logo

The Equivalence Condition When the Range of a Linear Transformation is Smaller than the Kernel 📂Linear Algebra

The Equivalence Condition When the Range of a Linear Transformation is Smaller than the Kernel

Theorem1

Let VV be a vector space, and T:VVT : V \to V be a linear transformation. Then, the following holds:

T2=T0    R(T)N(T) T^{2} = T_{0} \iff R(T) \subset N(T)

Here, T0T_{0} is the zero transformation, and R(T),N(T)R(T), N(T) are the respective range and null space of TT.

Generalization

Let U,V,WU, V, W be a vector space, and T1:UVT_{1} : U \to V, T2:VWT_{2} : V \to W be linear transformations. Then, the following holds:

T2T1=T0    R(T1)N(T2) T_{2}T_{1} = T_{0} \iff R(T_{1}) \subset N(T_{2})

Explanation

It’s actually an obvious matter if you think about it. The proof method for the generally written theorem is the same.

Meanwhile, a linear transformation that is T2=T0T^{2} = T_{0} is called Nilpotent.

Proof

()(\Longrightarrow)

Let’s assume T2=T0T^{2} = T_{0}. Let T(x)R(T)T(x) \in R(T) (xV)(x\in V). Then,

T(T(x))=T2(x)=0 T(T(x)) = T^{2}(x) = 0

Therefore, by the definition of N(T)N(T), T(x)N(T)T(x) \in N(T) is true. Hence,

R(T)N(T) R(T) \subset N(T)

()(\Longleftarrow)

Let’s assume R(T)N(T)R(T) \subset N(T). Then, for all xVx \in V, since T(x)R(T)N(T)T(x) \in R(T) \subset N(T), by the definition of N(T)N(T),

R(T)N(T) R(T) \subset N(T)


  1. Stephen H. Friedberg, Linear Algebra (4th Edition, 2002), p97 ↩︎