Preserving Vector Length: Exploring Matrix Transformations in R^2

In summary, the conversation discusses finding all matrix transformations that do not change the length of vectors in the plane. The possible transformations mentioned include rotation and using a general transform matrix with certain conditions. The conversation suggests starting with a specific vector and using matrix multiplication to find a condition for the transform matrix. However, the participants also express difficulty and suggest reflecting on the problem further.
  • #1
SNOOTCHIEBOOCHEE
145
0
Find all matrix transformations f:R^2 -----> R^2 which leave the length of vectors in the plane unchanged



Thats R as in the set of all real numbers R.


The only possible transformations i could possibly think of that would not change the length is rotation, other than that i am completley lost
 
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  • #2
There is another type which does not effect length.

I would start by looking at a general transform matrix and learning which elements effect lenght, how would you arrange it so the length remains unchanged. You will then need to do some form of proof.
 
  • #3
Just my random thoughts in trying to solve the problem: Wouldn't that be equivalent to saying t(AX) * AX = t(X) * X, where t(X) is the transpose of X?
 
  • #4
SNOOTCHIEBOOCHEE said:
The only possible transformations i could possibly think of that would not change the length is rotation, other than that i am completley lost

Try to do the following in order.

1.) Given a vector [itex]\vec{v}[/itex] in [itex]\mathbb{R}^2[/itex], write down an expression for its length.

2.) Now transform the vector by multiplying it by a 2x2 matrix [itex]A[/itex]:

[itex]\vec{v} \rightarrow \vec{v}^{\prime}=A\vec{v}[/itex].

3.) Write down an expression for the length of [itex]\vec{v}^{\prime}[/itex] in terms of [itex]\vec{v}[/itex] and [itex]A[/itex].

4.) Given that the lengths of [itex]\vec{v}[/itex] and [itex]\vec{v}^{\prime}[/itex] must be equal, deduce a condition for [itex]A^TA[/itex].

Try those steps and let us know where you get stuck.
 
  • #5
After thinking about it from all angles, reflect on the problem a little more.
 
  • #6
robphy said:
After thinking about it from all angles, reflect on the problem a little more.

I feel a collective groan would be appropriate here.
 

FAQ: Preserving Vector Length: Exploring Matrix Transformations in R^2

What are matrix transformations?

Matrix transformations are mathematical operations that involve multiplying a matrix by a vector to produce a new transformed vector. They are commonly used in computer graphics and other fields to manipulate and transform geometric shapes and objects.

How are matrix transformations represented?

Matrix transformations are typically represented as a matrix multiplied by a vector. The matrix contains the coefficients that determine the transformation, while the vector contains the coordinates of the point being transformed.

What types of matrix transformations are commonly used?

Some of the most commonly used matrix transformations include translation, rotation, scaling, and shearing. Translation moves an object in a certain direction, rotation rotates it around a fixed point, scaling changes its size, and shearing skews its shape.

How do matrix transformations affect geometric objects?

Matrix transformations can change the position, size, and orientation of geometric objects. They can also distort the shape of an object, depending on the type of transformation used.

What is the purpose of using matrix transformations?

Matrix transformations allow for efficient and accurate manipulation of geometric objects in various fields, such as computer graphics, image processing, and physics. They also provide a way to represent complex transformations in a simple and concise manner.

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