Linear Isomorphisms: Understand & Apply

  • Context: Undergrad 
  • Thread starter Thread starter Lauren1234
  • Start date Start date
  • Tags Tags
    Linear Linear algebra
Click For Summary

Discussion Overview

The discussion revolves around understanding and applying linear isomorphisms, particularly in the context of linear transformations and their representation through matrices. Participants explore how to demonstrate that specific mappings are linear isomorphisms, including the implications of linearity, injectivity, and surjectivity. The conversation includes hints for visualizing the transformations geometrically and mathematically.

Discussion Character

  • Exploratory
  • Technical explanation
  • Homework-related
  • Mathematical reasoning

Main Points Raised

  • Some participants suggest showing that the vector ##(1,0)## maps to ##(1/2, \sqrt{3}/2)## and ##(0,1)## maps to ##(-\sqrt{3}/2, 1/2## to establish the linear isomorphism.
  • There is a proposal that the linearity and injectivity of the transformation are intuitively clear, with a rotation mapping distinct points to distinct points.
  • Some participants discuss the use of the rank-nullity theorem to establish surjectivity from injectivity or vice versa.
  • Participants express uncertainty about whether their calculations demonstrate that the matrix represents a linear transformation.
  • There is a suggestion to associate a matrix with the linear transformation by calculating how the transformation acts on a basis of the vector space.
  • One participant asks if they should combine their results to show that the transformations are equivalent, indicating a need for clarification on the relationship between their findings and the definition of linear transformations.

Areas of Agreement / Disagreement

Participants generally agree on the steps needed to demonstrate the properties of linear isomorphisms, but there is uncertainty regarding the interpretation of their results and whether they conclusively show that the matrix represents a linear transformation. Multiple viewpoints on how to approach the problem remain present.

Contextual Notes

Some participants mention the need for careful drawing of diagrams to visualize the transformations, indicating that graphical representation may be important for understanding the mappings. There is also a reliance on specific mathematical definitions and theorems that may not be fully resolved in the discussion.

Lauren1234
Messages
26
Reaction score
3
0AACBAEF-10B0-414A-A458-B796ED8028B8.jpeg

how would I go about answering the above question I need some pointers on how to start?
 
Physics news on Phys.org
Hints:

You have to show that ##(1,0)## gets mapped to ##(1/2, \sqrt{3}/2)## and ##(0,1)## gets mapped to ##(-\sqrt{3}/2, 1/2)##. Showing that it is a linear isomorphism is intuitively clear: linearity is obvious, injectivity is also obvious because two different points get rotated to two different points with the same distance between them, and a rotation in the other direction over the same angle shows that your map is surjective. Of course, if you use some theorems like rank-nullity theorem you get surjectivity from injectivity or vice versa.
 
Math_QED said:
Hints:

You have to show that ##(1,0)## gets mapped to ##(1/2, \sqrt{3}/2)## and ##(0,1)## gets mapped to ##(-\sqrt{3}/2, 1/2)##. Showing that it is a linear isomorphism is intuitively clear: linearity is obvious, injectivity is also obvious because two different points get rotated to two different points with the same distance between them, and a rotation in the other direction over the same angle shows that your map is surjective. Of course, if you use some theorems like rank-nullity theorem you get surjectivity from injectivity or vice versa.
Fab I’ll give it a go. Is there a specific way I could draw the above also?
 
Lauren1234 said:
Fab I’ll give it a go. Is there a specific way I could draw the above also?

Draw? Sure. Draw the unit circle in the ##x-y##-plane. The vector ##(1,0)## is the vector both on the unit circle and on the ##x##-axis. Now, after applying the rotation it ends up at ##\pi/3## on the unit circle (60 degrees). Which vector is that? Basic trigoniometry will help here. Similarly you do the same for ##(0,1)##.
 
Math_QED said:
Draw? Sure. Draw the unit circle in the ##x-y##-plane. The vector ##(1,0)## is the vector both on the unit circle and on the ##x##-axis. Now, after applying the rotation it ends up at ##\pi/3## on the unit circle (60 degrees). Which vector is that? Basic trigoniometry will help here. Similarly you do the same for ##(0,1)##.
Yeah it says to draw the matrix bit as a carefully drawn diagram. So basically I need to draw a circle in the plane right think I’ve got you.
 
Math_QED said:
Hints:

You have to show that ##(1,0)## gets mapped to ##(1/2, \sqrt{3}/2)## and ##(0,1)## gets mapped to ##(-\sqrt{3}/2, 1/2)##. Showing that it is a linear isomorphism is intuitively clear: linearity is obvious, injectivity is also obvious because two different points get rotated to two different points with the same distance between them, and a rotation in the other direction over the same angle shows that your map is surjective. Of course, if you use some theorems like rank-nullity theorem you get surjectivity from injectivity or vice versa.
ive done this bit but I’m not exa sure what it shows does it tell me the matrix is a linear transformation?
 
Lauren1234 said:
ive done this bit but I’m not exa sure what it shows does it tell me the matrix is a linear transformation?

Do you know how to associate a matrix to a linear transformation, relative to some fixed bases?

Suppose we have a linear transformation ##T: V \to W## and ##\{e_1, \dots, e_n\}## a basis for ##V## and ##\{f_1, \dots, f_m\}## a basis for ##W##. Then you calculate ##T(e_1)## and write it in the form ##T(e_1) = \sum_{i=1}^m a_i f_i##. The coefficients ##(a_1, \dots, a_m)## come in the first column of the matrix. Similarly you calculate ##T(e_2)## to get the second column etc. The idea here is that a linear transformation is known completely if we know what the map does to a basis, so we put this information in a matrix.

In your case ##V = W = \mathbb{R}^2## and the basis for both ##V## and ##W## is ##\{(1,0), (0,1)\}##. So, you calculate ##T(1,0) ##. What coefficients do you get when you write this as a linear combination of ##(1,0)## and ##(0,1)##? These will go in the first column.
 
Math_QED said:
Do you know how to associate a matrix to a linear transformation, relative to some fixed bases?

Suppose we have a linear transformation ##T: V \to W## and ##\{e_1, \dots, e_n\}## a basis for ##V## and ##\{f_1, \dots, f_m\}## a basis for ##W##. Then you calculate ##T(e_1)## and write it in the form ##T(e_1) = \sum_{i=1}^m a_i f_i##. The coefficients ##(a_1, \dots, a_m)## come in the first column of the matrix. Similarly you calculate ##T(e_2)## to get the second column etc. The idea here is that a linear transformation is known completely if we know what the map does to a basis, so we put this information in a matrix.

In your case ##V = W = \mathbb{R}^2## and the basis for both ##V## and ##W## is ##\{(1,0), (0,1)\}##. So, you calculate ##T(1,0) ##. What coefficients do you get when you write this as a linear combination of ##(1,0)## and ##(0,1)##? These will go in the first column.
this is what I’ve done so far. Do I but them together and show they’re the same? And that means they’re a linear transformation.
8787722A-E9A4-4FCC-B188-60891F6453D6.jpeg
 
I told you what to do: Calculate ##T(1,0)## where ##T## is the rotation in your exercise.

Next, write ##T(1,0) = a (1,0) + b(0,1) = (a,b)## with ##a,b \in \mathbb{R}##. The coefficients ##(a,b)## will be the first column of your matrix.
 

Similar threads

  • · Replies 19 ·
Replies
19
Views
4K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 23 ·
Replies
23
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
Replies
10
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 3 ·
Replies
3
Views
4K