Linear independence of monomials

Branko Ćurgus

On this page $\mathbb{P}$ denotes a vector space of all polynomials over the field of real numbers $\mathbb{R}$. By $\mathbb{N}$ we denote the set of positive integers.

The determinant in the next theorem is called Vandermonde determinant. The characterizing feature of the Vandermonde determinant is that in each row we have the consecutive nonnegative powers of a fixed real number. The corresponding matrix and its transpose are called Vandermonde matrix.

Theorem 1. Let $n \in \mathbb{N}$ and let $x_0,x_1, \ldots, x_n \in \mathbb{R}$. Then \[ \left| \begin{array}{cccccc} 1 & x_0 & x_0^2 & \cdots & x_0^{n-1} & x_0^n \\ 1 & x_1 & x_1^2 & \cdots & x_1^{n-1} & x_1^n \\ \vdots & \vdots & \vdots & \ddots & \vdots & \vdots \\ 1 & x_{n-1} & x_{n-1}^2 & \cdots & x_{n-1}^{n-1} & x_{n-1}^n \\ 1 & x_n & x_n^2 & \cdots & x_n^{n-1} & x_n^n \end{array} \right| = \prod_{0 \leq j \lt k \leq n} \bigl( x_k - x_j \bigr). \]
Proof. By the definition of a $2\times2$ determinant the theorem is true for $n=1$: \[ \left| \begin{array}{cc} 1 & x_0 \\ 1 & x_1 \end{array} \right| = x_1 - x_0. \] To illustrate the general proof, we will start with the proof for the case $n=2$. We use column operations on the determinant to reduce the $3\times3$ determinant to the $2\times2$ determinant as follows: \begin{alignat*}{2} \left| \begin{array}{ccc} 1 & x_0 & x_0^2 \\ 1 & x_1 & x_1^2 \\ 1 & x_2 & x_2^2 \end{array} \right| & = \left| \begin{array}{ccc} 1 & x_0 & x_0^2 - x_0^2 \\ 1 & x_1 & x_1^2 - x_1 x_0 \\ 1 & x_2 & x_2^2 - x_2 x_0 \end{array} \right| & & \quad \small{\text{multiply the 2nd column by $x_0$ and subtract from the 3rd}}\\[5pt] & = \left| \begin{array}{ccc} 1 & x_0 & 0 \\ 1 & x_1 & x_1 (x_1 -x_0) \\ 1 & x_2 & x_2(x_2 -x_0) \end{array} \right| & & \quad \small{\text{do algebra}} \\[5pt] & = \left| \begin{array}{ccc} 1 & x_0 - x_0 & 0 \\ 1 & x_1 - x_0 & x_1 (x_1 -x_0) \\ 1 & x_2 - x_0 & x_2(x_2 -x_0) \end{array} \right| & & \quad \small{\text{multiply the 1st column by $x_0$ and subtract from the 2nd}} \\[5pt] & = \left| \begin{array}{ccc} 1 & 0 & 0 \\ 1 & x_1 - x_0 & x_1 (x_1 -x_0) \\ 1 & x_2 - x_0 & x_2(x_2 -x_0) \end{array} \right| & & \quad \small{\text{do algebra}} \\[5pt] & = 1 \, \left| \begin{array}{cc} x_1 - x_0 & x_1 (x_1 -x_0) \\ x_2 - x_0 & x_2(x_2 -x_0) \end{array} \right| & & \quad \small{\text{expand along the 1st row}} \\[5pt] & = (x_1 - x_0) (x_2 -x_0) \left| \begin{array}{cc} 1 & x_1 \\ 1 & x_2 \end{array} \right| & & \quad \small{\text{factor out the common factor in each row}} \\[5pt] & =(x_2 -x_0) (x_1 - x_0) (x_2 - x_1) & & \end{alignat*} The method of proof for the $(n+1)\times(n+1)$ determinant is identical to the preceding special case. We just have to apply the method $n-1$ times to reach the $2\times2$ determinant and after that get the algebraic expression for the original determinant. Here is the reasoning. The value of the determinant \[ \left| \begin{array}{cccccc} 1 & x_0 & x_0^2 & \cdots & x_0^{n-1} & x_0^n \\ 1 & x_1 & x_1^2 & \cdots & x_1^{n-1} & x_1^n \\ \vdots & \vdots & \vdots & \ddots & \vdots & \vdots \\ 1 & x_{n-1} & x_{n-1}^2 & \cdots & x_{n-1}^{n-1} & x_{n-1}^n \\ 1 & x_n & x_n^2 & \cdots & x_n^{n-1} & x_n^n \end{array} \right| \] will not change if we do the following: For $k \in \{2,\ldots,n+1\}$ replace the $k$th column by the column obtained by subtracting $(k-1)$st column from the $k$th column. We get the following determinant with the same value as the given one \[ \left| \begin{array}{cccccc} 1 & 0 & 0 & \cdots & 0 & 0 \\ 1 & x_1 - x_0 & x_1^2 - x_1 x_0 & \cdots & x_1^{n-1} - x_1^{n-2} x_0 & x_1^n - x_1^{n-1} x_0 \\ \vdots & \vdots & \vdots & \ddots & \vdots & \vdots \\ 1 & x_{n-1} - x_0 & x_{n-1}^2 - x_{n-1}x_0 & \cdots & x_{n-1}^{n-1} -x_{n-1}^{n-2} x_0 & x_{n-1}^n - x_{n-1}^{n-1}x_0 \\ 1 & x_n - x_0 & x_n^2 - x_n x_0 & \cdots & x_n^{n-1} - x_{n}^{n-2}x_0 & x_n^n - x_{n}^{n-1}x_0 \end{array} \right| . \] We expand this determinant along the 1st row and simplify entries to get \[ \left| \begin{array}{ccccc} x_1 - x_0 & x_1(x_1 - x_0) & \cdots & x_1^{n-2}(x_1 - x_0) & x_1^{n-1}(x_1 - x_0) \\ \vdots & \vdots & \ddots & \vdots & \vdots \\ x_{n-1} - x_0 & x_{n-1}(x_{n-1} - x_0) & \cdots & x_{n-1}^{n-2}(x_{n-1} - x_0) & x_{n-1}^{n-1}(x_{n-1} - x_0) \\ x_n - x_0 & x_n(x_n - x_0) & \cdots & x_{n}^{n-2}(x_n - x_0) & x_{n}^{n-1}(x_n - x_0) \end{array} \right| . \] Next, we factor out of the determinant the common factor present along each row to get \[ (x_n - x_0)(x_{n-1} - x_0) \cdots (x_1 - x_0) \left| \begin{array}{ccccc} 1 & x_1 & \cdots & x_1^{n-2} & x_1^{n-1} \\ \vdots & \vdots & \ddots & \vdots & \vdots \\ 1 & x_{n-1} & \cdots & x_{n-1}^{n-2} & x_{n-1}^{n-1} \\ 1 & x_n & \cdots & x_{n}^{n-2} & x_{n}^{n-1} \end{array} \right|. \] Notice that we started by the $(n+1)\times(n+1)$ determinant and the size of the determinant in the preceding expression is $n\times n$. We evaluate the preceding determinant by repeating the same procedure that we did above. We get additional factors in the product and the smaller determinant: \[ \left(\prod_{k=2}^n \bigl( x_k - x_1 \bigr) \right) \left( \prod_{k=1}^n \bigl( x_k - x_0 \bigr) \right) \left| \begin{array}{cccc} 1 & x_2 & \cdots & x_2^{n-2} \\ \vdots & \vdots & \ddots & \vdots \\ 1 & x_{n-1} & \cdots & x_{n-1}^{n-2} \\ 1 & x_n & \cdots & x_{n}^{n-2} \end{array} \right| . \] Notice that the size of the preceding determinant is $(n-1)\times (n-1)$. Repeating this procedure for the total of $n-1$ times, the given $(n+1)\times(n+1)$ determinant evaluates to the following expression \[ \prod_{j=0}^{n-2} \left( \prod_{k=j+1}^n \bigl( x_k - x_j \bigr) \right) \left| \begin{array}{cc} 1 & x_{n-1} \\ 1 & x_n \end{array} \right|, \] which further equals to \[ \prod_{j=0}^{n-1} \left( \prod_{k=j+1}^n \bigl( x_k - x_j \bigr) \right) = \prod_{0 \leq j \lt k \leq n} \bigl( x_k - x_j \bigr). \] Hence, the last product is the value of the determinant given in the theorem. This completes the proof.
Theorem 2. Let $n\in \mathbb{N}$ and let $\mathbb{P}_n$ be the vector space of all polynomials with real coefficients which are of degree less or equal $n$. The monomials $1, x, \ldots, x^n$ form a basis for $\mathbb{P}_n$.
