Proving V as a Direct Sum: Showing T Can Be Represented by an nxn Matrix

In summary: This is a summary of the content of the following conversation.Suppose that T : V -> V is a linear transformation of vector spaces over R whose minimal polynomial has no multiple roots. Show that V can be expressed as a direct sumof T-stable subspaces of dimensions at most 2. Show that, relative to a suitable basis, T can be represented by an n × n matrix with at most 2n non-zero entries, where n := dim(V).
  • #1
Treadstone 71
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"Suppose that T : V -> V is a linear transformation of vector spaces over
R whose minimal polynomial has no multiple roots. Show that V can be
expressed as a direct sum

V = V1 + V2 + · · · + Vt

of T-stable subspaces of dimensions at most 2. Show that, relative to a suitable basis, T can be represented by an n × n matrix with at most 2n non-zero entries, where n := dim(V)."

Our professor is a little behind in lectures, but our assignments are still rolling full speed ahead. I'm not sure where to start. Can someone give me a hint?
 
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  • #2
Hrm. My first thought is the fundamental theorem of algebra.
 
  • #3
If it were over C then of course you can diagonalize, but over R you can't. Remember roots will come in complex conjugate pairs because the minimal poly has real coefficients.

Put that together...
 
  • #4
You're saying even if there are no real roots, I can somehow use a 2x2 matrix to "represent" a complex root in a real vector space? Like
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  • #5
Not only am I saying that but so is the question.
 
  • #6
I can't get it right. What if the minimal poly has a single root only, where dim V>1?
 
  • #7
If it is a single root then it is necessarily real, since the characteristic poly is over R. All roots occur as complex conjugate pairs. In this case the matirx is diagonalizable, over R.
 
  • #8
How can you conclude from the fact that it has a single root that it's diagonalizable over R?
 
  • #9
Perhaps I was leaping to the conclusion that you meant single as in without multiplicity. If your 'minimal poly' of M has a single root, ie is m(x)=x-t, then M=tI. Since you have has a hypothesis that your minimal polynomial has no repeated roots we are in this situtation. Sorry if I didn't make it clear to you that I was using the hypotheses of the question. It is certainly not true that just because a matrix has one e-value it is diagonalizable, never mind over R or any other field. But we have the extra assumption here that we *have* to use.

The minimal poly is real with no repeated roots, ie it is of the form

m(x)=(x-a)(x-b)..(x-c)(x^2+dx+e)..(x^2+fx+g)

where all numbers are real, no repeated roots and all quadratics have non-real roots.
 
  • #10
So by "not multiple" the question really means "non-repeating"? I've been doing it assuming that it was either 1 or no real roots.
 
  • #11
Erm, just look up mutliple roots anywhere at all. I do not even know what you mean by 'one or no real roots'. Multiplicity of roots is a well defined concept if you ask me.
 

Related to Proving V as a Direct Sum: Showing T Can Be Represented by an nxn Matrix

1. What does it mean to prove V as a direct sum?

Proving V as a direct sum means showing that a vector space V can be decomposed into two or more subspaces that are mutually exclusive and together span the entire space V. This can be represented as V = U ⊕ W, where U and W are the subspaces.

2. How is T represented by an nxn matrix?

T can be represented by an nxn matrix by finding a basis for the vector space V and representing the linear transformation T as a matrix relative to that basis. This matrix will have n rows and n columns, where n is the dimension of the vector space V.

3. What is the significance of proving V as a direct sum?

Proving V as a direct sum can help in understanding the structure and properties of the vector space V. It can also simplify computations and make it easier to analyze the linear transformation T, as it can now be represented by a matrix.

4. Can any vector space be proven as a direct sum?

No, not all vector spaces can be proven as a direct sum. A vector space can only be proven as a direct sum if it can be decomposed into two or more mutually exclusive subspaces that span the entire space.

5. What is the process for proving V as a direct sum?

The process for proving V as a direct sum involves finding a basis for the vector space V, showing that the basis vectors for the subspaces are linearly independent, and then showing that the subspaces span the entire space. This can also be done by showing that the intersection of the subspaces is only the zero vector and that the direct sum of the subspaces is equal to the original vector space V.

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