Adjoint operator and orthogonal projection

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SUMMARY

The discussion centers on proving the relationship $T^{*}(Pr_{C}(y)) = Pr_{T^{*}(C)}(T^{*}y)$, where $T \in B(H)$ and $TT^{*}=I$, with $H$ as a Hilbert space and $C$ as a closed convex non-empty set. Participants explore the implications of this relationship, particularly in constructing the operator $T$ to satisfy the equations $Pr_{x + C}(y) = Pr_{C}(x + y)$ and $Pr_{\lambda C}(\lambda y) = \lambda Pr_{C}(y)$. The discussion highlights the necessity of defining $T$ correctly, noting that $T(y) = \lambda y$ is valid for scalar multiplication, while $Ty = y - x$ is not linear unless $x = 0.

PREREQUISITES
  • Understanding of adjoint operators in functional analysis
  • Familiarity with orthogonal projections in Hilbert spaces
  • Knowledge of bounded linear operators, specifically in the context of $B(H)$
  • Concept of closed convex sets in mathematical analysis
NEXT STEPS
  • Study the properties of adjoint operators in Hilbert spaces
  • Research the concept of orthogonal projections and their applications
  • Explore the construction of bounded linear operators in $B(H)$
  • Investigate the implications of convex sets in optimization problems
USEFUL FOR

Mathematicians, particularly those specializing in functional analysis, linear algebra, and optimization, will benefit from this discussion. It is also relevant for students and researchers exploring the applications of adjoint operators and projections in Hilbert spaces.

mathzero
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Hello,

I want to show $ T^{*}(Pr_{C}(y)) = Pr_{T^{*}(C)}(T^{*}y)$

where $T \in B(H)$ and $TT^{*}=I$ , $H$ is Hilbert space and $C$ is a closed convex non empty set.

but i don't know how to start, or what tricks needed to solve this type of problems.

also i want know how to construct $T$ to satisfying

$ Pr_{x + C}(y) = Pr_{C}(x + y)$ and $ Pr_{\lambda C}(\lambda y) = \lambda Pr_{C}(y)$

Thanks!
 
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mathzero said:
Hello,

I want to show $ T^{*}(Pr_{C}(y)) = Pr_{T^{*}(C)}(T^{*}y)$

where $T \in B(H)$ and $TT^{*}=I$ , $H$ is Hilbert space and $C$ is a closed convex non empty set.
Since $TT^* = I$, then $\|T^*x\| = \|x\|$ for all $x\in H$. Indeed, given $x\in H$, $\|T^*x\|^2 = \langle T^*x, T^*x\rangle = \langle TT^*x, x\rangle = \langle x,x\rangle = \|x\|^2$. Show that
$$\inf_{c\in C} \|T^*c - T^*y\| = \inf_{c\in C} \|c - y\|$$
and deduce $T^*(\operatorname{Pr}_C(y))$ is a point of $T^*(C)$ closest to $T^*y$. Then the result follows.
mathzero said:
also i want know how to construct $T$ to satisfying

$ Pr_{x + C}(y) = Pr_{C}(x + y)$ and $ Pr_{\lambda C}(\lambda y) = \lambda Pr_{C}(y)$
How does $T$ relate to those equations?
 
Thank you!

Euge said:
How does $T$ relate to those equations?

i want apply this result $T^{*}(Pr_{C}(y)) = Pr_{T^{*}(C)}(T^{*}y)$, to

$Pr_{x + C}(y) = Pr_{C}(x + y)$ and $Pr_{\lambda C}(\lambda y) = \lambda Pr_{C}(y)$

by creating $T$ first and later deducing $T^{*}$ (i don't know if this is possible!),

i imagine maybe, just by letting $Ty = y - x$ then $T^{*}y= y + x$? this can be possible?
 
Last edited:
mathzero said:
Thank you!
i want apply this result $T^{*}(Pr_{C}(y)) = Pr_{T^{*}(C)}(T^{*}y)$, to

$Pr_{x + C}(y) = Pr_{C}(x + y)$ and $Pr_{\lambda C}(\lambda y) = \lambda Pr_{C}(y)$

by creating $T$ first and later deducing $T^{*}$ (i don't know if this is possible!),

i imagine maybe, just by letting $Ty = y - x$ then $T^{*}y= y + x$? this can be possible?

In the case $\operatorname{Pr}_C(\lambda C) = \lambda \operatorname{Pr}_C(y)$, you can take $T(y) = \lambda y$, for all $y\in H$, which defines an element of $B(H)$ with $\|T\| = \lvert \lambda \rvert$. For the other equation, you suggest letting $Ty = y - x$, but this does not define a linear operator unless $x = 0$.
 

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