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Elementary Symmetric Polynomial


An elementary symmetric polynomial e_k(x_1,...,x_n), for nonnegative integers n and k, is the sum of all products of k distinct variables:

 e_k(x_1,...,x_n)=sum_(1<=i_1<...<i_k<=n)x_(i_1)...x_(i_k).

The convention is e_0=1, with e_k=0 for k>n. For example, e_2(x_1,x_2,x_3)=x_1x_2+x_1x_3+x_2x_3. The products e_lambda=product_(i)e_(lambda_i) form a vector basis for the symmetric polynomials in these variables over any field, where lambda ranges over partitions whose parts are at most n, including the empty partition (Macdonald 1995, pp. 19-21).

For n>=1, the polynomial map (x_1,...,x_n)|->(e_1,...,e_n) has Jacobian matrix J=(partiale_i/partialx_j)_(1<=i,j<=n), with determinant

 detJ=product_(1<=i<j<=n)(x_i-x_j)=(-1)^(n(n-1)/2)Delta(x_1,...,x_n),

where Delta is the Vandermonde determinant (Bracciali and Piñar 2023, p. 189). The polynomial discriminant of the monic polynomial p(t)=product_(j=1)^(n)(t-x_j) is (detJ)^2. Consequently, J is nonsingular iff the roots x_j are pairwise distinct.


See also

Chromatic Quasisymmetric Function, Complete Homogeneous Symmetric Polynomial, Fundamental Theorem of Symmetric Functions, Polynomial Discriminant, Shareshian-Wachs Conjecture, Symmetric Function, Symmetric Polynomial, Vandermonde Determinant, Vieta's Formulas

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References

Bracciali, C. F. and Piñar, M. A. "On Multivariate Orthogonal Polynomials and Elementary Symmetric Functions." Numer. Algorithms 92, 183-206, 2023. https://doi.org/10.1007/s11075-022-01434-4.Macdonald, I. G. Symmetric Functions and Hall Polynomials, 2nd ed. Oxford, England: Oxford University Press, 1995.Wu, X. "Recursive Algorithm Without Extra Function Evaluations for the Jacobian Matrix of Viéta's Polynomial System with Applications." Appl. Math. Comput. 162, 539-548, 2005. https://doi.org/10.1016/j.amc.2003.12.107.

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Elementary Symmetric Polynomial

Cite this as:

Weisstein, Eric W. "Elementary Symmetric Polynomial." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/ElementarySymmetricPolynomial.html

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