Question about linear transformations

In summary: After answering these questions, do you have any thoughts on it?In summary, the author is asking about a linear map and how it affects the area. They have fixed a basis and written the linear transformation in a matrix form. They diagonalized the matrix and found that the area after ##n## applications of the map is limited by an ellipse. They are trying to find an answer to the question of how many points are in the region bounded by the ellipse and they are looking for help from the reader.
  • #1
ythamsten
16
0

Homework Statement


Hey PF, I'm here again asking about linear transformations, ha ha.
Let C={(x,y) [itex]\in[/itex] [itex]\mathbb R[/itex]2 | x²+y²≤1} a circle of radius 1 and consider the linear transform
T:[itex]\mathbb R[/itex]2→[itex]\mathbb R[/itex]2
(x,y) [itex]\mapsto[/itex] ([itex]\frac{5x+3y}{4}[/itex],[itex]\frac{3x+5y}{4}[/itex])​
Find all values of a natural n for which Tn(C), the image of C after n applications of T, contains at least 2013 points (a,b) with coordinates a, b [itex]\in[/itex] [itex]\mathbb Z[/itex].

Homework Equations


N/A


The Attempt at a Solution


At first I've fixed for both input and output basis for the map ε = {e1,e2} (i.e. the canonic basis) writing the linear transformation in a matrix form:
[tex]\begin{pmatrix}
T\end{pmatrix}^{ε}_{ε}\begin{pmatrix}
x\\
y
\end{pmatrix}_{ε}
=\begin{pmatrix}
\frac{5}{4} & \frac{3}{4}\\
\frac{3}{4} & \frac{5}{4}
\end{pmatrix}\begin{pmatrix}
x\\
y
\end{pmatrix}_ε[/tex]
Then, knowing I'm going to be applying the linear transformation n times, I thought would be a wise choice to diagonalize it, taking advantage of it's nice form to do so:
[tex]\begin{pmatrix}
T\end{pmatrix}^{ε}_{ε} = -\frac{1}{2}\begin{pmatrix}
1 & 1\\
1 & -1
\end{pmatrix}\begin{pmatrix}
2 & 0\\
0 & \frac{1}{2}
\end{pmatrix}\begin{pmatrix}
-1 & -1\\
-1 & 1
\end{pmatrix}[/tex]
But right now, I'm having a little bit of trouble to figure out how to count the number of points on the maps that has both coordinates belonging to [itex]\mathbb Z[/itex]. Hope for some help, thanks in advance guys.
 
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  • #2
I will respond, but I am not sure how much help I can offer. I have two questions, at least.

1. What does the image of a circle under a linear map look like?

2. We have spoken before about how the the determinant of the matrix associated with a linear map will tell you how area scales. So what is then the area of the transformed region after ##n## applications of the mapping?

After answering these questions, do you have any thoughts on it?
 
  • #3
Well, I can see that after you apply the transformation on the circle, we expand vectors in the (1,1) by a factor of 2, and contract the ones in the (1,-1) direction by a factor of two either. Then, the image of the circle after applying T n times is limited by an ellipse centered at the origin, with semi-axis sized 2^n, in the (1,1) direction, and 1/(2^n), in the (1,-1) direction.
Since det(T)=1, applying the transformation doesn't actually change the value of the area.
My thoughts on it would be to count only the (c,c); c [itex]\in[/itex] [itex]\mathbb Z[/itex], since I'm sure that the number of those kind of points is growing with each time I apply T in the region C. Is this a good way to go?
 
  • #4
Right. It would seem to me as well that as ##n## grows larger the image looks more and more like the line ##y=x##.

Maybe you can use your diagonalization to determine for which ##n## we reach points like ##(1000,1000)##. You have ##T^n \mathbf{x} = P^{-1}D^nP \mathbf{x}##, right?

Do you have access to an answer to the question?
 
  • #5
Hm, I'm going to try that indeed... I guess the right answer would be n≥11. I think I would be able to find somewhere an answer model, since it was a question in a Math Olympiad. If you are interested let me now.
 

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another in a way that preserves the structure of the original space. In other words, it transforms a set of vectors into another set of vectors while maintaining their relative positions and proportions.

2. What are the key properties of linear transformations?

Linear transformations have two key properties: additivity and homogeneity. Additivity means that the transformation of the sum of two vectors is equal to the sum of their individual transformations. Homogeneity means that scaling a vector and then transforming it is equivalent to transforming the original vector and then scaling the result.

3. How are linear transformations represented?

Linear transformations can be represented by matrices. Each column of the matrix represents the transformation of a basis vector in the original space. The resulting vector after transformation is then found by multiplying the matrix by the original vector.

4. What is the difference between a linear transformation and a non-linear transformation?

A linear transformation preserves the structure and properties of the original space, while a non-linear transformation does not. This means that a linear transformation will always result in a straight line or plane, while a non-linear transformation can result in curved or distorted shapes.

5. What are some real-world applications of linear transformations?

Linear transformations have many applications in fields such as physics, engineering, and computer graphics. They are used to model and analyze systems that exhibit linear relationships, such as electrical circuits and motion in physics. In computer graphics, linear transformations are used to rotate, scale, and translate objects in 3D space.

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