Universal Quantum Computer Simulation of 50 Qubits on Europe`s First Exascale Supercomputer Harnessing Its Heterogeneous CPU-GPU Architecture

2025/11/05 by De Raedt, Hans, Kraus, Jiri, Herten, Andreas +5 · 6 citations
Computer Science · #Computational Physics (physics.comp-ph) #Distributed #FOS: Computer and information sciences #FOS: Physical sciences #Parallel #Parallel Computing and Optimization Techniques #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph) #Quantum-Dot Cellular Automata #and Cluster Computing (cs.DC)

paper · doi:10.48550/arxiv.2511.03359

openalex publication_date 2025/11/05 · openalex created_date 2025/11/07 · openalex updated_date 2026/07/28

Abstract

We have developed a new version of the high-performance Jülich universal quantum computer simulator (JUQCS-50) that leverages key features of the GH200 superchips as used in the JUPITER supercomputer, enabling simulations of a 50-qubit universal quantum computer for the first time. JUQCS-50 achieves this through three key innovations: (1) extending usable memory beyond GPU limits via high-bandwidth CPU-GPU interconnects and LPDDR5 memory; (2) adaptive data encoding to reduce memory footprint with acceptable trade-offs in precision and compute effort; and (3) an on-the-fly network traffic optimizer. These advances result in a 16.6-fold speedup over the previous 48-qubit record on the K computer

Citations

• Quantum error correction below the surface code threshold
• Atlas: Hierarchical Partitioning for Quantum Circuit Simulation on GPUs (Extended Version)
• Quantum computing: A taxonomy, systematic review and future directions
• O(N³) Measurement Cost for Variational Quantum Eigensolver on\n Molecular Hamiltonians
• Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer

Cited by

• SOFT: a high-performance simulator for universal fault-tolerant quantum circuits
• Resolving Structure in Prethermal Floquet Dynamics with Precision Quantum Computation
• The Convergence Frontier: Integrating Machine Learning and High Performance Quantum Computing for Next-Generation Drug Discovery
• Opportunities and Challenges for Data Quality in the Era of Quantum Computing
• Multi-GPU Quantum Circuit Simulation and the Impact of Network Performance
• Optimizing Memory Efficiency and Index Ordering to Simulate Quantum Circuits Using Tensor Decision Diagrams

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