Proof. By the definition of a polynomial of degree less or equal $n$ we have \[ \mathbb{P}_n = \operatorname{Span} \bigl\{ a_0 + a_1 x + \cdots + a_n x^n \, : \, a_k \in \mathbb{R} \ \forall k \in \{0,1,\ldots,n\} \bigr\}. \] To prove $1, x, \ldots, x^n$ form a basis for $\mathbb{P}_n$ we need to prove that they are linearly independent. To prove the linear independence we need to prove the following implication: For all $\alpha_0, \alpha_1,\ldots, \alpha_n \in \mathbb{R}$ we have \[ \alpha_0 + \alpha_1 x + \cdots + \alpha_n x^n = 0 \ \ \forall x \in \mathbb{R} \quad \Rightarrow \quad \alpha_k = 0 \ \ \forall k \in \{0,1,\ldots,n\}. \] To prove this implication assume \begin{equation} \label{eq:a1}\tag{1} \bbox[5px, #88FF88, border: 1pt solid green]{ \alpha_0 + \alpha_1 x + \cdots + \alpha_n x^n = 0 \quad \forall x \in \mathbb{R} }. \end{equation} The objective is to prove \begin{equation} \label{eq:claim}\tag{2} \bbox[5px, #FF4444, border: 1pt solid red]{ \alpha_k = 0 \quad \forall k \in \{0,1,\ldots,n\} }. \end{equation} Let $x_0, x_1, \ldots, x_n$ be distinct real numbers. That is we assume that \begin{equation} \label{eq:a2}\tag{3} \bbox[5px, #88FF88, border: 1pt solid green]{ \prod_{0\leq j \lt k \leq n}\bigl(x_k - x_j\bigr) \neq 0 }. \end{equation} Since the assumption $\eqref{eq:a1}$ holds for all $x \in \mathbb{R}$ we have that \begin{equation} \label{eq:e4}\tag{4} \bbox[5px, #88FF88, border: 1pt solid green]{ \alpha_0 \cdot 1 + \alpha_1 x_k + \cdots + \alpha_n x_k^n = 0 \quad \forall k \in \{0,1,\ldots,n\} }. \end{equation} In $\eqref{eq:e4}$ we have $n+1$ linear equations with $n+1$ unknowns $\alpha_0, \alpha_1, \ldots ,\alpha_n.$ This system can be written in matrix form as follows \begin{equation}\label{eq:e5}\tag{5} \bbox[5px, #88FF88, border: 1pt solid green]{ \left[ \begin{array}{ccccc} 1 & x_0 & \cdots & x_0^{n-1} & x_0^n \\ 1 & x_1 & \cdots & x_1^{n-1} & x_1^n \\ \vdots & \vdots & \ddots & \vdots & \vdots \\ 1 & x_{n-1} & \cdots & x_{n-1}^{n-1} & x_{n-1}^n \\ 1 & x_n & \cdots & x_n^{n-1} & x_n^n \end{array} \right] \left[ \begin{array}{c} \alpha_0 \\[2pt] \alpha_1 \\[2pt] \vdots \\[2pt] \alpha_{n-1}\\[2pt] \alpha_n \end{array} \right] = \left[ \begin{array}{c} 0 \\[2pt] 0 \\[2pt] \vdots \\[2pt] 0 \\[2pt] 0 \end{array} \right] }. \end{equation} In $\eqref{eq:e5}$ we have a homogeneous matrix equation with the Vandermonde matrix. In Theorem 1 we proved that the determinant of the Vandermonde matrix equals the expression in $\eqref{eq:a2}$ for which we assume that it is not zero. Therefore the matrix in $\eqref{eq:e5}$ is invertible. Consequently, equation $\eqref{eq:e5}$ implies that \begin{equation*} \bbox[5px, #88FF88, border: 1pt solid green]{ \left[ \begin{array}{c} \alpha_0 \\[2pt] \alpha_1 \\[2pt] \vdots \\[2pt] \alpha_{n-1}\\[2pt] \alpha_n \end{array} \right] = \left[ \begin{array}{c} 0 \\[2pt] 0 \\[2pt] \vdots \\[2pt] 0 \\[2pt] 0 \end{array} \right] }. \end{equation*} The preceding vector equality can be rewritten as \begin{equation*} \bbox[5px, #88FF88, border: 1pt solid green]{ \alpha_k = 0 \quad \forall k \in \{0,1,\ldots,n\} }. \end{equation*} Thus, the claim in $\eqref{eq:claim}$ has been greenified, that is it has been proved. Since by the definition of polynomials of degree less or equal to $n$ we have \begin{equation*} \bbox[5px, #88FF88, border: 1pt solid green]{ \mathbb{P}_n = \operatorname{Span} \bigl\{ 1, x, \ldots, x^n\bigr\} } \end{equation*} we have proved that $\bigl\{ 1, x, \ldots, x^n\bigr\}$ is a basis for $\mathbb{P}_n.$ This completes the proof.