Linear Algebra : Proving that Every map is an identity operator

In summary: However, A also belongs to the whole space V. This means that A is a subspace of both U and V. So, A must be a subspace of the intersection of U and V which is U itself. Therefore, A=U.Sorry for the confusion. I hope this clarifies it.
  • #1
vish_maths
61
1
Suppose T belongs to L(V,V) where L(A,W) denotes the set of linear mappings from Vector spaces A to W, is such that every subspace of V with dimension dim V - 1 is invariant under T. Prove that T is a scalar multiple of the identity operator.

My attempt : Let U be one of the sub spaces of V which has dimension = dim V -1.
Let a basis to U be defined as (V1, ...,Vj-1,Vj+1,...Vn) where j ranges from 1 to n

Now, this basis can be extended to form a basis of V as (V1,...,Vn)
=> v = a1V1+...+aj-1Vj-1+aj+1Vj+1...+anVn+ajVj
=>Tv =a1T(V1) + ... + an T(Vn) + ajT(Vj)
===================
A

now since T belongs to L(V,V), => T(Vi) belongs to V
or A belongs to V -------------(1)

However, by the problem statement:

subspace of dimension dim V - 1 is invariant under T
=>A belongs to U
=>T(Vi) (i≠j) belongs to span ( Basis of U )
Since, j ranges from 1 to n
=> T(Vi) = λiVi where λ is a scalar.

Now, having proved that every basis vector is an eigen vector, I am stuck at trying to prove that T is a scalar multiple of the identity operator for any vector V
 
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  • #2
I have moved this to homework.

Here are some remarks. Some remarks are very minor, and some are more vital:

vish_maths said:
Suppose T belongs to L(V,V) where L(A,W) denotes the set of linear mappings from Vector spaces A to W, is such that every subspace of V with dimension dim V - 1 is invariant under T. Prove that T is a scalar multiple of the identity operator.

My attempt : Let U be one of the sub spaces of V which has dimension = dim V -1.
Let a basis to U be defined as (V1, ...,Vj-1,Vj+1,...Vn) where j ranges from 1 to n

First, using [itex]V_i[/itex] as elements of the basis is quite confusing. We don't want to confuse this with the space V!
Furthermore, you seem to leave out the vector Vj. This indicates to me that j is a fixed number. Saying that j ranges from 1 to n makes no sense.
For example: let j=2. Then your basis U is defined as (V1,V3,V4,...,Vn). Then you say that 2 ranges from 1 to n. This clearly makes little sense.
Finally, I don't see why you just don't take a basis of U to be defined as (V1,...,V_(n-1)).

These remarks are very minor of course, but I'm telling you anyway.

Now, this basis can be extended to form a basis of V as (V1,...,Vn)
=> v = a1V1+...+aj-1Vj-1+aj+1Vj+1...+anVn+ajVj
=>Tv =a1T(V1) + ... + an T(Vn) + ajT(Vj)

What is v?? Why do we care about Tv?

now since T belongs to L(V,V), => T(Vi) belongs to V
or A belongs to V -------------(1)

What is A? I can't really follow the rest of your proof until you say what A is. In the very beginning you say something about L(A,W). This seems to indicate that A is a space? How can a space belong to V?

Isn't it obvious that T(vi) belongs to V as T is a linear map with codomain V? Is this what you meant?
 
  • #3
Hi
I did not intend to portray j as a fixed number . but you are right regarding taking basis of U to be defined as (V_1...,V_(n-1)).
I actually meant that if V has the basis as V1,...Vn . then there can be C(N,1) subspaces which have dimension = dim V - 1.

Sorry about not being able to use the subscripts. For some reason, my browser does not support them.

v is a vector in the span of (V1,...Vn). I thought Tv can be used to conclude some results because it is given that T maps from V to V

I did actually mark A . I meant A to be the span of the basis vectors of a particular subspace U which is different from that given in the question. I should have marked it as something different. Let's take it as B.

Thanks
 
  • #4
vish_maths said:
Hi
I did not intend to portray j as a fixed number . but you are right regarding taking basis of U to be defined as (V_1...,V_(n-1)).
I actually meant that if V has the basis as V1,...Vn . then there can be C(N,1) subspaces which have dimension = dim V - 1.

C(N,1)??

Sorry about not being able to use the subscripts. For some reason, my browser does not support them.

v is a vector in the span of (V1,...Vn). I thought Tv can be used to conclude some results because it is given that T maps from V to V

I did actually mark A . I meant A to be the span of the basis vectors of a particular subspace U which is different from that given in the question. I should have marked it as something different. Let's take it as B.

Wait, so A is the span of the basis vectors of U?? Then isn't A=U??
And what do you mean with "A belongs to U" or "A belongs to V" then?? You mean subset?
 
  • #5
micromass said:
C(N,1)??
Wait, so A is the span of the basis vectors of U?? Then isn't A=U??
And what do you mean with "A belongs to U" or "A belongs to V" then?? You mean subset?

So, there can be many subspaces with dimension = dim V - 1 . they equal =NC1 . dim V = N
*where NCr = N!/(r!)(N-r)! .*

A = T ( a1 V_1 +aj V_j-1 +aj+1 V_j+1...+an V_n)

Since U is invariant under T, A has to belong to the subspace U.
 
Last edited:

Related to Linear Algebra : Proving that Every map is an identity operator

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with linear equations and their representations in vector spaces. It involves the study of linear transformations, matrices, and systems of linear equations.

2. What is an identity operator?

An identity operator is a linear transformation that leaves every vector unchanged. In other words, it maps every vector to itself.

3. How can we prove that every map is an identity operator?

To prove that every map is an identity operator, we can use the definition of an identity operator and show that the given map satisfies the condition of leaving every vector unchanged. This can be done by showing that the map satisfies the properties of linearity and that it maps each basis vector to itself.

4. Why is it important to prove that every map is an identity operator?

Proving that every map is an identity operator is important because it helps us understand the fundamental properties of linear transformations. It also allows us to generalize our understanding of linear algebra and apply it to various fields such as physics, engineering, and computer science.

5. Can every linear transformation be represented by an identity operator?

No, not every linear transformation can be represented by an identity operator. Only linear transformations that leave every vector unchanged can be represented by an identity operator. Other linear transformations may have different properties and cannot be represented in this form.

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