Algorithmes hybrides quantiques-classiques pour le calcul haute performance
Océane Koska
High-Performance Computing (HPC) is today the main tool for large-scale scientific computing, but performance gains are increasingly limited by architectural and energy constraints. At the same time, quantum computing is an emerging paradigm, still under development, but already promising for accelerating certain computational kernels. A central challenge is therefore to understand how to efficiently integrate quantum processors within existing HPC infrastructures, rather than treating them as isolated accelerators. The objective of this thesis is to explore hybrid quantum-classical computing, both from the algorithmic perspective and in terms of programming models. We investigate how to coherently combine classical and quantum resources within hybrid workflows, leveraging the respective strengths of each paradigm. As a primary use case, we focus on solving linear systems of equations, a fundamental building block of scientific computing and HPC. First, we address the challenge of encoding classical data into quantum representations, which remains a major bottleneck for hybrid algorithms. We propose an improved preprocessing method for matrix encoding into unitaries using a Pauli decomposition, reducing the associated computational cost. Next, we introduce a hybrid solver based on the Quantum Singular Value Transformation (QSVT). Inspired by classical numerical linear algebra, we propose a mixed-precision iterative refinement approach, combining low-precision quantum solves with high-precision classical corrections. A detailed analysis of convergence, errors, and computational cost shows that hybridization can reduce the quantum resources required to reach a given precision.Finally, we address programming and implementation aspects through the design of a hybrid quantum-classical programming framework, Q-Pragma, aimed at facilitating the integration of quantum acceleration into existing HPC environments. Overall, this work contributes to the development of more practical and usable hybrid quantum-HPC codes, bridging the gap between theoretical algorithms and real-world high-performance applications.
•Jun 12, 2026•0 citations