Classification Algorithms Archives - IEEE Transactions on Quantum Engineering

Information-Theoretic Analysis of Bayesian Quantum State Search

February 3, 2026Zhelun Li, Koji TerashiQuantum ComputingBayes methods, Classification Algorithms, Gain measurement, Information entropy, Integrated circuit modeling, Probability distribution, Quantum circuit, Quantum computing, Quantum state, Qubit

Abstract: We present an information-theoretic approach to quantum state classification based on sequential Bayesian inference. In each measurement step, the algorithm updates a probability distribution over candidate states by applying Bayes’ rule to the observed outcome. For each measurement shot on an unknown quantum state, the algorithm selects the observable with the highest expected information […]

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, […]