Vector space isomorphism

In summary, we have a conversation discussing a linear mapping $\Phi$ from a real vector space to a space of real-valued functions. The main goal is to show that a restriction of $\Phi$ onto a specific vector space is a vector space isomorphism. To prove this, it is shown that the restriction is injective and surjective, using properties of polynomials and the number of roots they can have.
  • #1
mathmari
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Hey! :eek:

Let $V$ be the real vector space $\mathbb{R}[X]$ and $M \subset \mathbb{R}$ a set with $d$ elements. Let $$U_1 := \{ f \in \mathbb{R}[X] | \forall m \in M : f(m) = 0\}, \ \ U_2 := \{ f \in \mathbb{R}[X] \mid \deg(f) \leq d − 1\}$$ be two vector spaces of $V$. Let $\Phi: V\rightarrow Ab(M,\mathbb{R})$ be a linear mapping that is defined by $\Phi (f)(m):=f(m)$.

I want to show that $\Phi\mid_{U_2}:U_2\rightarrow \text{Ab}(M,\mathbb{R})$ is a vector space isomorphism.

So, we have to show that $\Phi$ is injective ans surjective.

To show that the mapping is injective, we take to elements of $U_2$, say $f,g\in U_2$.

For them it holds that $f(m)=g(m)=0$ for every $m\in M$.

Suppose that $\Phi (f)=\Phi (g)$ then it follows that $f(m)=g(m)$.

Is this correct? So, $\Phi$ is injective, right? (Wondering)

How can we show that the mapping is surjective?
 
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  • #2
Hi mathmari,

Based on context, I assume $\operatorname{Ab}(M,\Bbb R)$ is the space of real-valued functions on $M$, with addition and scalar multiplication defined pointwise. (Although, the symbol $\operatorname{Ab}$ used in such a way would indicate homomorphisms of abelian groups.)

Since $\Phi$ is a linear transformation, so is $\Phi \big|_{U_2}$. So to show $\Phi|_{U_2}$ is injective, it suffices to show $\operatorname{Ker}(\Phi\big|_{U_2}) = 0$. If $f\in \operatorname{Ker}(\Phi\big|_{U_2})$, then $f(m) = 0$ for all $m\in M$. Since $f\in U_2$, $f$ has degree less than $d$, and hence has less than $d$ roots. (Recall: A polynomial of degree $n$ over a field has no more than $n$ roots.) As $M$ has $d$ elements, we deduce $f = 0$. Hence, $\Phi|_{U_2}$ is injective.

To see that $\Phi|_{U_2}$ is surjective, let $M = \{m_1,\ldots, m_d\}$, take an element $g : M \to \Bbb R$, and define $f(x) = \sum\limits_{j = 1}^d g(m_j)\, f_j(x)$, where

$$f_j(x) = \prod_{{k=1 \atop k\neq j}}^d \frac{x-m_k}{m_j - m_k}$$

Show that $f\in U_2$ and $\Phi(f) = g$.
 

1. What is a vector space isomorphism?

A vector space isomorphism is a mathematical concept that refers to a bijective linear transformation between two vector spaces that preserves the algebraic structures of addition and scalar multiplication. In simpler terms, it is a one-to-one correspondence between two vector spaces that maintains their basic operations and properties.

2. How is a vector space isomorphism represented?

A vector space isomorphism can be represented using a linear transformation matrix, which is a rectangular array of numbers that describes the relationship between the two vector spaces. It can also be represented symbolically using function notation, such as f: V → W, where V and W are the two vector spaces.

3. What are the properties of a vector space isomorphism?

Some key properties of a vector space isomorphism include bijectivity (meaning it is both one-to-one and onto), linearity (preserving the operations of addition and scalar multiplication), and the preservation of vector space properties, such as dimension and basis. It is also important to note that isomorphisms are reversible, meaning that there is an inverse isomorphism that can be defined between the two vector spaces.

4. How is vector space isomorphism different from vector space homomorphism?

While both concepts involve linear transformations between vector spaces, the key difference is that vector space isomorphism is bijective, while vector space homomorphism may not be. In other words, isomorphisms involve a one-to-one correspondence between vector spaces, while homomorphisms may map multiple elements of one vector space to the same element in another vector space.

5. Why is vector space isomorphism important?

Vector space isomorphism is important because it allows us to understand the relationship between different vector spaces and their structures. It also helps us to identify and prove fundamental properties and theorems in linear algebra, such as the isomorphism theorems and the rank-nullity theorem. Additionally, isomorphisms can be used to simplify and solve complex problems involving vector spaces by transforming them into more familiar spaces.

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