Complexification of subspace

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In summary: C.In summary, the conversation discusses subspaces of a real vector space V and its complexification V_C. The real subspace of G is defined as the intersection of G and V. The annihilator subspaces F^perp and G^perp are defined using the symplectic form w[u,v]. The results (F^perp)_C = (F_C)^perp and (G_R)_C = G^*_C are mentioned and a proof is discussed for (F^perp)_C subset of (F_C)^perp. The conversation also touches on the conditions for a subspace to be a vector subspace.
  • #1
julian
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Let F be a subspace of a real vector space V and let

G \subset V_C

i.e. a subspace of its complexification. Define the real subspace of G by


G_R := G \cap V.


There is a symplectic form w[u,v]. The annihilator subspace F^perp of V is defined by


F^perp = {v \in V : w[u,v] = 0 for all u \in F}


The annihilator subspace G^perp of V_C is defined by


G^perp = {v \in V_C : w[u,v] = 0 for all u \in G}.


Then the following results hold:


(F^perp)_C = (F_C)^perp,


It is easy to see that (F^perp)_C subset of (F_C)^perp. Could somone prove it the other way? I'm thinking F_C is larger than F so the annihilator condition is more restrictive?

thanks
 
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  • #2
had a quick look & think it should work both ways

[tex]\Rightarrow[/tex]
[tex] p \in F^{\perp}[/tex]
[tex] p_c \in (F^{\perp})_c, \ \ p_c = p_1 + ip_2, \ \ p_1, p_2 \in F^{\perp} [/tex]

now take
[tex] f_c \in F_c, \ \ f_c = f_1 + i f_2, \ \ f_1, f_2 \in F [/tex]

[tex] w[p_c,f_c] = w[ f_1 + if_2, p_1 + ip_2 ] = 0 [/tex]

so
[tex] p_c \in (F_c)^{\perp}[/tex]
 
  • #3
and the other
[tex] \Leftarrow[/tex]

[tex] f_c \in F_c, \ \ f_c = f_1 + i f_2, \ \ f_1, f_2 \in F [/tex]

[tex]q \in (F_c)^{\perp}, \ \ w[f_c,q] = 0 , \ \ \forall f_c \in F_c [/tex]

[tex]q \in V_c, \ \ q = q_1 + iq_2, \ \ q_1,q_2 \in V [/tex]

[tex] w[q,f_c]=0 \ \implies \ w[q_1, f_1] = 0 \ \implies \ q_1 \in F^{\perp} [/tex]
 
Last edited:
  • #4
Thank you.


to prove the very last part do you put f_1=f_2 which implies from real and imaginary parts of w [q,f_c] are


w [q_1 + q_2 , f_1] =0

w[q_1 - q_2, f_1] = 0

adding gives

w[q_1,f_1] = 0 ?
 
  • #5
no i'ev assumed w is a linear operator
w[q_1 + i q_2, f_1] = w[q_1, f_1] + w[i q_2, f_1] = 0

so it follows that each part must be zero (though you may need to be careful with conjugates)
 
  • #6
I'm not sure you can put f_2 = 0 - it's not necessarily an element of F
 
  • #7
F is a subspace, so must contain the zero vector by def'n
 
  • #8
Are you assuming the subspace is a Vector subspace?

thanks
 
  • #9
yeah that's generally what's meant by a subspace of a vector space...
 
Last edited:
  • #10
A subspace will be a vector space if it is closed under addition and multiplication by the field, but what if these conditions are not imposed?


I have another question (I don't know if it has a relation to the above). I mentioned a G at the begining. In the book he also says that if G=G^* then (G_R)_C. I know that we cannot have $z w = w^* in general and maybe that has something to do with it.
 
  • #11
sorry I meant


(G_R)_C = G
 

1. What is the complexification of a subspace?

The complexification of a subspace is a process in which a real vector space is extended to include complex numbers, resulting in a larger vector space known as a complex vector space. This allows for the representation of complex-valued vectors and operations on those vectors.

2. How is the complexification of a subspace different from the original subspace?

The complexification of a subspace adds an additional dimension to the original subspace, allowing for the representation of complex numbers. This means that the complexified subspace has a larger basis and can represent a wider range of vectors than the original subspace.

3. Why is the complexification of a subspace useful?

The complexification of a subspace is useful because it allows for the representation of complex-valued data, which is often necessary in many areas of science, such as quantum mechanics and signal processing. It also simplifies mathematical calculations involving complex numbers.

4. Can any subspace be complexified?

Yes, any real vector space can be complexified. However, the resulting complex vector space may not always have the same properties as the original subspace, such as orthogonality or dimensionality. It is important to consider these factors when complexifying a subspace.

5. Are there any drawbacks to complexifying a subspace?

The main drawback of complexifying a subspace is that it adds an extra dimension to the original subspace, which can make calculations and visualizations more complex. It is also important to note that the resulting complex vector space may not always have the same properties as the original subspace.

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