Linear Algebra: does it form a basis?

In summary: Since a is the coefficient on t^2 and b is the coefficient on t, we can leta=a_2 and b=a_1to finda_2(t^2-1)+a_1(b+1)=a_2 t^2+a_1 t +(a_1-a_
  • #1
brushman
113
1

Homework Statement


See attachment.

The Attempt at a Solution



I already did parts i and ii (correctly, I hope). On part iii I found 2 linearly independent elements to be: t+1, t^2 - 1.

However, I don't understand how to show that these form a basis of W. Because W is a subspace of P2, and P2 has dimension 3, we know W has at most dimension 3. But I only have 2 elements, not 3, so I can't use this to show that I have a basis. Perhaps the constraint that p(-1) = 0 reduces the dimension, but I don't know how to prove this.

Thanks.
 

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  • #2
brushman said:
However, I don't understand how to show that these form a basis of W. Because W is a subspace of P2, and P2 has dimension 3, we know W has at most dimension 3. But I only have 2 elements, not 3, so I can't use this to show that I have a basis. Perhaps the constraint that p(-1) = 0 reduces the dimension, but I don't know how to prove this.

Thanks.

A polynomial in W is can be represented by an ordered pair of numbers (a0, a1): p(t)=a0+a1t+(a1-a0)t^2. So the set W is isomorphic with the set of ordered pair of numbers ...

ehild
 
  • #3
the constraint that -1 is a root gives
[itex]a_0-a_1+a_2=0[/itex]
[itex]a_0=a_1-a_2[/itex]

so then

[itex]a(t^2-1)+b(t+1)=at^2-a+bt+a=at^2+bt+(b-a)[/itex]

since a is the coefficient on t^2 and b is the coefficient on t we can let
[itex]a=a_2[/itex] and [itex]b=a_1[/itex]
to find
[itex]a_2(t^2-1)+a_1(b+1)=a_2 t^2+a_1 t +(a_1-a_2)[/itex]
from the constraint we found [itex]a_0=a_1-a_2[/itex]
and so
[itex]a_2(t^2-1)+a_1(b+1)=a_2t^2+b_1t+a_0[/itex]

you follow?

I should also add, every constraint you add to a system reduces the dimension of it by 1, adding another root would make it a 1 dimensional problem
 
  • #4
genericusrnme said:
the constraint that -1 is a root gives
[itex]a_0-a_1+a_2=0[/itex]
[itex]a_0=a_1-a_2[/itex]

so then

[itex]a(t^2-1)+b(t+1)=at^2-a+bt+a=at^2+bt+(b-a)[/itex]

since a is the coefficient on t^2 and b is the coefficient on t we can let
[itex]a=a_2[/itex] and [itex]b=a_1[/itex]
to find
[itex]a_2(t^2-1)+a_1(b+1)=a_2 t^2+a_1 t +(a_1-a_2)[/itex]
from the constraint we found [itex]a_0=a_1-a_2[/itex]
and so
[itex]a_2(t^2-1)+a_1(b+1)=a_2t^2+b_1t+a_0[/itex]

you follow?

Not really...:smile: I would do it just on the opposite way.

Those polynomials which have root -1, are of form pa,b(t)=at^2+bt+(b-a), that is pa,b(t)=a(t^2-1)+b(t+1), which means all such polynomials are linear combination of the basic "vectors" p1=t^2-1 and p2=t+1. Two basic vectors define a two-dimensional subspace.

genericusrnme said:
I should also add, every constraint you add to a system reduces the dimension of it by 1, adding another root would make it a 1 dimensional problem

That is right.
With one more constraint, there would be only one free parameter, so the space would become one-dimensional.


ehild
 

1. What is a basis in linear algebra?

A basis in linear algebra is a set of vectors that can be used to represent any other vector in a given vector space. It is similar to the concept of a coordinate system in geometry, where a set of basis vectors can be used to uniquely describe any point in space.

2. How do you know if a set of vectors forms a basis?

In order for a set of vectors to form a basis, they must be linearly independent and span the entire vector space. This means that none of the vectors in the set can be written as a linear combination of the others, and that together they can represent any vector in the vector space.

3. Can a set of two vectors form a basis?

Yes, a set of two vectors can form a basis in certain vector spaces, such as the 2-dimensional plane. However, in higher dimensional spaces, a larger set of vectors may be needed to form a basis.

4. How does a basis relate to matrix operations?

A basis is closely related to matrix operations, as each basis vector can be represented as a column in a matrix. Matrix multiplication can then be used to perform operations on the vectors, such as transforming them into a new basis or finding linear combinations of them.

5. Is a basis unique?

In most cases, a basis is not unique. There can be multiple different sets of basis vectors that can be used to represent the same vector space. However, a basis is always unique within a specific vector space and is dependent on the choice of coordinate system.

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