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The '''determinant''' is a number that embeds most information about a matrix.

F
or a matrix effecting a [[LinearAlgebra/Basis#Change_of_Basis|change of basis]], the determinant is the scaling factor of space between bases.

The determinant of '''''A''''' is often notated as ''|'''A'''|''.
The '''determinant''' is a number that embeds most information about a square matrix. Chiefly, for a matrix used to transform [[LinearAlgebra/Basis#Change_of_Basis|bases]], the determinant is the scaling factor of space in the transformation.
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Given an [[LinearAlgebra/SpecialMatrices#Upper_Triangular_Matrices|upper triangular matrix]], the determinant is the product of the diagonal. The determinant of '''''A''''' is notated as ''|'''A'''|''.
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If a matrix cannot be [[LinearAlgebra/Elimination|eliminated]] into an upper triangular matrix, it is '''degenerate''' and [[LinearAlgebra/MatrixProperties#Invertible|non-invertible]]. This directly means that the determinant is zero. This generally only happens if there is multicolinearity. The determinant of any non-square matrix is 0.
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As noted in the properties below, elimination does not change the determinant (although row exchanges flip the sign of it). Given a matrix of shape 2 by 2, the determinant is calculated like:
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Given a [[LinearAlgebra/SpecialMatrices#Diagonal_Matrices|diagonal matrix]], the determinant is the product of the [[LinearAlgebra/EigenvaluesAndEigenvectors|eigenvalues]]. {{{
    | a b |
det | c d | = ad - bc
}}}
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If a matrix cannot be [[LinearAlgebra/Diagonalization|diagonalized]], it is '''defective'''. This simply means that one of the eigenvalues is zero; it may still be invertible and therefore have a non-zero determinent.

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There is an important connection between determinants and [[LinearAlgebra/Elimination|elimination]]. A matrix does not need to be eliminated to arrive at the determinant, but if a matrix ''cannot'' be eliminated into an upper triangular matrix, it is '''degenerate and non-invertible''' and the determinant is 0. This generally only happens if there is multicolinearity. This does lead to a convenient test for [[LinearAlgebra/Invertability|invertability]].
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== Test for Invertibility ==
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There is a direct connection between [[LinearAlgebra/MatrixProperties#Invertible|invertibility]] and having a non-zero determinant. As a result, calculation of the determinant is a simple test for invertibility.

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== Special Matrices and their Determinants ==

For the [[LinearAlgebra/SpecialMatrices#Identity_Matrix|identity matrix]], the determinant is 1.

For a [[LinearAlgebra/SpecialMatrices#Permutation_Matrices|permutation matrix]], the determinant is 1 if there are an even number of row exchanges in the matrix or -1 if there are an odd number of row exchanges.

For an [[LinearAlgebra/Orthogonality#Matrices|orthogonal matrix]], the determinant is 1 or -1.

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== Properties ==
=== Properties ===
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The determinant of the [[LinearAlgebra/MatrixInversion|inverse]] is the inverse of the determinant: ''|'''A'''^-1^| = 1/|'''A'''|''. The determinant of the [[LinearAlgebra/Invertability|inverse]] is the inverse of the determinant: ''|'''A'''^-1^| = 1/|'''A'''|''.
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[[LinearAlgebra/MatrixTransposition|Transposition]] does not change the determinent: ''|'''A'''^T^| = |'''A'''|''. [[LinearAlgebra/Transposition|Transposition]] does not change the determinent: ''|'''A'''^T^| = |'''A'''|''.
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----



== Special Matrices ==

For the [[LinearAlgebra/SpecialMatrices#Identity_Matrix|identity matrix]], the determinant is 1.

For a [[LinearAlgebra/SpecialMatrices#Permutation_Matrices|permutation matrix]], the determinant is 1 if there are an even number of row exchanges in the matrix or -1 if there are an odd number of row exchanges.

For an [[LinearAlgebra/Orthogonality#Matrices|orthogonal matrix]], the determinant is 1 or -1.

