Vector space
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A vector space over a field (frequently the real numbers) is an object which arises in linear algebra and abstract algebra. A vector space over a field
consists of a set (of vectors) and two operations, vector addition and scalar multiplication, which obey the following rules:
Contents
Axioms of a vector space
- Under vector addition, the set of vectors forms an abelian group. Thus, addition is associative and commutative and there is an additive identity (usually denoted
) and additive inverses.
- Scalar multiplication is associative, so if
and
then
.
- Scalar multiplication is distributive over both vector and scalar addition, so if
and
then
.
- if
,
Subspaces
If , and
is a vector space itself, then it is called a subspace of
.
Independent Subsets
Let be any vector space. Let
be a subset of
such that no linear combination of elements of
with coefficients not all zero gives the null vector. Then
is said to be a linearly independent subset of
. An independent subset is said to be maximal if on adding any other element it ceases to be independent.
Linear Manifolds
Let be a subset of some vector space
. Then it can be proved that the set of all linear combinations of the elements of
forms a vector space. This space is said to have been generated by
, and is called the linear manifold
of
.
Generating Subset
If is a subset of a vector space
, such that
,
is said to be a generating subset of
. A generating subset is said to be minimal if on removing any element it ceases to be generating.
Basis and dimension
The following statements can be proved using the above definitions:
- All minimal generating subsets have the same cardinality.
- All maximal independent subsets have the same cardinality.
- The cardinality of an independent subset can never exceed that of a generating subset.
An independent generating subset of is said to be its basis. A basis is always a maximal independent subset and a minimal generating subset. As can be easily seen, the cardinalities of all bases are equal. This cardinality is said to be the dimension of
.
Isomorphism
Any two vector spaces of the same dimension are said to be isomporphous - any result obtained for one can be applied to the other.