Imaginary Projections: Complex Versus Real Coefficients

Given a multivariate complex polynomial ${p\in\mathbb{C}[z_1,\ldots,z_n]}$, the imaginary projection $\mathcal{I}(p)$ of $p$ is defined as the projection of the variety $\mathcal{V}(p)$ onto its imaginary part. We focus on studying the imaginary projection of complex polynomials and we state explicit results for certain families of them with arbitrarily large degree or dimension. Then, we restrict to complex conic sections and give a full characterization of their imaginary projections, which generalizes a classification for the case of real conics. That is, given a bivariate complex polynomial $p\in\mathbb{C}[z_1,z_2]$ of total degree two, we describe the number and the boundedness of the components in the complement of $\mathcal{I}(p)$ as well as their boundary curves and the spectrahedral structure of the components. We further show a realizability result for strictly convex complement components which is in sharp contrast to the case of real polynomials.Comment: 24 pages; Revised versio

Matter as Spectrum of Spacetime Representations

Bound and scattering state Schr\"odinger functions of nonrelativistic quantum mechanics as representation matrix elements of space and time are embedded into residual representations of spacetime as generalizations of Feynman propagators. The representation invariants arise as singularities of rational representation functions in the complex energy and complex momentum plane. The homogeneous space $GL(2,C)/U(2)$ with rank 2, the orientation manifold of the unitary hypercharge-isospin group, is taken as model of nonlinear spacetime. Its representations are characterized by two continuous invariants whose ratio will be related to gauge field coupling constants as residues of the related representation functions. Invariants of product representations define unitary Poincar\'e group representations with masses for free particles in tangent Minkowski spacetime.Comment: 37 pages, latex, macros include

The inverse moment problem for convex polytopes: implementation aspects

We give a detailed technical report on the implementation of the algorithm presented in Gravin et al. (Discrete & Computational Geometry'12) for reconstructing an $N$-vertex convex polytope $P$ in $\mathbb{R}^d$ from the knowledge of $O(Nd)$ of its moments

Non intrusive polynomial chaos-based stochastic macromodeling of multiport systems

We present a novel technique to efficiently perform the variability analysis of electromagnetic systems. The proposed method calculates a Polynomial Chaos-based macromodel of the system transfer function that includes its statistical properties. The combination of a non-intrusive Polynomial Chaos approach with the Vector Fitting algorithm allows to describe the system variability features with accuracy and efficiency. The results of the variability analysis performed with the proposed method are verified by means of comparison with respect to the standard Monte Carlo analysis