QCLS: Quantum Computing for Scientific Computing
The goal of the project is to develop advanced methods and software approaches for solving large-scale linear systems using quantum and hybrid computing, thereby improving the efficiency of scientific simulations and data-intensive applications.
Duration: 2026–2029
Project acronym: QCLS
Project leader: dr. Ezhilmathi Krishnasamy
Project coordinator: Rudolfovo – Science and Technology Centre Novo mesto
Industrial partner: 3 TAV Izbrane informacije d.o.o.
Funding: The project is co-financed by the European Regional Development Fund.
Project description
Modern science and engineering rely on solving complex mathematical problems, which often lead to large systems of linear equations. These problems are fundamental in fields such as artificial intelligence, physical simulations, fluid dynamics, and plasma physics.
Classical computing is approaching its limits in terms of performance, energy consumption, and scalability. Quantum computing offers a promising alternative, with the potential to significantly accelerate computations while improving energy efficiency.
The QCLS project focuses on developing new quantum algorithms for solving large linear systems and on exploring hybrid approaches that combine classical and quantum computing. A key objective is to bridge the gap between the theoretical potential of quantum technologies and their practical application in real-world scientific and industrial problems.
Methodological approach
The project combines quantum computing, scientific computing, and high-performance computing (HPC).
Research activities include the development and testing of quantum algorithms in simulation environments, followed by their gradual integration into hybrid systems. The project:
uses quantum simulators and frameworks (e.g., Qiskit, PennyLane),
develops new algorithms for solving linear systems,
explores hybrid quantum-classical architectures,
evaluates performance, accuracy, and scalability.
Key objectives and results
develop a software framework for solving large linear systems on quantum simulators,
establish a hybrid computing approach combining classical and quantum methods,
explore standalone quantum computing capabilities,
improve algorithm efficiency for applications in AI, machine learning, and physics,
contribute to the advancement of quantum computing through scientific publications and knowledge transfer.
Regional relevance
QCLS contributes to the development of quantum technologies in Slovenia and Europe while strengthening collaboration between research and industry.
By linking Rudolfovo with an industrial partner, the project supports knowledge transfer and the development of advanced digital solutions. It enhances Slovenia’s integration into the European quantum ecosystem and contributes to building innovation capacity and future competencies in this strategic field.
