Difference between revisions of "Vector space"

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An introduction to the important concepts of vector spaces and linear algebra may be found on the [[Basis and coordinates]] page
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==Definition==
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A vector space {{M|V}} over a [[Field|field]] {{M|F}} is a non empty set {{M|V}} and the binary operations:
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* <math>+:V\times V\rightarrow V</math> given by <math>+(x,y)=x+y</math> - vector addition
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* <math>\times:F\times V\rightarrow V</math> given by  <math>\times(\lambda,x)=\lambda x</math> - scalar multiplication
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Such that the following 8 "axioms of a vector space" hold
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===Axioms of a vector space===
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# <math>(x+y)+z=x+(y+z)\ \forall x,y,z\in V</math>
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# <math>x+y=y+x\ \forall x,y\in V</math>
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# <math>\exists e_a\in V\forall x\in V:x+e_a=x</math> - this <math>e_a</math> is denoted <math>0</math> once proved unique.
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# <math>\forall x\in V\ \exists y\in V:x+y=e_a</math> - this <math>y</math> is denoted <math>-x</math> once proved unique.
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# <math>\lambda(x+y)=\lambda x+\lambda y\ \forall\lambda\in F,\ x,y\in V</math>
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# <math>(\lambda+\mu)x = \lambda x+\mu x\ \forall\lambda,\mu\in F,\ x\in V</math>
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# <math>\lambda(\mu x)=(\lambda\mu)x\ \forall\lambda,\mu\in F,\ x\in V</math>
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# <math>\exists e_m\in F\forall x\in V:e_m x = x</math> - this <math>e_m</math> is denoted <math>1</math> once proved unique.
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===Notation===
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We denote a vector space as "Let <math>(V,F)</math> be a vector space" often we will write simply "let <math>V</math> be a vector space" if it is understood what the field is, because [[Mathematicians are lazy|mathematicians are lazy]]
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A [[Norm|normed]] vector space may be denoted <math>(V,\|\cdot\|_V,F)</math>
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===Example===
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Take <math>\mathbb{R}^n</math>, an entry <math>v\in\mathbb{R}^n</math> may be denoted <math>(v_1,...,v_n)=v</math>, scalar multiplication and addition are defined as follows:
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* <math>\lambda\in\mathbb{R},v\in\mathbb{R}^n</math> we define scalar multiplication <math>\lambda v=(\lambda v_1,...,\lambda v_n)</math>
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* <math>u,v\in\mathbb{R}^n</math> - we define addition as <math>u+v=(u_1+v_1,...,u_n+v_n)</math>
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==Important concepts==
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* [[Linear map|Linear maps]] - the homomorphisms and isomorphisms of vector spaces
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* [[Span, linear independence, linear dependence, basis and dimension]]
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* [[Norm]]
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* [[Linear isometry]]
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{{Definition|Linear Algebra}}

Latest revision as of 16:30, 23 August 2015

An introduction to the important concepts of vector spaces and linear algebra may be found on the Basis and coordinates page

Definition

A vector space V over a field F is a non empty set V and the binary operations:

  • +:V×VV given by +(x,y)=x+y - vector addition
  • ×:F×VV given by ×(λ,x)=λx - scalar multiplication

Such that the following 8 "axioms of a vector space" hold

Axioms of a vector space

  1. (x+y)+z=x+(y+z) x,y,zV
  2. x+y=y+x x,yV
  3. eaVxV:x+ea=x - this ea is denoted 0 once proved unique.
  4. xV yV:x+y=ea - this y is denoted x once proved unique.
  5. λ(x+y)=λx+λy λF, x,yV
  6. (λ+μ)x=λx+μx λ,μF, xV
  7. λ(μx)=(λμ)x λ,μF, xV
  8. emFxV:emx=x - this em is denoted 1 once proved unique.

Notation

We denote a vector space as "Let (V,F) be a vector space" often we will write simply "let V be a vector space" if it is understood what the field is, because mathematicians are lazy

A normed vector space may be denoted (V,V,F)

Example

Take Rn, an entry vRn may be denoted (v1,...,vn)=v, scalar multiplication and addition are defined as follows:

  • λR,vRn we define scalar multiplication λv=(λv1,...,λvn)
  • u,vRn - we define addition as u+v=(u1+v1,...,un+vn)

Important concepts