Scynergy 2025#
Welcome to SCynergy 2025 workshop!
advancing Supercomputing, AI, and quantum technologies in Europe
Supercomputing, artificial intelligence, and quantum computing are reshaping industries, research, and society at large. SCynergy 2025 brings together businesses, researchers, and policymakers to explore practical applications, share knowledge, and build collaborations that will shape the future of these technologies in Europe.
Organised by Supercomputing Luxembourg, with the support of EuroHPC JU and Women in HPC, SCynergy provides a platform for experts and decision-makers to discuss how high-performance computing (HPC), AI, and quantum technologies can be applied effectively across sectors such as finance, space, healthtech, and industry.
Useful links and material#
(TBD) Specific items from LuxProvide/PennyLane-GPU
All training material should be in Qiskit
Topics for introduction
Prerequisite (read beforehand)#
Algebra (missing)
Complex numbers (missing)
Qubits, Gates, circuits (missing)
Hamiltonian - introduction (missing)
Classical SVM (?, missing)
Live tutorial
Qiskit introduction (adapt from Pennylane one)
Define and print basic circuits manually
Device simulators (ideal vs noisy vs fake)
Run simple circuit examples (missing?)
Basic end-to-end example
Grover?, but simpler/shorter, more showing the different stages of the end-to-end pipeline (data preprocessing, quantum computation, result interpretation)
[NOTE] closing jupyter lab does not stop the job on the HPC note – need to document (using scancel)
graph TD subgraph Problem direction LR; A((Define Molecule)) A --> B(Select active orbitals & electrons) end subgraph Mapping direction LR; C(Choose Qubit Mapping: Jordan-Wigner/Parity) C --> D(Select Ansatz: UCCSD, PUCCD, etc. This defines circuit structure.) end Problem --> Mapping subgraph Circuit direction LR; E(Initialize Parameters - all zero) E --> F(Initial state = Hartree-Fock state) F --> G(Run Quantum Circuit & Measure) end Mapping --> Circuit Circuit --> H(Compute Energy i.e. Expectation Value of Hamiltonian) H --> I{Convergence?} I -- No --> J(Update Parameters via Classical Optimizer) --> Circuit I -- Yes --> K(Return Optimized Energy & Parameters);
Acknowledgements#
We extend our gratitude to the Irish Centre for High-End Computing (ICHEC) and University of Galway for providing computing and for all-encompassing invaluable support. This project was funded by the EuroHPC JU under grant agreement No 951732 and Ireland.
Warning
Add appropriate logos.


