Linear isomorphism in the context of Vector addition


Linear isomorphism in the context of Vector addition

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⭐ Core Definition: Linear isomorphism

In mathematics, and more specifically in linear algebra, a linear map (or linear mapping) is a particular kind of function between vector spaces, which respects the basic operations of vector addition and scalar multiplication. A standard example of a linear map is an matrix, which takes vectors in -dimensions into vectors in -dimensions in a way that is compatible with addition of vectors, and multiplication of vectors by scalars.

A linear map is a homomorphism of vector spaces. Thus, a linear map satisfies , where and are scalars, and and are vectors (elements of the vector space ). A linear mapping always maps the origin of to the origin of , and linear subspaces of onto linear subspaces in (possibly of a lower dimension); for example, it maps a plane through the origin in to either a plane through the origin in , a line through the origin in , or just the origin in . Linear maps can often be represented as matrices, and simple examples include rotation and reflection linear transformations.

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Linear isomorphism in the context of Determinant

In mathematics, the determinant is a scalar-valued function of the entries of a square matrix. The determinant of a matrix A is commonly denoted det(A), det A, or |A|. Its value characterizes some properties of the matrix and the linear map represented, on a given basis, by the matrix. In particular, the determinant is nonzero if and only if the matrix is invertible and the corresponding linear map is an isomorphism. However, if the determinant is zero, the matrix is referred to as singular, meaning it does not have an inverse.

The determinant is completely determined by the two following properties: the determinant of a product of matrices is the product of their determinants, and the determinant of a triangular matrix is the product of its diagonal entries.

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