $f:mathbb Rtomathbb R$ is continuous.
    Given a real symmetric matrix $AintextSym(n)$, 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 $f:textSym(n)totextSym(n)$ is continuous.




    Assuming $fin C^infty(mathbb R)$, is the induced map $f:textSym(n)totextSym(n)$ 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









    $endgroup$














      7












      7








      7


      2



      $begingroup$


      Assume that $f:mathbb Rtomathbb R$ is continuous.
      Given a real symmetric matrix $AintextSym(n)$, 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 $f:textSym(n)totextSym(n)$ is continuous.




      Assuming $fin C^infty(mathbb R)$, is the induced map $f:textSym(n)totextSym(n)$ 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 $AintextSym(n)$, 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 $f:textSym(n)totextSym(n)$ is continuous.




      Assuming $fin C^infty(mathbb R)$, is the induced map $f:textSym(n)totextSym(n)$ 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 6 hours ago









      MizarMizar

      1,5981023




      1,5981023




















          2 Answers
          2






          active

          oldest

          votes


















          6












          $begingroup$

          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:



          $$f_n^*(X) = frac12pi iint_C f_n(z)(z I_p - X)^-1 dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $HinmathrmSym(p),$



          beginalign*
          f_n^*(X+H)
          &= frac12pi iint_C f_n(z)(z I_p - X-H)^-1 dz\
          &= frac12pi iint_C f_n(z)(z I_p - X)^-1+f_n(z)(z I_p - X)^-1H(z I_p - X)^-1 +dots dz\
          &= frac12pi iint_C f_n(z)sum_lambda(z-lambda)^-1P_lambda +f_n(z)sum_lambda_1,lambda_2(z-lambda_1)^-1(z-lambda_2)^-1P_lambda_1HP_lambda_2+dots dz\
          &= f_n^*(X)+sum_lambda_1,lambda_2 P_lambda_1 H P_lambda_2int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          endalign*



          The second equality uses the Taylor expansion $$(A-H)^-1=A^-1+A^-1HA^-1+dots$$ 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 $int_C f_n(z)(z-lambda)^-1(z-mu)^-1dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          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
            5 hours ago


















          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
            43 mins ago












          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









          6












          $begingroup$

          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:



          $$f_n^*(X) = frac12pi iint_C f_n(z)(z I_p - X)^-1 dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $HinmathrmSym(p),$



          beginalign*
          f_n^*(X+H)
          &= frac12pi iint_C f_n(z)(z I_p - X-H)^-1 dz\
          &= frac12pi iint_C f_n(z)(z I_p - X)^-1+f_n(z)(z I_p - X)^-1H(z I_p - X)^-1 +dots dz\
          &= frac12pi iint_C f_n(z)sum_lambda(z-lambda)^-1P_lambda +f_n(z)sum_lambda_1,lambda_2(z-lambda_1)^-1(z-lambda_2)^-1P_lambda_1HP_lambda_2+dots dz\
          &= f_n^*(X)+sum_lambda_1,lambda_2 P_lambda_1 H P_lambda_2int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          endalign*



          The second equality uses the Taylor expansion $$(A-H)^-1=A^-1+A^-1HA^-1+dots$$ 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 $int_C f_n(z)(z-lambda)^-1(z-mu)^-1dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          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
            5 hours ago















          6












          $begingroup$

          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:



          $$f_n^*(X) = frac12pi iint_C f_n(z)(z I_p - X)^-1 dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $HinmathrmSym(p),$



          beginalign*
          f_n^*(X+H)
          &= frac12pi iint_C f_n(z)(z I_p - X-H)^-1 dz\
          &= frac12pi iint_C f_n(z)(z I_p - X)^-1+f_n(z)(z I_p - X)^-1H(z I_p - X)^-1 +dots dz\
          &= frac12pi iint_C f_n(z)sum_lambda(z-lambda)^-1P_lambda +f_n(z)sum_lambda_1,lambda_2(z-lambda_1)^-1(z-lambda_2)^-1P_lambda_1HP_lambda_2+dots dz\
          &= f_n^*(X)+sum_lambda_1,lambda_2 P_lambda_1 H P_lambda_2int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          endalign*



          The second equality uses the Taylor expansion $$(A-H)^-1=A^-1+A^-1HA^-1+dots$$ 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 $int_C f_n(z)(z-lambda)^-1(z-mu)^-1dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          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
            5 hours ago













