Is the Adjoint of a Linear Operator Equal to the Original Operator?

In summary, the conversation discusses how to prove that rank(T) = rank(T*) for a linear operator T on a finite-dimensional inner product space V. One method is to use the fact that the number of linearly independent rows of a matrix is equal to the number of linearly independent columns of its adjoint, and that rank(T) is equal to the rank of the matrix representation of T with respect to a basis. Another way is to show that the kernel of T is equal to the kernel of its adjoint, and that the adjoint of the adjoint is the linear operator itself.
  • #1
mathboy
182
0
Let T:V -> V be a linear operator on a finite-dimensional inner product space V.
Prove that rank(T) = rank(T*).

So far I've proven that rank (T*T) = rank(T) by showing that ker(T*T) = ker(T). But I can't think of how to go from there.
 
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  • #2
Oh, should I use the fact that the number of linearly independent rows of a matrix A is equal to the number of linearly independent columns of A*, and that rank(T) = rank of matrix represenation of T wrt to a basis? Or is there a better way?

rank(T)=rank([T])=rank([T]*)=rank([T*])=rank(T*)
 
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  • #3
well, dimV=dimT+dimKerT=dimT*+dimkerT*
but kerT=kerT*, one way to prove it is if
v not zero in ker T, then T(v)=0, so 0=<Tv,v>=<v,T*v>
but v isn't zero then T*(v)=0, you can do it also vice versa.
 
  • #4
But <v,T*v>=0 implies T*v=0 only if <v,T*v>=0 for ALL v in V, not just for v in kerT.
 
  • #5
imT* is the orthogonal complement of kerT. So dimV=rankT*+dimkerT=rankT+dimkerT.
 
  • #6
Wow! Morphism, do you look these proofs up somewhere, or do you figure it out completely from scratch? If the latter, then you must be a genius!
 
  • #7
It's just experience and not any form of genius - I already knew that fact, and it turned out to be helpful here.
 
  • #8
How is the adjoint of the adjoint of a linear operator, the linear operator itself? i.e. A**=A?
 

What is the adjoint of a linear operator?

The adjoint of a linear operator is another linear operator that represents the transpose of the original operator. It is denoted by A* and is defined as the linear operator that satisfies the property <Ax, y> = <x, A*y> for all vectors x and y.

How is the adjoint of a linear operator calculated?

The adjoint of a linear operator can be calculated by taking the transpose of the matrix representation of the original operator and then taking the conjugate of each element in the matrix.

What is the significance of the adjoint of a linear operator in mathematics?

The adjoint of a linear operator is important in many areas of mathematics, including functional analysis, differential equations, and quantum mechanics. It allows for the formulation of important mathematical concepts such as self-adjoint operators and the spectral theorem.

How is the adjoint of a linear operator related to the concept of inner product?

The adjoint of a linear operator is closely related to the inner product of two vectors. In fact, the defining property of the adjoint operator involves the inner product. The adjoint operator allows for the extension of the inner product to function spaces and infinite-dimensional vector spaces.

Can the adjoint of a linear operator exist for all linear operators?

No, the adjoint of a linear operator only exists for operators on an inner product space. Additionally, not all operators on an inner product space have an adjoint. For example, a non-invertible linear operator does not have an adjoint.

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