Linear transformation, subspace and kernel

In summary, we have a linear transformation g: R^2x2 -> R with U as the kernel, where U is the set of 2x2 symmetric matrices. A basis for U is given by [[1,0],[0,0]], [[0,1],[0,0]], [[0,0],[1,0]], and [[0,0],[0,1]]. We can write g as g([[a,b],[c,d]])=0*a+1*b+(-1)*c+0*d, and this transformation will send all matrices of the form [[a,b],[b,c]] to 0, regardless of the values of a, b, and c. However, simply writing [0,1
  • #1
Tala.S
43
0
Hi

We have a linear transformation g : ℝ^2x2 → ℝ g has U as kernel,

U: the 2x2 symmetric matrices

(ab)
(bc)

A basis for U is

(10)(01)(00)
(01)(10)(01)I thought this would be easy but I've been sitting with the problem for a while and I have no clue on how to solve it (maybe because I don't fully understand it).

But this is how I understand it : we need to find a linear transformation that transforms symmetric 2x2 matrices (R^4) to 1x1 matrices (R), so we have

g(a,b,b,c) = (a b b c) = 0

?
 
Last edited:
Physics news on Phys.org
  • #2
Tala.S said:
Hi

We have a linear transformation g : ℝ^2x2 → ℝ g has U as kernel,

U: the 2x2 symmetric matrices

(ab)
(bc)

A basis for U is

(10)(01)(00)
(01)(10)(01)


I thought this would be easy but I've been sitting with the problem for a while and I have no clue on how to solve it (maybe because I don't fully understand it).

But this is how I understand it : we need to find a linear transformation that transforms symmetric 2x2 matrices (R^4) to 1x1 matrices (R), so we have

g(a,b,b,c) = (a b b c) = 0

?

How about this? For a general 2x2 matrix [[a,b],[c,d]] you can write a linear transformation to R as g(a,b,c,d)=w*a+x*b+y*c+z*d. You have to find w,x,y,z such that g=0 if and only if the matrix is symmetric.
 
  • #3
But how can we find the values for w,x,y and z so that g = 0 when we don't even know the values of a,b,b and c ?
 
  • #4
Tala.S said:
But how can we find the values for w,x,y and z so that g = 0 when we don't even know the values of a,b,b and c ?

Try sample matrices. Like your basis for U.
 
  • #5
like this :

a * [[1,0],[0,0]] + b * [[0,1],[1,0]] + c * [[0,0],[0,1]] = 0 ?
 
  • #6
Tala.S said:
like this :

a * [[1,0],[0,0]] + b * [[0,1],[1,0]] + c * [[0,0],[0,1]] = 0 ?

No. Take a matrix in your basis. Like [[1,0],[0,0]]. Figure out what a,b,c and d are. Then put them into the form for g. You want g to give you a real number, not a matrix.
 
  • #7
a * [[1,0],[0,0]] + b * [[1,0],[0,0]] + c * [[1,0],[0,0]] +d* [[1,0],[0,0]] = 0

(a,b,c,d) = 0

But shouldn't it be a [[a,b],[b,c]] matrix ?
 
  • #8
Tala.S said:
a * [[1,0],[0,0]] + b * [[1,0],[0,0]] + c * [[1,0],[0,0]] +d* [[1,0],[0,0]] = 0

(a,b,c,d) = 0

But shouldn't it be a [[a,b],[b,c]] matrix ?

No again. Let's back up. Let's take a basis of R2x2. e1=[[1,0],[0,0]], e2=[[0,1],[0,0]], e3=[[0,0],[1,0]], e4=[[0,0],[0,1]]. That's a basis for R2x2, right? What should g(e1) be?
 
  • #9
g(e1) = [[1,0,0,0]]

g(e2) = [[0,1,0,0]]

g(e3) = [[0,0,1,0]]

g(e4) = [[0,0,0,1]]
 
Last edited:
  • #10
Tala.S said:
g(e1) = [[1,0],[0,0]]

g(e2) = [[0,1],[1,0]]

g(e3) = [[0,0],[0,1]]

No no. g is a linear transformation from R2x2 to R! R is the real numbers, not matrices. g(e1) should be a number. Which number?
 
