2 citations · 4 across the 8 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
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…
Optimizing State Preparation for Variational Quantum Regression on NISQ Hardware
Frans Perkkola, Ilmo Salmeperä, Arianne Meijer-van de Griend +3
The execution of quantum algorithms on modern hardware is often constrained by noise and qubit decoherence, limiting the circuit depth and the number of gates that can be executed.…