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In mathematics, and more specifically in linear algebra, a linear map (also called a linear mapping, linear transformation, vector space homomorphism, or in some contexts linear function) is a mapping between two vector spaces that preserves the operations of vector addition and scalar multiplication.
For b ∈ L, let F b be the map / (). Then F b ≠ F c if b ≠ c. Moreover, the K-linear transformations from L to K are exactly the maps of the form F b as b varies over the field L. When K is the prime subfield of L, the trace is called the absolute trace and otherwise it is a relative trace. [4]
Linear maps are mappings between vector spaces that preserve the vector-space structure. Given two vector spaces V and W over a field F, a linear map (also called, in some contexts, linear transformation or linear mapping) is a map: That is compatible with addition and scalar multiplication, that is
For instance, a "map" is a "continuous function" in topology, a "linear transformation" in linear algebra, etc. Some authors, such as Serge Lang, [8] use "function" only to refer to maps in which the codomain is a set of numbers (i.e. a subset of R or C), and reserve the term mapping for more general functions.
In linear algebra, particularly projective geometry, a semilinear map between vector spaces V and W over a field K is a function that is a linear map "up to a twist", hence semi-linear, where "twist" means "field automorphism of K". Explicitly, it is a function T : V → W that is:
scaleType: supported values are linear for a linear mapping between the data values and the color scale, log for a log mapping, pow for a power mapping (the exponent can be provided as pow 0.5), sqrt for a square-root mapping, and quantize for a quantized scale, i.e. the data is grouped in as many classes as the color palette has colors.
The transpose is a map ′ ′ and is defined for linear maps between any vector spaces and , without requiring any additional structure. The Hermitian adjoint maps Y → X {\displaystyle Y\to X} and is only defined for linear maps between Hilbert spaces, as it is defined in terms of the inner product on the Hilbert space.
Example: A continuous and bounded linear map that is not bounded on any neighborhood: If : is the identity map on some locally convex topological vector space then this linear map is always continuous (indeed, even a TVS-isomorphism) and bounded, but is bounded on a neighborhood if and only if there exists a bounded neighborhood of the origin ...