2025-04-13

1077: Complex Conjugate of Complex Vectors Space

<The previous article in this series | The table of contents of this series | The next article in this series>

definition of complex conjugate of complex vectors space

Topics


About: vectors space

The table of contents of this article


Starting Context



Target Context


  • The reader will have a definition of complex conjugate of complex vectors space.

Orientation


There is a list of definitions discussed so far in this site.

There is a list of propositions discussed so far in this site.


Main Body


1: Structured Description


Here is the rules of Structured Description.

Entities:
C: with the canonical field structure
V: { the C vectors spaces }, with any addition, +, and any scalar multiplication,
V: =V, { the C vectors spaces }, with the addition, , and the scalar multiplication, , specified below
//

Conditions:
v,vV(vv=v+v)

vV,cC(cv=cv)
//


2: Note


V=V means that they are the same sets-wise.

There is the bijective correspondence, f:VV,vv, which is not any vectors space homomorphism: f(cv)=cv=cv=cf(v), which is not linear.

f(v) is called "conjugate of v".

When V is d-dimensional and has a basis, B={b1,...,bd}, B is also a basis for V: for c1b1...cdbd=0, c1b1+...+cdbd=0, which implies that c1=...=cd=0, which implies that c1=...=cd=0, so, B is linearly independent on V; for each vV, v=v1b1+...+vdbd=v1b1...vdbd, so, B spans V.

The components set of any vV with respect to B is (v1,...,vd)t, which means that v=v1b1+...+vdbd, which means that v=v1b1...vdbd, so, the components set of vV with respect to B is (v1,...,vd), which is frequently denoted as the row vector, as a custom.

When V has an inner product, ,V, ,:V×VC,(v,v)v,f1(v)V is often called "inner product", although the definition of inner product on real or complex vectors space is on a single vectors space.

For v=vjbj and v=vlbl, v,v=vjbj,vlbl=vlbl,f1(vjbj)V=vlbl,vjbjV=vjvlbl,bjV, and especially if the basis is orthonormal, =vjvlδl,j=jvjvj=(v1,...,vd)(v1,...,vd)t.

Let us see that V is indeed a C vectors space.

1) for any elements, v1,v2V, v1v2V (closed-ness under addition): v1v2=v1+v2V=V.

2) for any elements, v1,v2V, v1v2=v2v1 (commutativity of addition): v1v2=v1+v2=v2+v1=v2v1.

3) for any elements, v1,v2,v3V, (v1v2)v3=v1(v2v3) (associativity of additions): (v1v2)v3=(v1+v2)+v3=v1+(v2+v3)=v1(v2v3).

4) there is a 0 element, 0V, such that for any vV, v0=v (existence of 0 vector): 0V=V, and v0=v+0=v.

5) for any element, vV, there is an inverse element, vV, such that vv=0 (existence of inverse vector): v:=vV=V, and vv=v+v=0.

6) for any element, vV, and any scalar, rC, rvV (closed-ness under scalar multiplication): rv=rvV=V.

7) for any element, vV, and any scalars, r1,r2C, (r1+r2)v=r1vr2v (scalar multiplication distributability for scalars addition): (r1+r2)v=(r1+r2)v=(r1+r2)v=r1v+r2v=r1vr2v.

8) for any elements, v1,v2V, and any scalar, rC, r(v1v2)=rv1rv2 (scalar multiplication distributability for vectors addition): r(v1v2)=r(v1+v2)=rv1+rv2=rv1rv2.

9) for any element, vV, and any scalars, r1,r2C, (r1r2)v=r1(r2v) (associativity of scalar multiplications): (r1r2)v=(r1r2)v=(r1r2)v=r1(r2v)=r1(r2v).

10) for any element, vV, 1v=v (identity of 1 multiplication): 1v=1v=1v=v.


References


<The previous article in this series | The table of contents of this series | The next article in this series>