Give a linear map that satisfies given properties

Click For Summary

Discussion Overview

The discussion revolves around finding a linear map $\phi:\mathbb{R}^3\rightarrow \mathbb{R}^2$ that satisfies specific properties related to given vectors in $\mathbb{R}^3$. Participants explore the implications of linear independence and dependence of the vectors involved, as well as the conditions under which such a linear map can exist.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant asserts that the vectors $v_1, v_2, w$ are linearly independent and proposes a method to express an arbitrary vector in $\mathbb{R}^3$ as a linear combination of these vectors.
  • Another participant suggests a straightforward approach to find the matrix representation of the linear map $\phi$ using the relationship between the vectors and their images under $\phi$.
  • A third participant reiterates the straightforward method and expresses appreciation for the clarification.
  • A different participant presents an alternative method by setting up a matrix representation of the linear map and deriving equations based on the mappings of the specified vectors to their images.
  • This participant derives a set of equations from the mappings and solves them to find the matrix $A$ representing the linear map.

Areas of Agreement / Disagreement

While some participants agree on the correctness of the initial approach, there are multiple methods proposed for finding the linear map, indicating that no consensus exists on a single method or conclusion.

Contextual Notes

The discussion includes various assumptions about linear independence and dependence of the vectors, as well as the implications of these properties on the existence of the linear map. The mathematical steps involve solving a system of equations, which may depend on the interpretations of the mappings.

mathmari
Gold Member
MHB
Messages
4,984
Reaction score
7
Hey! :o

Let $v_1:\begin{pmatrix}1 \\ 1\\ 1\end{pmatrix}, \ \ v_2:\begin{pmatrix}1 \\ 0\\ 1\end{pmatrix}\in \mathbb{R}^3$.

  1. Let $w=\begin{pmatrix}1 \\ 0 \\2\end{pmatrix}\in \mathbb{R}^3$. If possible, give a linear map $\phi:\mathbb{R}^3\rightarrow \mathbb{R}^2$ such that $\phi (v_1)=\begin{pmatrix}1 \\ 0\end{pmatrix}, \ \ \phi (v_2)=\begin{pmatrix}0 \\ 1\end{pmatrix}, \ \ \phi (w)=\begin{pmatrix}0 \\ 0\end{pmatrix}$.
  2. Let $w'=\begin{pmatrix}0 \\ 1 \\0\end{pmatrix}\in \mathbb{R}^3$. If possible, give a linear map $\phi:\mathbb{R}^3\rightarrow \mathbb{R}^2$ such that $\phi (v_1)=\begin{pmatrix}1 \\ 0\end{pmatrix}, \ \ \phi (v_2)=\begin{pmatrix}0 \\ 1\end{pmatrix}, \ \ \phi (w')=\begin{pmatrix}0 \\ 0\end{pmatrix}$.
I have done the following:

  1. The three vectors $v_1,v_2, w$ are linearly independent and so they form a basis of $\mathbb{R}^3$.

    We consider an arbitrary vector in $\mathbb{R}^3$ and we write it as a linear combination of the vectors of the basis.

    \begin{equation*}\begin{pmatrix}x_1 \\ x_2\\ x_3\end{pmatrix}=c_1\begin{pmatrix}1 \\ 1\\ 1\end{pmatrix}+c_2\begin{pmatrix}1 \\ 0\\ 1\end{pmatrix}+c_3\begin{pmatrix}1 \\ 0 \\2\end{pmatrix}=\begin{pmatrix}1 & 1 & 1\\ 1 & 0 & 0 \\ 1 & 1 & 2\end{pmatrix}\begin{pmatrix}c_1\\ c_2 \\ c_3\end{pmatrix}\end{equation*}

    We multiply by the inverse matrix and we get
    \begin{equation*}\begin{pmatrix}c_1\\ c_2 \\ c_3\end{pmatrix}=P^{-1}\begin{pmatrix}x_1 \\ x_2\\ x_3\end{pmatrix}=\begin{pmatrix}0 & 1 & 0\\ 2 & -1 & -1 \\ -1 & 0 & 1\end{pmatrix}\begin{pmatrix}x_1 \\ x_2\\ x_3\end{pmatrix}=\begin{pmatrix}x_2 \\ 2x_1-x_2-x_3\\ -x_1+x_3\end{pmatrix}\end{equation*}

