Quantum Technologies
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Enhancing quantum computing robustness and potential

For quantum computers (QCs) to be truly effective, they must solve meaningful problems. Exploring how to scale their computational power is done in three notable ways.

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First, hybrid High-Performance Computing-QC (HPC-QC) uses quantum computers as co-processors for computations where it offers an advantage. HPC-QC can both enhance the capabilities of current quantum devices and accelerate the performance of classical HPC systems in the future. It also increases accessibility to quantum technologies by leveraging existing HPC infrastructure and encouraging their adoption within HPC communities.

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Second, combining QCs with AI: the advances in one can help overcome challenges in the other. For example, quantum algorithms may improve machine learning performance, while AI techniques can assist in optimising quantum circuits and error correction.

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Third, connecting multiple QCs using a quantum communication network can enable to combine their computational resources. This modular or distributed architecture offers a path to scaling quantum systems beyond the limits of individual devices.

Maturity

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More diversified access to large AI models Increase in co-evolution between hardware and AI Collaboration between humans and AI Democratisation of XR content creation using generative AI Public investments in XR continue to increase Standardisation of data space architectures for secure and trusted data sharing Growing significance of augmented data management Trusted digital recognitions are emerging Digital Trust Frameworks: from hierarchical to distributed trust Emerging dualuse of AI in cybersecurity More accessible privacy-enhancing technologies to share data Rising pressure to prepare for post-quantum cryptography Emergence of measures for secure Internet of Things The growing need for security protocols to work in the cloud Growing investments in the European cloud infrastructure & sovereignty More AI-driven hardware in data centres to manage workloads in the cloud Increasing need for heterogeneous and hybrid computing platforms Trade-offs in accuracy with approximate computing Fixed wireless access Fibre optic networks: strategic infrastructure for the knowledge economy Enhancing quantum computing robustness and potential Quantum sensing integration to other domains

Drivers

Impact

education

Education

  • A workforce with more specific skills sets and interdisciplinary knowledge is required.
Research

Research

  • Improving the robustness of quantum computers will stimulate interest in quantum computing.
  • Integrating QC with HPC will lower the barrier of usage for the HPC users.
  • Research on QC&AI will increase.
Operations

Operations

  • Start thinking and realising the integration of quantum computing to the existing infrastructure and ecosystem.
  • Start thinking on how to give access for education, research and use case development.
  • Develop quantum expertise for operation and user support.
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