          6












          6








          6





          $begingroup$

          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:



          $$f_n^*(X) = frac12pi iint_C f_n(z)(z I_p - X)^-1 dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $HinmathrmSym(p),$



          beginalign*
          f_n^*(X+H)
          &= frac12pi iint_C f_n(z)(z I_p - X-H)^-1 dz\
          &= frac12pi iint_C f_n(z)(z I_p - X)^-1+f_n(z)(z I_p - X)^-1H(z I_p - X)^-1 +dots dz\
          &= frac12pi iint_C f_n(z)sum_lambda(z-lambda)^-1P_lambda +f_n(z)sum_lambda_1,lambda_2(z-lambda_1)^-1(z-lambda_2)^-1P_lambda_1HP_lambda_2+dots dz\
          &= f_n^*(X)+sum_lambda_1,lambda_2 P_lambda_1 H P_lambda_2int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          endalign*



          The second equality uses the Taylor expansion $$(A-H)^-1=A^-1+A^-1HA^-1+dots$$ 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 $int_C f_n(z)(z-lambda)^-1(z-mu)^-1dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          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:



          $$f_n^*(X) = frac12pi iint_C f_n(z)(z I_p - X)^-1 dz$$
          where $C$ is an anticlockwise circle in the complex plane with $J$ in its interior. For $HinmathrmSym(p),$



          beginalign*
          f_n^*(X+H)
          &= frac12pi iint_C f_n(z)(z I_p - X-H)^-1 dz\
          &= frac12pi iint_C f_n(z)(z I_p - X)^-1+f_n(z)(z I_p - X)^-1H(z I_p - X)^-1 +dots dz\
          &= frac12pi iint_C f_n(z)sum_lambda(z-lambda)^-1P_lambda +f_n(z)sum_lambda_1,lambda_2(z-lambda_1)^-1(z-lambda_2)^-1P_lambda_1HP_lambda_2+dots dz\
          &= f_n^*(X)+sum_lambda_1,lambda_2 P_lambda_1 H P_lambda_2int_0^1 f'_n(tlambda_1+(1-t)lambda_2)+dots dt
          endalign*



          The second equality uses the Taylor expansion $$(A-H)^-1=A^-1+A^-1HA^-1+dots$$ 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 $int_C f_n(z)(z-lambda)^-1(z-mu)^-1dz =int_0^1 f'_n(tlambda+(1-t)mu)dt.$



          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 6 hours ago









          DapDap

          91826




          91826







          • 1




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












          • 1




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







          1




          1




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




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











          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
            43 mins ago
















          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
            43 mins ago














          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 3 hours ago









          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
            43 mins ago

















          • $begingroup$
            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
            43 mins ago
















          $begingroup$
          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
          43 mins ago





          $begingroup$
          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
          43 mins ago


















          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

          Ружовы пелікан Змест Знешні выгляд | Пашырэнне | Асаблівасці біялогіі | Літаратура | НавігацыяДагледжаная версіяправерана1 зменаДагледжаная версіяправерана1 змена/ 22697590 Сістэматыкана ВіківідахВыявына Вікісховішчы174693363011049382

          ValueError: Error when checking input: expected conv2d_13_input to have shape (3, 150, 150) but got array with shape (150, 150, 3)2019 Community Moderator ElectionError when checking : expected dense_1_input to have shape (None, 5) but got array with shape (200, 1)Error 'Expected 2D array, got 1D array instead:'ValueError: Error when checking input: expected lstm_41_input to have 3 dimensions, but got array with shape (40000,100)ValueError: Error when checking target: expected dense_1 to have shape (7,) but got array with shape (1,)ValueError: Error when checking target: expected dense_2 to have shape (1,) but got array with shape (0,)Keras exception: ValueError: Error when checking input: expected conv2d_1_input to have shape (150, 150, 3) but got array with shape (256, 256, 3)Steps taking too long to completewhen checking input: expected dense_1_input to have shape (13328,) but got array with shape (317,)ValueError: Error when checking target: expected dense_3 to have shape (None, 1) but got array with shape (7715, 40000)Keras exception: Error when checking input: expected dense_input to have shape (2,) but got array with shape (1,)

          Illegal assignment from SObject to ContactFetching String, Id from Map - Illegal Assignment Id to Field / ObjectError: Compile Error: Illegal assignment from String to BooleanError: List has no rows for assignment to SObjectError on Test Class - System.QueryException: List has no rows for assignment to SObjectRemote action problemDML requires SObject or SObject list type error“Illegal assignment from List to List”Test Class Fail: Batch Class: System.QueryException: List has no rows for assignment to SObjectMapping to a user'List has no rows for assignment to SObject' Mystery