3. Vector Spaces

3.2. Definition and Axioms of Vector Spaces

This subsection formalizes what it means for a set to be a vector space over a field (like ℝ).

Definition:
A vector space

VV

V over a field

FF

F is a set equipped with:

  • Vector addition:

    +:V×VV+ : V \times V \to V

  • Scalar multiplication:

    :F×VV\cdot : F \times V \to V


    that satisfy the following 8 axioms for all

    u,v,wVu, v, w \in V

    and

    a,bFa, b \in F

    :

  1. u+v=v+uu + v = v + u

    (commutativity)

  2. (u+v)+w=u+(v+w)(u + v) + w = u + (v + w)

    (associativity of addition)

  3. There exists a zero vector

    0V0 \in V

    such that

    v+0=vv + 0 = v

  4. Each

    vVv \in V

    has an additive inverse

    vV-v \in V

    such that

    v+(v)=0v + (-v) = 0

  5. a(u+v)=au+ava(u + v) = au + av

    (distributivity over vector addition)

  6. (a+b)v=av+bv(a + b)v = av + bv

    (distributivity over field addition)

  7. a(bv)=(ab)va(bv) = (ab)v

    (compatibility of scalar multiplication)

  8. 1v=v1 \cdot v = v

    (identity element of scalar multiplication)