Elementary symmetric polynomial


In mathematics, specifically in commutative algebra, the elementary symmetric polynomials are one type of basic building block for symmetric polynomials, in the sense that any symmetric polynomial can be expressed as a polynomial in elementary symmetric polynomials. That is, any symmetric polynomial is given by an expression involving only additions and multiplication of constants and elementary symmetric polynomials. There is one elementary symmetric polynomial of degree in variables for each nonnegative integer, and it is formed by adding together all distinct products of distinct variables.

Definition

The elementary symmetric polynomials in variables, written for, are defined by
and so forth, ending with
In general, for we define
so that if.
Thus, for each non-negative integer less than or equal to there exists exactly one elementary symmetric polynomial of degree in variables. To form the one that has degree, we take the sum of all products of -subsets of the variables.
Given an integer partition , one defines the symmetric polynomial, also called an elementary symmetric polynomial, by
Sometimes the notation is used instead of.

Examples

The following lists the elementary symmetric polynomials for the first four positive values of .
For :
For :
For :
For :

Properties

The elementary symmetric polynomials appear when we expand a linear factorization of a monic polynomial: we have the identity
That is, when we substitute numerical values for the variables, we obtain the monic univariate polynomial whose roots are the values substituted for and whose coefficients are up to their sign the elementary symmetric polynomials. These relations between the roots and the coefficients of a polynomial are called Vieta's formulas.
The characteristic polynomial of a square matrix is an example of application of Vieta's formulas. The roots of this polynomial are the eigenvalues of the matrix. When we substitute these eigenvalues into the elementary symmetric polynomials, we obtain, up to their sign, the coefficients of the characteristic polynomial, which are invariants of the matrix. In particular, the trace is the value of, and thus the sum of the eigenvalues. Similarly, the determinant is, up to the sign, the constant term of the characteristic polynomial; more precisely the determinant is the value of. Thus the determinant of a square matrix is the product of the eigenvalues.
The set of elementary symmetric polynomials in variables generates the ring of symmetric polynomials in variables. More specifically, the ring of symmetric polynomials with integer coefficients equals the integral polynomial ring. This fact is one of the foundations of invariant theory. For other systems of symmetric polynomials with a similar property see power sum symmetric polynomials and complete homogeneous symmetric polynomials.

Fundamental theorem of symmetric polynomials

For any commutative ring, denote the ring of symmetric polynomials in the variables with coefficients in by. This is a polynomial ring in the n elementary symmetric polynomials for.
This means that every symmetric polynomial has a unique representation
for some polynomial. Another way of saying the same thing is that the ring homomorphism that sends to for defines an isomorphism between and.

Proof sketch

The theorem may be proved for symmetric homogeneous polynomials by a double mathematical induction with respect to the number of variables and, for fixed, with respect to the degree of the homogeneous polynomial. The general case then follows by splitting an arbitrary symmetric polynomial into its homogeneous components.
In the case the result is obvious because every polynomial in one variable is automatically symmetric.
Assume now that the theorem has been proved for all polynomials for variables and all symmetric polynomials in variables with degree. Every homogeneous symmetric polynomial in can be decomposed as a sum of homogeneous symmetric polynomials
Here the "lacunary part" is defined as the sum of all monomials in which contain only a proper subset of the variables, i.e., where at least one variable is missing.
Because is symmetric, the lacunary part is determined by its terms containing only the variables, i.e., which do not contain. More precisely: If and are two homogeneous symmetric polynomials in having the same degree, and if the coefficient of before each monomial which contains only the variables equals the corresponding coefficient of, then and have equal lacunary parts.
But the terms of which contain only the variables are precisely the terms that survive the operation of setting to 0, so their sum equals, which is a symmetric polynomial in the variables that we shall denote by. By the inductive assumption, this polynomial can be written as
for some. Here the doubly indexed denote the elementary symmetric polynomials in variables.
Consider now the polynomial
Then is a symmetric polynomial in, of the same degree as, which satisfies
. In other words, the coefficient of before each monomial which contains only the variables equals the corresponding coefficient of. As we know, this shows that the lacunary part of coincides with that of the original polynomial. Therefore the difference has no lacunary part, and is therefore divisible by the product of all variables, which equals the elementary symmetric polynomial. Then writing, the quotient is a homogeneous symmetric polynomial of degree less than which by the inductive assumption can be expressed as a polynomial in the elementary symmetric functions. Combining the representations for and one finds a polynomial representation for.
The uniqueness of the representation can be proved inductively in a similar way. The fact that the polynomial representation is unique implies that is isomorphic to.

Alternative proof

The following proof is also inductive, but does not involve other polynomials than those symmetric in, and also leads to a fairly direct procedure to effectively write a symmetric polynomial as a polynomial in the elementary symmetric ones. Assume the symmetric polynomial to be homogeneous of degree ; different homogeneous components can be decomposed separately. Order the monomials in the variables lexicographically, where the individual variables are ordered, in other words the dominant term of a polynomial is one with the highest occurring power of, and among those the one with the highest power of, etc. Furthermore parametrize all products of elementary symmetric polynomials that have degree . The essential ingredient of the proof is the following simple property, which uses multi-index notation for monomials in the variables.
Lemma. The leading term of is.
Now one proves by induction on the leading monomial in lexicographic order, that any nonzero homogeneous symmetric polynomial of degree can be written as polynomial in the elementary symmetric polynomials. Since is symmetric, its leading monomial has weakly decreasing exponents, so it is some with a partition of. Let the coefficient of this term be, then is either zero or a symmetric polynomial with a strictly smaller leading monomial. Writing this difference inductively as a polynomial in the elementary symmetric polynomials, and adding back to it, one obtains the sought for polynomial expression for.
The fact that this expression is unique, or equivalently that all the products of elementary symmetric polynomials are linearly independent, is also easily proved. The lemma shows that all these products have different leading monomials, and this suffices: if a nontrivial linear combination of the were zero, one focuses on the contribution in the linear combination with nonzero coefficient and with the largest leading monomial; the leading term of this contribution cannot be cancelled by any other contribution of the linear combination, which gives a contradiction.