Optimization Archives - IEEE Transactions on Quantum Engineering

Quantum-Assisted Optimization and Security for Trustworthy AI-Driven Healthcare

March 25, 2026Hafiz Muhammad Waseem, Gregory Epiphaniou, Carsten MapleOpen Access, Quantum InformationAccuracy, Artificial intelligence, Complexity theory, Decision making, Electronic healthcare, Genomics, Medical services, Optimization, Scalability, Security

Abstract: Digital health increasingly relies on artificial intelligence for clinical decision-making, patient management, and distributed learning, yet two persistent challenges remain: the computational complexity of optimization tasks, such as operating-room scheduling and genomic feature selection, and the need for robust security in federated and Internet-of-Medical-Things (IoMT) systems that are vulnerable to poisoning and spoofing attacks. […]

Advanced Quantum Annealing for the Bi-Objective Traveling Thief Problem: An ε-Constraint-Based Approach

March 16, 2026Nguyen Hoang Viet, Nguyen Xuan Tung, Trinh Van Chien, Won-Joo HwangOpen Access, Quantum ComputingAnnealing, Hardware, Interference, Linear programming, Optimization, Quantum annealing, Scalability, Transforms, Traveling salesman problems, Urban areas

Abstract: This paper addresses the Bi-Objective Traveling Thief Problem (BI-TTP), a challenging multi-objective optimization problem that requires the simultaneous optimization of travel cost and item profit. Conventional methods for the BI-TTP often face severe scalability issues due to the complex interdependence between routing and packing decisions, as well as the inherent complexity and large problem […]

Accelerating the Max-Cut problems via distributed Ising machine solvers

February 23, 2026Xing-yu Wu, Yi-Xin Zhang, Chen-rui Fan, Chuan WangOpen AccessApproximation algorithms, Computational modeling, Distributed computing, Hardware, Optimization, Partitioning algorithms, Quantum computing, Qubit, Scalability, Stationary state

Abstract: The Ising machine, as a quantum-inspired computing system, can be used to efficiently solve combinatorial optimization problems. Ongoing studies have positioned it to potentially surpass the performance limitations of traditional computers. However, such Ising machines also suffer from scalability as the solution quality becomes sub-optimal when the problem size increases. In this work, we […]

Quantum Annealing for Robust Principal Component Analysis

February 6, 2026Ian Tomeo, Panagiotis Markopoulos, Andreas SavakisQuantum ComputingAnnealing, Computers, Feature extraction, Hardware, Matrix decomposition, Optimization, Principal component analysis, Quantum annealing, Qubit, Robustness

Abstract: Principal component analysis is commonly used for dimensionality reduction, feature extraction, denoising, and visualization. The most commonly used principal component analysis method is based upon optimization of the L2-norm; however, the L2-norm is known to exaggerate the contribution of errors and outliers. When optimizing over the L1-norm, the components generated are known to exhibit […]

A Quantum Variational Approach to Phase-Only Pattern Synthesis

January 30, 2026Sigurd HuberQuantum ComputingAntenna arrays, Antennas, Iterative methods, Linear antenna arrays, Optimization, Phased arrays, Polynomials, Quantum annealing, Quantum computing, Transmitting antennas

Abstract: Phase-only pattern synthesis is a long-standing and hard to solve problem in antenna engineering. Due to its nonlinear nature, this kind of optimization problem is classically approached with iterative algorithms, where the convergence time depends on the problem topology. Often these heuristic solution routines get stuck in local optima and yield suboptimal results. This […]

Feedback-Based Quantum Algorithm for Excited States Calculation

January 16, 2026Salahuddin Abdul Rahman, Özkan Karabacak, Rafal WisniewskiQuantum ComputingApproximation algorithms, Convergence, Lyapunov methods, Optimization, Quantum algorithm, Quantum chemistry, Quantum circuit, Quantum computing, Qubit, Stationary state

Abstract: Recently, feedback-based quantum algorithms have been introduced to calculate the ground states of Hamiltonians, inspired by quantum Lyapunov control theory. This article aims to generalize these algorithms to the problem of calculating an eigenstate of a given Hamiltonian, assuming that the lower energy eigenstates are known. To this aim, we propose a new design […]

Equivariant Quantum Approximate Optimization Algorithm

January 16, 2026Boris Tsvelikhovskiy, Ilya Safro, Yuri AlexeevQuantum ComputingApproximation algorithms, Heuristic algorithms, Linear programming, Machine learning algorithms, Mixers, Optimization, Partitioning algorithms, Quantum circuit, Standards, Stationary state

Abstract: Constructing effective mixer Hamiltonians is essential for enhancing the performance of the quantum approximate optimization algorithm (QAOA) in solving combinatorial optimization problems. In this work, we develop a systematic methodology for designing QAOA mixers that align with the symmetries of the classical objective function, with the goal of achieving values (mean, median, and minimum […]

Optimal Allocation of Pauli Measurements for Low-Rank Quantum State Tomography

January 16, 2026Zhen Qin, Casey Jameson, Zhexuan Gong, Michael B. Wakin, Zhihui ZhuQuantum InformationAccuracy, Current measurement, Density measurement, Loss measurement, Measurement uncertainty, Noise measurement, Optimization, Quantum state, Sensors, Tomography

Abstract: The process of reconstructing quantum states from experimental measurements, accomplished through quantum state tomography (QST), plays a crucial role in verifying and benchmarking quantum devices. A key challenge of QST is to find out how the accuracy of the reconstruction depends on the number of state copies used in the measurements. When multiple measurement […]

Black-Box Optimization of the Storage Location Assignment Problem in Logistics Centers Using an Annealing Algorithm

December 19, 2025Hiromitsu Kigure Takeshi Baba Makoto Taniguchi Hirotaka KajiQuantum ComputingAnnealing, Closed box, Genetic algorithms, Hardware, Legged locomotion, Linear programming, Logistics, Mathematical models, Optimization, Quantum annealing

Abstract: The manufacturing industry encounters numerous optimization problems, one of which is the optimization of storage location assignment (OSLA) problem in logistics. OSLA is a combinatorial optimization problem focused on improving the efficiency of picking operations in logistics centers. We explore quantum annealing (QA) as a potential solution to combinatorial optimization problems and investigate its […]

Robust H∞ Uncertainties-Tolerant Observer-Based Reference Quantum Trajectory Tracking Control for Lindblad Master Equation

December 18, 2025Shin-Yi Wen Bor-Sen Chen Chun-Liang LinEnabling TechnologiesControl design, Estimation, Feedback control, Mathematical models, Optimization, Pollution measurement, Quantum state, Quantum system, Trajectory, Trajectory tracking

Abstract: In this article, a robust output feedback reference quantum trajectory tracking control design is proposed through the simultaneous continuous weak measurement of noncommuting observables. Using the robust H∞ uncertainties-tolerant observer-based reference quantum trajectory tracking control (UTOBRQTTC) design strategy, the proposed method can robustly estimate the quantum trajectory and robustly track a sequence of any […]