Subspace¶
A subset \(U\) of vector space \(\setv\) is called a subspace if \(U\) is also a vector space on the same definitions of addition and scalar multiplication as on \(\setv\).
Conditions for subspace¶
A subset \(U\) of vector space \(\setv\) is a subspace of \(\setv\) if and only if \(U\) satisfies the following three conditions
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Additive Identity
The additive identity \(0 \in U\)
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Closed under Addition
If \(u,v \in U\), then \(u + v \in U\)
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Closed under Multiplication
If \(u \in U\), then \(\lambda u \in u\) for all \(\lambda \in \field\)
With these conditions, empty sets are not a vector subspace of \(\setv\) and must contain at least one element to qualify as a vector space. The smalles subspace of \(\setv\) is \(\{ 0 \}\) and the largest subspace is \(\setv\) itself.
It is easy to verify that the subspaces of \(\real^{2}\) are \(\{ 0\}\), \(\real^{2}\) and all lines through the origin (\(0\)). For \(\real^{3}\), the subspaces will be \(\{ 0\}\), \(\real^{3}\), the set of all lines through origin, and the set of all planes through the origin.
Sum of Subspaces¶
For subsets \(U_{1}, U_{2}, \ldots U_{m}\) of \(\setv\), the sum denoted by \(U_{1} + U_{2} + \cdots + U_{m}\) is the set of all possible sums of elements of all the \(m\) subsets. More precisely
Furthermore, this sum of subspaces is the smallest subspace containing all the subspaces \(U_{1}, \ldots, U_{m}\).
Direct Sum¶
For subsets \(U_{1}, U_{2}, \ldots, U_{m}\), the direct sum is denoted by
The sum is a direct sum when any element of the direct sum can be expressed as the sum of elements of the subsets in a unique way.
where \(u_{i} \in U_{i}\) and there is a unique way to write this sum.
As an example, let
\(U_{1} + \cdots + U_{m}\) is a direct sum if and only if there is a way to write \(0\) as a sum \(u_{1} + \cdots + u_{m}\) such that all the \(u_{i}\) are \(0\).
The sum of two subspaces is a direct sum if and only if the intersection of those two subspaces is \(0\), i.e., for \(U, W \in \setv\), we have \(U \cap W = \{ 0 \}\)