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 $t→∞$
$begingroup$
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 $C^infty$.
fa.functional-analysis real-analysis sp.spectral-theory
$endgroup$
add a comment |
$begingroup$
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 $C^infty$.
fa.functional-analysis real-analysis sp.spectral-theory
$endgroup$
add a comment |
$begingroup$
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 $C^infty$.
fa.functional-analysis real-analysis sp.spectral-theory
$endgroup$
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
fa.functional-analysis real-analysis sp.spectral-theory
asked yesterday
MizarMizar
1,6181024
1,6181024
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
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 $C^1.$
$endgroup$
1
$begingroup$
Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
$endgroup$
– Mizar
yesterday
$begingroup$
Higher derivative estimates follow from the formula $sum_j=0^kfracf(lambda_j)prod_ellneq j(lambda_j-lambda_ell)=frac1k!int_Delta_kf^(k)(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex $t_jge 0,sum t_j=1$ (assuming wlog the $lambda_j$'s are distinct).
$endgroup$
– Mizar
10 hours ago
$begingroup$
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 $LHS=sum_j=1^kint_0^1fracf'(t_0lambda_0+(1-t_0)lambda_j)prod_ellneq j,ell>0(lambda_j-lambda_ell)$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^(k-1)(z)=(1-t_0)^k-1f^(k)(t_0lambda_0+(1-t_0)z)$.
$endgroup$
– Mizar
9 hours ago
add a comment |
$begingroup$
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.
New contributor
$endgroup$
$begingroup$
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
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
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 $C^1.$
$endgroup$
1
$begingroup$
Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
$endgroup$
– Mizar
yesterday
$begingroup$
Higher derivative estimates follow from the formula $sum_j=0^kfracf(lambda_j)prod_ellneq j(lambda_j-lambda_ell)=frac1k!int_Delta_kf^(k)(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex $t_jge 0,sum t_j=1$ (assuming wlog the $lambda_j$'s are distinct).
$endgroup$
– Mizar
10 hours ago
$begingroup$
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 $LHS=sum_j=1^kint_0^1fracf'(t_0lambda_0+(1-t_0)lambda_j)prod_ellneq j,ell>0(lambda_j-lambda_ell)$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^(k-1)(z)=(1-t_0)^k-1f^(k)(t_0lambda_0+(1-t_0)z)$.
$endgroup$
– Mizar
9 hours ago
add a comment |
$begingroup$
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 $C^1.$
$endgroup$
1
$begingroup$
Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
$endgroup$
– Mizar
yesterday
$begingroup$
Higher derivative estimates follow from the formula $sum_j=0^kfracf(lambda_j)prod_ellneq j(lambda_j-lambda_ell)=frac1k!int_Delta_kf^(k)(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex $t_jge 0,sum t_j=1$ (assuming wlog the $lambda_j$'s are distinct).
$endgroup$
– Mizar
10 hours ago
$begingroup$
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 $LHS=sum_j=1^kint_0^1fracf'(t_0lambda_0+(1-t_0)lambda_j)prod_ellneq j,ell>0(lambda_j-lambda_ell)$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^(k-1)(z)=(1-t_0)^k-1f^(k)(t_0lambda_0+(1-t_0)z)$.
$endgroup$
– Mizar
9 hours ago
add a comment |
$begingroup$
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 $C^1.$
$endgroup$
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 $C^1.$
answered yesterday
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
yesterday
$begingroup$
Higher derivative estimates follow from the formula $sum_j=0^kfracf(lambda_j)prod_ellneq j(lambda_j-lambda_ell)=frac1k!int_Delta_kf^(k)(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex $t_jge 0,sum t_j=1$ (assuming wlog the $lambda_j$'s are distinct).
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– Mizar
10 hours ago
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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 $LHS=sum_j=1^kint_0^1fracf'(t_0lambda_0+(1-t_0)lambda_j)prod_ellneq j,ell>0(lambda_j-lambda_ell)$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^(k-1)(z)=(1-t_0)^k-1f^(k)(t_0lambda_0+(1-t_0)z)$.
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– Mizar
9 hours ago
add a comment |
1
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Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
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– Mizar
yesterday
$begingroup$
Higher derivative estimates follow from the formula $sum_j=0^kfracf(lambda_j)prod_ellneq j(lambda_j-lambda_ell)=frac1k!int_Delta_kf^(k)(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex $t_jge 0,sum t_j=1$ (assuming wlog the $lambda_j$'s are distinct).
$endgroup$
– Mizar
10 hours ago
$begingroup$
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 $LHS=sum_j=1^kint_0^1fracf'(t_0lambda_0+(1-t_0)lambda_j)prod_ellneq j,ell>0(lambda_j-lambda_ell)$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^(k-1)(z)=(1-t_0)^k-1f^(k)(t_0lambda_0+(1-t_0)z)$.
$endgroup$
– Mizar
9 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
yesterday
$begingroup$
Excellent! I see how to generalize it to higher derivatives. I am amazed by the speed of your answer :-)
$endgroup$
– Mizar
yesterday
$begingroup$
Higher derivative estimates follow from the formula $sum_j=0^kfracf(lambda_j)prod_ellneq j(lambda_j-lambda_ell)=frac1k!int_Delta_kf^(k)(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex $t_jge 0,sum t_j=1$ (assuming wlog the $lambda_j$'s are distinct).
$endgroup$
– Mizar
10 hours ago
$begingroup$
Higher derivative estimates follow from the formula $sum_j=0^kfracf(lambda_j)prod_ellneq j(lambda_j-lambda_ell)=frac1k!int_Delta_kf^(k)(sum_jt_jlambda_j),dt_0cdots dt_k$, $Delta_k$ being the standard simplex $t_jge 0,sum t_j=1$ (assuming wlog the $lambda_j$'s are distinct).
$endgroup$
– Mizar
10 hours ago
$begingroup$
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 $LHS=sum_j=1^kint_0^1fracf'(t_0lambda_0+(1-t_0)lambda_j)prod_ellneq j,ell>0(lambda_j-lambda_ell)$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^(k-1)(z)=(1-t_0)^k-1f^(k)(t_0lambda_0+(1-t_0)z)$.
$endgroup$
– Mizar
9 hours ago
$begingroup$
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 $LHS=sum_j=1^kint_0^1fracf'(t_0lambda_0+(1-t_0)lambda_j)prod_ellneq j,ell>0(lambda_j-lambda_ell)$. We are done applying induction with $g:=f'(t_0lambda_0+(1-t_0)z)$ in place of $f(z)$ and noticing $g^(k-1)(z)=(1-t_0)^k-1f^(k)(t_0lambda_0+(1-t_0)z)$.
$endgroup$
– Mizar
9 hours ago
add a comment |
$begingroup$
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.
New contributor
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$begingroup$
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
add a comment |
$begingroup$
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.
New contributor
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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.
New contributor
$endgroup$
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.
New contributor
New contributor
answered yesterday
B ChinB Chin
1
1
New contributor
New contributor
$begingroup$
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
add a comment |
$begingroup$
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
add a comment |
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