Kernel and Range of a Linear Mapping

In summary, the linear mapping T from P^{R} to P^{R}_{2} can be defined as T(p(x)) = p(2) + p(1)x + p(0)x^{2}. The kernel of this mapping is the set of all vectors that are mapped to 0, which in this case is when p(2)= p(1)= p(0)= 0. The range of this mapping is the entire set P^{R}_{2}, as the kernel only contains the zero vector and the range must contain everything else.
  • #1
Smazmbazm
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0

Homework Statement



Find the kernel and range of the following linear mapping.

b) The mapping T from [itex]P^{R} to P^{R}_{2}[/itex] defined by

[itex]T(p(x)) = p(2) + p(1)x + p(0)x^{2}[/itex]

The Attempt at a Solution



I'm not sure how to go about this one. Normally I would use the formula T(x) = A * v but in this case I don't know how to find A or v. Would be great if someone could point me in the right direction.

Thanks in advanced.
 
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  • #2
I assume you know that the kernel is the set mapped to 0. T(p(x))= 0 (for all x) if and only if p(2)= p(1)= p(0)= 0.

And the range is the entire set PR2. Do you see why?
 
  • #3
Yes I know that the kernel is the set that is mapped to 0. I think I'm just having trouble with understanding what [itex]T(p(x)) = p(2) + p(1)x + p(0)x^{2}[/itex] actual means. It's a bit too general for me. What is [itex]p(x)[/itex]? Is that saying that the power representation for [itex]p(x)[/itex] is [itex]p(2) + p(1)x + p(0)x^{2} [/itex]? Or the mapping of the power series [itex]p(x)[/itex] from [itex]P^{R}[/itex] to [itex]P^{R}_{2}[/itex] results in [itex]p(2) + p(1)x + p(0)x{2}[/itex]

I think I understand why the range is the entire set [itex]P^{R}_{2}[/itex], because if the kernel only contains the zero vector then the range must contain everything else?
 

Related to Kernel and Range of a Linear Mapping

1. What is the definition of a linear mapping?

A linear mapping, also known as a linear transformation, is a mathematical function that maps one vector space to another while preserving the basic structure of the space. This means that the transformation follows certain rules, such as preserving addition and scalar multiplication.

2. What is the kernel of a linear mapping?

The kernel of a linear mapping is the set of all vectors in the domain that get mapped to the zero vector in the codomain. In other words, it is the set of all inputs that result in an output of zero.

3. How is the kernel related to the null space?

The kernel of a linear mapping is equivalent to the null space of its associated matrix. This means that the vectors in the kernel are the same as the vectors in the null space of the matrix representing the linear transformation.

4. What is the range of a linear mapping?

The range of a linear mapping is the set of all possible outputs that can be obtained from the inputs in the domain. In other words, it is the set of all vectors that can be reached by applying the linear transformation to the input vectors.

5. Can the kernel and range of a linear mapping be empty sets?

Yes, it is possible for the kernel and range of a linear mapping to be empty sets. This can happen if the linear transformation maps all vectors in the domain to the zero vector, resulting in an empty kernel, or if there are no outputs that can be obtained from the inputs, resulting in an empty range.

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