    So
    \begin{equation*}\begin{pmatrix}x_1 \\ x_2\\ x_3\end{pmatrix}=x_2\begin{pmatrix}1 \\ 1\\ 1\end{pmatrix}+(2x_1-x_2-x_3)\begin{pmatrix}1 \\ 0\\ 1\end{pmatrix}+( -x_1+x_3)\begin{pmatrix}1 \\ 0 \\2\end{pmatrix}\end{equation*}

    We calculate $\phi \begin{pmatrix}x_1 \\ x_2\\ x_3\end{pmatrix}$ using the linearity of $\phi$:
    \begin{align*}\phi \begin{pmatrix}x_1 \\ x_2\\ x_3\end{pmatrix}&=\phi \left (x_2\begin{pmatrix}1 \\ 1\\ 1\end{pmatrix}+(2x_1-x_2-x_3)\begin{pmatrix}1 \\ 0\\ 1\end{pmatrix}+( -x_1+x_3)\begin{pmatrix}1 \\ 0 \\2\end{pmatrix}\right )\\ & =x_2\cdot \phi \begin{pmatrix}1 \\ 1\\ 1\end{pmatrix}+(2x_1-x_2-x_3)\cdot \phi \begin{pmatrix}1 \\ 0\\ 1\end{pmatrix}+( -x_1+x_3)\cdot \phi \begin{pmatrix}1 \\ 0 \\2\end{pmatrix}\\ & =x_2 \begin{pmatrix}1 \\ 0\end{pmatrix}+(2x_1-x_2-x_3) \begin{pmatrix}0\\ 1\end{pmatrix}+( -x_1+x_3) \begin{pmatrix}0 \\ 0 \end{pmatrix}\\ & = \begin{pmatrix}x_2 \\ 2x_1-x_2-x_3 \end{pmatrix}\end{align*}
  2. The vectors $v_1, v_2, w'$ are linearly dependent, since \begin{equation*}\begin{pmatrix}0 \\ 1\\ 0\end{pmatrix}=\begin{pmatrix}1 \\ 1\\ 1\end{pmatrix}-\begin{pmatrix}1 \\ 0\\ 1\end{pmatrix}\Rightarrow w'=v_1-v_2\end{equation*}

    We apply $\phi$ at this equation and we get: \begin{equation*}\phi (w')=\phi (v_1-v_2)=\phi (v_1)-\phi (v_2)\Rightarrow \begin{pmatrix}0 \\ 0\end{pmatrix}=\begin{pmatrix}1 \\ 0\end{pmatrix}-\begin{pmatrix}0 \\ 1\end{pmatrix}\Rightarrow \begin{pmatrix}0 \\ 0\end{pmatrix}=\begin{pmatrix}1 \\ -1\end{pmatrix}\end{equation*}

    Therefore there is no linear map $\phi:\mathbb{R}^3\rightarrow \mathbb{R}^2$ such that$\phi (v_1)=\begin{pmatrix}1 \\ 0\end{pmatrix}$, $\phi (v_2)=\begin{pmatrix}0 \\ 1\end{pmatrix}$ und $\phi (w')=\begin{pmatrix}0 \\ 0\end{pmatrix}$.
Is everything correct? (Wondering)
 
Last edited by a moderator:
Physics news on Phys.org
Hey mathmari!

