Contraction transformation proof

In summary, the conversation discusses the process of building a matrix representation for a contraction transformation from V to V, regardless of the basis given to V. It also explores the calculation of the kernel and range of the transformation T(x1,x2,x3)=(x1,x2,x2*x3), and clarifies that the kernel subspace is (0,0,x3) and the range does not include points like (0,0,1).
  • #1
charmmy
13
0
1. Homework Statement

Q1) Show that a contraction transformation from V to V has a diagonal matrix representation regardless of the basis given to V (same basis in domain and range).

!2) T(x1,x2,x3)=(x1,x2,x2*x3) find the kernel and range T for this transformation.

2. Homework Equations
3. The Attempt at a Solution

Q1)how do we go about building a matrix representation? just arbitarily orr?? Where should I even start?

Q2) the transformation is not linear, so we can't actually find an Echloen matrix to row reduce?
 
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  • #2
You've seen the problem correctly. T isn't linear. So you can't use matrices. You'll have to think more directly about what kernel and range mean. Start with the kernel. How can (x1,x2,x2*x3)=(0,0,0)?
 
  • #3
charmmy said:

Homework Statement



Show that a contraction transformation from V to V has a diagonal matrix representation regardless of the basis given to V (same basis in domain and range).

Homework Equations


The Attempt at a Solution



how do we go about building a matrix representation? just arbitarily orr?? Where should I even start?

You posted a completely different question to begin with. I wish I had quoted it. Then you deleted that question and substituted another. PLEASE DON'T DO THAT. Can you guess how confusing this can be?
 
  • #4
You build a matrix representation by picking a basis [tex]\{v_1,\ldots,v_n\}[/tex] for V. Then a linear transformation [tex] L:V\rightarrow V[/tex] has a matrix representation [tex]L_{mn}[/tex] by decomposing [tex]L(v_m)[/tex] in terms of the basis according to

[tex] L(v_m) = \sum_n L_{mn} v_n.[/tex]

You should start with the definition of a contraction and apply that to an arbitrary basis vector.

(Dick, if I'm googling correctly, a contraction is a multiplication by a scalar a, with 0<a<1. charmmy should post the definition to verify this.)

Edit: I evidently didn't see the original version of the question...
 
  • #5
its only possible if x1 =0; x2=0 and x3=0 right? so its the trivial solution?
 
  • #6
fzero said:
You build a matrix representation by picking a basis [tex]\{v_1,\ldots,v_n\}[/tex] for V. Then a linear transformation [tex] L:V\rightarrow V[/tex] has a matrix representation [tex]L_{mn}[/tex] by decomposing [tex]L(v_m)[/tex] in terms of the basis according to

[tex] L(v_m) = \sum_n L_{mn} v_n.[/tex]

You should start with the definition of a contraction and apply that to an arbitrary basis vector.

(Dick, if I'm googling correctly, a contraction is a multiplication by a scalar a, with 0<a<1. charmmy should post the definition to verify this.)

Edit: I evidently didn't see the original version of the question...

The original question is back if you look quick. It might change at any moment.
 
  • #7
I'ms so sorry about that. I didn't realize you've answered the question before I change it. Can I post both the questions under the same post then?



1. Homework Statement


Q1) Show that a contraction transformation from V to V has a diagonal matrix representation regardless of the basis given to V (same basis in domain and range).

!2) T(x1,x2,x3)=(x1,x2,x2*x3) find the kernel and range T for this transformation.

2. Homework Equations



The Attempt at a Solution



Q1)how do we go about building a matrix representation? just arbitarily orr?? Where should I even start?

Q2) the transformation is not linear, so we can't actually find an Echloen matrix to row reduce?
 
  • #8
charmmy said:
its only possible if x1 =0; x2=0 and x3=0 right? so its the trivial solution?

Don't change the question again, ok? Post a new thread for the other one. No, (x1,x2,x2*x3)=(0,0,0) doesn't just have the trivial solution. There are others.
 
  • #9
Okay. sorry about the confusion


fzero: contraction does mean multiplication with a scalar between 0 and 1.

dick: hmm in that case, x3 would be a free variable? since x2 and x1 must be zero.
 
  • #10
charmmy said:
Okay. sorry about the confusion


fzero: contraction does mean multiplication with a scalar between 0 and 1.

dick: hmm in that case, x3 would be a free variable? since x2 and x1 must be zero.

Yes. x3 doesn't matter. So the kernel subspace is (0,0,x3). Now what about the image?
 
  • #11
the image would just be everything in R3 is that correct?
 
  • #12
charmmy said:
the image would just be everything in R3 is that correct?

It would seem so to me.
 
  • #13
Dick said:
It would seem so to me.

Ooops. I take that back. Points like (0,0,1) aren't in the range, are they?
 

1. What is a "Contraction transformation proof"?

A contraction transformation proof is a mathematical method used to show that a given function or expression can be simplified or reduced to a simpler form. It involves breaking down the function into smaller parts and then using properties of contraction transformations, such as distributivity or associativity, to simplify the expression.

2. How is a "Contraction transformation proof" different from other proof techniques?

Contraction transformation proofs specifically focus on the use of contraction transformations to simplify an expression, while other proof techniques may use different methods such as induction, contradiction, or direct proof. Additionally, contraction transformation proofs often involve breaking down the expression into smaller parts, whereas other techniques may focus on the overall structure of the expression.

3. What are some common contraction transformations used in "Contraction transformation proofs"?

Some common contraction transformations include distributivity, associativity, and commutativity. Distributivity involves breaking down an expression into smaller terms and then combining like terms. Associativity involves rearranging the terms in an expression without changing the overall value. Commutativity involves changing the order of terms in an expression without changing the overall value.

4. What are the benefits of using a "Contraction transformation proof"?

Using a contraction transformation proof can help simplify complex expressions, making them easier to understand and work with. It can also help identify patterns and relationships between different parts of an expression, leading to new insights and potential solutions.

5. How can I improve my skills in using "Contraction transformation proofs"?

Practice is key in improving your skills in using contraction transformation proofs. Start by mastering the basic contraction transformations and then move on to more complex expressions. It can also be helpful to work with a peer or instructor to get feedback and discuss different approaches to solving problems using contraction transformations.

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