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Newton's Inequality

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Contents

Background

For x_1, \ldots, x_n, we define the symmetric sum s_k to be the coefficient of t^{n-k} in the polynomial \prod_{i=1}^{n}(t+x_i) (see Viete's sums). We define the symmetric average d_k to be \textstyle s_k/{n \choose k}.

Statement

For non-negative x_1, \ldots, x_n and 0 < k < n,

d_k^2 \ge d_{k-1}d_{k+1},

with equality exactly when all the x_i are equal.

Proof

Lemma. For real x_1 , \ldots, x_m, there exist real x'_1, \ldots, x'_{m-1} with the same symmetric averages d_0, \ldots, d_{m-1}.

Proof. We consider the derivative of P(t) = \prod_{i=1}^n (t+x_i). The roots of P are -x_1, \ldots, -x_n. Without loss of generality, we assume that the x_i increase as i increases. Now for any i \in [1, m-1], P'(t) must have a root between x_i and x_{i+1} by Rolle's theorem if x_i \neq x_{i+1}, and if x_i = x_{i+1} = \cdots = x_{i+k}, then x_{i} is a root of P k+1 times, so it must be a root of P' k times. It follows that P' must have m-1 non-positive, real roots, i.e., for some non-negative reals x'_1, \ldots, x'_{m-1},

{}P'(t) = m \prod_{i=1}^{m-1}(t+x'_i).

It follows that the symmetric sum s'_k for x'_1, \ldots, x'_{m-1} is \frac{m-k}{m}s_k, so the symmetric average d'_k = \frac{s'_k}{{m-1 \choose k}} = \frac{m-k}{m} \cdot \frac{s_k}{{m-1 \choose k}} = \frac{s_k}{{m \choose k}} = d_k.

Thus to prove Newton's theorem, it is sufficient to prove

d_{n-1}^2 \ge d_{n-2}d_n

for any n. Since this is a homogenous inequality, we may normalize it so that d_n = \prod_{i=1}^{n}x_i = 1. The inequality then becomes

(n-1)\left(\sum_{i=1}^{n}\frac{1}{x_i} \right)^2 \ge 2n \sum_{0\le i<j \le n} \frac{1}{x_ix_j}.

Expanding the left side, we see that this is

(n-1)\sum_{i=1}^{n}\frac{1}{x_i^2}  + (n-1)\sum_{0\le i<j \le n}\frac{2}{x_ix_j} \ge 2n \sum_{0\le i<j \le n} \frac{1}{....

But this is clearly equivalent to

\sum_{\rm sym}\frac{1}{x_1^2} \ge \sum_{\rm sym}\frac{1}{x_1x_2},

which holds by the rearrangement inequality.

See Also

Want to learn how to tackle those tough MATHCOUNTS and AMC counting and probability problems? Check out Art of Problem Solving's Introduction to Counting & Probability by David Patrick.
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