Proving the Relationship Between Inner Products and Linear Transformations

In summary, the adjoint of a vector space is defined as the vector space that satisfies <v,Tw>=<T*v,w> for every v in V.
  • #1
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let V be a vector space with inner product, and T:V->V linear trans.
then for V on R, prove that for every v in V, <v,T(v)>=0 iff T*=-T.

now i got so far that: from <v,T(v)>=0 we have <v,(T+T*)(v)>=0 for every v, here I am stuck, i guess if it's for every v, if i were to write (T+T*)(v)=av for some scalar a, then i would get: a<v,v>=0 for every v, so a=0, and we get what we wanted, but I am not sure that T and T* are eigen functions i.e in the form I've given.
any pointers?
 
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  • #2
The adjoint is defined by the requirement:

<v,Tw>=<T*v,w>
 
  • #3
yes i know, and i got to this equation by getting <T*(v),v>=0 and it's symmetric bacuase it's on R, but still i don't see how your remark helps me here?
 
  • #4
Um... then use T*=-T, and then there's one more step. I'm really doing nothing but copying definitions for you.
 
  • #5
but T* doesn't necessarily equals -T, or am i missing something here?
T* is defined as a linear trans between V to V that satisifes <v,T(w)>=<T*(w),v> how from this definition you conclude that T*=-T?

and i need to prove that if <v,Tv>=0 for every v in V then T*=-T, if i were using the antecendent that i weren't proving were i?
 
  • #6
One very useful fact about quadratic forums Q, such as
Q(v) := <v, T(v)>,​
is that you can construct a bilinear form by considering
Q(v+w).​

Maybe this is helpful?
 
  • #7
doh, i shouldv'e know that it has something to do with this.
anyway, if Q(v)=<v,Tv>=0
then
<(T*+T)(v),(T*+T)(v)>=1/2(Q((T+T*)v)-Q((T+T*)(v))-Q((T*+T)(v)))=0
so (T*+T)(v)= for every v in V.
is this good enough?

thanks hurkyl.
 
  • #8
Sorry, I didn't notice the second f in iff. I guess you already did the direction I was thinking of. I'm not sure what you're doing in your last post though. You have:

<(T*+T)(v),(T*+T)(v)>=1/2(Q((T+T*)v)-Q((T+T*)(v))-Q((T*+T)(v)))=0

which, given your definition of Q, translates to:

<(T*+T)(v),(T*+T)(v)>=1/2(<(T+T*)v,T(T+T*)v>-<(T+T*)v,T(T+T*)v>-<(T+T*)v,T(T+T*)v>)

I don't think that's right. I'm pretty sure Hurkyl wants you to use a v and a w in order to get a relation between <v,Tw> and <Tv,w>
 
  • #9
but q(v) is defined as q(v)=f(v,v) for some symmetric bilinear form f.
so if i define: q(v):=<v,Tv>
so: q(v+w)=<v+w,Tv+Tw>=<v,Tv>+<w,Tw>+<v,Tw>+<w,Tv>=
=<v+w,T(w+v)>=0
so from this i can <(T+T*)v,(T+T*)v>=1/2(q(2(T+T*)(v))-2q((T+T*)(v))
q((T+T*)(v))=0 and so is the first term.
isn't this correct?
 

1. What is an inner product?

An inner product is a mathematical operation that takes in two vectors and produces a scalar value. It measures the similarity between two vectors by calculating the angle between them and their relative magnitudes.

2. How is an inner product different from a cross product?

An inner product is a type of dot product that results in a scalar value, while a cross product results in a vector value. Additionally, an inner product takes in two vectors and produces a scalar, whereas a cross product takes in two vectors and produces a vector that is perpendicular to both of the original vectors.

3. What are the properties of an inner product?

An inner product must satisfy the following properties: linearity in the first argument, symmetry, and positive definiteness. Linearity means that the inner product of a vector and a linear combination of other vectors is equal to the same linear combination of the inner products between the first vector and each of the other vectors. Symmetry means that the order of the vectors does not matter in the inner product. Positive definiteness means that the inner product of a vector with itself is always positive, except for the zero vector.

4. How is an inner product used in vector spaces?

An inner product is used in vector spaces to define the length or magnitude of a vector, as well as the angle between two vectors. It is also used in the process of finding orthogonal bases and solving systems of linear equations.

5. Can an inner product be defined for any type of vector?

No, an inner product can only be defined for certain types of vectors, specifically vectors in a vector space that satisfies the properties mentioned above. This includes Euclidean spaces and other types of spaces such as Hilbert spaces and Banach spaces.

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