Is the Projection Operator Self-Adjoint Only with Orthogonal Subspaces?

In summary, the conversation was about proving that a projection, $f$, of a vector space, $V$, onto one of its subspaces, $V_1$, along another subspace, $V_2$, is self-adjoint if and only if $V_1$ and $V_2$ are orthogonal. The given solution was checked and it was found that the "$\Rightarrow$" proof was correct, but the "$\Leftarrow$" proof needed to show that the inner product is preserved for any two vectors in $V_1\oplus V_2$.
  • #1
smile1
19
0
Hello everyone

I hope someone can check the solution for me.

Here is the problem:
Let $V=V_1\oplus V_2$, $f$ is the projection of $V$ onto $V_1$ along $V_2$( i.e. if $v=v_1+v_2, v_i\in V_i$ then $f(v)=v_1$). Prove that $f$ is self-adjoint iff $<V_1,V_2>=0$

my solution is this:
proof:"$\Rightarrow$"let $v_1\in V_1, v_2\in V_2$,
then $<f(v_1),v_2>=<v_1,f*(v_2)>=<v_1,f(v_2)>$, since if $f$ is self-adjoint,
then $f(v_2)=0, f(v_1)=v_1$, it follows that $<v_1,v_2>=<v_1,0>=0$,
hence $<v_1,v_2>=0$

"$\Leftarrow$" let $v_1\in V_1, v_2\in V_2$,
$<f(v_1),v_2>=<v_1,v_2>=0$, since $<v_1,v_2>=0$
$<v_1,f(v_2)>=<v_1,0>=0$
hence $<f(v_1),v_2>=<v_1,f(v_2)>$, $f$ is self adjoint.

It seems like something is wrong with my proof, but I really don't know. Hope someone can check it.

Thanks
 
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  • #2
smile said:
Hello everyone

I hope someone can check the solution for me.

Here is the problem:
Let $V=V_1\oplus V_2$, $f$ is the projection of $V$ onto $V_1$ along $V_2$( i.e. if $v=v_1+v_2, v_i\in V_i$ then $f(v)=v_1$). Prove that $f$ is self-adjoint iff $<V_1,V_2>=0$

my solution is this:
proof:"$\Rightarrow$"let $v_1\in V_1, v_2\in V_2$,
then $<f(v_1),v_2>=<v_1,f*(v_2)>=<v_1,f(v_2)>$, since if $f$ is self-adjoint,
then $f(v_2)=0, f(v_1)=v_1$, it follows that $<v_1,v_2>=<v_1,0>=0$,
hence $<v_1,v_2>=0$

"$\Leftarrow$" let $v_1\in V_1, v_2\in V_2$,
$<f(v_1),v_2>=<v_1,v_2>=0$, since $<v_1,v_2>=0$
$<v_1,f(v_2)>=<v_1,0>=0$
hence $<f(v_1),v_2>=<v_1,f(v_2)>$, $f$ is self adjoint.

It seems like something is wrong with my proof, but I really don't know. Hope someone can check it.
The "$\Rightarrow$" proof is fine. To show the converse implication, you need to take two vectors, $v_1\oplus v_2$ and $w_1\oplus w_2$ say, in $V_1\oplus V_2$, and check that $\langle f(v_1\oplus v_2),w_1\oplus w_2\rangle = \langle v_1\oplus v_2,f(w_1\oplus w_2)\rangle.$
 

Related to Is the Projection Operator Self-Adjoint Only with Orthogonal Subspaces?

What is a self-adjoint transformation?

A self-adjoint transformation is a linear transformation that is equal to its own adjoint. In other words, the matrix representing the transformation is equal to its own transpose.

How is a self-adjoint transformation different from a normal transformation?

A normal transformation is defined as a linear transformation that commutes with its adjoint. This means that the matrix representing the transformation and its adjoint are able to be multiplied in either order and still result in the same matrix. A self-adjoint transformation is a special case of a normal transformation where the matrix representing the transformation is equal to its own adjoint.

What is the importance of self-adjoint transformations in mathematics and science?

Self-adjoint transformations have many important applications in mathematics and science. They are used in quantum mechanics, where they represent observables such as energy and momentum. In linear algebra, self-adjoint transformations have special properties that make them easier to study and work with. They also have important applications in signal processing and image processing.

How are self-adjoint transformations related to eigenvalues and eigenvectors?

Self-adjoint transformations have real eigenvalues and orthogonal eigenvectors. This means that they can be diagonalized by a unitary matrix, making them easier to study and work with. In addition, the eigenvalues of a self-adjoint transformation correspond to the possible values of the observable it represents in quantum mechanics.

What are some examples of self-adjoint transformations?

Some examples of self-adjoint transformations include the identity transformation, rotations in two or three dimensions, and reflections across a line or plane. In quantum mechanics, the position and momentum operators are also self-adjoint transformations.

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