论文标题

双曲线多项式的线性切片和对称多项式函数的阳性

Linear slices of hyperbolic polynomials and positivity of symmetric polynomial functions

论文作者

Riener, Cordian, Schabert, Robin

论文摘要

如果其所有$ n $ roots都在实际线上,那么$ n $的真正单变量多项式称为双曲线。这样的多项式在不同的应用中很自然地出现,例如在组合和优化中。本文的重点是双曲线多项式的家族,这些家族是通过系数上的$ k $线性条件确定的。与这种双曲线多项式家族相对应的系数形成了一个半代数集,我们称之为\ emph {双曲线切片}。我们在这里更详细地研究了这些物体的几何形状。双曲线多项式相对于真实零的多重性进行了自然分层,并且该分层也引起双曲线切片的分层。我们这里的主要重点是双曲线切片的\ emph {局部极端点},即线性函数的局部极端点,我们表明,这些精确的双曲线片中的双曲线多项式与最多具有$ k $不同的根源相对应,我们可以表明该家族的convex hull a convex hull是一个polyhedron。在这些结果的基础上,我们为对称真实品种和对称半代数集的研究给出了结果。在这里,我们表明,由对称多项式定义的集合可以用基本对称的多项式来稀疏表示,可以在几个不同的坐标的点上采样。例如,这允许算法简化,例如,验证这种多项式是非负的,或者由该多项式定义的半代数集是空的。

A real univariate polynomial of degree $n$ is called hyperbolic if all of its $n$ roots are on the real line. Such polynomials appear quite naturally in different applications, for example, in combinatorics and optimization. The focus of this article are families of hyperbolic polynomials which are determined through $k$ linear conditions on the coefficients. The coefficients corresponding to such a family of hyperbolic polynomials form a semi-algebraic set which we call a \emph{hyperbolic slice}. We initiate here the study of the geometry of these objects in more detail. The set of hyperbolic polynomials is naturally stratified with respect to the multiplicities of the real zeros and this stratification induces also a stratification on the hyperbolic slices. Our main focus here is on the \emph{local extreme points} of hyperbolic slices, i.e., the local extreme points of linear functionals, and we show that these correspond precisely to those hyperbolic polynomials in the hyperbolic slice which have at most $k$ distinct roots and we can show that generically the convex hull of such a family is a polyhedron. Building on these results, we give consequences of our results to the study of symmetric real varieties and symmetric semi-algebraic sets. Here, we show that sets defined by symmetric polynomials which can be expressed sparsely in terms of elementary symmetric polynomials can be sampled on points with few distinct coordinates. This in turn allows for algorithmic simplifications, for example, to verify that such polynomials are non-negative or that a semi-algebraic set defined by such polynomials is empty.

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