Computing the Van der Monde Determinant

Example

The Van der Monde determinant associated to numbers \(x_1,\dots ,x_n\), \(n\geq 2\), is

\[ V_n \DefEq \det\, \left[ \begin{array}{ccccc} 1 & x_1 & x_{1}^{2} & \cdots & x_{1}^{n-1} \\ 1 & x_2 & x_{2}^{2} & \cdots & x_{2}^{n-1} \\ \vdots & \vdots & & \ddots & \vdots \\ 1 & x_n & x_{n}^{2} & \cdots & x_{n}^{n-1} \\ \end{array} \right] \]

We will use the multilinearity properties of the determinant operation to show

\[ V_n\ =\ \prod_{1\leq j< i \leq n} (x_i-x_j) \]

Proof

We compute by induction. If \(n=2\), we find

\[ \det\, \left[ \begin{array}{cc} 1 & x_1 \\ 1 & x_2 \end{array} \right] = x_2 - x_1 = \prod_{1\leq j < i \leq 2} (x_i - x_j) \]

as claimed. Now let \( n>2 \), and suppose the claim is true for \(n-1\); i.e.

\[ V_{n-1} = \det\, \left[ \begin{array}{ccccc} 1 & x_1 & x_{1}^{2} & \cdots & x_{1}^{n-1} \\ 1 & x_2 & x_{2}^{2} & \cdots & x_{2}^{n-1} \\ \vdots & \vdots & & \ddots & \vdots \\ 1 & x_{n-1} & x_{n-1}^{2} & \cdots & x_{n-1}^{n-1} \\ \end{array} \right] = \prod_{1\leq j < i \leq n-1} \]

We need to infer the validity of the stated formula for \(V_n\). Do do this, note

\[ V_{n} = \det\, \left[ \begin{array}{ccccc} 1 & x_1-x_n & x_{1}^{2}-x_nx_1 & \cdots & x_{1}^{n-1}-x_nx_{1}^{n-2} \\ 1 & x_2-x_n & x_{2}^{2}-x_nx_2 & \cdots & x_{2}^{n-1}-x_nx_{2}^{n-2} \\ \vdots & \vdots & & \ddots & \vdots \\ 1 & x_{n-1}-x_n & x_{n-1}^{2}-x_nx_{n-1} & \cdots & x_{n-1}^{n-1}-x_nx_{n-1}^{n-2} \\ 1 & 0 & 0 & \cdots & 0 \end{array} \right] \]

obtained by subtracting \(x_n\) times (second last column) from (last column). Then subtract \(x_n\) times (third last column) from (second last column) etc. Expand now along the last row to get

\[ V_{n} = (-1)^{n+1}\det\, \left[ \begin{array}{cccc} x_1-x_n & x_{1}^{2}-x_nx_1 & \cdots & x_{1}^{n-1}-x_nx_{1}^{n-2} \\ x_2-x_n & x_{2}^{2}-x_nx_2 & \cdots & x_{2}^{n-1}-x_nx_{2}^{n-2} \\ \vdots & & \ddots & \vdots \\ x_{n-1}-x_n & x_{n-1}^{2}-x_nx_{n-1} & \cdots & x_{n-1}^{n-1}-x_nx_{n-1}^{n-2} \end{array} \right] \]

The first row is a multiple of \((x_1-x_n)\). The second row is a multiple of \((x_2-x_n)\) etc. Thus

\(V_n\)\(=\)\( (-1)^{n+1}(x_1-x_n)\dots (x_{n-1}-x_n)\det \left[ \begin{array}{cccc} 1 & x_1 & \cdots & x_{1}^{n-2} \\ 1 & x_2 & \cdots & x_{2}^{n-2} \\ \vdots & & \ddots & \vdots \\ 1 & x_{n-1} & \cdots & x_{n-1}^{n-2} \end{array} \right] \)
\(\)\(=\)\( (-1)^{n-1}\left( \prod_{1\leq i < n} (x_i-x_n) \right) V_{n-1} \)
\(\)\(=\)\( (-1)^{n-1}\left( \prod_{1\leq i < n} (-1)(x_n-x_i) \right) V_{n-1} \)
\(\)\(=\)\( (-1)^{2(n-1)}\left( \prod_{1\leq i < n} (x_n-x_i) \right) \left( \prod_{1\leq j < i \leq n-1} (x_i-x_j) \right) \)
\(\)\(=\)\( \prod_{1\leq j < i \leq n} (x_i - x_j) \)

which is exactly what we wanted to show.