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Section 2.5 Subspace of a vector space

We define subspace of a vector space in this section.

Definition 2.5.1.

Let \(V\) be a vector space over a field \(F\text{.}\) A (nonempty) subset \(W\) of \(V\) is said to be a subspace of \(V\) if \(W\) is a vector space over \(F\) on its own right with operations of vector addition and scalar multiplication on \(V\text{.}\)

Remark 2.5.2.

A subspace \(W\) of \(V\) is written as \(W\leq V\text{,}\) and if it is a proper subspace (i.e., \(W\leq V\) and \(W\neq V\)) then it is written as \(W< V\text{.}\)
We give following criterion to check whether a given nonempty subset of a vector space is a subspace or not.
For any vector space \(V\) over a field \(F\text{,}\) \(V\) and \(\{0\}\) are subspaces. The \(\{0\}\) is called the trivial subspace.
Consider an \(n\)-dimensional vector space \(F^n\) over a field \(F\) (refer to Example 2.2.2). Let \(e_i=(0,0,\ldots,0,1,0,\ldots,0)\) where \(1\) is at the \(i\)-th place and \(i=1,2,\ldots,n\text{.}\) Consider a subset
\begin{equation*} W=\big\{\alpha_1 e_{i_1}+\alpha_2 e_{i_2}+\cdots\alpha_r e_{i_r}:\alpha_i\in F\text{ and } i_j\in\{1,2,\ldots,n\} \big\}. \end{equation*}
This is a subspace of \(F^n\text{.}\)
Consider vector space of matrices \(M_{n\times n}(F)\) over a field \(F\) (refer to Example 2.2.2). A subset of all diagonal matrices in \(M_{n\times n}(F)\text{,}\) i.e.,
\begin{equation*} D_n(F)=\big\{{\rm diag}(a_1,a_2,\ldots,a_n):a_i\in F\big\} \end{equation*}
is a subspace of \(M_{n\times n}(F)\text{.}\)
Consider the direct sum \(V\bigoplus W\) of vector spaces \(V,W\) over a field \(F\) (refer to Section 2.2). A subset
\begin{equation*} S=\big\{ (v,0):v\in V\big\} \end{equation*}
is a subspace of \(V\bigoplus W\text{.}\)
Let \(V\) be a vector space over a field \(F\text{,}\) and \(I\) be an indexing set. Let \(S_i\leq V\) (\(i\in I\)) be subspaces of \(V\text{.}\) The set
\begin{equation*} \bigcap_{i\in I}S_i \end{equation*}
is a subspace of \(V\text{.}\)
Let \(V\) be a vector space over a field \(F\) and \(I\) be an indexing set. For each \(i\in I\text{,}\) let \(S_i\leq V\) be a subspace. The set
\begin{equation*} \sum_{i\in I}S_i=\bigg\{v_1+v_2+\cdots+v_r:v_j\in\bigcup_{i\in I}S_i \text{ and }r\in\N \bigg\} \end{equation*}
is a subspace.
Let \(A\in M_{m\times n}(F)\text{.}\) The set
\begin{equation*} \ker(A)=\big\{X\in M_{n\times 1}(F): AX=0 \big\} \end{equation*}
is a subspace of \(M_{n\times 1}(F)\text{.}\)

Definition 2.5.11. (Subspace spanned by a nonempty subset).

Let \(S\) be a nonempty subset of a vector space \(V\text{.}\) The subspace spanned by \(S\) is the intersection of all subspaces containing \(S\text{.}\) We denote it by \(\langle S\rangle\) or by \(\Span(S)\text{.}\)
By Example 2.5.8, the intersection of subspaces is again a subspace. Note that a subspace spanned by \(S\) is the smallest subspace of \(V\) containing \(S\text{.}\)

Definition 2.5.13.

Let \(W\leq V\) be a subspace of a vector space \(V\) over a field \(F\text{.}\) A subset \(S\) of \(V\) is said to span subspace \(W\) if the subspace generated by \(S\text{,}\) \(\langle S\rangle=W\text{.}\)

Remark 2.5.14.

If \(S\) spans \(W\) then, any subset \(S^\prime\) of \(V\) containing \(S\) also spans \(W\text{.}\)

Definition 2.5.15.

Let \(V\) be a vector space over a field \(F\text{,}\) and let \(v\) be a nonzero vector in \(V\text{.}\) The subspace spanned by \(v\text{,}\) \(\langle v\rangle=\{\alpha v:\alpha\in F\}\) is called line through \(v\text{.}\)