collaborators

9 papers

quant-ph2026

Architecture-aware Unitary Synthesis

Frans Perkkola, Arianne Meijer-van de Griend, Jukka K. Nurminen

We present a novel architecture-aware transpilation method for exact general unitary gate synthesis on superconducting quantum hardware. Our approach is tightly integrated with the…

quant-ph2026

Explainable quantum regression algorithm with encoded data structure

C. -C. Joseph Wang, F. Perkkola, I. Salmenperä +2

Hybrid variational quantum algorithms are promising for solving practical problems, such as combinatorial optimization, quantum chemistry simulation, quantum machine learning, and…

quant-ph2026

The Average Relative Entropy and Transpilation Depth determines the noise robustness in Variational Quantum Classifiers

Aakash Ravindra Shinde, Arianne Meijer - van de Griend, Jukka K. Nurminen

Variational Quantum Algorithms (VQAs) have been extensively researched for applications in Quantum Machine Learning (QML), Optimization, and Molecular simulations. Although designe…

cs.LG2026

Performance Estimation in Binary Classification Using Calibrated Confidence

Juhani Kivimäki, Jakub Białek, Wojtek Kuberski +1

Model monitoring is a critical component of the machine learning lifecycle, safeguarding against undetected drops in the model's performance after deployment. Traditionally, perfor…

quant-ph2025

Influence of Data Dimensionality Reduction Methods on the Effectiveness of Quantum Machine Learning Models

Aakash Ravindra Shinde, Jukka K. Nurminen

Data dimensionality reduction techniques are often utilized in the implementation of Quantum Machine Learning models to address two significant issues: the constraints of NISQ quan…

quant-ph2025

Perspectives on Utilization of Measurements in Quantum Algorithms

Valter Uotila, Ilmo Salmenperä, Leo Becker +3

Measurement is a fundamental operation in quantum computing and has many important use cases in quantum algorithms. This article provides a comprehensive overview of the basic meas…