Show that T preserves scalar multiplication - Linear Transformations

For \lambda= 0, T(\lambda x)= T(0, 0)= 0= \lambda T(x). For \lambda\ne 0, T(\lambda x)= T(\lambda x_1, \lambda x_2)= \frac{(\lambda x_1)^3}{(\lambda x_2)^2}= \frac{\lambda^3 x_1^3}{\lambda^2 x_2^2}= \lambda\frac{(x_1)^3}{(x_2)^2}= \lambda T(x).
  • #1
NewtonianAlch
453
0

Homework Statement



Let T:ℝ[itex]^{2}[/itex]→ℝ be defined by
T[tex]\left(\begin{array}{c} x_{1} \\x_{2}\end{array}\right)[/tex] = (0 if x[itex]_{2}[/itex] = 0. [itex]\frac{x^{3}_{1}}{x^{2}_{2}}[/itex] otherwise.)

Show that T preserves scalar multiplication, i.e T(λx) = λT(x) for all λ [itex]\in[/itex] ℝ and all x [itex]\in[/itex] ℝ[itex]^{2}[/itex]

The Attempt at a Solution



T(λx) = T[tex]\left(\begin{array}{c} (λx_{1}) \\(λx_{2})\end{array}\right)[/tex] = (λ0 = 0 if x[itex]_{2}[/itex] = 0, or [itex]\frac{(λx_{1})^{3}}{(λx_{2})^{2}}[/itex])
= λT[tex]\left(\begin{array}{c} x_{1} \\x_{2}\end{array}\right)[/tex] = λ0 = 0 if x[itex]_{2}[/itex] = 0, or
λ*[tex]\left(\begin{array}{c} (x_{1})^{3} \\(x_{2})^{2}\end{array}\right)[/tex]

Is that a correct proof?

It's a bit hard to read because whenever I try to put a vector, it puts it into a new line.
 
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  • #2
It's putting new lines wherever you try to put a vector because you are putting "bits and pieces" inside [ tex ] tags. Don't do that. Put entire equations inside [ tex ] tags.

Also do "[itex]x_2= 0[/itex]" and "[itex]x_2\ne 0[/itex]" separately. You have "[itex]x_2= 0[/itex]" in two different places which makes it hard to read.

If [itex]x_2= 0[/itex], then [itex]\lambda x_2= 0[/itex] for any [itex]\lambda[/itex] so [itex]T(\lambda x)= 0= \lambda T(x)[/itex].

If [itex]x_2\ne 0[/itex], then [itex]\lambda x_2\ne 0[/itex] for any [itex]\lambda[/itex] except [itex]\lambda= 0[/itex] so you should do two separate cases, [itex]\lambda= 0[/itex] and [itex]\lambda\ne 0[/itex], here.
 

Related to Show that T preserves scalar multiplication - Linear Transformations

1. What does it mean for T to preserve scalar multiplication?

Preserving scalar multiplication means that when a scalar (a number) is multiplied by a vector and then transformed by T, the result is the same as transforming the original vector by T and then multiplying it by the same scalar.

2. How can I show that T preserves scalar multiplication?

To show that T preserves scalar multiplication, you can use a mathematical proof. This involves taking a scalar k and a vector v, and showing that T(kv) = kT(v) for all values of k and v. Alternatively, you can also use specific examples to demonstrate the property.

3. Why is preserving scalar multiplication important for linear transformations?

Preserving scalar multiplication is important for linear transformations because it ensures that the transformation maintains the linear property of scaling. This is crucial for applications in physics, engineering, and other fields where scaling is a fundamental concept.

4. What are some examples of linear transformations that preserve scalar multiplication?

Some examples of linear transformations that preserve scalar multiplication include rotations, reflections, and dilations. These transformations maintain the scaling property, meaning that the distance between any two points on the original object is the same as the distance between the corresponding points on the transformed object.

5. How does preserving scalar multiplication relate to the concept of linearity?

Preserving scalar multiplication is one of the key properties of linearity. Linearity refers to the property of a function or transformation to maintain the operations of addition and scalar multiplication. Preserving scalar multiplication ensures that the transformation remains linear, as it maintains the property of scaling.

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