Definition of the Determinant of a Matrix

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Discussion Overview

The discussion revolves around the definition of the determinant of a matrix, exploring its properties, derivations, and various interpretations. Participants examine the determinant from multiple perspectives, including its multilinearity, alternating properties, and connections to eigenvalues, while questioning the adequacy of existing definitions.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Conceptual clarification

Main Points Raised

  • Some participants propose deriving the definition of the determinant from its basic properties, such as the determinant of a product being the product of the determinants and the determinant of a transpose being equal to the determinant of the original matrix.
  • One participant suggests that the determinant is the only multilinear alternating function in the vector space, up to a constant, and proposes proving this by induction.
  • Another participant clarifies that for an n-dimensional vector space, the space of alternating, multilinear functions is one-dimensional, which is relevant to the definition of the determinant.
  • There is a suggestion that the determinant can be thought of as a polynomial in the matrix entries, raising questions about how this relates to the properties of the polynomial.
  • One participant introduces the idea of defining the determinant as a function that is constant under conjugation of matrices, relating it to the product of diagonal entries for diagonal matrices.
  • Several participants express uncertainty about whether the determinant is uniquely determined by its multilinearity and other properties, with one participant suggesting a desire for fewer conditions in its definition.
  • Another viewpoint presents the determinant as the product of the eigenvalues of the corresponding linear transformation, describing this as a more intuitive geometric interpretation.
  • A later reply challenges the usefulness of the eigenvalue definition, particularly in cases where matrices do not have eigenvalues.

Areas of Agreement / Disagreement

Participants express a range of views on the definition and properties of the determinant, with no consensus reached on a singular definition or approach. Multiple competing interpretations and questions remain unresolved.

Contextual Notes

Some participants note the limitations of existing definitions, particularly regarding their applicability to lower-dimensional matrices or their reliance on complex properties like alternating multilinearity.

Who May Find This Useful

This discussion may be of interest to those studying linear algebra, particularly in understanding the conceptual foundations and various interpretations of the determinant in mathematical contexts.

zeta12ti
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How could one derive a definition of the determinant from some of its basic properties such as det of product = product of dets or the determinant of a transpose is the determinant of the untransposed matrix?

Upon instigating research on determiniants, all I've found are definitions that either only cover lower dimensional matrices or define the determinant to be some strange expression with little motivation.
 
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I think the determinant is the only mutilinear alternating function in the vector space - up to a constant. If you require the map to have a value of 1 on the identity matrix then you get the determinant.

Try proving this - say by induction.
 
lavinia said:
I think the determinant is the only mutilinear alternating function in the vector space - up to a constant. If you require the map to have a value of 1 on the identity matrix then you get the determinant.
To clarify, Lavinia means that the top exterior power of a vector space is one-dimensional. I.e. for an n-dimensional vector space V, the vector space of alternating, multilinear functions f:V^n->R is one-dimensional. This is only true for the top dimension.
 
zhentil said:
To clarify, Lavinia means that the top exterior power of a vector space is one-dimensional. I.e. for an n-dimensional vector space V, the vector space of alternating, multilinear functions f:V^n->R is one-dimensional. This is only true for the top dimension.

Yes. this is the same statement.

the determinant is a polynomial in the matrix entries. I wonder how this all translates into the properties of this polynomial.
 
lavinia said:
Yes. this is the same statement.

the determinant is a polynomial in the matrix entries. I wonder how this all translates into the properties of this polynomial.

How about this as another way to think of the determinant. Consider all functions on square matrices that are constant under conjugation.

f(X) = f(AXA ^-1)

for all square matrices X and invertible square matrices ,A.

For instance the trace is such a function.

Define the determinant to be that function which equals the product of the diagonal entries on any diagonal matrix.
 
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Thanks for the responses. However, I have a question.
Is the determinant uniquely determined by its multilinearity and the properties I mentioned above?
I am hoping that the determinant can be made into a type of analogue of the complex abosolute value with as few other conditions as possible (alternating multilinear is a bit too...esoteric for my tastes)
 
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zeta12ti said:
Thanks for the responses. However, I have a question.
Is the determinant uniquely determined by its multilinearity and the properties I mentioned above?
I am hoping that the determinant can be made into a type of analogue of the complex abosolute value with as few other conditions as possible (alternating multilinear is a bit too...esoteric for my tastes)

alternating multilinear on any n-vectors uniquely determines the determinant up to a constant.
 
I like how it's covered in Linear Algebra Done Wrong, which is free and easy to find online. Once he gets to the definition of determinant I think the coverage is pretty standard but the motivation behind the definition is nicely included.
 
zeta12ti said:
Thanks for the responses. However, I have a question.
Is the determinant uniquely determined by its multilinearity and the properties I mentioned above?
I am hoping that the determinant can be made into a type of analogue of the complex abosolute value with as few other conditions as possible (alternating multilinear is a bit too...esoteric for my tastes)

An equivalent definition is that the determinant is the product of the eigenvalues of the linear transformation that corresponds to the matrix (ie., it is the factor of signed scale of n-paralleletopes embedded in the target vector space versus the domain). This definition is a bit more intuitive and easier to work with geometrically. If you're looking for a formula that refers directly to the entries of an arbitrary matrix representation of the linear transformation, then you are left with the alternating multilinear map, embodied in the Levi-Civita symbol or Laplace's expansion by minors (equivalent, just re-ordered).
The relation between the two definitions is derived through basic geometric algebra (the wedge product).
 
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  • #10
^The product of eigenvalues is not equivalent or helpful is the matrix does not have any eigenvalues.
 

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