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== Definition ==
Let {{math|''A''}} be an {{math|''m'' × ''n''}} matrix with [[real number|real]] or [[complex number|complex]] entries.{{efn|The definition, and the purely algebraic part of the theory, of compound matrices requires only that the matrix have entries in a [[commutative ring]]. In this case, the matrix corresponds to a [[module homomorphism|homomorphism]] of [[finitely generated module|finitely generated]] [[free module]]s.}} If {{math|''I''}} is a [[subset]] of size {{math|''r''}} of {{math|{1, ..., ''m''<nowiki>}</nowiki>}} and {{math|''J''}} is a subset of size {{math|''s''}} of {{math|{1, ..., ''n''<nowiki>}</nowiki>}}, then the '''{{math|(''I'', ''J''
The '''''r''
In some applications of compound matrices, the precise ordering of the rows and columns is unimportant. For this reason, some authors do not specify how the rows and columns are to be ordered.<ref>Kung, Rota, and Yan, p. 305.</ref>
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For example, consider the matrix
:<math>A = \begin{pmatrix} 1 & 2 & 3 & 4 \\ 5 & 6 & 7 & 8 \\ 9 & 10 & 11 & 12 \end{pmatrix}.</math>
The rows are indexed by {{math|{1, 2, 3<nowiki>}</nowiki>}} and the columns by {{math|{1, 2, 3, 4<nowiki>}</nowiki>}}. Therefore, the rows of {{math|''C''<sub>2
:<math>\{1, 2\} < \{1, 3\} < \{2, 3\}</math>
and the columns are indexed by
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Let {{math|''c''}} be a scalar, {{math|''A''}} be an {{math|''m'' × ''n''}} matrix, and {{math|''B''}} be an {{math|''n'' × ''p''}} matrix. For {{math|''k''}} a positive [[integer]], let {{math|''I''<sub>''k''</sub>}} denote the {{math|''k'' × ''k''}} [[identity matrix]]. The [[transpose]] of a matrix {{math|''M''}} will be written {{math|''M''{{i sup|T}}}}, and the [[conjugate transpose]] by {{math|''M''{{i sup|*}}}}. Then:<ref>Horn and Johnson, p. 22.</ref>
* {{math|1=''C''<sub>0
* {{math|1=''C''<sub>1</sub>(''A'') = ''A''}}.
* {{math|1=''C''<sub>''r'' </sub>(''cA'') = ''c''{{i sup|''r''}}''C''<sub>''r'' </sub>(''A'')}}.
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* If {{math|1 ≤ ''r'' ≤ min(''m'', ''n'')}}, then {{math|1=''C''<sub>''r'' </sub>(''A''{{i sup|T}}) = ''C''<sub>''r'' </sub>(''A''){{i sup|T}}}}.
* If {{math|1 ≤ ''r'' ≤ min(''m'', ''n'')}}, then {{math|1=''C''<sub>''r'' </sub>(''A''<sup>*</sup>) = ''C''<sub>''r'' </sub>(''A'')<sup>*</sup>}}.
* {{math|1=''C''<sub>''r'' </sub>(''AB'') = ''C''<sub>''r'' </sub>(''A'')
Assume in addition that {{math|''A''}} is a [[square matrix]] of size {{math|''n''}}. Then:<ref>Horn and Johnson, pp. 22, 93, 147, 233.</ref>
* {{math|1=''C''<sub>''n''
* If {{math|''A''}} has one of the following properties, then so does {{math|''C''<sub>''r'' </sub>(''A'')}}:
** [[Upper triangular]],
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{{see also|Exterior algebra}}
Give {{math|'''R'''<sup>''n''</sup>}} the [[canonical basis|standard coordinate basis]] {{math|'''e'''<sub>1</sub>, ..., '''e'''<sub>''n''</sub>}}. The {{math|''r''}}
:<math>\wedge^r \mathbf{R}^n</math>
whose [[basis (linear algebra)|basis]] consists of the formal symbols
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Suppose that {{math|''A''}} is an {{math|''m'' × ''n''}} matrix. Then {{math|''A''}} corresponds to a [[linear transformation]]
:<math>A \colon \mathbf{R}^n \to \mathbf{R}^m.</math>
Taking the {{math|''r''}}
:<math>\wedge^r A \colon \wedge^r \mathbf{R}^n \to \wedge^r \mathbf{R}^m.</math>
The matrix corresponding to this linear transformation (with respect to the above bases of the exterior powers) is {{math|''C''<sub>''r'' </sub>(''A'')}}. Taking exterior powers is a [[functor]], which means that<ref>Joseph P.S. Kung, Gian-Carlo Rota, and [[Catherine Yan|Catherine H. Yan]], ''[[Combinatorics: The Rota Way]]'', Cambridge University Press, 2009, p. 306. {{isbn|9780521883894}}</ref>
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{{see also|Adjugate matrix}}
Let {{math|''A''}} be an {{math|''n'' × ''n''}} matrix. Recall that its '''{{mvar|r}}
:<math>(-1)^{\sigma(I) + \sigma(J)} \det A_{J^c, I^c},</math>
where, for any set {{math|''K''}} of integers, {{math|''σ''(''K'')}} is the sum of the elements of {{math|''K''}}. The '''adjugate''' of {{math|''A''}} is its 1st higher adjugate and is denoted {{math|adj(''A'')}}. The generalized [[Laplace expansion]] formula implies
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and let {{math|''J''}} denote the ''[[exchange matrix]]'':
:<math>J = \begin{pmatrix} & & 1 \\ & \cdots & \\ 1 & & \end{pmatrix}.</math>
Then '''Jacobi's theorem''' states that the {{math|''r''}}
:<math>\operatorname{adj}_r(A) = JC_{n-r}(SAS)^TJ.</math>
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