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 "P" can be expressed as a polynomial in elementary symmetric polynomials: "P" can be given by an expression involving only additions and multiplication of constants and elementary symmetric polynomials. There is one elementary symmetric polynomial of degree "d" in "n" variables for any "d" ≤ "n", and it is formed by adding together all distinct products of "d" distinct variables.
Definition
The elementary symmetric polynomials in variables "X"1, …, "X""n", written "e""k"("X"1, …, "X""n") for "k" = 0, 1, ..., "n", can be defined as:and so forth, down to :(sometimes the notation σ"k" is used instead of "e""k").In general, for "k" ≥ 0 we define:
Thus, for each positive integer less than or equal to , there exists exactly one elementary symmetric polynomial of degree in variables. To form the one which has degree , we form all products of -tuples of the variables and add up these terms.
The fact that and so forth is the defining feature of commutative algebra. That is, the polynomial ring formed by taking all linear combinations of products of the elementary symmetric polynomials is a commutative ring.
Examples
The following lists the elementary symmetric polynomials for the first four positive values of . (In every case, is also one of the polynomials.)
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For : :
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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 (with variable λ) whose roots are the values substituted for and whose coefficients are the elementary symmetric polynomials.
The characteristic polynomial of a linear operator is an example of this. The roots are the eigenvalues of the operator. When we substitute these eigenvalues into the elementary symmetric polynomials, we obtain the coefficients of the characteristic polynomial, which are numerical invariants of the operator. This fact is useful in linear algebra and its applications and generalizations, like tensor algebra and disciplines which extensively employ tensor fields, such as differential geometry.
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 (See below for a more general statement and proof.) 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.
The fundamental theorem of symmetric polynomials
For any ring "A" denote the ring of symmetric polynomials in the variables with coefficients in "A" by . : is a polynomial ring in the "n" elementary symmetric polynomials for "k" = 1, ..., "n".(Note that is not among these polynomials; since , it cannot be member of "any" set of algebraically independent elements.)
This means that every symmetric polynomial has a unique representation:for some polynomial . Another way of saying the same thing is that is isomorphic to the polynomial ring through an isomorphism that sends to for .
Proof sketch
The theorem may be proved for symmetric homogeneous polynomials by a double mathematical induction with respect to the number of variables "n" and, for fixed "n", with respect to the degree of the homogeneous polynomial. The general case then follows by splitting an arbitrary symmetric polynomial into its homogeneous components (which are again symmetric).
In the case "n" = 1 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 "n" variables with degree < "d". Every homogeneous symmetric polynomial "P" in can be decomposed as a sum of homogeneous symmetric polynomials:Here the "lacunary part" is defined as the sum of all monomials in "P" which depend only on a proper subset of the "n" variables "X"1, ..., "X""n", i.e., where one variable "X""j" is missing.
Because "P" is symmetric the lacunary part is determined by the coefficients of all monomials which only depend on the variables "X"1, ..., "X""n"−1. The sum of all these monomials is equal to a polynomial which is symmetric in "n"−1 variables. According to the induction assumption can be written as : for some . Here the doubly-indexed denote the elementary symmetric polynomials in "n"−1 variables.
Consider now the polynomial :Then is a symmetric polynomial whose lacunary part coincides with that of the original polynomial "P" (note here that the difference is divisible by "X""n", therefore in the three polynomials "R", and finally all monomials involving only "X"1, ... ,"X""n"−1 are identical). Therefore the difference "P"−"R" has zero lacunary part and is of the form . The first factor coincides with the elementary symmetric polynomial , the second factor "Q" is a homogeneous symmetric polynomial of lower degree