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Proofs of AM-GM

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This pages lists some proofs of the weighted AM-GM Inequality. The inequality's statement is as follows: for all nonnegative reals a_1, \dotsc, a_n and nonnegative reals \lambda_1, \dotsc, \lambda_n such that \sum_{i=1}^n \lambda_i = 1, then \sum_{i=1}^n \lambda_i a_i \ge \prod_{i=1}^n a_i^{\lambda_i}, with equality if and only if a_i = a_j for all i,j such that \lambda_i, \lambda_j \neq 0.

We first note that we may disregard any a_i for which \lambda_i= 0, as they contribute to neither side of the desired inequality. We also note that if a_i= 0 and \lambda_i \neq 0, for some i, then the right-hand side of the inequality is zero and the right hand of the inequality is greater or equal to zero, with equality if and only if a_j = 0 = a_i whenever \lambda_j\neq 0. Thus we may henceforth assume that all a_i and \lambda_i are strictly positive.

Contents

Complete Proofs

Proof by Convexity

We note that the function x \mapsto \ln x is strictly concave. Then by Jensen's Inequality, \ln \sum_i \lambda_i a_i \ge \lambda_i \sum_i \ln a_i = ln \prod_i a_i^{\lambda_i} , with equality if and only if all the a_i are equal. Since x \mapsto \ln x is a strictly increasing function, it then follows that \sum_i \lambda_i a_i \ge \prod_i a_i^{\lambda_i}, with equality if and only if all the a_i are equal, as desired. \blacksquare

Alternate Proof by Convexity

This proof is due to G. Pólya.

Note that the function f:x \mapsto e^x is strictly convex. Let g(x) be the line tangent to f at (0,1); then g(x) = x+1. Since f is also a continuous, differentiable function, it follows that f(x) \ge g(x) for all x, with equality exactly when x=0, i.e., 1+x \le e^x, with equality exactly when x=0.

Now, set r_i = a_i/\biggl( \sum_{j=1}^n \lambda_j a_j \biggr) - 1, for all integers 1\le i \le n. Our earlier bound tells us that r_i +1 \le \exp(r_i), so (r_i +1)^{\lambda_i} \le \exp(\lambda_i r_i) . Multiplying n such inequalities gives us \frac{\prod_{i=1}^n a_i^{\lambda_i}}{ \sum_{i=1}^n \lambda_i r_i} = \prod_{i=1}^n (r_i + 1) \le \prod_{i=1}^n \exp \lambda_i ... so \prod_{i=1}^n a_i^{\lambda_i} \le \sum_{i=1}^n \lambda_i r_i , as desired. Equality holds when r_i is always equal to zero, i.e., when a_i = a_j for all i,j such that \lambda_i , \lambda_j \neq 0. \blacksquare

Proofs of Unweighted AM-GM

These proofs use the assumption that \lambda_i = 1/n, for all integers 1 \le i \le n.

Proof by Rearrangement

Define the n sequence \{ r_{ij}\}_{i=1}^{n} as r_{ij} = \sqrt[n]{a_i}, for all integers 1 \le i,j \le n. Evidently these sequences are similarly sorted. Then by the Rearrangement Inequality, \sum_i a_i = \sum_i \prod_j r_{ij} \ge \sum_i \prod_j r_{i,i+j} = n \prod_i \sqrt[n]{a_i} , where we take our indices modulo n, with equality exactly when all the r_{ij}, and therefore all the a_i, are equal. Dividing both sides by n gives the desired inequality. \blacksquare

Proof by Cauchy Induction

We first prove that the inequality holds for two variables. Note that (\sqrt{a}, \sqrt{b}), (\sqrt{a}, \sqrt{b}) are similarly sorted sequences. Then by the Rearrangement Inequality, \sqrt{ab} = \frac{ \sqrt{a} \sqrt{b} + \sqrt{b} \sqrt{a}}{2} \le \frac{ \sqrt{a} \sqrt{a} + \sqrt{b} \sqrt{b}}{2} = \frac{a+b... with equality exactly when a=b.

We next prove that if the inequality holds for n variables (with equality when all are equal to zero), than it holds for 2n variables (with equality when all are equal to zero). Indeed, suppose the inequality holds for n variables. Let A_n, A'_n, A_{2n} denote the arithmetic means of (a_1, \dotsc, a_n), (a_{n+1}, \dotsc, a_{2n}), (a_1, \dotsc, a_{2n}), respectively; let G_n, G'_n, G_{2n} denote their respective geometric means. Then G_{2n} = \sqrt{G_n G'_n} \le \frac{G_n + G'_n}{2} \le \frac{A_n + A'_n}{2} = A_2n, with equality when all the numbers a_1, \dotsc, a_{2n} are equal, as desired.

These two results show by induction that the theorem holds for n=2^k, for all integers k. In particular, for every integer n, there is an integer N >n such that the theorem holds for N variables.

Finally, we show that if N>n and the theorem holds for N variables, then it holds for n variables a_1, \dotsc, a_n with arithmetic mean A_n and geometric mean G_n. Indeed, set b_k = a_k for 1\le k \le n, and let b_k = A_k for n < k \le N. Then G_k^{n/N} \cdot A_k^{(N-n)/N} = \prod_{i=1}^N b_i^{1/N} \le \sum_{i=1}^N b_i/N = A_n . It follows that G_k^{n/N} \le A_k^{n/N}, or G_n \le A_n, with equality exactly when all the a_i are equal to A_k.

The last two results show that for all positive integers n, the theorem holds for n variables. Therefore the theorem is true. \blacksquare

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