In mathematics, and more specifically in linear algebra and functional analysis, the kernel (also known as null space or nullspace) of a linear map L : V → W between two vector spaces V and W, is the set of all elements v of V for which L(v) = 0, where 0 denotes the zero vector in W. That is, in set-builder notation,
The kernel of L is a linear subspace of the domain V. In the linear map L : V → W, two elements of V have the same image in W if and only if their difference lies in the kernel of L:
It follows that the image of L is isomorphic to the quotient of V by the kernel:
This implies the rank–nullity theorem:
where, by “rank” we mean the dimension of the image of L, and by “nullity” that of the kernel of L.
When V is an inner product space, the quotient V / ker(L) can be identified with the orthogonal complement in V of ker(L). This is the generalization to linear operators of the row space, or coimage, of a matrix.
The notion of kernel applies to the homomorphisms of modules, the latter being a generalization of the vector space over a field to that over a ring. The domain of the mapping is a module, and the kernel constitutes a "submodule". Here, the concepts of rank and nullity do not necessarily apply.
North star shining on you
April pretends to be june
Calm seas swallowing lives
Of those too young to die
No lullabies to sing you to sleep
As if he died, a soul they could keep
Awakening! awakening!
Awakening! awakening!
But no lullabies
Why no lullabies?
Lullaby lullaby
Lullaby lullaby
No lullabies to sing you to sleep