Find Basis of R^n Subspace with Sum X^2=1

In summary, a basis in the context of R^n subspaces is a set of linearly independent vectors that span the subspace. The basis can be determined using methods such as the Gram-Schmidt process or matrix methods. The equation X^2=1 represents a subspace in R^n that is defined by all vectors that satisfy the equation. An R^n subspace can have multiple bases, as a basis is not unique. Finding the basis of a given subspace can help in solving problems by providing a more efficient and organized way of representing and manipulating vectors, as well as offering insight into the subspace's structure and properties.
  • #1
zairizain
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Homework Statement



Let V=(x1,x2,..Xn) Sum X = 0 be a subspace of R^n. Find a basis of V such that Sum X^2=1

Homework Equations


The Attempt at a Solution


for Sum X =0

x1+x2+..+xn =0

xn= -x1-x2-...

So <x1, x2, ...,-x1-x2-...>=<x1, 0,0...,-x1> +<0,x2,0,...,-x2)+...

=x1<1,0,0,...,-1>+x2<0,1,0,...-1>+...
norm, ||x1||=||x2||=||xn||=... = 2^(1/2)

Basis {<1/norm x1, 0, 0,..-1/norm x1>, <0,1/normx2,0,...-1/normx2>,...}For Sum X^2=0

x1^2 +x2^2+...+xn^2 =1
xn^2 = 1- (x1^2 +x2^2+...)

That all I can do. Please guide me.
 
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  • #2


Your solution for Sum X=0 looks correct. For Sum X^2=1, we can use the same approach as before. Let's start by writing out the equation:

x1^2 +x2^2+...+xn^2 =1

We can rewrite this as:

(x1^2-1)+(x2^2-1)+...+(xn^2-1)=0

Now, we can use our previous basis for Sum X=0 and simply add 1 to each element. This will give us a new basis where the sum of squares is equal to 1:

Basis {<1/norm x1 +1, 0, 0,..,-1/norm x1 +1>, <0,1/normx2 +1,0,...,-1/normx2 +1>,...}

Alternatively, we can use the Gram-Schmidt process to find an orthogonal basis for V. Starting with our original basis for Sum X=0, we can use the following algorithm:

1. Let v1=<1/norm x1, 0, 0,..,-1/norm x1>
2. Let u2=<0,1/normx2,0,...,-1/normx2>
3. Let v2=u2-<v1,u2>/<v1,v1>*v1
4. Normalize v2: v2=v2/||v2||
5. Continue this process for all remaining vectors in the original basis.

This will give us an orthogonal basis for V, and we can then normalize each vector to make it an orthonormal basis.
 

What is the definition of "basis" in the context of R^n subspaces?

In linear algebra, a basis is a set of linearly independent vectors that span a vector space. In the context of R^n subspaces, a basis is a set of vectors that can be combined to create any vector in the subspace.

How do you determine the basis of a given R^n subspace?

To determine the basis of a given R^n subspace, you can use the Gram-Schmidt process. This involves finding a set of orthogonal vectors that span the subspace and then normalizing them to create an orthonormal basis. Another method is to use matrix methods, such as row reduction, to find a basis for the subspace.

What does the equation X^2=1 represent in the context of R^n subspaces?

The equation X^2=1 represents a subspace in R^n that is defined by all vectors that satisfy the equation. In other words, it represents a set of vectors that, when squared, equal 1.

Can an R^n subspace have more than one basis?

Yes, an R^n subspace can have multiple bases. This is because a basis is not unique and there can be multiple sets of linearly independent vectors that span the same subspace.

How can finding the basis of a given R^n subspace help in solving problems?

Finding the basis of a given R^n subspace can help in solving problems because it allows for a more efficient and organized way of representing and manipulating vectors in the subspace. It also allows for easier computations and simplification of solutions. Additionally, the basis can provide insight into the structure and properties of the subspace.

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