Predictive models Archives - IEEE Transactions on Quantum Engineering

Analysis of Parameterized Quantum Circuits: On the Connection Between Expressibility and Types of Quantum Gates

May 19, 2025Yu Liu; Kazuya Kaneko; Kentaro Baba; Jumpei Koyama; Koichi Kimura; Naoyuki TakedaQuantum Computing, UncategorizedAccuracy, Additives, Computational modeling, Integrated circuit modeling, Kernel, Logic gates, Predictive models, Quantum circuit, Qubit, Topology

Abstract: Expressibility is a crucial factor of a parameterized quantum circuit (PQC). In the context of variational-quantum-algorithm-based quantum machine learning (QML), a QML model composed of a highly expressible PQC and a sufficient number of qubits is theoretically capable of approximating any arbitrary continuous function. While much research has explored the relationship between expressibility and […]

Learning a Quantum Computer’s Capability

July 18, 2024Daniel Hothem, Kevin Young, Tommie Catanach, Timothy ProctorQuantum InformationComputational modeling, Computers, Integrated circuit modeling, Neural networks, Predictive models, Program processors, Quantum computing

Accurately predicting a quantum computer’s capability—which circuits it can run and how well it can run them—is a foundational goal of quantum characterization and benchmarking. As modern quantum computers become increasingly hard to simulate, we must develop accurate and scalable predictive capability models to help researchers and stakeholders decide which quantum computers to build and […]

Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning

November 17, 2023Sangwoo Park, Osvaldo SimeoneQuantum InformationCalibration, Data models, Machine learning, Predictive models, Training, Training data, Uncertainty

Quantum machine learning is a promising programming paradigm for the optimization of quantum algorithms in the current era of noisy intermediate-scale quantum computers. A fundamental challenge in quantum machine learning is generalization, as the designer targets performance under testing conditions while having access only to limited training data. Existing generalization analyses, while identifying important general […]

Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning

November 17, 2023Sangwoo Park, Osvaldo Simeone,Quantum InformationCalibration, Data models, Machine learning, Predictive models, Training, Training data, Uncertainty

Prediction of Solar Irradiance One Hour Ahead Based on Quantum Long Short-Term Memory Network

June 14, 2023Yunjun YuQuantum ComputingAtmospheric modeling, Computational modeling, Data models, Feature extraction, Forecasting, Mathematical models, Predictive models

The short-term forecasting of photovoltaic (PV) power generation ensures the scheduling and dispatching of electrical power, helps design a PV-integrated energy management system, and enhances the security of grid operation. However, due to the randomness of solar energy, the output of the PV system will fluctuate, which will affect the safe operation of the grid. […]