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We prove independence of eigenvectors for distinct eigenvalues by induction on the number of vectors. A single eigenvector is nonzero and hence independent. Suppose the first $d-1$ are independent, and let ${\sum }_{j=1}^d{c}_j{v}_j=0$. Applying $A-{\lambda }_{d}I$ givesBy the induction hypothesis every coefficient in this shorter relation vanishes. The eigenvalues are distinct, so $c_j=0$ for $j<d$. The original relation becomes $c_d{v}_d=0$, and $v_d\ne 0$ gives $c_d=0$. Thus the entire family of eigenvectors is linearly independent. The argument works over either the real or complex field.

The independence of eigenvectors for distinct eigenvalues ensures that such eigenvectors form a linearly independent set. For completeness, apply ${\prod }_{j\ne k}(M-{\lambda }_{j}I)$ to a proposed relation ${\sum }_i{c}_i{\mathbf{e}}_i=0$. It leaves $c_k{\prod }_{j\ne k}({\lambda }_k-{\lambda }_j){\mathbf{e}}_k=0$, so every $c_k=0$. Thus the three eigenvectors form a basis over the relevant field and $\mathbf{x}={\sum }_i{a}_i(t){\mathbf{e}}_i$. Substitution into the linear system of ordinary differential equations gives ${\sum }_i({\dot{a}}_i-{\lambda }_i{a}_i){\mathbf{e}}_i=0$; linear independence implies ${\dot{a}}_i={\lambda }_i{a}_i$. HenceA real matrix may have a complex conjugate pair of eigenvalues. In that case the calculation is over $\mathbb{C}$ and conjugate coefficients yield real solutions; equivalently use real and imaginary parts of the complex modes. No unstated assumption that all three eigenvalues are real is needed.

Let $A{v}_1={\lambda }_1{v}_1$ and $A{v}_2={\lambda }_2{v}_2$, with both vectors nonzero and ${\lambda }_1\ne {\lambda }_2$. If $c_1{v}_1+c_2{v}_2=0$, apply $A-{\lambda }_{2}I$ to get $c_1({\lambda }_1-{\lambda }_2)v_1=0$. Hence $c_1=0$, and then $c_2=0$.

For the general independence of eigenvectors for distinct eigenvalues, use induction. In a relation ${\sum }_{j=1}^n{c}_j{v}_j=0$, applying $A-{\lambda }_{n}I$ gives ${\sum }_{j=1}^{n-1}{c}_j({\lambda }_j-{\lambda }_n)v_j=0$. Independence of the first $n-1$ vectors makes each coefficient vanish. Distinctness of the eigenvalues then gives $c_1=\cdots =c_{n-1}=0$, and the original relation gives $c_n=0$. No Hermitian assumption is required.

Work over the field containing the stated $n$ distinct eigenvalues of $B$; in a real formulation these must be real to obtain real eigenvectors. Choose one eigenvector for each distinct eigenvalue. By independence of eigenvectors for distinct eigenvalues, these $n$ vectors are a basis. Consequently each eigenspace $E_{\lambda }(B)$ has dimension one: in an expansion in this eigenbasis, $Bw=\lambda w$ forces every coefficient with a different eigenvalue to vanish.

Now let $v\ne 0$ be any eigenvector of $B$. By part (d), $Av$ belongs to its one-dimensional eigenspace, so $Av=\mu v$ for some scalar $\mu$. This proves that $v$ is an eigenvector of $A$, including the case $Av=0$, where $\mu =0$. This is the crucial one-dimensional step in simple spectrum gives simultaneous diagonalization.