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

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Homework Help Overview

The discussion revolves around a linear transformation T on a vector space V over the reals, specifically focusing on expressing V as a direct sum of T-stable subspaces with dimensions at most 2. The participants are exploring the implications of the minimal polynomial of T having no multiple roots and how this affects the representation of T as an n × n matrix.

Discussion Character

  • Conceptual clarification, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Participants are considering the implications of the fundamental theorem of algebra and the nature of roots in relation to the minimal polynomial. There is discussion about the representation of complex roots in real vector spaces using 2x2 matrices. Questions arise regarding the conditions under which a matrix is diagonalizable over the reals, particularly in the context of minimal polynomials with single roots.

Discussion Status

The conversation is active, with participants questioning assumptions about the nature of roots and their multiplicities. Some have offered insights into how to represent complex roots and the implications of the minimal polynomial's structure, while others are clarifying definitions and exploring the conditions for diagonalizability.

Contextual Notes

There is an ongoing discussion about the definitions of multiple roots and their implications for the problem at hand. Participants are navigating the constraints of the problem, particularly regarding the characteristics of the minimal polynomial and its roots.

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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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Hrm. My first thought is the fundamental theorem of algebra.
 
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...
 
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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Not only am I saying that but so is the question.
 
I can't get it right. What if the minimal poly has a single root only, where dim V>1?
 
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.
 
How can you conclude from the fact that it has a single root that it's diagonalizable over R?
 
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.
 

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