Linear tranformations equality

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In summary, we are given a system of 5 equations and 3 variables, and are asked to find the unique solutions, which turn out to be <0,0,0>. We are then asked about the equality of two linear transformations, g and f, in relation to their kernels and images. It is determined that if kerf=kerg=<0,0,0>, then the transformations are equal, but if imf=img=<0,0,0>, there may be infinite linear transformations that are not equal. Ultimately, it is concluded that if imf=img=<0,0,0>, the transformations are equal.
  • #1
sphlanx
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Homework Statement



We are given a homogeneous system of 5 equations and 3 variables. We are asked to find the solutions (which i found to be unique and <0,0,0>) and then we are asked(along loads of other stuff:P):

a)If any two linear transformations g and f have kerf=kerg=<0,0,0> then they are equal.
b)If any two linear transformations g and f have imf=img=<0,0,0> then they are equal.

Homework Equations





The Attempt at a Solution



a) is wrong because there are infinite linear transformations with ker=<0,0,0> but different images. for (positive but not absolutely sure i am correct because the dimension of the images would be equal)
i think b) is correct but i am not sure. I would say that if imf=img=<0,0,0> then they are both the zero linear map so they are equal. Thanks again in advance
 
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  • #2
Sounds to me like you've got it down!
 
  • #3


I would first commend you on finding the unique solution to the system of equations and for recognizing the importance of the question being asked. Your reasoning for part a) is correct - having the same kernel does not necessarily mean that two linear transformations are equal because there can be infinite transformations with the same kernel but different images. However, for part b), I would suggest that you provide a more thorough explanation. While it is true that if imf=img=<0,0,0> then they are both the zero linear map, it is important to also mention that the zero linear map is unique and therefore, any two transformations with the same image must be equal to the zero linear map and, by extension, equal to each other. This is because the image of a linear transformation is determined solely by its action on the basis vectors of the vector space, and if both transformations have the same image, they must have the same action on the basis vectors and therefore, be equal. Overall, your understanding and explanation of part b) is correct.
 

FAQ: Linear tranformations equality

What is a linear transformation?

A linear transformation is a mathematical function that maps a vector space into another vector space, while preserving the basic structure of the space. In simpler terms, it is a transformation that preserves lines and the origin.

What is the significance of equality in linear transformations?

Equality in linear transformations means that the outputs of two different linear transformations are exactly the same. This is important because it shows that the two transformations have the same effect on all inputs, and can therefore be considered equivalent.

How can I determine if two linear transformations are equal?

To determine if two linear transformations are equal, you can check if they have the same matrix representation. If the matrices are the same, then the transformations are equal. Another way is to check if they have the same effect on a set of basis vectors.

Can linear transformations be equal if they have different matrices?

Yes, linear transformations can be equal even if their matrices are different. This is because the matrix representation of a linear transformation depends on the basis chosen, and different bases can result in different matrices for the same transformation. As long as the effects on all inputs are the same, the transformations are considered equal.

What is the relationship between linear transformations and matrices?

Linear transformations and matrices are closely related, as every linear transformation can be represented by a matrix and every matrix represents a linear transformation. The matrix representation of a linear transformation depends on the choice of basis, and different matrices can represent the same transformation. However, the composition of linear transformations corresponds to matrix multiplication, making matrices a useful tool for understanding and working with linear transformations.

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