What Does \Re2 \rightarrow \Re2 Mean in Linear Transformations?

In summary: Basically, if you can figure out what the function is that maps one set to another, you can determine if the function is one-to-one or onto. If you can't figure it out, then it might not be a one-to-one or onto function.Thanks Chiro!The notation ##T_1:\mathbb R^2\to\mathbb R^2## tells us that ##T_1## is a function with domain ##\mathbb R^2## and codomain ##\mathbb R^2##. The notation ##x\to Ax## should mean "the function that takes x to Ax". Wouldn't you denote that function by A? Hm, I guess that
  • #1
DmytriE
78
0
Hi Pf,

Here is a question regard a test review that we have. I am not looking for the answer but rather a clarification about the notation.

1. What does the following mean? T1: [itex]\Re[/itex]2 [itex]\rightarrow[/itex] [itex]\Re[/itex]2 by x [itex]\rightarrow[/itex] Ax?

2. What does it mean to go [itex]\Re[/itex]2 [itex]\rightarrow[/itex] [itex]\Re[/itex]2

Thanks.
 
Physics news on Phys.org
  • #2
DmytriE said:
Hi Pf,

Here is a question regard a test review that we have. I am not looking for the answer but rather a clarification about the notation.

1. What does the following mean? T1: [itex]\Re[/itex]2 [itex]\rightarrow[/itex] [itex]\Re[/itex]2 by x [itex]\rightarrow[/itex] Ax?

2. What does it mean to go [itex]\Re[/itex]2 [itex]\rightarrow[/itex] [itex]\Re[/itex]2

Thanks.

Hey DmytriE.

Basically the LHS of the arrow is your starting space and the RHS is your target space. In other words we are starting in R^2 (2D vector with real numbers in each element) and we are going to a 2D vector.

In terms x -> Ax, this means that we start with a vector x and then we apply the operator A to the vector x by calculating Ax using normal matrix multiplication to get a new vector (still in R^2) called x' where x' = Ax.
 
  • #3
Thanks Chiro!
 
  • #4
The technical terms for "starting space" and "target space" are "domain" and "codomain". The notation ##\mathbb R## (\mathbb R) is more common than ##\Re## (\Re).

It strikes me as a bit odd to write "##T_1:\mathbb R^2\to\mathbb R^2## by ##x\to Ax##". The notation ##T_1:\mathbb R^2\to\mathbb R^2## tells us that ##T_1## is a function with domain ##\mathbb R^2## and codomain ##\mathbb R^2##. The notation ##x\to Ax## should mean "the function that takes x to Ax". Wouldn't you denote that function by A? Hm, I guess that the most likely explanation is that A is a matrix, and the person who wrote this would like to emphasize that the linear operator T1 that corresponds to the matrix A isn't the same thing as A (even though T1 acting on x gives us the same result as A times x).

By the way, I prefer to use the \mapsto arrow in the second notation, i.e. I would write ##x\mapsto Ax## instead of ##x\to Ax##. Some people prefer to never use the mapsto arrow. That's OK too.
 
  • #5
I was trying to us the \mapsto arrow but when I clicked on it it gave me the bidirectional arrow and I did not know it's proper name so I just selected the normal arrow.

Here is another thing that confused me and my professor explained but I guess I was unable to grasp it. What is the difference between onto and one-to-one? What quantities would you look at to determine if it is one-to-one or onto (i.e. Null(A) or Col(A))? An example would help a lot.
 
  • #6
A function f:X→Y is said to be injective (or one-to-one) if for all x,y in X, f(x)=f(y) implies x=y.

A function f:X→Y is said to be surjective (or onto) if for all y in Y, there's an x in X such that f(x)=y.

You can find examples in the wikipedia articles for these terms.
 

FAQ: What Does \Re2 \rightarrow \Re2 Mean in Linear Transformations?

What is the notation used for linear transformations?

The notation used for linear transformations is a matrix representation, where the columns correspond to the basis vectors of the output space and the rows correspond to the coordinates of the input vectors.

How do you represent a linear transformation using matrix notation?

A linear transformation can be represented using a matrix by multiplying the transformation matrix with the coordinates of a vector in the input space.

What does the notation [T] represent in linear transformations?

The notation [T] represents the transformation matrix of a linear transformation, where the columns correspond to the basis vectors of the output space and the rows correspond to the coordinates of the input vectors.

How is the composition of two linear transformations represented in notation?

The composition of two linear transformations T and S is represented as T ◦ S, where the output of S is used as the input for T.

What is the difference between the notation for a linear transformation and a matrix?

The notation for a linear transformation is a matrix representation, while a matrix refers to a rectangular array of numbers. The notation for a linear transformation is used to represent the transformation itself, while a matrix is used to perform computations and operations on vectors.

Similar threads

Replies
2
Views
1K
Replies
3
Views
1K
Replies
1
Views
1K
Replies
2
Views
1K
Replies
9
Views
2K
Replies
1
Views
726
Back
Top