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MUIRHEAD'S INEQUALITY

In mathematics, 'Muirhead's inequality', also known as the "bunching" method, generalizes the inequality of arithmetic and geometric means.

Contents
Two preliminary definitions
The "''a''-mean"
Doubly stochastic matrices
The inequality
Another equivalent condition
Symmetric sum-notation tricks
Deriving the arithmetic-geometric mean inequality
Examples
References

Two preliminary definitions


The "''a''-mean"

For any real vector
:a=(a_1,dots,a_n)
define the "''a''-mean" [''a''] of nonnegative real numbers ''x''1, ..., ''x''''n'' by
:[a]={1 over n!}sum_sigma x_{sigma_1}^{a_1}cdots x_{sigma_n}^{a_n},
where the sum extends over all permutations σ of { 1, ..., ''n'' }.
In case ''a'' = (1, 0, ..., 0), this is just the ordinary arithmetic mean of ''x''1, ..., ''x''''n''. In case ''a'' = (1/''n'', ..., 1/''n''), it is the geometric mean of ''x''1, ..., ''x''''n''. (When ''n'' = 2, this is the Heinz mean.)
Doubly stochastic matrices

An ''n'' × ''n'' matrix ''P'' is ''doubly stochastic'' precisely if both ''P'' and its transpose ''P''T are stochastic matrices. A ''stochastic matrix'' is a square matrix of nonnegative real entries in which the sum of the entries in each column is 1. Thus, a doubly stochastic matrix is a square matrix of nonnegative real entries in which the sum of the entries in each row and the sum of the entries in each column is 1.

The inequality


Muirhead's inequality states that [''a''] ≤ [''b''] for all ''x''''i'' ≥ 0 if and only if there is some doubly stochastic matrix ''P'' for which ''a'' = ''Pb''.
The proof makes use of the fact that every doubly stochastic matrix is a weighted average of permutation matrices (Birkhoff-von Neumann theorem).
Another equivalent condition

Because of the symmetry of the sum, no generality is lost by sorting the exponents into decreasing order:
:a_1 geq a_2 geq cdots geq a_n
:b_1 geq b_2 geq cdots geq b_n
Then the existence of a doubly stochastic matrix ''P'' such that ''a'' = ''Pb'' is equivalent to the following system of inequalities:
:a_1 leq b_1
:a_1+a_2 leq b_1+b_2
:a_1+a_2+a_3 leq b_1+b_2+b_3
:qquad dotsqquad dotsqquad dotsqquad dots
:a_1+cdots +a_{n-1} leq b_1+cdots+b_{n-1}
:a_1+cdots +a_n=b_1+cdots+b_n.
(The ''last'' one is an equality; the others are weak inequalities.)
The sequence b_1, ldots, b_n is said to 'majorize' the sequence a_1, ldots, a_n.

Symmetric sum-notation tricks


It is useful to use a kind of special notation for the sums. A success in reducing an inequality in this form means that the only condition for testing it is to verify whether one exponent sequence (lpha_1, ldots, lpha_n) majorizes the other one.
:sum_{sym} x_1^{lpha_1} cdots x_n^{lpha_n}
This notation requires developing every permutation, developing an expression made of n! monomials, for instance:
:sum_{sym} x^3 y^2 z^0 = x^3 y^2 z^0 + x^3 z^2 y^0 + y^3 x^2 z^0 + y^3 z^2 x^0 + z^3 x^2 y^0 + z^3 y^2 x^0 = x^3 y^2 + x^3 z^2 + y^3 x^2 + y^3 z^2 + z^3 x^2 + z^3 y^2 !

Deriving the arithmetic-geometric mean inequality


Let
:a_G = left( rac 1 n , ldots , rac 1 n
ight)
:a_A = ( 1 , 0, 0, ldots , 0 ),
we have
:a_{A1} = 1 > a_{G1} = rac 1 n ,
:a_{A1} + a_{A2} = 1 > a_{G1} + a_{G2} = rac 2 n,
:qquad dotsqquad dotsqquad dots,
:a_{A1} + cdots + a_{An} = a_{G1} + cdots + a_{Gn} = 1 ,
then
:[''aA''] ≥ [''aG'']
which is
: rac 1 {n!} (x_1^1 cdot x_2^0 cdots x_n^0 + cdots + x_1^0 cdots x_n^1) (n-1)! geq rac 1 {n!} (x_1 cdot cdots cdot x_n)^{ rac 1 n} n!
yielding the inequality.

Examples


Suppose you want to prove that ''x''2 + ''y''2 ≥ 2''xy'' by using bunching (Muirhead's inequality):
We transform it in the symmetric-sum notation:
:sum_ mathrm{sym} x^2 y^0 ge sum_mathrm{sym} x^1 y^1
The sequence (2, 0) majorizes the sequence (1, 1), thus the inequality holds by bunching. Again,
:x^3+y^3+z^3 ge 3 x y z
:sum_ mathrm{sym} x^3 y^0 z^0 ge sum_mathrm{sym} x^1 y^1 z^1
which yields
: 2 x^3 + 2 y^3 + 2 z^3 ge 6 x y z
the sequence (3, 0, 0) majorizes the sequence (1, 1, 1), thus the inequality holds by bunching.

References



★ ''Combinatorial Theory'' by John N. Guidi, based on lectures given by Gian-Carlo Rota in 1998, MIT Copy Technology Center, 2002.

★ Kiran Kedlaya's guide to solving inequalities at [1].

Simple explanation with examples

Reference on PlanetMath (Muirhead's theorem)

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