  • #11
1?

I'm still confused because we don't have g and I'm not sure what the method is to find g.
 
  • #12
Tala.S said:
1?

I'm still confused because we don't have g and I'm not sure what the method is to find g.

Nope, you don't have g yet. We are still working on that. But you do know e1 is symmetric, so e1 is in U the kernel of g. What does that tell you about g(e1)?
 
  • #13
But isn't e1 =[[1,0],[0,0]] ? How is this symmetric?
 
  • #14
Tala.S said:
But isn't e1 =[[1,0],[0,0]] ? How is this symmetric?

I'm using a shorthand. I mean [[1,0],[0,0]] to be the matrix whose first row is 1,0 and the second row is 0,0. That's symmetric. Yes?
 
  • #15
Is g(e1)=a
 
  • #16
Tala.S said:
Is g(e1)=a

What is 'a'? What does 'kernel' mean? Explain 'kernel' in your own words.
 
  • #17
Could the linear transformation be [0,1,-1,0] ?
 
  • #18
Tala.S said:
Could the linear transformation be [0,1,-1,0] ?

It would if you can tell me what that means. I would like you to define g by telling me how g acts on a basis. What are g(e1), g(e2), g(e3) and g(e4)?
 
  • #19
We need to find a linear transformation g: R^2x2 -> R that has U as kernel.
That means that all matrices of this type [a, b, b, c] will be transformed to zero since U is the kernel.
We need to find a linear transformation that 'sends' U to zero. Since we have two b's one can have a negative value and the other a positive value, a and c will be zero because we're going to multiply it with zero.
So no matter what the value of b is it will always be zero because +b-b = 0.

So our linear transformation can be :

[0,1,-1,0] or [0,-1,1,0]

?
 
  • #20
Tala.S said:
We need to find a linear transformation g: R^2x2 -> R that has U as kernel.
That means that all matrices of this type [a, b, b, c] will be transformed to zero since U is the kernel.
We need to find a linear transformation that 'sends' U to zero. Since we have two b's one can have a negative value and the other a positive value, a and c will be zero because we're going to multiply it with zero.
So no matter what the value of b is it will always be zero because +b-b = 0.

So our linear transformation can be :

[0,1,-1,0] or [0,-1,1,0]

?

Absolutely right. But just writing [0,1,-1,0] doesn't say what you just told me. You mean that g([[a,b],[c,d]])=0*a+1*b+(-1)*c+0*d, right?
 
  • #21
Yes that's what I mean :)
 
  • #22
Tala.S said:
Yes that's what I mean :)

Great! Now try and think of ways to express yourself more clearly. Just saying '[0,1,-1,0]' is more of a puzzle than an answer.
 
  • #23
Are you thinking about g(e1), g(e2), g(e3) and g(e4)?
 
  • #24
Tala.S said:
Are you thinking about g(e1), g(e2), g(e3) and g(e4)?

I was thinking that in the general you don't explain enough when you write something down, but sure, speaking of those, writing [0,1,-1,0] doesn't tell me much. Wouldn't giving the values of g(e1), g(e2), g(e3) and g(e4) describe the tranformation more clearly?
 

FAQ: Linear transformation, subspace and kernel

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another vector space while preserving the structure of the space. It satisfies two properties: additivity and homogeneity.

2. What is a subspace?

A subspace is a subset of a vector space that is itself a vector space. It must satisfy three properties: closure under addition, closure under scalar multiplication, and contain the zero vector.

3. How is a linear transformation represented?

A linear transformation can be represented by a matrix. Each column of the matrix represents the image of a basis vector from the input space, and the columns are arranged in the same order as the basis vectors of the output space.

4. What is the kernel of a linear transformation?

The kernel of a linear transformation, also known as the null space, is the set of all vectors in the input space that are mapped to the zero vector in the output space by the linear transformation. It is a subspace of the input space.

5. How can I determine if a set of vectors forms a subspace?

To determine if a set of vectors forms a subspace, you can check if it satisfies the three properties of a subspace: closure under addition, closure under scalar multiplication, and contains the zero vector. You can also check if the set is spanned by a linearly independent set of vectors.

Back
Top