Quantum state Archives - IEEE Transactions on Quantum Engineering

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 […]

Fast State Stabilization Using Deep Reinforcement Learning for Measurement-Based Quantum Feedback Control

September 4, 2025Chunxiang Song Yanan Liu Daoyi Dong Hidehiro YonezawaQuantum ComputingConvergence, Current measurement, Deep Reinforcement Learning, Feedback control, Quantum computing, Quantum entanglement, Quantum state, Quantum system, Trajectory, Velocity measurement

Abstract: The stabilization of quantum states is a fundamental problem for realizing various quantum technologies. Measurement-based-feedback strategies have demonstrated powerful performance, and the construction of quantum control signals using measurement information has attracted great interest. However, the interaction between quantum systems and the environment is inevitable, especially when measurements are introduced, which leads to decoherence. […]

Generalized Quantum-Assisted Digital Signature

August 4, 2025Alberto Tarable; Rudi Paolo Paganelli; Elisabetta Storelli; Alberto Gatto; Marco FerrariQuantum InformationDigital signatures, Error analysis, Forgery, Hash functions, NIST, Protocols, Quantum channels, Quantum state, Qubit, Standards

This article introduces generalized quantum-assisted digital signature (GQaDS), an improved version of a recently proposed scheme whose information-theoretic security is inherited by adopting quantum key distribution keys for digital signature purposes. Its security against forging is computed considering a trial-and-error approach taken by the malicious forger, and GQaDS parameters are optimized via an analytical approach […]

Benchmarking Quantum Machine Learning Kernel Training for Classification Tasks

February 13, 2025Diego Alvarez-EstevezQuantum SoftwareBenchmark testing, Estimation, Kernel, Machine learning, Quantum computing, Quantum mechanics, Quantum state, Support vector machines, Training, Vectors

Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine learning. However, the practical applicability of these methods remains an open question, particularly beyond the context of specifically crafted toy problems, and given the current limitations of quantum hardware. For more about this […]

Advance Sharing Procedures for the Ramp Quantum Secret Sharing Schemes With the Highest Coding Rate

January 17, 2025Ryutaroh MatsumotoQuantum InformationCryptography, Encoding, Finite element analysis, Hands, Proposals, Quantum state, Reviews, Standards, Symbols, Teleportation

Abstract: In some quantum secret sharing schemes, it is known that some shares can be distributed to participants before a secret is given to the dealer. However, it is unclear whether some shares can be distributed before a secret is given in the ramp quantum secret sharing schemes with the highest coding rate. This article […]

Noise Robustness of Quantum Relaxation for Combinatorial Optimization

August 6, 2024Kentaro Tamura, Yohichi Suzuki, Rudy Raymond, Hiroshi C. Watanabe, Yuki Sato, Ruho Kondo, Michihiko Sugawara, Naoki YamamotoQuantum ComputingApproximation algorithms, Decoding, Encoding, Noise, Optimization, Quantum state, Qubit

Relaxation is a common way for dealing with combinatorial optimization problems. Quantum random-access optimization (QRAO) is a quantum-relaxation-based optimizer that uses fewer qubits than the number of bits in the original problem by encoding multiple variables per qubit using quantum random-access code (QRAC). Reducing the number of qubits will alleviate physical noise (typically, decoherence), and […]

Noise Robustness of Quantum Relaxation for Combinatorial Optimization

August 6, 2024Kentaro Tamura, Yohichi Suzuki, Rudy Raymond, Hiroshi C. Watanabe, Yuki Sato, Ruho Kondo, Michihiko Sugawara, Naoki YamamotoQuantum Computer ArchitectureApproximation algorithms, Decoding, Encoding, Noise, Optimization, Quantum state, Qubit

Relaxation is a common way for dealing with combinatorial optimization problems.

Approximate Solutions of Combinatorial Problems via Quantum Relaxations

July 4, 2024Bryce Fuller, Charles Hadfield, Jennifer R. Glick, Takashi Imamichi, Toshinari Itoko, Richard J. Thompson, Yang Jiao, Marna M. Kagele, Adriana W. Blom-Schieber, Rudy Raymond, Antonio MezzacapoRegularApproximate Ratio, Approximate Solution, Binary Optimization, Classification Algorithms, Combinatorial Problem, Cost function, Cut Value, Eigenstates, Energy Relaxation, Estimation Algorithm, Hamiltonian Operator, Numerical Simulations, Optimal Cut, Optimal Objective Value, Pauli Matrices, Quantum computing, Quantum Information, Quantum state, Random Code, Relaxation Spectrum, Relaxed State

This article delves into the role of the quantum Fisher information matrix (FIM) in enhancing the performance of parameterized quantum circuit (PQC)-based reinforcement learning agents. While previous studies have highlighted the effectiveness of PQC-based policies preconditioned with the quantum FIM in contextual bandits, its impact in broader reinforcement learning contexts, such as Markov decision processes, […]

Approximate Solutions of Combinatorial Problems via Quantum Relaxations

July 4, 2024Bryce Fuller, Charles Hadfield, Jennifer R. Glick, Takashi Imamichi, Toshinari Itoko, Richard J. Thompson, Yang Jiao, Marna M. Kagele, Adriana W. Blom-Schieber, Rudy Raymond, Antonio MezzacapoQuantum ComputingCodes, Computers, Optimization, Quantum entanglement, Quantum state, Qubit, Stationary state

Combinatorial problems are formulated to find optimal designs within a fixed set of constraints and are commonly found across diverse engineering and scientific domains. Understanding how to best use quantum computers for combinatorial optimization remains an ongoing area of study. Here, we propose new methods for producing approximate solutions to quadratic unconstrained binary optimization problems, […]

On Quantum Natural Policy Gradients

June 24, 2024André Sequeira, Luis Paulo Santos, Luis Soares Barbosa,Regular, UncategorizedBasic Conditions, Deep Reinforcement Learning, Estimation Error, Expected Value, Fisher Information, Fisher Information Matrix, Gradient Ascent, Gradient Update, Infidelity, Less Than Or Equal, Markov Decision Process, Matrix Inequalities, Natural Gradient, Normal Vector, Optimal Policy, Policy Gradient, Policy Gradient Method, Policy Parameters, Policy Space, Positive Semidefinite Matrix, Preconditioning, Projector, Proximal Policy Optimization, Quantum circuit, Quantum Measurement, Quantum state, Reward Function, Square Root, Standard Gradient, State Space