The complete homogeneous symmetric polynomial {h_d(x_1,\dots,x_n)} of {n} variables {x_1,\dots,x_n} and degree {d} can be defined as

\displaystyle h_d(x_1,\dots,x_n) := \sum_{1 \leq i_1 \leq \dots \leq i_d \leq n} x_{i_1} \dots x_{i_d},

thus for instance

\displaystyle h_0(x_1,\dots,x_n) = 0,

\displaystyle h_1(x_1,\dots,x_n) = x_1 + \dots + x_n,


\displaystyle h_2(x_1,\dots,x_n) = x_1^2 + \dots + x_n^2 + \sum_{1 \leq i < j \leq n} x_i x_j.

One can also define all the complete homogeneous symmetric polynomials of {n} variables simultaneously by means of the generating function

\displaystyle \sum_{d=0}^\infty h_d(x_1,\dots,x_n) t^d = \frac{1}{(1-t x_1) \dots (1-tx_n)}. \ \ \ \ \ (1)

We will think of the variables {x_1,\dots,x_n} as taking values in the real numbers. When one does so, one might observe that the degree two polynomial {h_2} is a positive definite quadratic form, since it has the sum of squares representation

\displaystyle h_2(x_1,\dots,x_n) = \frac{1}{2} \sum_{i=1}^n x_i^2 + \frac{1}{2} (x_1+\dots+x_n)^2.

In particular, {h_2(x_1,\dots,x_n) > 0} unless {x_1=\dots=x_n=0}. This can be compared against the superficially similar quadratic form

\displaystyle x_1^2 + \dots + x_n^2 + \sum_{1 \leq i < j \leq n} \epsilon_{ij} x_i x_j

where {\epsilon_{ij} = \pm 1} are independent randomly chosen signs. The Wigner semicircle law says that for large {n}, the eigenvalues of this form will be mostly distributed in the interval {[-\sqrt{n}, \sqrt{n}]} using the semicircle distribution, so in particular the form is quite far from being positive definite despite the presence of the first {n} positive terms. Thus the positive definiteness is coming from the finer algebraic structure of {h_2}, and not just from the magnitudes of its coefficients.

One could ask whether the same positivity holds for other degrees {d} than two. For odd degrees, the answer is clearly no, since {h_d(-x_1,\dots,-x_n) = -h_d(x_1,\dots,x_n)} in that case. But one could hope for instance that

\displaystyle h_4(x_1,\dots,x_n) = \sum_{1 \leq i \leq j \leq k \leq l \leq n} x_i x_j x_k x_l

also has a sum of squares representation that demonstrates positive definiteness. This turns out to be true, but is remarkably tedious to establish directly. Nevertheless, we have a nice result of Hunter that gives positive definiteness for all even degrees {d}. In fact, a modification of his argument gives a little bit more:

Theorem 1 Let {n \geq 1}, let {d \geq 0} be even, and let {x_1,\dots,x_n} be reals.

  • (i) (Positive definiteness) One has {h_d(x_1,\dots,x_n) \geq 0}, with strict inequality unless {x_1=\dots=x_n=0}.
  • (ii) (Schur convexity) One has {h_d(x_1,\dots,x_n) \geq h_d(y_1,\dots,y_n)} whenever {(x_1,\dots,x_n)} majorises {(y_1,\dots,y_n)}, with equality if and only if {(y_1,\dots,y_n)} is a permutation of {(x_1,\dots,x_n)}.
  • (iii) (Schur-Ostrowski criterion for Schur convexity) For any {1 \leq i < j \leq n}, one has {(x_i - x_j) (\frac{\partial}{\partial x_i} - \frac{\partial}{\partial x_j}) h_d(x_1,\dots,x_n) \geq 0}, with strict inequality unless {x_i=x_j}.

Proof: We induct on {d} (allowing {n} to be arbitrary). The claim is trivially true for {d=0}, and easily verified for {d=2}, so suppose that {d \geq 4} and the claims (i), (ii), (iii) have already been proven for {d-2} (and for arbitrary {n}).

If we apply the differential operator {(x_i - x_j) (\frac{\partial}{\partial x_i} - \frac{\partial}{\partial x_j})} to {\frac{1}{(1-t x_1) \dots (1-tx_n)}} using the product rule, one obtains after a brief calculation

\displaystyle \frac{(x_i-x_j)^2 t^2}{(1-t x_1) \dots (1-tx_n) (1-t x_i) (1-t x_j)}.

Using (1) and extracting the {t^d} coefficient, we obtain the identity

\displaystyle (x_i - x_j) (\frac{\partial}{\partial x_i} - \frac{\partial}{\partial x_j}) h_d(x_1,\dots,x_n)

\displaystyle = (x_i-x_j)^2 h_{d-2}( x_1,\dots,x_n,x_i,x_j). \ \ \ \ \ (2)

The claim (iii) then follows from (i) and the induction hypothesis.

To obtain (ii), we use the more general statement (known as the Schur-Ostrowski criterion) that (ii) is implied from (iii) if we replace {h_d} by an arbitrary symmetric, continuously differentiable function. To establish this criterion, we induct on {n} (this argument can be made independently of the existing induction on {d}). If {(y_1,\dots,y_n)} is majorised by {(x_1,\dots,x_n)}, it lies in the permutahedron of {(x_1,\dots,x_n)}. If {(y_1,\dots,y_n)} lies on a face of this permutahedron, then after permuting both the {x_i} and {y_j} we may assume that {(y_1,\dots,y_m)} is majorised by {(x_1,\dots,x_m)}, and {(y_{m+1},\dots,y_n)} is majorised by {(x_{m+1},\dots,x_n)} for some {1 \leq m < n}, and the claim then follows from two applications of the induction hypothesis. If instead {(y_1,\dots,y_n)} lies in the interior of the permutahedron, one can follow it to the boundary by using one of the vector fields {(x_i - x_j) (\frac{\partial}{\partial x_i} - \frac{\partial}{\partial x_j})}, and the claim follows from the boundary case.

Finally, to obtain (i), we observe that {(x_1,\dots,x_n)} majorises {(x,\dots,x)}, where {x} is the arithmetic mean of {x_1,\dots,x_n}. But {h_d(x,\dots,x)} is clearly a positive multiple of {x^d}, and the claim now follows from (ii). \Box

If the variables {x_1,\dots,x_n} are restricted to be nonnegative, the same argument gives Schur convexity for odd degrees also.

The proof in Hunter of positive definiteness is arranged a little differently than the one above, but still relies ultimately on the identity (2). I wonder if there is a genuinely different way to establish positive definiteness that does not go through this identity.