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Newton's Inequality

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Contents

Background

For , we define the symmetric sum to be the coefficient of in the polynomial (see Viete's sums). We define the symmetric average to be .

Statement

For non-negative and ,

,

with equality exactly when all the are equal.

Proof

Lemma. For real , there exist real with the same symmetric averages .

Proof. We consider the derivative of . The roots of are . Without loss of generality, we assume that the increase as increases. Now for any , must have a root between and by Rolle's theorem if , and if x_i = x_{i+1} = \cdots = x_{i+k}, then is a root of times, so it must be a root of times. It follows that must have non-positive, real roots, i.e., for some non-negative reals ,

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

It follows that the symmetric sum for is , 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

for any . Since this is a homogenous inequality, we may normalize it so that . 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}{x_ix_j}.

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

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