Is T(x,y) = (x,0) a linear transformation

In summary, the conversation discusses the determination of a linear transformation T(x,y)=(x,0) and the necessary conditions for it to hold. It is concluded that T is a linear transformation if x and y are real numbers and T(0)=0 and T(-v)=-T(v).
  • #1
sara_87
763
0

Homework Statement



I have to determine whether the following is a linear transformation

T(x,y)=(x,0)

Homework Equations





The Attempt at a Solution



again, let v=(v1, v2) and w=(w1,w2)

then, T(v+w)=T(v1+w1, v2+w2)=(v1+w1, 0)

and, T(v)+T(w)=(v1+w1, 0)
so the first condition holds.

AND:

let c be a constant:
T(cv)=T(cv1,cv2)=(cv1, 0)=c(v1,0)=cT(v)
so both conditions hold
therefore it's linear transformation
is that correct?
 
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  • #2
You haven't said what x and y are! If they are real numbers, that is that T is a function from R2 to R2, then yes, those are exactly what you need to show. (Of course, taking c= 0 in the second shows T(0)= 0 and taking c= -1 shows T(-v)= -T(v) which are required by not necessary to prove separately.)
 
  • #3
yea it isedit: nevermind listen to halls, you do need to be more precise with this kind of thing probably
 

1. What is a linear transformation?

A linear transformation is a mathematical function that maps a set of values in one space to another space in a linear fashion. This means that the resulting output is a linear combination of the input values.

2. How do you determine if a transformation is linear?

To determine if a transformation is linear, you can use the properties of linearity: additivity and homogeneity. This means that the transformation must preserve addition and scalar multiplication.

3. What does it mean for T(x,y) = (x,0) to be a linear transformation?

If T(x,y) = (x,0) is a linear transformation, it means that it preserves the x-coordinate and sets the y-coordinate to 0. This satisfies the properties of linearity, making it a valid linear transformation.

4. What are some examples of linear transformations?

Some common examples of linear transformations include rotations, reflections, and dilations. In matrix form, linear transformations can also include scaling, shearing, and projection.

5. How can linear transformations be useful in science?

Linear transformations have many applications in science, such as data analysis, image processing, and modeling physical systems. They can also be used to convert between different coordinate systems and simplify complex equations.

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