Proving Orthogonal Compliments of Subspaces in Matrix Algebra

In summary, To prove that the set W of row vectors x in R^m such that xA=0 is a subspace of R^m, the only thing that needs to be shown is that W is closed under addition and multiplication. To prove that the subspace W in part a. and the column space of A are orthogonal compliments, one way to approach it is to show that the dot product of any row vector in W with any column vector in the column space is equal to zero. This can be seen by looking at the corresponding entry in the vector xA=0, which will always be zero. It is safe to assume that the operations of addition and scalar multiplication are normal unless otherwise specified.
  • #1
mlarson9000
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0

Homework Statement


Let A be an mxn matrix.
a. Prove that the set W of row vectors x in R^m such that xA=0 is a subspace of R^m.

b. Prove that the subspace W in part a. and the column space of A are orthogonal compliments.


Homework Equations





The Attempt at a Solution


a. to be a subspace, I believe i only need to show that W is closed under addition and multiplication. So I just show that (rx+sy)A=0. Right?

b. Not too sure about this. Should I try to show that x dotted with a=0 for all x and a? Or should try to do something with the properties of orthogonal compliments? I can show that dim(W)= nullity(A), but I don't think that's really going to do anything for me.
 
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  • #2
For part a you have the right idea.

For part b, If you look at the row vector x dotted with one of the columns of W, say a, then where in the vector xA can you find that number?
 
  • #3
For a row vector x dotted with the column vector ai, the resuting value will be the ith column of the 1xn zero vector. This for me does not guarantee that the value will be zero, however.
 
  • #4
mlarson9000 said:
For a row vector x dotted with the column vector ai, the resuting value will be the ith column of the 1xn zero vector. This for me does not guarantee that the value will be zero, however.

I don't get it. The result is the ith entry in a zero vector. How might that not be zero?
 
  • #5
If addition or scalar multiplication are redefined, then the zero vector can have nonzero entries. So since the problem doesn't say anything about that, I am to assume that everything is normal?
 
  • #6
If they don't explicitly tell you to use a nonstandard addition or scalar product, then sure, assume everything is normal.
 

FAQ: Proving Orthogonal Compliments of Subspaces in Matrix Algebra

What is an orthogonal compliment?

An orthogonal compliment is a mathematical term used to describe the set of all vectors that are perpendicular, or orthogonal, to a given vector or set of vectors.

What is the importance of proving orthogonality?

Proving orthogonality is important in a variety of mathematical fields, including linear algebra, geometry, and physics. It allows us to understand and manipulate vectors and their relationships to one another.

How is orthogonality proven in a mathematical proof?

To prove orthogonality, we must show that the dot product of two vectors is equal to 0. This means that the two vectors are perpendicular to each other, and therefore, orthogonal.

What are some real-world applications of orthogonal compliments?

Orthogonal compliments have many practical uses, such as in computer graphics, where they are used to determine the direction of light and shadows. They are also used in signal processing, where they help to eliminate noise from signals.

Are orthogonal compliments and orthogonal projections the same thing?

No, they are not the same thing. While orthogonal compliments refer to the set of vectors perpendicular to a given vector or set of vectors, orthogonal projections involve projecting a vector onto a subspace that is orthogonal to a given vector or set of vectors.

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