Smoothness of finite-dimensional functional calculus
$begingroup$
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 $C^infty$.
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 $Aintext{Sym}(n)$, 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
$endgroup$
add a comment |
$begingroup$
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 $C^infty$.
fa.functional-analysis real-analysis sp.spectral-theory
$endgroup$
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
fa.functional-analysis real-analysis sp.spectral-theory
asked 2 days ago
MizarMizar
1,6231024
1,6231024
add a comment |
add a comment |
2 Answers
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$begingroup$
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 $C^1.$
$endgroup$
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
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
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2 Answers
2
active
oldest
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$begingroup$
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 $C^1.$
$endgroup$
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
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:
$$f_n^*(X) = frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1} dz$$
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 $C^1.$
$endgroup$
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
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:
$$f_n^*(X) = frac{1}{2pi i}int_C f_n(z)(z I_p - X)^{-1} dz$$
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 $C^1.$
$endgroup$
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 $C^1.$
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
add a comment |
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
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
$endgroup$
$begingroup$
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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