Approximation Algorithms for Optimization of Real-Valued General Conjugate Complex Forms

TL;DR

This paper develops polynomial-time approximation algorithms for optimizing real-valued conjugate complex forms over various complex constraint sets, improving performance ratios and establishing new probabilistic bounds and formulas.

Contribution

It introduces the first probability lower bounds for random sampling in complex sets and a polarization formula linking conjugate forms to multilinear forms.

Findings

Improved approximation ratios for complex polynomial optimization.

Established the first probabilistic bounds for sampling over complex sets.

Proposed a novel polarization formula connecting conjugate forms and multilinear forms.

Abstract

Complex polynomial optimization has recently gained more and more attention in both theory and practice. In this paper, we study the optimization of a real-valued general conjugate complex form over various popular constraint sets including the m-th roots of complex unity, the complex unit circle, and the complex unit sphere. A real-valued general conjugate complex form is a homogenous polynomial function of complex variables as well as their conjugates, and always takes real values. General conjugate form optimization is a wide class of complex polynomial optimization models, which include many homogenous polynomial optimization in the real domain with either discrete or continuous variables, and Hermitian quadratic form optimization as well as its higher degree extensions. All the problems under consideration are NP-hard in general and we focus on polynomial-time approximation algorithms with worst-case performance ratios. These approximation ratios improve previous results when restricting our problems to some special classes of complex polynomial optimization, and improve or equate previous results when restricting our problems to some special classes of polynomial optimization in the real domain. These algorithms are based on tensor relaxation and random sampling. Our novel technical contributions are to establish the first set of probability lower bounds for random sampling over the m-th root of unity, the complex unit circle, and the complex unit sphere, and propose the first polarization formula linking general conjugate forms and complex multilinear forms.