For an [[LinearAlgebra/SpecialMatrices#Upper_Triangular_Matrices|upper triangular matrix]], the determinant is the product of the diagonal.

For a [[LinearAlgebra/SpecialMatrices#Diagonal_Matrices|diagonal matrix]], the determinant is the product of the [[LinearAlgebra/EigenvaluesAndEigenvectors|eigenvalues]]. If a matrix cannot be [[LinearAlgebra/Diagonalization|diagonalized]], it is '''defective''' and one of the eigenvalues is zero. It may still be invertible.

Determinants

The determinant is a number that embeds most information about a square matrix. Chiefly, for a matrix used to transform bases, the determinant is the scaling factor of space in the transformation.


Definition

The determinant of A is notated as |A|.

The determinant of any non-square matrix is 0.

Given a matrix of shape 2 by 2, the determinant is calculated like:

    | a b |
det | c d | = ad - bc

There is an important connection between determinants and elimination. A matrix does not need to be eliminated to arrive at the determinant, but if a matrix cannot be eliminated into an upper triangular matrix, it is degenerate and non-invertible and the determinant is 0. This generally only happens if there is multicolinearity. This does lead to a convenient test for invertability.

Properties

Determinants can be factored: |AB| = |A| |B|.

The determinant of the inverse is the inverse of the determinant: |A-1| = 1/|A|.

Transposition does not change the determinent: |AT| = |A|.

Exchanging rows flips the sign of the determinant. This is the intuitive explanation for the determinant of the permutation matrix as noted above. If U = PA, then |U| = |P| |A|.

Multiplying a single row of a matrix by some factor simply means that the determinant was multiplied by the same factor.

    ┌      ┐           ┌    ┐
    │ ta tb│           │ a b│
det │  c  d│ = t * det │ c d│
    └      ┘           └    ┘

Multiplying every row of a matrix by some factor means that the determinant was multiplied by the same factor to the nth power.

    ┌      ┐           ┌      ┐               ┌    ┐
    │ ta tb│           │  a  b│               │ a b│
det │ tc td│ = t * det │ tc td│ = t * t * det | c d|
    └      ┘           └      ┘               └    ┘

Adding to or subtracting from a single row of a matrix means that the determinant is the sum of the determinants of the two factored-out matrices.

    ┌        ┐       ┌    ┐       ┌    ┐
    │ a+x b+y│       │ a b│       │ x y│
det │   c   d│ = det │ c d│ + det │ c d│
    └        ┘       └    ┘       └    ┘

Furthermore, elimination does not change the determinant at all.

    ┌          ┐       ┌    ┐       ┌      ┐       ┌    ┐           ┌    ┐       ┌    ┐
    │    a    b│       │ a b│       │  a  b│       │ a b│           │ a b│       │ a b│ 
det │ c-ma d-mb│ = det │ c d│ - det │ ma mb│ = det │ c d│ - m * det │ a b│ = det │ c d│ - m * 0
    └          ┘       └    ┘       └      ┘       └    ┘           └    ┘       └    ┘


Special Matrices

For the identity matrix, the determinant is 1.

For a permutation matrix, the determinant is 1 if there are an even number of row exchanges in the matrix or -1 if there are an odd number of row exchanges.

For an orthogonal matrix, the determinant is 1 or -1.

For an upper triangular matrix, the determinant is the product of the diagonal.

For a diagonal matrix, the determinant is the product of the eigenvalues. If a matrix cannot be diagonalized, it is defective and one of the eigenvalues is zero. It may still be invertible.

Large matrices, especially with mostly zeros, can be broken up.

    ┌        ┐
    | 2 0 0 0|           ┌    ┐
    | 0 a b 0|           │ a b│
det | 0 c d 0| = 2 * det │ c d│ * 3
    | 0 0 0 3|           └    ┘
    └        ┘


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LinearAlgebra/Determinant (last edited 2026-01-21 16:26:27 by DominicRicottone)