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Every n-dimensional Real Vector Space is Isomorphic to R^n 📂Linear Algebra

Every n-dimensional Real Vector Space is Isomorphic to R^n

Definition1

Let VV and WW be called a vector space. If there exists an invertible (bijective) linear transformation T:VWT : V \to W, then VV and WW are said to be isomorphic. TT is called an isomorphism.

Theorem

Every nn-dimentional real vector space is isomorphic to Rn\mathbb{R}^{n}.

Explanation

Another way to express the theorem is as follows.

“A R\mathbb{R}-vector space VV being isomorphic to Rn\mathbb{R}^{n}” is equivalent to “being dimV=n\dim{V}=n”.

Proof2

Let VV be a nn-dimensional real vector space. Then, the proof is completed by showing the existence of a one-to-one and onto linear transformation TT that satisfies the following.

T:VRn T : V \to \mathbb{R}^{n}


Let’s call S={v1,v2,,vn}S = \left\{ \mathbf{v}_{1}, \mathbf{v}_{2}, \dots, \mathbf{v}_{n} \right\} a basis of VV. Then, for every vV\mathbf{v} \in V, there exists a unique linear combination of bases as follows.

v=k1v1+k2v2++knvn,kiR \mathbf{v} = k_{1}\mathbf{v}_{1} + k_{2}\mathbf{v}_{2} + \cdots + k_{n}\mathbf{v}_{n},\quad k_{i}\in \mathbb{R}

Now, define the transformation TT as follows.

T(v)=(k1,k2,,kn) T(\mathbf{v}) = (k_{1}, k_{2}, \dots, k_{n})

  • Part 1. TT is linear

    Let’s say v,uV\mathbf{v}, \mathbf{u} \in V is expressed as follows.

    v=k1v1+k2v2++knvnandu=d1v1+d2v2++dnvn \begin{equation} \mathbf{v}=k_{1}\mathbf{v}_{1} + k_{2}\mathbf{v}_{2} + \cdots + k_{n}\mathbf{v}_{n} \quad \text{and} \quad \mathbf{u}=d_{1}\mathbf{v}_{1} + d_{2}\mathbf{v}_{2} + \cdots + d_{n}\mathbf{v}_{n} \end{equation}

    And let’s call it cRc\in \mathbb{R}. Then, by the following, TT is linear.

    T(v+cu)=T((k1+cd1)v1+(k2+cd2)v2++(kn+cdn)vn)=(k1+cd1,k2+cd2,,kn+cdn)=(k1,k2,,kn)+c(d1,d2,,dn)=T(v)+cT(u) \begin{align*} T(\mathbf{v} + c\mathbf{u}) &= T\left( (k_{1}+ cd_{1})\mathbf{v}_{1} + (k_{2}+cd_{2})\mathbf{v}_{2} + \cdots + (k_{n}+cd_{n})\mathbf{v}_{n} \right) \\ &= \left( k_{1}+ cd_{1}, k_{2}+cd_{2}, \dots, k_{n}+cd_{n}\right) \\ &= \left( k_{1}, k_{2}, \dots, k_{n}\right) + c\left(d_{1}, d_{2}, \dots, d_{n}\right) \\ &= T(\mathbf{v}) + cT(\mathbf{u}) \end{align*}

  • Part 2. TT is one-to-one.

    If v,u\mathbf{v}, \mathbf{u} satisfies (1)(1), and let’s call it vu\mathbf{v} \ne \mathbf{u}. Then, for at least one ii, kidik_{i}\ne d_{i} must hold. Therefore,

    (k1,k2,,kn)=T(v)T(u)=(d1,d2,,dn) \left( k_{1}, k_{2}, \dots, k_{n}\right) = T(\mathbf{v}) \ne T(\mathbf{u}) = \left(d_{1}, d_{2}, \dots, d_{n}\right)

  • Part 3. TT is onto

    Let’s call it x=(x1,x2,,xn)Rn\mathbf{x} = (x_{1}, x_{2}, \dots, x_{n})\in \mathbb{R}^{n}. Then, since VV is the set of all linear combinations of vi\mathbf{v}_{i}s, there exists a vV\mathbf{v} \in V that satisfies the following.

    v=x1v1+x2v2++xnvn \mathbf{v} = x_{1}\mathbf{v}_{1} + x_{2}\mathbf{v}_{2} + \cdots + x_{n}\mathbf{v}_{n}

    Therefore, every TT is onto.

See Also


  1. Stephen H. Friedberg, Linear Algebra (4th Edition, 2002), p102 ↩︎

  2. Howard Anton, Elementary Linear Algebra: Aplications Version (12th Edition, 2019), p471-473 ↩︎