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math121b:about_vectors_and_tensors [2020/02/03 20:55]
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math121b:about_vectors_and_tensors [2026/02/21 14:41] (current)
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 The whole point of doing abstract vector space, is to show that, we can do linear algebra without using the crutches of 'basis' The whole point of doing abstract vector space, is to show that, we can do linear algebra without using the crutches of 'basis'
  
- Let $V = \R^2$. Can you give a basis of linear functions on $V$? +1. Let $V = \R^2$. Can you give a basis of linear functions on $V$? 
  
- Suppose $V = \R^2$ with standard coordinates $(x,y)$ on $\R^2$. We choose a new basis $e_1 = (1,1), e_2=(0,2)$. Now, we are going to find the dual basis for $e_1, e_2$. These are two elements $h^1, h^2$ in $V^*$, or equivalently, we have two functions $h^1(x,y)$ and $h^2(x,y)$ on $\R^2$ (these superscripts $1,2$ are just labels, don't confuse them with power of a function). I will give you a hint of how to find $h^1(x,y)$. First of all, $h^1(x,y)$ is a linear function, so it is of the form $h^1(x,y) = ax+by$ for some unknown constants $a,b$. Then, we recall that the function $h^1$ evaluate on the point $e_1$ equals to $1$. Where is $e_1$? Recall $e_1=(1,1)$, so we plug in the coordinate $e_1$ as $(x,y)$ into $h^1(x,y)$, and we require $h^1(1,1)=1$. Similarly, we also require that the function $h^1$'s value on $e_2$ equal to $0$. This will help you determine $h^1$. Try on your own determine $h^2$. Draw on a piece of paper, the lines of $h^1(x,y)=-1, 0, 1$ and $h^2(x,y) = -1,0,1$. You should see a skewed a grid. +2. Suppose $V = \R^2$ with standard coordinates $(x,y)$ on $\R^2$. We choose a new basis $e_1 = (1,1), e_2=(0,2)$. Now, we are going to find the dual basis for $e_1, e_2$. These are two elements $h^1, h^2$ in $V^*$, or equivalently, we have two functions $h^1(x,y)$ and $h^2(x,y)$ on $\R^2$ (these superscripts $1,2$ are just labels, don't confuse them with power of a function). I will give you a hint of how to find $h^1(x,y)$. First of all, $h^1(x,y)$ is a linear function, so it is of the form $h^1(x,y) = ax+by$ for some unknown constants $a,b$. Then, we recall that the function $h^1$ evaluate on the point $e_1$ equals to $1$. Where is $e_1$? Recall $e_1=(1,1)$, so we plug in the coordinate $e_1$ as $(x,y)$ into $h^1(x,y)$, and we require $h^1(1,1)=1$. Similarly, we also require that the function $h^1$'s value on $e_2$ equal to $0$. This will help you determine $h^1$. Try on your own determine $h^2$. Draw on a piece of paper, the lines of $h^1(x,y)=-1, 0, 1$ and $h^2(x,y) = -1,0,1$. You should see a skewed a grid. 
  
- (Quotient vector space). Let $V$ be a vector space, $W \subset V$ be a subspace. We define a set $V / W$ as following,  
-  - two elements $v, v'$ in $V$ are called equivalent, if $v - v' \in W$. It is denoted as $v \sim v'$.  
-  - an equivalence class of $V$ is a maximal subset of $V$ where every two elements in it are equivalent.  
-    - let $v \in V$, there is exactly one equivalence class that contains $v$, and is denoted as $[v]$.  
-  - $V / W$ is the set of equivalence classes of $V$, that means, an element in $V/W$ is an equivalence class of $V$.  
  
-For example, let $V = \R^2$, and $W$ is the one-dimensional subspace defined by $x=y$, or $W = span_\R (1,1)$. Then $(2,3)$ and $(4,5)$ are in the same equivalence classes, because $(2,3)-(4,5)=(-2,-2)$ and is  in $W$.  
- 
-Show that the set $V / W$ can be equipped with a vector space structure 
  
  
math121b/about_vectors_and_tensors.1580763307.txt.gz · Last modified: 2026/02/21 14:45 (external edit)