Proving Linearity of a Transformation: Where to Start?

In summary: It is true that ##f_A## is linear when ##A## is as stated in the problem, but that's not because ##f_A## is linear for all c, but because the problem is written so that when ##A## is the given matrix, ##f_A(c)## is the same function as ##f_c##. In other words, the notation is a bit weird and confusing.
  • #1
dylanhouse
42
0

Homework Statement



See attached image below.

Homework Equations





The Attempt at a Solution



I know for it to be a linear transformation it must be that: f(x)+f(y)=f(x+y) and f(tx)=tf(x) where t is a scalar. I'm not sure where to start with this proof.
 

Attachments

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  • #2
dylanhouse said:

Homework Statement



See attached image below.

Homework Equations


The Attempt at a Solution



I know for it to be a linear transformation it must be that: f(x)+f(y)=f(x+y) and f(tx)=tf(x) where t is a scalar. I'm not sure where to start with this proof.
It's not very clear from the description but the transformation could also be "desribed" this way: f : R → M2x2,
where
$$ f(c) = \begin{bmatrix} 1 & c \\ 0 & 1\end{bmatrix}$$

Start by calculating f(x), f(y), and f(x + y) and seeing if f(x) + f(y) = f(x + y). Then check that f(tx) = t*f(x).
 
  • #3
dylanhouse said:

Homework Statement



I know for it to be a linear transformation it must be that: f(x)+f(y)=f(x+y) and f(tx)=tf(x) where t is a scalar. I'm not sure where to start with this proof.

Homework Statement


Do you understand what the domain of the transformation is and its "formula" as it acts on the domain?
 
  • #4
Mark44 said:
It's not very clear from the description but the transformation could also be "desribed" this way: f : R → M2x2,
where
$$ f(c) = \begin{bmatrix} 1 & c \\ 0 & 1\end{bmatrix}$$

How do you know it isn't a transformation from ##R^2## to ##R^2##?
 
  • #5
dylanhouse said:

Homework Statement



See attached image below.

Homework Equations


The Attempt at a Solution



I know for it to be a linear transformation it must be that: f(x)+f(y)=f(x+y) and f(tx)=tf(x) where t is a scalar. I'm not sure where to start with this proof.
You didn't actually post the definition of ##f_A##. The image says that ##f_A## is "described" by that matrix, but what does that mean?
Mark44 said:
It's not very clear from the description but the transformation could also be "desribed" this way: f : R → M2x2,
where
$$ f(c) = \begin{bmatrix} 1 & c \\ 0 & 1\end{bmatrix}$$

Start by calculating f(x), f(y), and f(x + y) and seeing if f(x) + f(y) = f(x + y). Then check that f(tx) = t*f(x).
I don't think this is right. The problem said we should check that ##f_A## is linear for all c. So, there should be one function for each value of c. The function you called f is just one function. It's more likely that we should check that what you called f(c) is linear, i.e. that for all real numbers c, we have f(c)(ax+by)=af(c)x+bf(c)y for all vectors x,y and all real numbers a,b.

The OP should explain how ##f_A## is defined.
 
  • #6
I'm not sure. We only did a little on matrix transformations. Would f(x) be that matrix with x instead of c?
 
  • #7
LCKurtz said:
How do you know it isn't a transformation from ##R^2## to ##R^2##?
What I wrote is how I interpreted the OP's attachment.
Fredrik said:
You didn't actually post the definition of ##f_A##. The image says that ##f_A## is "described" by that matrix, but what does that mean?



I don't think this is right. The problem said we should check that ##f_A## is linear for all c. So, there should be one function for each value of c. The function you called f is just one function. It's more likely that we should check that what you called f(c) is linear, i.e. that for all real numbers c, we have f(c)(ax+by)=af(c)x+bf(c)y for all vectors x,y and all real numbers a,b.

The OP should explain how ##f_A## is defined.

Yes. It was unclear to me, as well.
 
  • #8
This is the original question, as stated on the handout.
 

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  • #9
OK, but the notation ##f_A## where A is a matrix, or the concept of a function being "described" by a matrix, should be explained somewhere in the book.

I would guess that you're supposed to show that regardless of the value of c, the function ##f_A:\mathbb R^2\to\mathbb R^2## defined by ##f_A(x)=Ax## for all ##x\in\mathbb R^2##, is linear. (It is however a little bit weird to ask for this, since these functions are linear for all 2×2 matrices A, not just the ones mentioned in the problem. So you should still try to find a definition in your book or in some other handout).
 
  • #10
The statement of problem 8 (which you posted here) strongly suggests that ##f_A## is to be interpreted the way I did in my previous post.
 

Related to Proving Linearity of a Transformation: Where to Start?

1. What is a linear transformation?

A linear transformation is a mathematical operation that maps one vector space to another in a way that preserves the structure of the original space. This means that the transformation must satisfy two properties: scaling and addition.

2. How do you prove that a transformation is linear?

To prove that a transformation is linear, you must show that it satisfies the two properties of linear transformations: scaling and addition. This can be done by using the definition of a linear transformation and performing the necessary calculations.

3. What is the importance of proving a linear transformation?

Proving a linear transformation is important because it ensures that the transformation is valid and can be used in further mathematical calculations. It also helps to understand the relationship between different vector spaces and how they can be transformed.

4. Can a linear transformation be represented by a matrix?

Yes, a linear transformation can be represented by a matrix. This is because a linear transformation can be seen as a mapping of vectors to different vectors, which can be represented by a matrix multiplication.

5. How do you prove that two linear transformations are equivalent?

To prove that two linear transformations are equivalent, you must show that they produce the same result for all input vectors. This can be done by comparing the matrices representing each transformation, or by using the definition of linear transformations to perform calculations.

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