Proving Invariance of Transformations and the Linearity of a Specific Operation

In summary: I have a loose grasp on why that may be, but what's the formal proof?After another week of classes, he still hasn't addressed invariant transformations. I understand that the image is to the column space as the kernel is to the nullspace for a transformations. That is, the image is what is the output of a given transformation. Yet I still don't see how T(im(T)) = im(T). The same goes for showing that the intersection of two spaces is also T invariant. Any help would be much appreciated!There is a theorem which states that for any linear transformation there exists a subspace invariant under the transformation. However, I can't seem to find a derivation of this theorem in any
  • #1
Hallingrad
29
0
Hey guys,

I was wondering how you would go about proving that the image of a transformation T, im(T), is invariant? And following that, how would you prove T(W1 [tex]\bigcap[/tex] W2) is invariant if T(W1) and T(W2) are both invariant.

On an unrelated note, another questions asks to show that
TX = X - (P^-1 * X * P) is a linear operation, but no matter what I do, I always come up with it showing that it's in fact not a linear operation. What do you guys think?

Thanks a lot for any help ^_^.
 
Physics news on Phys.org
  • #2
Proving the image of a transformation is invariant is pretty straightforward from the definition. Where are you getting stuck?
 
  • #3
Office_Shredder said:
Proving the image of a transformation is invariant is pretty straightforward from the definition. Where are you getting stuck?

Well we haven't yet covered what an invariant transformation is, but the assignment is due before the next lecture :/. Any advice on where to start?
 
  • #4
A subspace W of a vector space V is called invariant under T if T(W) is a subset of W (so T can be defined as a function from W to W also). Invariance isn't describing the function, it's describing the subspace.
 
  • #5
Office_Shredder said:
A subspace W of a vector space V is called invariant under T if T(W) is a subset of W (so T can be defined as a function from W to W also). Invariance isn't describing the function, it's describing the subspace.

With that in mind though, how do you show that T(im(T) = im(T)? That is what we're trying to show, right? And what about the intersection of W1 and W2?
 
  • #6
You want to show that T(im(T)) is a subset of im(T). So if x is in T(im(T)) then x is in im(T). Can you see why this is true?
 
  • #7
Office_Shredder said:
You want to show that T(im(T)) is a subset of im(T). So if x is in T(im(T)) then x is in im(T). Can you see why this is true?

I have a loose grasp on why that may be, but what's the formal proof?
 
  • #8
After another week of classes, he still hasn't addressed invariant transformations. I understand that the image is to the column space as the kernel is to the nullspace for a transformations. That is, the image is what is the output of a given transformation. Yet I still don't see how T(im(T)) = im(T). The same goes for showing that the intersection of two spaces is also T invariant. Any help would be much appreciated!
 
  • #9
You don't want that T(im(T)) = im(T), you just want that it is a subset! Consider the rewording of the question: Show that any element in im(T), say y, has the property that T(y) is in im(T). Do you see why this is always true?
 

Related to Proving Invariance of Transformations and the Linearity of a Specific Operation

1. What is the concept of invariance of transformations?

The invariance of transformations is a fundamental principle in mathematics and physics that states that the underlying properties of a system remain unchanged under certain transformations. In other words, the system remains the same even after it has been transformed in some way.

2. What types of transformations are considered invariant?

The most commonly studied type of invariant transformation is the rigid body transformation, which includes translations, rotations, and reflections. Other types of transformations that are often considered invariant include scale transformations, time translations, and gauge transformations.

3. Why is the concept of invariance important in science?

Invariance plays a crucial role in scientific theories and models, as it allows us to simplify complex systems and make predictions about how they will behave under different conditions. It also helps us to identify underlying principles and relationships that remain unchanged regardless of the specific details of the system.

4. How is invariance tested or proven in scientific experiments?

Invariance can be tested through a variety of methods, depending on the specific system and transformation being studied. In some cases, mathematical proofs can be used to demonstrate invariance. In others, experiments can be designed to test the system under different transformations and observe whether the underlying properties remain unchanged.

5. What are some real-world applications of invariance of transformations?

Invariance of transformations has many practical applications in fields such as physics, engineering, and computer science. For example, invariance principles are used in the design of aircraft and other structures to ensure their stability and performance under different conditions. Invariance is also used in image and signal processing to identify patterns and features that remain unchanged under certain transformations.

Similar threads

  • Linear and Abstract Algebra
Replies
3
Views
1K
  • Linear and Abstract Algebra
Replies
3
Views
1K
  • Linear and Abstract Algebra
Replies
8
Views
1K
  • Math POTW for Graduate Students
Replies
4
Views
864
  • Linear and Abstract Algebra
Replies
27
Views
2K
  • Linear and Abstract Algebra
Replies
9
Views
2K
Replies
27
Views
1K
  • Linear and Abstract Algebra
Replies
1
Views
1K
  • Linear and Abstract Algebra
Replies
1
Views
1K
  • Linear and Abstract Algebra
Replies
1
Views
1K
Back
Top