Looks correct to me. (Nod)

Btw, here is how we can do 1. in a more straight forward fashion.
Let $\phi(x)=Ax$, then:
$$A\begin{pmatrix}v_1&v_2&w\end{pmatrix}=\begin{pmatrix}\phi(v_1)&\phi(v_2)&\phi(w)\end{pmatrix}
\implies A\begin{pmatrix}1&1&1\\1&0&0\\1&1&2\end{pmatrix}=\begin{pmatrix}1&0&0\\0&1&0\end{pmatrix}
\implies A=\begin{pmatrix}1&1&1\\1&0&0\\1&1&2\end{pmatrix}^{-1}\begin{pmatrix}1&0&0\\0&1&0\end{pmatrix}$$
(Nerd)
 
Klaas van Aarsen said:
Looks correct to me. (Nod)

Btw, here is how we can do 1. in a more straight forward fashion.
Let $\phi(x)=Ax$, then:
$$A\begin{pmatrix}v_1&v_2&w\end{pmatrix}=\begin{pmatrix}\phi(v_1)&\phi(v_2)&\phi(w)\end{pmatrix}
\implies A\begin{pmatrix}1&1&1\\1&0&0\\1&1&2\end{pmatrix}=\begin{pmatrix}1&0&0\\0&1&0\end{pmatrix}
\implies A=\begin{pmatrix}1&1&1\\1&0&0\\1&1&2\end{pmatrix}^{-1}\begin{pmatrix}1&0&0\\0&1&0\end{pmatrix}$$
(Nerd)

Ahh ok! Thanks a lot! (Star)
 
An alternative method: Since A maps R3 to R2 it can be represented by a matrix with three columns and two rows. Write it as
$A= \begin{pmatrix}a & b & c \\ d & e & f\end{pmatrix}$
A maps $\begin{pmatrix}1 \\ 1 \\ 1\end{pmatrix}$ to $\begin{pmatrix} 1 \\ 0 \end{pmatrix}$ so $
\begin{pmatrix}a & b & c \\ d & e & f\end{pmatrix}
\begin{pmatrix}1 \\ 1 \\ 1\end{pmatrix}= \begin{pmatrix}a+ b+ c \\ d+ e+ f\end{pmatrix}= \begin{pmatrix}1 \\ 0 \end{pmatrix}
$
so we have the equations a+ b+ c= 1 and d+ e+ f= 0.

A maps $\begin{pmatrix}1 \\ 0 \\ 1\end{pmatrix}$ to $\begin{pmatrix} 0 \\ 1 \end{pmatrix}$ so $\begin{pmatrix}a & b & c \\ d & e & f\end{pmatrix}
\begin{pmatrix}1 \\ 0 \\ 1\end{pmatrix}= \begin{pmatrix}a+ c \\ d+ f\end{pmatrix}= \begin{pmatrix}0 \\ 1 \end{pmatrix}
$
so we have the equations a+ c= 0 and d+ f= 1.

A maps $\begin{pmatrix}1 \\ 0 \\ 2\end{pmatrix}$ to $\begin{pmatrix} 0 \\ 0 \end{pmatrix}$ so $\begin{pmatrix}a & b & c \\ d & e & f\end{pmatrix}
\begin{pmatrix}1 \\ 0 \\ 2\end{pmatrix}= \begin{pmatrix}a+ 2c \\ d+ 2f\end{pmatrix}= \begin{pmatrix}0 \\ 0 \end{pmatrix}
$
so we have the equations a+ 2c= 0 and d+ 2f= 0.

We have six equations, a+ b+ c= 1, d+ e+ f= 0, a+ c= 0, d+ f= 1, a+ 2c= 0, and d+ 2f= 0, to solve for a, b, c, d, e, and f.


From a+ c= 0 and a+ 2c= 0, c= 0. From d+ f= 1 and d+ 2f= 0, f= -1. Then a+ 0= 0 so a= 0 and d- 1= 1 so d= 2. a+ b+ c= 0+ b+ 0= 1 so b= 1. d+ e+ f= 2+ e- 1= 0 so e= -1.
$A= \begin{pmatrix}0 & 1 & 0 \\ 2 & -1 & -1 \end{pmatrix}$.


 

Similar threads

  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 2 ·
Replies
2
Views
3K
  • · Replies 2 ·
Replies
2
Views
1K
  • · Replies 3 ·
Replies
3
Views
2K
Replies
7
Views
2K
  • · Replies 34 ·
2
Replies
34
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 11 ·
Replies
11
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K