Is the Set of Orthogonal Vectors to Any Non-Zero Vector a Subspace?

In summary, the set of all vectors orthogonal to any non-zero vector in a vector space V^{n}, denoted by \left\{|V^{1}_{\bot}> |V^{2}_{\bot}> |V^{3}_{\bot}> ... \right\}, forms a subspace V^{n-1}. To prove this, one can show that if X and Y are orthogonal to V and c is a scalar, then cX and X+Y are also orthogonal to V using properties of the inner product. This is a standard Linear Algebra question and was originally seen in a quantum mechanics textbook.
  • #1
ercagpince
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Homework Statement


In a space [tex]V^{n}[/tex] , prove that the set of all vectors
[tex]\left\{|V^{1}_{\bot}> |V^{2}_{\bot}> |V^{3}_{\bot}> ... \right\}[/tex]
orthogonal to any [tex]|V> \neq 0[/tex] , form a subspace [tex]V^{n-1}[/tex]

Homework Equations





The Attempt at a Solution


I tried to make a linear combination from that set and product with <V|, I yielded nothing logical , at least I didn't understand the outcome .
I wrote <V| as linear combination of basis in V^n vector space , I thought
that since the |V> and those vectors share the same vector space , it might be possible that they have the same orthogonal basis (just an assumption which is probably false) .

All it left to me the product of components of these vectors as a matrix , but as i said before I have no clue that I am doing the right thing to solve this problem .
 
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  • #2
X is orthogonal to V if <V|X>=0. To show such vectors form a subspace you just have to show if X and Y are orthogonal to V and c is a scalar then cA and A+B are also orthogonal to V.
 
  • #3
What are A and B ?
 
  • #4
ercagpince said:
What are A and B ?

Ooops. I meant show cX and X+Y are orthogonal to V. Forgot my notation.
 
  • #5
how can I show it ?
That is the problem actually .
 
  • #6
Use properties of the inner product! <V|(X+Y)>=<V|X>+<V|Y>, for example.
 
  • #7
Why in the world is this under "physics"? This is a pretty standard Linear Algebra question!
 
  • #8
I saw this problem on a quantum mechanics textbook , that's why I subscribed it in here .

Thank you dick by the way .
 

FAQ: Is the Set of Orthogonal Vectors to Any Non-Zero Vector a Subspace?

What is a linear combination subspace?

A linear combination subspace is a mathematical concept that involves combining two or more vectors using scalar multiplication and addition. The resulting vector is still within the same subspace as the original vectors and can be represented as a linear combination of those vectors.

How is a linear combination subspace different from a regular subspace?

A linear combination subspace is a subset of a regular subspace. While a regular subspace is closed under addition and scalar multiplication, a linear combination subspace is specifically formed by combining vectors in a linear manner.

Can a linear combination subspace be infinite-dimensional?

Yes, a linear combination subspace can be infinite-dimensional. This means that there can be an infinite number of vectors used to form the subspace using linear combinations.

How is a linear combination subspace used in real-world applications?

Linear combination subspaces are used to model and solve many real-world problems in various fields such as engineering, physics, and economics. They can be used to represent and manipulate complex systems and make predictions based on the relationships between different variables.

Can a linear combination subspace have a basis that is not linearly independent?

No, a linear combination subspace must have a basis that is linearly independent. This ensures that the vectors used to form the subspace are not redundant and can accurately represent the subspace without any redundancy or overlap.

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