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Necessary and Sufficient Conditions for Linear Transformations to be Surjective and Injective 📂Linear Algebra

Necessary and Sufficient Conditions for Linear Transformations to be Surjective and Injective

Theorem 11

The following two propositions are equivalent concerning a linear transformation T:VWT: V \to W.

  • TT is one-to-one.
  • N(T)=ker(T)={0}N(T) = \text{ker}(T) = \left\{ \mathbf{0} \right\}

Explanation

This means that understanding the kernel of TT is a method to determine whether TT is one-to-one or not. According to the theorem, a linear transformation being one-to-one is equivalent to the following condition.

x0    T(x)0 \mathbf{x} \ne \mathbf{0} \implies T(\mathbf{x}) \ne \mathbf{0}

Proof

  • (    )(\implies)

    Let’s assume that TT is one-to-one. Since TT is a linear transformation, the following holds.

    T(0)=0 T(\mathbf{0})=\mathbf{0}

    However, assuming that TT is one-to-one, the element of VV that satisfies the above equation is uniquely 0\mathbf{0}. Therefore, the following holds.

    ker(T)={0} \text{ker}(T) = \left\{ \mathbf{0} \right\}

  • (    )(\impliedby)

    Let’s assume ker(T)={0}\text{ker}(T) = \left\{ \mathbf{0} \right\}. Let’s say u,vV\mathbf{u}, \mathbf{v} \in V are distinct vectors. Therefore, uv0\mathbf{u} - \mathbf{v} \ne \mathbf{0}. Then, by assumption, the following holds.

    T(u)T(v)=T(uv)0 T(\mathbf{u}) - T(\mathbf{v}) = T(\mathbf{u} - \mathbf{v}) \ne \mathbf{0}

    Thus, we obtain the following.

    uv    T(u)T(v) \mathbf{u} \ne \mathbf{v} \implies T(\mathbf{u}) - T(\mathbf{v})

    Therefore, TT is one-to-one.

Theorem 2

Concerning a linear transformation T:VVT: V \to V, if VV is finite-dimensional, the following propositions are equivalent.

  • TT is one-to-one.
  • N(T)=ker(T)={0}N(T) = \text{ker}(T) = \left\{ \mathbf{0} \right\}
  • TT is onto. In other words, the range of TT is the same as VV. R(T)=VR(T)=V

Explanation

This is a special case when VV is finite-dimensional and W=VW=V, as proved in Theorem 1. The first two propositions being equivalent was proved in Theorem 1, so we will prove the equivalence of the first and third propositions.

Proof2

Let S={v1,,vn}S = \left\{ \mathbf{v}_{1}, \dots, \mathbf{v}_{n} \right\} be the basis of VV. Then, since every T(v)T(\mathbf{v}) can be represented by a linear transformation of T(vi)T(\mathbf{v}_{i}), we can know that the set QQ generates R(T)R(T).

Q={T(v1),T(vn)} Q = \left\{ T(\mathbf{v}_{1}),\dots T(\mathbf{v}_{n}) \right\}

Here, since the number of elements in QQ is dim(V)=n\dim(V)=n, QQ being linearly independent is equivalent to QQ generating VV. But since QQ generates R(T)R(T), showing that QQ is linearly independent is the same as showing R(T)=VR(T)=V. Therefore, the proof shifts to proving the following.

TT is one-to-one     \iff QQ is linearly independent
  • (    )(\implies)

    Let’s assume that TT is one-to-one. And let’s assume the constants cic_{i} satisfy the following equation.

    c1T(v1)+c2T(v2)++cnT(vn)=0 \begin{equation} c_{1}T(\mathbf{v}_{1}) + c_{2}T(\mathbf{v}_{2}) + \cdots + c_{n}T(\mathbf{v}_{n}) = \mathbf{0} \label{1} \end{equation}

    Then, since TT is a linear transformation, the following holds.

    T(c1v1++cnvn)=0 T (c_{1}\mathbf{v}_{1} + \cdots + c_{n}\mathbf{v}_{n}) = \mathbf{0}

    Since we assumed TT is one-to-one, by Theorem 1, the constants satisfying the above equation are only 0\mathbf{0}.

    c1v1++cnvn=0 c_{1}\mathbf{v}_{1} + \cdots + c_{n}\mathbf{v}_{n} = \mathbf{0}

    But since vi\mathbf{v}_{i} are the elements of the basis, the constants that satisfy the above equation are only 00.

    c1=c2==cn=0 c_{1}=c_{2}=\cdots=c_{n}=0

    Thus, since the constants that satisfy (1)\eqref{1} are only 00, QQ is linearly independent.

  • (    )(\impliedby)

    Assume that QQ is linearly independent. And let’s assume the constants cic_{i} satisfy the following equation.

    c1T(v1)+c2T(v2)++cnT(vn)=0 c_{1}T(\mathbf{v}_{1}) + c_{2}T(\mathbf{v}_{2}) + \cdots + c_{n}T(\mathbf{v}_{n}) = \mathbf{0}

    Then, by assumption, we know that the constants that satisfy the above equation are only 00.

    c1=c2==cn=0 \begin{equation} c_{1}=c_{2}=\cdots=c_{n}=0 \label{2} \end{equation}

    But since TT is a linear transformation, the following holds.

    T(c1v1++cnvn)=c1T(v1)+c2T(v2)++cnT(vn)=0 T(c_{1}\mathbf{v}_{1} + \cdots + c_{n}\mathbf{v}_{n}) = c_{1}T(\mathbf{v}_{1}) + c_{2}T(\mathbf{v}_{2}) + \cdots + c_{n}T(\mathbf{v}_{n}) = \mathbf{0}

    Then, by (2)\eqref{2}, only 0\mathbf{0} satisfies the above equation.

    T(0)=T(0v1++0vn)=0 T(\mathbf{0}) = T(0\mathbf{v}_{1} + \cdots + 0\mathbf{v}_{n}) = \mathbf{0}

    Therefore, by Theorem 1 TT is one-to-one.


  1. Howard Anton, Elementary Linear Algebra: Aplications Version (12th Edition, 2019), p460-462 ↩︎

  2. Walter Rudin, Principles of Mathmatical Analysis (3rd Edition, 1976), p207 ↩︎