Find out if it's linear transformation

In summary: The two given vectors are not linearly independent, so the linear transformation does not exist.In summary, for the linear transformation ##g : \mathbb{R}^2 \rightarrow \mathbb{R}^2## to exist, it must satisfy the conditions ##g(\vec v_1 + \vec v_2) = g(\vec v_1) + g(\vec v_2)## and ##g(\alpha \vec v) = \alpha g(\vec v)## for any vectors in ##\mathbb{R}^2## and any scalar ##\alpha##. However, in this case, the two given vectors, (2, -3) and (-1/2,
  • #1
Kernul
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Homework Statement


Does a linear transformation ##g : \mathbb{R}^2 \rightarrow \mathbb{R}^2## so that ##g((2, -3)) = (5, -4)## and ##g((-\frac{1}{2}, \frac{3}{4})) = (0, 2)## exist?

Homework Equations

The Attempt at a Solution


For a linear transformation to exist we need to know if those two satisfy the following conditions:
##g(\vec v_1 + \vec v_2) = g(\vec v_1) + g(\vec v_2)## for any ##\vec v_1, \vec v_2## in ##\mathbb{R}^2##
##g(\alpha \vec v) = \alpha g(\vec v)## for any scalar ##\alpha##
So I thought I should do like this:
I sum the two vectors ##(2, -3)## and ##(-\frac{1}{2}, \frac{3}{4})## like this ##g((2, -3) + (-\frac{1}{2}, \frac{3}{4}))## and put it equal to the sum of ##(5, -4)## and ##(0, 2)##. I will then have something like this:
##g((2, -3) + (-\frac{1}{2}, \frac{3}{4})) = (5, -4) + (0, 2)##
##g((\frac{3}{2}, -\frac{9}{4})) = (5, -2)##
But at this point I actually don't know if it really exist or not. Am I missing something?
 
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  • #2
Kernul said:

Homework Statement


Does a linear transformation ##g : \mathbb{R}^2 \rightarrow \mathbb{R}^2## so that ##g((2, -3)) = (5, -4)## and ##g((-\frac{1}{2}, \frac{3}{4})) = (0, 2)## exist?

Am I missing something?

Do you notice anything about the two vectors being acted on by ##g##?
 
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  • #3
PeroK said:
Do you notice anything about the two vectors being acted on by ##g##?
Oh! If I multiply by ##-4## the second vector acted on by ##g##, I'll get the first vector! But I have to multiply the vector that is is equal to by ##-4## too. And since ##(0, -8)## is not equal to ##(5, -4)## means that the linear transformation doesn't exist, right?
 
  • #4
Kernul said:
Oh! If I multiply by ##-4## the second vector acted on by ##g##, I'll get the first vector! But I have to multiply the vector that is is equal to by ##-4## too. And since ##(0, -8)## is not equal to ##(5, -4)## means that the linear transformation doesn't exist, right?

Exactly.
 
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1. What is a linear transformation?

A linear transformation is a function that maps vectors from one vector space to another, while preserving the operations of vector addition and scalar multiplication. In simpler terms, it is a function that takes in vectors as inputs and outputs another vector in a way that maintains the direction and scaling of the original vector.

2. How can I determine if a transformation is linear?

To determine if a transformation is linear, you can check if it satisfies two properties: the preservation of vector addition and scalar multiplication. This means that for any two vectors u and v, and any scalar c, the transformation T must satisfy T(u+v) = T(u) + T(v) and T(cu) = cT(u). If both of these conditions are met, then the transformation is linear.

3. What are some examples of linear transformations?

Some common examples of linear transformations include translations, rotations, reflections, and dilations. Other examples can include matrix transformations, such as scaling or shearing, and polynomial functions.

4. Can a non-linear function be considered a linear transformation?

No, a non-linear function cannot be considered a linear transformation because it does not satisfy the properties of preservation of vector addition and scalar multiplication. Non-linear functions often involve operations such as exponentiation or logarithms, which do not maintain the direction and scaling of vectors.

5. Why is it important to determine if a transformation is linear?

Determining if a transformation is linear is important because it allows us to understand how the transformation affects vectors and the relationships between them. It also helps in solving mathematical problems and making predictions in fields such as physics, engineering, and statistics. Additionally, linear transformations have many useful properties and can be easily represented and manipulated using matrices.

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