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The technique of semidefinite programming (SDP) relaxation can be used to obtain a nontrivial bound on the optimal value of a nonconvex quadratically constrained quadratic program (QCQP). We explore concave quadratic inequalities that hold…

Optimization and Control · Mathematics 2016-09-30 Jaehyun Park , Stephen Boyd

The paper is devoted to optimization of resonances associated with 1-D wave equations in inhomogeneous media. The medium's structure is represented by a nonnegative function B. The problem is to design for a given $\alpha \in \R$ a medium…

Spectral Theory · Mathematics 2013-02-22 Illya M. Karabash

In developing strategies of manipulating surface electromagnetic waves, it has been recently recognized that a complete forbidden band gap can exist in a periodic surface-wave photonic crystal, which has subsequently produced various…

Optics · Physics 2016-06-28 Zhen Gao , Fei Gao , Youming Zhang , Hongyi Xu , Baile Zhang

A semidefinite program (SDP) is a particular kind of convex optimization problem with applications in operations research, combinatorial optimization, quantum information science, and beyond. In this work, we propose variational quantum…

Quantum Physics · Physics 2024-06-19 Dhrumil Patel , Patrick J. Coles , Mark M. Wilde

We consider time-harmonic linear elasticity equations in domains containing two-dimensional semi-infinite strips. Since for such problems there exist modes with different signs of group and phase velocity, standard perfectly matched layer…

Numerical Analysis · Mathematics 2015-06-17 Martin Halla , Lothar Nannen

We consider a problem in eigenvalue optimization, in particular finding a local minimizer of the spectral abscissa - the value of a parameter that results in the smallest value of the largest real part of the spectrum of a matrix system.…

Optimization and Control · Mathematics 2014-11-11 Vyacheslav Kungurtsev , Wim Michiels , Moritz Diehl

We propose a novel methodology for solving a two-stage adjustable robust convex optimisation problem with a general (proximable) convex objective function and constraints defined by sum-of-squares (SOS) convex polynomials. These problems…

Optimization and Control · Mathematics 2026-02-17 Neil D. Dizon , Bethany I. Caldwell , Vaithilingam Jeyakumar , Guoyin Li

A new approach to solving a class of rankconstrained semi-definite programming (SDP) problems, which appear in many signal processing applications such as transmit beamspace design in multiple-input multiple-output (MIMO) radar, downlink…

Information Theory · Computer Science 2016-10-10 Matthew W. Morency , Sergiy A. Vorobyov

We consider two-dimensional phononic crystals formed from silicon and voids, and present optimized unit cell designs for (1) out-of-plane, (2) in-plane and (3) combined out-of-plane and in-plane elastic wave propagation. To feasibly search…

Computational Physics · Physics 2013-04-23 Osama R. Bilal , Mahmoud I. Hussein

In this work we show theoretically that it is possible to design a large band gap in the infrared range using a one-dimensional Photonic Crystal heterostructure made of porous silicon. Stacking together multiple photonic crystal…

We study the bandgap properties of two-dimensional photonic crystals created by a lattice of rods or holes conformed in a symmetric or asymmetric triangular structure. Using the plane-wave analysis, we calculate a minimum value of the…

Optics · Physics 2009-11-11 Aaron Matthews , Xue-Hua Wang , Yuri Kivshar , Min Gu

A method is introduced to analyze the degeneracy properties of the band structure of a photonic crystal making use of the super cells. The band structure associated with a super cell of a photonic crystal has degeneracies at the edge of the…

Materials Science · Physics 2007-05-23 Liang Wu , Sailing He

In this work, we propose a new local optimization method to solve a class of nonconvex semidefinite programming (SDP) problems. The basic idea is to approximate the feasible set of the nonconvex SDP problem by inner positive semidefinite…

Optimization and Control · Mathematics 2012-02-27 Quoc Tran Dinh , Wim Michiels , Moritz Diehl

The problem of optimizing over the cone of nonnegative polynomials is a fundamental problem in computational mathematics, with applications to polynomial optimization, control, machine learning, game theory, and combinatorics, among others.…

Optimization and Control · Mathematics 2018-06-20 Georgina Hall

This paper gives an overview of recent work on three-dimensional (3D) photonic crystals with a "full and complete" 3D photonic band gap. We review five main aspects: 1) spontaneous emission inhibition, 2) spatial localization of light…

Quantum Physics · Physics 2015-04-28 W. L. Vos , L. A. Woldering

Motivated by applications in wireless communications, this paper develops semidefinite programming (SDP) relaxation techniques for some mixed binary quadratically constrained quadratic programs (MBQCQP) and analyzes their approximation…

Optimization and Control · Mathematics 2014-03-18 Zi Xu , Mingyi Hong , Zhi-Quan Luo

Semidefinite programs (SDPs) are standard convex problems that are frequently found in control and optimization applications. Interior-point methods can solve SDPs in polynomial time up to arbitrary accuracy, but scale poorly as the size of…

Optimization and Control · Mathematics 2022-01-10 Jared Miller , Yang Zheng , Mario Sznaier , Antonis Papachristodoulou

A method for solving the inverse problem of designing the structure of a one-dimensional photonic crystal is proposed and experimentally implemented. It is known that a one-dimensional photonic crystal with a spatial sinusoidal modulation…

Optics · Physics 2023-08-09 P. S. Emelyantsev , N. I. Pyshkov , S. E. Svyakhovskiy

We propose a new homotopy-based conditional gradient method for solving convex optimization problems with a large number of simple conic constraints. Instances of this template naturally appear in semidefinite programming problems arising…

Optimization and Control · Mathematics 2025-01-31 Pavel Dvurechensky , Gabriele Iommazzo , Shimrit Shtern , Mathias Staudigl

In this paper, we propose an iterative algorithm to address the nonconvex multi-group multicast beamforming problem with quality-of-service constraints and per-antenna power constraints. We formulate a convex relaxation of the problem as a…

Signal Processing · Electrical Eng. & Systems 2021-11-10 Jochen Fink , Renato L. G. Cavalcante , Slawomir Stanczak