Can a Matrix Be Expressed as a Sum of Diagonalizable and Nilpotent Matrices?

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Discussion Overview

The discussion revolves around the question of whether a matrix can be expressed as a sum of a diagonalizable matrix and a nilpotent matrix. It explores concepts from linear algebra, particularly focusing on normal forms of matrices and the conditions under which such decompositions can occur.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant inquires about the steps to express a matrix as a sum of a diagonalizable and a nilpotent matrix, requesting a layman's explanation.
  • Another participant asks about known normal forms for matrices, indicating a potential connection to the topic.
  • A response clarifies that "normal form" refers to specific representations of matrices, such as row echelon form or diagonal form, rather than vector normalization.
  • A later reply suggests that under the assumption of an algebraically closed field, every linear map satisfies some minimal polynomial, leading to a decomposition into a direct sum based on polynomial factors.
  • It is proposed that if a linear transformation T satisfies a polynomial of the form (X-c)^r, then T can be expressed as the sum of a diagonalizable matrix (cId) and a nilpotent matrix (T-cId).
  • Further questions arise regarding the definitions and processes involved, such as the Euclidean algorithm and the meaning of "T satisfies (X-c)^r," as well as how to achieve the diagonalizable matrix cId.

Areas of Agreement / Disagreement

Participants express varying levels of understanding and interpretation of the concepts discussed, with some seeking clarification on specific terms and methods. There is no consensus on the process or definitions, and multiple viewpoints regarding the topic are present.

Contextual Notes

Some limitations include the dependence on the assumption that the field is algebraically closed and the need for clarity on mathematical terms and processes like the Euclidean algorithm and primary decomposition theorem.

MathIdiot
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How do you write a matrix as a sum of a diagonalizable matrix and a nilpotent matrix?

It would be great if you could describe the steps in Layman's terms because I am not so hot in Linear Algebra.

Thanks
 
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What sort of normal forms do you know for matrices?
 
I'm not sure what you mean. The only ideas about "normal" I know is normalizing a vector. Normalizing a basis of vectors as well as normalizing a basis of orthogonal vectors to get an orthonormal basis. And orthogonal matrices. Is this at all what your implying?
 
No; I'm using "normal form" to describe the category of things like row echelon form or diagonal form -- methods for representing matrices in some sort of specialized format which is easy to manipulate.
 
Oh, ok (sorry).
They are square, they don't have any other specialized format.
 
it is not true in general,so first assume the field is algebraically closed. then assume you know that every linear map satisfies some minimal polynomial

then use the euclidean algorithm to decompose the space into a direct sum on each factor of which the polynomial is of form (X-c)^r.

then note that if T satisfies (X-c)^r, then it is the sum of T-cId and cId, where cID is diagonalizable, and T-cId satisfies X^r, hence is nilpotent.

done.
 
Ok, I hope you can clarify a few things from your last statement.
Those assumptions sound fine.
However what is the euclidean algorithm?
Also, what is meant by "T satisfies (X-c)^r"?
Lastly how do you get cID? What I mean really is, how does one achieve this diagonalizable matrix?
 
Euclidean algorithm, I believe, goes like this:

let f, g be polynomials in F[x] such that g does not equal 0. Then there exists uniquely determined polynomials q and r such that

f = qg + r

and r = 0 or deg r < deg gMathwonk, is this what is known as the primary decomposition theorem?
 
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