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MATH
[1251]

Proofs from Rank-nullity

All proofs from Rank-nullity.

Back to Rank-nullity

Let k=dim⁡ker⁡(T)k=\dim\ker(T) and choose a basis

u1,…,uku_1,\ldots,u_k

for ker⁡(T)\ker(T). Extend it to a basis of VV:

u1,…,uk,v1,…,vr.u_1,\ldots,u_k,v_1,\ldots,v_r.

The vectors T(v1),…,T(vr)T(v_1),\ldots,T(v_r) span im⁡(T)\operatorname{im}(T). Indeed, if x∈Vx\in V, write

x=a1u1+⋯+akuk+b1v1+⋯+brvr.x=a_1u_1+\cdots+a_ku_k+b_1v_1+\cdots+b_rv_r.

Applying TT gives

T(x)=b1T(v1)+⋯+brT(vr),T(x)=b_1T(v_1)+\cdots+b_rT(v_r),

because T(ui)=0T(u_i)=0 for each ii.

The vectors T(v1),…,T(vr)T(v_1),\ldots,T(v_r) are linearly independent. If

c1T(v1)+⋯+crT(vr)=0,c_1T(v_1)+\cdots+c_rT(v_r)=0,

then

T(c1v1+⋯+crvr)=0,T(c_1v_1+\cdots+c_rv_r)=0,

so c1v1+⋯+crvr∈ker⁡(T)c_1v_1+\cdots+c_rv_r\in\ker(T). It is therefore a linear combination of u1,…,uku_1,\ldots,u_k. Since the full list

u1,…,uk,v1,…,vru_1,\ldots,u_k,v_1,\ldots,v_r

is linearly independent, c1=⋯=cr=0c_1=\cdots=c_r=0. Thus T(v1),…,T(vr)T(v_1),\ldots,T(v_r) is a basis of the image, so rank⁡(T)=r\operatorname{rank}(T)=r. The basis of VV has k+rk+r vectors, giving

rank⁡(T)+nullity⁡(T)=r+k=dim⁡(V).\operatorname{rank}(T)+\operatorname{nullity}(T)=r+k=\dim(V).