6.2 Null Spaces and Ranges
Definition 6.2.1. Let \(T\in \mathcal {L}(A,B)\). The null space of \(T\) is the subset of \(A\) consisting of those vectors that \(T\) maps to zero: \[\text {null}(T)=\{X\in A: TX=0\}.\]
We now propose that the null space of any linear map is a subspace of the domain.
Proof. Let \(T\in \mathcal {L}(A,B)\).
- i.
- \(T(0)=T(0+0)=T(0)+T(0)\), and subtracting \(T(0)\) from both sides gives \(T(0)=0\). So \(0\in \text {null}\,T\) and the null space is not empty.
- ii.
- If \(x,y\in \) null\(T\) then \(T(x+y)=T(x)+T(y)=0+0=0\), so \((x+y)\in \) null\(T\).
- iii.
- If \(x\in \) null\(T\) and \(\alpha \in \mathbb {F}\), then \(T(\alpha x)=\alpha T(x)=\alpha \cdot 0=0\), so \(\alpha x\in \) null\(T\).
Being a non-empty subset of \(A\) closed under addition and scalar multiplication, null\(T\) is a subspace of \(A\). □
Definition 6.2.3. \(T\in \mathcal {L}(A,B)\) is called injective if \(Tx=Ty\implies x=y\) \(\forall x,y\in A\).
Proof. Suppose \(T\) is injective and let \(x\in \) null\(T\). Then \(Tx=0=T0\), and injectivity gives \(x=0\). So null\(T=\{0\}\).
Conversely suppose null\(T=\{0\}\) and let \(Tx=Ty\). By linearity \(T(x-y)=Tx-Ty=0\), so \(x-y\in \) null\(T=\{0\}\), giving \(x-y=0\), that is \(x=y\). So \(T\) is injective.
This is a genuine economy: for a linear map, injectivity need only be checked at the single vector \(0\), not at every pair of vectors. □
Definition 6.2.5. Let \(T\in \mathcal {L}(A,B)\). The range of \(T\) is a subset of \(B\) consisting vectors of the form \(Tx\) for \(x\in A\). i.e. Range\(T=\{Tx|x\in A\}\).
Proof. \(0=T(0)\) lies in range\(T\), so it is not empty. If \(u,v\in \) range\(T\), say \(u=Tx\) and \(v=Ty\), then \(u+v=Tx+Ty=T(x+y)\in \) range\(T\); and for \(\alpha \in \mathbb {F}\), \(\alpha u=\alpha Tx=T(\alpha x)\in \) range\(T\). Hence range\(T\) is a subspace of \(B\). □
The next theorem is the central counting fact about linear maps. It says that what a linear transformation collapses and what it reaches are not independent: the dimensions of the two must add up to the dimension of the domain. Every part of the theorem after it is a consequence of that one equation.
Theorem 6.2.8 (Rank–nullity theorem).
- i.
- If \(A\) is finite dimensional and \(T\in \mathcal {L}(A,B)\) then range\(T\) is a finite dimensional subspace of \(B\) and \[\dim A=\dim \text {null}\,T+\dim \text {range}\,T.\]
- ii.
- If \(A\) and \(B\) are finite dimensional with \(\dim A> \dim B\), then no linear transformation from \(A\) to \(B\) is injective.
- iii.
- If \(\dim A<\dim B\), then no linear transformation from \(A\) to \(B\) is surjective.
Proof.
- i.
- Let \(\dim A=n\) and let \(\{u_1,\dots ,u_k\}\) be a basis of null\(T\), so \(\dim \text {null}\,T=k\). Being a linearly independent set in \(A\), it extends to a
basis
\[\{u_1,\dots ,u_k,v_1,\dots ,v_m\}\]
of \(A\), where \(k+m=n\). The claim is that \(\{Tv_1,\dots ,Tv_m\}\) is a basis of range\(T\); granting this, \(\dim \text {range}\,T=m=n-k\), which is the assertion.
It spans range\(T\)
Let \(y\in \) range\(T\), say \(y=Tx\). Write \(x\) in the basis above as \(x=\sum _{i=1}^{k}a_iu_i+\sum _{j=1}^{m}b_jv_j\). Applying \(T\) and using \(Tu_i=0\), \[y=Tx=\sum _{i=1}^{k}a_iTu_i+\sum _{j=1}^{m}b_jTv_j=\sum _{j=1}^{m}b_jTv_j.\]
It is linearly independent
Suppose \(\sum _{j=1}^{m}c_jTv_j=0\). By linearity \(T\left (\sum _{j}c_jv_j\right )=0\), so \(\sum _{j}c_jv_j\in \) null\(T\) and can therefore be written in the basis of the null space as \(\sum _{j}c_jv_j=\sum _{i}d_iu_i\). Rearranging, \[\sum _{j=1}^{m}c_jv_j-\sum _{i=1}^{k}d_iu_i=0,\] a linear relation among the vectors of a basis of \(A\). All its coefficients must therefore vanish; in particular every \(c_j=0\).
So \(\{Tv_1,\dots ,Tv_m\}\) is a basis of range\(T\), which is in particular finite dimensional, and \(\dim A=k+m=\dim \text {null}\,T+\dim \text {range}\,T\).
- ii.
- Since range\(T\) is a subspace of \(B\), \(\dim \text {range}\,T\leq \dim B\). By part (i), \[\dim \text {null}\,T=\dim A-\dim \text {range}\,T\geq \dim A-\dim B>0,\] so null\(T\neq \{0\}\) and by Proposition 6.2.4 \(T\) is not injective.
- iii.
- By part (i), \(\dim \text {range}\,T=\dim A-\dim \text {null}\,T\leq \dim A<\dim B\). A subspace of strictly smaller dimension cannot be all of \(B\), so range\(T\neq B\) and \(T\) is not surjective.
Remark. Parts (ii) and (iii) are worth reading as statements about systems of equations. A homogeneous system with more unknowns than equations is a linear map from a larger space to a smaller one, so by (ii) it is not injective — which is exactly the familiar fact that such a system always has a non-trivial solution.
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