Simple Complex Vector Space Proof Clarification

In summary, to prove that if cv = 0, then v = 0 in a vector space V over a field ℂ where c ≠ 0, we can use the fact that ℂ is a field and therefore the multiplicative inverse of any non-zero scalar exists. This allows us to manipulate the equation to show that v = 0.
  • #1
RJLiberator
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Homework Statement


Let v ∈ V and c ∈ ℂ, with c ≠ 0. Prove that if cv = 0, then v = 0.

Homework Equations


Vector space axioms.

The Attempt at a Solution



Simple proof overall, but I have one major clarification question.

v = 1v
= (c^(-1)c)v
= c^(-1) (cv)
= c^(-1) 0
v
= 0

My question is, in a complex vector space, is it safe to assume that c^(-1) exists in this proof?
If it does, I feel very confident about this proof.
If it doesn't then I need to do something else.

I don't see anywhere in the vector space axioms that states the multiplicative inverse exists.
But, it makes sense to me that an inverse does exist for any possible scalar choice here.
 
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  • #2
RJLiberator said:
But, it makes sense to me that an inverse does exist for any possible scalar choice here.

Yes indeed, because ##\mathbb{C}## is a field. More generally, one always speaks of a vector space over a field. (Real and complex numbers are the common choices, but there are others.) So the existence of ##\mathbb{c}^{-1}## for ##\mathbb{c} \neq 0## really follows from the field axioms, not from the vector space axioms.
 
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  • #3
Beautiful! I was searching the vector space axioms and had them in my head. The field axioms clearly state this.

thank you, once again, Krylov.
 
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FAQ: Simple Complex Vector Space Proof Clarification

1. What is a simple complex vector space?

A simple complex vector space is a type of vector space that is defined over the field of complex numbers and has only one subspace, which is the zero subspace. This means that there are no non-trivial subspaces in a simple complex vector space.

2. What makes a proof about a complex vector space complex?

A proof about a complex vector space can be considered complex if it involves multiple steps and requires a deep understanding of linear algebra and complex numbers. It may also involve advanced mathematical concepts such as eigenvectors, eigenvalues, and unitary transformations.

3. How is a complex vector space different from a real vector space?

A complex vector space differs from a real vector space in that it is defined over the field of complex numbers, while a real vector space is defined over the field of real numbers. This means that the scalars used in a complex vector space are complex numbers, which have both a real and imaginary component, while the scalars in a real vector space are only real numbers.

4. What is the importance of proving properties of vector spaces?

Proving properties of vector spaces is important because it allows us to better understand the structure and behavior of these mathematical objects. It also helps us to develop new theorems and concepts that can be applied to various fields such as physics, engineering, and computer science.

5. How can a simple complex vector space proof be used in real-world applications?

A simple complex vector space proof can be used in real-world applications in fields such as signal processing, quantum mechanics, and control theory. For example, the proof of the spectral theorem, which states that every Hermitian matrix can be diagonalized by a unitary matrix, is a fundamental result that has many practical applications in physics and engineering.

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