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In the various branches of mathematics that fall under the heading of abstract algebra, the kernel of a homomorphism measures the degree to which the homomorphism fails to be injective.
The definition of kernel takes various forms in various contexts. But in all of them, the kernel of a homomorphism is trivial (in a sense relevant to that context) if and only if the homomorphism is injective. The fundamental theorem on homomorphisms (or first isomorphism theorem) is a theorem, again taking various forms, that applies to the quotient algebra defined by the kernel.
In this article, we first survey kernels for some important types of algebraic structures; then we give general definitions from universal algebra for generic algebraic structures.
Let V and W be vector spaces and let T be a linear transformation from V to W. If 0W is the zero vector of W, then the kernel of T is the preimage of the singleton set {0W}; that is, the subsetIf X and Y are sets and every element of X is also an element of Y, then we say or write: X is a subset of (or is included in) Y; X ⊆ Y; Y is a superset of (or includes X; Y ⊇ X. Every set Y is a subset of itself. A subset of Y which is not equa of V consisting of all those elements of V that are mapped by T to the element 0W. The kernel is usually denoted "ker T" (or a variation). In symbols:
Since a linear transformation preserves zero vectors, the zero vector 0V of V must belong to the kernel. The transformation T is injective if and only if its kernel is only the singleton set {0V}.
It turns out that ker T is always a subspace of V. Thus, it makes sense to speak of the quotient spaceIn linear algebra, the quotient of a vector space V by a subspace N is a vector space obtained by "collapsing" N to zero. The space obtained is called a quotient space and is denoted V ''N (read V mod N . Definition Formally, the construction is as follow V/(ker T). The first isomorphism theorem for vector spaces states that this quotient space is naturally isomorphic to the image of T (which is a subspace of W). As a consequence, the dimension of V equals the dimension of the kernel plus the dimension of the image.
If V and W are finite-dimensional and basesAbstract algebra Algebra Linear algebra In mathematics, a subset B of a vector space V is said to be a basis of V if it satisfies one of the four equivalent conditions: B is both a set of linearly independent vectors and a generating set of V''. B is a mi have been chosen, then T can be described by a matrixAbstract algebra Algebra Linear algebra In mathematics, a matrix (plural matrices is a rectangular table of numbers or, more generally, of elements of a fixed ring. In this article, if unspecified, the entries of a matrix are always real or complex number M, and the kernel can be computed by solving the homogenous system of linear equations Mv = 0. In this representation, the kernel corresponds to the nullspace of M. The dimension of the nullspace, called the nullity of M, is given by the number of columns of M minus the rank of M, as a consequence of the rank-nullity theorem.
Solving homogeneous differential equations often amounts to computing the kernel of certain differential operators. For instance, in order to find all twice- differentiable functions f from the real line to itself such that
let V be the space of all twice differentible functions, let W be the space of all functions, and define a linear operator T from V to W by
for f in V and x an arbitrary real number.
One can define kernels for homomorphisms between modules over a ring in an analogous manner. This includes kernels for homomorphisms between abelian groups as a special case. This example captures the essence of kernels in general abelian categories; see Kernel (category theory).