A real moment-HSOS hierarchy for complex polynomial optimization with real coefficients

Jie Wang () and Victor Magron ()
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Jie Wang: Chinese Academy of Sciences
Victor Magron: LAAS CNRS & IMT

Computational Optimization and Applications, 2025, vol. 90, issue 1, No 3, 53-75

Abstract: Abstract This paper proposes a real moment-HSOS hierarchy for complex polynomial optimization problems with real coefficients. We show that this hierarchy provides the same sequence of lower bounds as the complex analogue, yet is much cheaper to solve. In addition, we prove that global optimality is achieved when the ranks of the moment matrix and certain submatrix equal two in case that a sphere constraint is present, and as a consequence, the complex polynomial optimization problem has either two real optimal solutions or a pair of conjugate optimal solutions. A simple procedure for extracting a pair of conjugate optimal solutions is given in the latter case. Various numerical examples are presented to demonstrate the efficiency of this new hierarchy, and an application to polyphase code design is also provided.

Keywords: Complex polynomial optimization; Semidefinite relaxation; Moment-HSOS hierarchy; Polyphase code design; Conjugate invariance; Primary 90C23; Secondary 90C22; 90C26 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10589-024-00617-0

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