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Orthogonal matrices are important for a number of reasons, both theoretical and practical. The n × n orthogonal matrices form a group under matrix multiplication, the orthogonal group denoted by O(n), which—with its subgroups—is widely used in mathematics and the
Matrices can be generalized in different ways. Abstract algebra uses matrices with entries in more general fields or even rings, while linear algebra codifies properties of matrices in the notion of linear maps. It is possible to consider matrices with infinitely many columns and rows.
Several important classes of matrices are subsets of each other. This article lists some important classes of matrices used in mathematics, science and engineering. A matrix (plural matrices, or less commonly matrixes) is a rectangular array of numbers called entries. Matrices have a long history of both study and application, leading to ...
The scalar matrices are the center of the algebra of matrices: that is, they are precisely the matrices that commute with all other square matrices of the same size. [ a ] By contrast, over a field (like the real numbers), a diagonal matrix with all diagonal elements distinct only commutes with diagonal matrices (its centralizer is the set of ...
In linear algebra, linear transformations can be represented by matrices.If is a linear transformation mapping to and is a column vector with entries, then there exists an matrix , called the transformation matrix of , [1] such that: = Note that has rows and columns, whereas the transformation is from to .
Let A be an m × n matrix with real or complex entries. [a] If I is a subset of size r of {1, ..., m} and J is a subset of size s of {1, ..., n}, then the (I, J )-submatrix of A, written A I, J , is the submatrix formed from A by retaining only those rows indexed by I and those columns indexed by J.
The above formula shows that its Lie algebra is the special linear Lie algebra consisting of those matrices having trace zero. Writing a 3 × 3 {\displaystyle 3\times 3} -matrix as A = [ a b c ] {\displaystyle A={\begin{bmatrix}a&b&c\end{bmatrix}}} where a , b , c {\displaystyle a,b,c} are column vectors of length 3, then the gradient over one ...
The defining property for the gamma matrices to generate a Clifford algebra is the anticommutation relation {,} = + = ,where the curly brackets {,} represent the anticommutator, is the Minkowski metric with signature (+ − − −), and is the 4 × 4 identity matrix.